From fb134d8e6d771134b29b4191495065752c90153d Mon Sep 17 00:00:00 2001 From: Dylan Van Assche Date: Tue, 16 Apr 2024 15:18:07 +0200 Subject: [PATCH] docs: update docs after Docker organization name change --- docs/execution-framework/bench_executor.html | 2 +- .../bench_executor/fuseki.html | 6 +- .../bench_executor/morphkgc.html | 6 +- .../bench_executor/morphrdb.html | 6 +- .../bench_executor/mysql.html | 6 +- .../bench_executor/ontop.html | 6 +- .../bench_executor/postgresql.html | 6 +- .../bench_executor/rmlmapper.html | 763 ++++++++------- .../bench_executor/rmlmapper_jar.html | 918 ++++++++++++++++++ .../bench_executor/rmlstreamer.html | 4 +- .../bench_executor/sdmrdfizer.html | 4 +- .../bench_executor/virtuoso.html | 6 +- .../bench_executor/yarrrml.html | 6 +- docs/execution-framework/search.js | 2 +- 14 files changed, 1341 insertions(+), 400 deletions(-) create mode 100644 docs/execution-framework/bench_executor/rmlmapper_jar.html diff --git a/docs/execution-framework/bench_executor.html b/docs/execution-framework/bench_executor.html index 4fa6c12..1466acf 100644 --- a/docs/execution-framework/bench_executor.html +++ b/docs/execution-framework/bench_executor.html @@ -37,7 +37,7 @@

Submodules

  • postgresql
  • query
  • rmlmapper
    • -
  • rmlmapper_docker
    • +
  • rmlmapper_jar
  • rmlstreamer
  • sdmrdfizer
  • stats
    • diff --git a/docs/execution-framework/bench_executor/fuseki.html b/docs/execution-framework/bench_executor/fuseki.html index 6c8d344..8d6cc19 100644 --- a/docs/execution-framework/bench_executor/fuseki.html +++ b/docs/execution-framework/bench_executor/fuseki.html @@ -139,7 +139,7 @@

    45 # Set Java heap to 1/2 of available memory instead of the default 1/4 46 max_heap = int(psutil.virtual_memory().total * (1/2)) 47 - 48 super().__init__(f'blindreviewing/fuseki:v{VERSION}', 'Fuseki', + 48 super().__init__(f'kgconstruct/fuseki:v{VERSION}', 'Fuseki', 49 self._logger, 50 ports={'3030': '3030'}, 51 environment={ @@ -364,7 +364,7 @@

    46 # Set Java heap to 1/2 of available memory instead of the default 1/4 47 max_heap = int(psutil.virtual_memory().total * (1/2)) 48 - 49 super().__init__(f'blindreviewing/fuseki:v{VERSION}', 'Fuseki', + 49 super().__init__(f'kgconstruct/fuseki:v{VERSION}', 'Fuseki', 50 self._logger, 51 ports={'3030': '3030'}, 52 environment={ @@ -556,7 +556,7 @@

    46 # Set Java heap to 1/2 of available memory instead of the default 1/4 47 max_heap = int(psutil.virtual_memory().total * (1/2)) 48 -49 super().__init__(f'blindreviewing/fuseki:v{VERSION}', 'Fuseki', +49 super().__init__(f'kgconstruct/fuseki:v{VERSION}', 'Fuseki', 50 self._logger, 51 ports={'3030': '3030'}, 52 environment={ diff --git a/docs/execution-framework/bench_executor/morphkgc.html b/docs/execution-framework/bench_executor/morphkgc.html index f502c12..049b159 100644 --- a/docs/execution-framework/bench_executor/morphkgc.html +++ b/docs/execution-framework/bench_executor/morphkgc.html @@ -126,7 +126,7 @@

    42 self._logger = Logger(__name__, directory, verbose) 43 os.umask(0) 44 os.makedirs(os.path.join(self._data_path, 'morphkgc'), exist_ok=True) - 45 super().__init__(f'blindreviewing/morph-kgc:v{VERSION}', 'Morph-KGC', + 45 super().__init__(f'kgconstruct/morph-kgc:v{VERSION}', 'Morph-KGC', 46 self._logger, 47 volumes=[f'{self._data_path}/morphkgc:/data', 48 f'{self._data_path}/shared:/data/shared']) @@ -344,7 +344,7 @@

    43 self._logger = Logger(__name__, directory, verbose) 44 os.umask(0) 45 os.makedirs(os.path.join(self._data_path, 'morphkgc'), exist_ok=True) - 46 super().__init__(f'blindreviewing/morph-kgc:v{VERSION}', 'Morph-KGC', + 46 super().__init__(f'kgconstruct/morph-kgc:v{VERSION}', 'Morph-KGC', 47 self._logger, 48 volumes=[f'{self._data_path}/morphkgc:/data', 49 f'{self._data_path}/shared:/data/shared']) @@ -538,7 +538,7 @@

    43 self._logger = Logger(__name__, directory, verbose) 44 os.umask(0) 45 os.makedirs(os.path.join(self._data_path, 'morphkgc'), exist_ok=True) -46 super().__init__(f'blindreviewing/morph-kgc:v{VERSION}', 'Morph-KGC', +46 super().__init__(f'kgconstruct/morph-kgc:v{VERSION}', 'Morph-KGC', 47 self._logger, 48 volumes=[f'{self._data_path}/morphkgc:/data', 49 f'{self._data_path}/shared:/data/shared']) diff --git a/docs/execution-framework/bench_executor/morphrdb.html b/docs/execution-framework/bench_executor/morphrdb.html index a076384..6906551 100644 --- a/docs/execution-framework/bench_executor/morphrdb.html +++ b/docs/execution-framework/bench_executor/morphrdb.html @@ -125,7 +125,7 @@

    42 43 os.umask(0) 44 os.makedirs(os.path.join(self._data_path, 'morphrdb'), exist_ok=True) - 45 super().__init__(f'blindreviewing/morph-rdb:v{VERSION}', 'Morph-RDB', + 45 super().__init__(f'kgconstruct/morph-rdb:v{VERSION}', 'Morph-RDB', 46 self._logger, 47 volumes=[f'{self._data_path}/shared:/data/shared', 48 f'{self._data_path}/morphrdb:/data']) @@ -335,7 +335,7 @@

    43 44 os.umask(0) 45 os.makedirs(os.path.join(self._data_path, 'morphrdb'), exist_ok=True) - 46 super().__init__(f'blindreviewing/morph-rdb:v{VERSION}', 'Morph-RDB', + 46 super().__init__(f'kgconstruct/morph-rdb:v{VERSION}', 'Morph-RDB', 47 self._logger, 48 volumes=[f'{self._data_path}/shared:/data/shared', 49 f'{self._data_path}/morphrdb:/data']) @@ -521,7 +521,7 @@

    43 44 os.umask(0) 45 os.makedirs(os.path.join(self._data_path, 'morphrdb'), exist_ok=True) -46 super().__init__(f'blindreviewing/morph-rdb:v{VERSION}', 'Morph-RDB', +46 super().__init__(f'kgconstruct/morph-rdb:v{VERSION}', 'Morph-RDB', 47 self._logger, 48 volumes=[f'{self._data_path}/shared:/data/shared', 49 f'{self._data_path}/morphrdb:/data']) diff --git a/docs/execution-framework/bench_executor/mysql.html b/docs/execution-framework/bench_executor/mysql.html index be92358..a2ae724 100644 --- a/docs/execution-framework/bench_executor/mysql.html +++ b/docs/execution-framework/bench_executor/mysql.html @@ -162,7 +162,7 @@

    52 os.makedirs(tmp_dir, exist_ok=True) 53 os.makedirs(os.path.join(self._data_path, 'mysql'), exist_ok=True) 54 - 55 super().__init__(f'blindreviewing/mysql:v{VERSION}', 'MySQL', + 55 super().__init__(f'kgconstruct/mysql:v{VERSION}', 'MySQL', 56 self._logger, 57 ports={PORT: PORT}, 58 environment={'MYSQL_ROOT_PASSWORD': 'root', @@ -541,7 +541,7 @@

    53 os.makedirs(tmp_dir, exist_ok=True) 54 os.makedirs(os.path.join(self._data_path, 'mysql'), exist_ok=True) 55 - 56 super().__init__(f'blindreviewing/mysql:v{VERSION}', 'MySQL', + 56 super().__init__(f'kgconstruct/mysql:v{VERSION}', 'MySQL', 57 self._logger, 58 ports={PORT: PORT}, 59 environment={'MYSQL_ROOT_PASSWORD': 'root', @@ -827,7 +827,7 @@

    53 os.makedirs(tmp_dir, exist_ok=True) 54 os.makedirs(os.path.join(self._data_path, 'mysql'), exist_ok=True) 55 -56 super().__init__(f'blindreviewing/mysql:v{VERSION}', 'MySQL', +56 super().__init__(f'kgconstruct/mysql:v{VERSION}', 'MySQL', 57 self._logger, 58 ports={PORT: PORT}, 59 environment={'MYSQL_ROOT_PASSWORD': 'root', diff --git a/docs/execution-framework/bench_executor/ontop.html b/docs/execution-framework/bench_executor/ontop.html index 0e06e2f..7516699 100644 --- a/docs/execution-framework/bench_executor/ontop.html +++ b/docs/execution-framework/bench_executor/ontop.html @@ -176,7 +176,7 @@

    64 65 environment = {'ONTOP_JAVA_ARGS': f'-Xmx{max_heap} -Xms{max_heap}', 66 'ONTOP_LOG_LEVEL': log_level} - 67 super().__init__(f'blindreviewing/ontop:v{VERSION}', name, + 67 super().__init__(f'kgconstruct/ontop:v{VERSION}', name, 68 self._logger, 69 ports={'8888': '8888'}, 70 environment=environment, @@ -707,7 +707,7 @@

    65 66 environment = {'ONTOP_JAVA_ARGS': f'-Xmx{max_heap} -Xms{max_heap}', 67 'ONTOP_LOG_LEVEL': log_level} - 68 super().__init__(f'blindreviewing/ontop:v{VERSION}', name, + 68 super().__init__(f'kgconstruct/ontop:v{VERSION}', name, 69 self._logger, 70 ports={'8888': '8888'}, 71 environment=environment, @@ -1002,7 +1002,7 @@

    65 66 environment = {'ONTOP_JAVA_ARGS': f'-Xmx{max_heap} -Xms{max_heap}', 67 'ONTOP_LOG_LEVEL': log_level} -68 super().__init__(f'blindreviewing/ontop:v{VERSION}', name, +68 super().__init__(f'kgconstruct/ontop:v{VERSION}', name, 69 self._logger, 70 ports={'8888': '8888'}, 71 environment=environment, diff --git a/docs/execution-framework/bench_executor/postgresql.html b/docs/execution-framework/bench_executor/postgresql.html index 8f47207..f58af26 100644 --- a/docs/execution-framework/bench_executor/postgresql.html +++ b/docs/execution-framework/bench_executor/postgresql.html @@ -168,7 +168,7 @@

    55 os.makedirs(os.path.join(self._data_path, 'postgresql'), exist_ok=True) 56 self._tables: List[str] = [] 57 - 58 super().__init__(f'blindreviewing/postgresql:v{VERSION}', 'PostgreSQL', + 58 super().__init__(f'kgconstruct/postgresql:v{VERSION}', 'PostgreSQL', 59 self._logger, 60 ports={PORT: PORT}, 61 environment={'POSTGRES_PASSWORD': PASSWORD, @@ -558,7 +558,7 @@

    56 os.makedirs(os.path.join(self._data_path, 'postgresql'), exist_ok=True) 57 self._tables: List[str] = [] 58 - 59 super().__init__(f'blindreviewing/postgresql:v{VERSION}', 'PostgreSQL', + 59 super().__init__(f'kgconstruct/postgresql:v{VERSION}', 'PostgreSQL', 60 self._logger, 61 ports={PORT: PORT}, 62 environment={'POSTGRES_PASSWORD': PASSWORD, @@ -848,7 +848,7 @@

    56 os.makedirs(os.path.join(self._data_path, 'postgresql'), exist_ok=True) 57 self._tables: List[str] = [] 58 -59 super().__init__(f'blindreviewing/postgresql:v{VERSION}', 'PostgreSQL', +59 super().__init__(f'kgconstruct/postgresql:v{VERSION}', 'PostgreSQL', 60 self._logger, 61 ports={PORT: PORT}, 62 environment={'POSTGRES_PASSWORD': PASSWORD, diff --git a/docs/execution-framework/bench_executor/rmlmapper.html b/docs/execution-framework/bench_executor/rmlmapper.html index 4283f14..f531ce9 100644 --- a/docs/execution-framework/bench_executor/rmlmapper.html +++ b/docs/execution-framework/bench_executor/rmlmapper.html @@ -93,16 +93,16 @@

    10 11import os 12import psutil - 13import subprocess - 14from typing import Optional - 15from timeout_decorator import timeout, TimeoutError # type: ignore + 13from typing import Optional + 14from timeout_decorator import timeout, TimeoutError # type: ignore + 15from bench_executor.container import Container 16from bench_executor.logger import Logger 17 - 18VERSION = '6.2.1' + 18VERSION = '6.0.0' 19TIMEOUT = 6 * 3600 # 6 hours 20 21 - 22class RMLMapper(): + 22class RMLMapper(Container): 23 """RMLMapper container for executing R2RML and RML mappings.""" 24 25 def __init__(self, data_path: str, config_path: str, directory: str, @@ -126,139 +126,141 @@

    43 self._verbose = verbose 44 45 os.makedirs(os.path.join(self._data_path, 'rmlmapper'), exist_ok=True) - 46 - 47 @property - 48 def root_mount_directory(self) -> str: - 49 """Subdirectory in the root directory of the case for RMLMapper. + 46 super().__init__(f'kgconstruct/rmlmapper:v{VERSION}', 'RMLMapper', + 47 self._logger, + 48 volumes=[f'{self._data_path}/rmlmapper:/data', + 49 f'{self._data_path}/shared:/data/shared']) 50 - 51 Returns - 52 ------- - 53 subdirectory : str - 54 Subdirectory of the root directory for RMLMapper. - 55 - 56 """ - 57 return __name__.lower() - 58 - 59 @timeout(TIMEOUT) - 60 def _execute_with_timeout(self, arguments: list) -> bool: - 61 """Execute a mapping with a provided timeout. + 51 @property + 52 def root_mount_directory(self) -> str: + 53 """Subdirectory in the root directory of the case for RMLMapper. + 54 + 55 Returns + 56 ------- + 57 subdirectory : str + 58 Subdirectory of the root directory for RMLMapper. + 59 + 60 """ + 61 return __name__.lower() 62 - 63 Returns - 64 ------- - 65 success : bool - 66 Whether the execution was successfull or not. - 67 """ - 68 # Set Java heap to 90% of available memory instead of the default 1/4 - 69 max_heap = int(psutil.virtual_memory().total * 0.9) - 70 - 71 # Execute command - 72 cmd = f'java -Xmx{max_heap} -Xms{max_heap}' + \ - 73 ' -jar rmlmapper.jar' - 74 if self._verbose: - 75 cmd += ' -vvvvvvvvvvvvv' - 76 cmd += f' {" ".join(arguments)}' - 77 - 78 self._logger.debug(f'Executing RMLMapper with arguments ' - 79 f'{" ".join(arguments)}') - 80 - 81 exitcode, output = subprocess.getstatusoutput(cmd) - 82 self._logger.debug(output) - 83 return exitcode == 0 + 63 @timeout(TIMEOUT) + 64 def _execute_with_timeout(self, arguments: list) -> bool: + 65 """Execute a mapping with a provided timeout. + 66 + 67 Returns + 68 ------- + 69 success : bool + 70 Whether the execution was successfull or not. + 71 """ + 72 # Set Java heap to 1/2 of available memory instead of the default 1/4 + 73 max_heap = int(psutil.virtual_memory().total * (1/2)) + 74 + 75 # Execute command + 76 cmd = f'java -Xmx{max_heap} -Xms{max_heap}' + \ + 77 ' -jar /rmlmapper/rmlmapper.jar' + 78 if self._verbose: + 79 cmd += ' -vvvvvvvvvvvvv' + 80 cmd += f' {" ".join(arguments)}' + 81 + 82 self._logger.debug(f'Executing RMLMapper with arguments ' + 83 f'{" ".join(arguments)}') 84 - 85 def execute(self, arguments: list) -> bool: - 86 """Execute RMLMapper with given arguments. - 87 - 88 Parameters - 89 ---------- - 90 arguments : list - 91 Arguments to supply to RMLMapper. - 92 - 93 Returns - 94 ------- - 95 success : bool - 96 Whether the execution succeeded or not. - 97 """ - 98 try: - 99 return self._execute_with_timeout(arguments) -100 except TimeoutError: -101 msg = f'Timeout ({TIMEOUT}s) reached for RMLMapper' -102 self._logger.warning(msg) -103 -104 return False + 85 return self.run_and_wait_for_exit(cmd) + 86 + 87 def execute(self, arguments: list) -> bool: + 88 """Execute RMLMapper with given arguments. + 89 + 90 Parameters + 91 ---------- + 92 arguments : list + 93 Arguments to supply to RMLMapper. + 94 + 95 Returns + 96 ------- + 97 success : bool + 98 Whether the execution succeeded or not. + 99 """ +100 try: +101 return self._execute_with_timeout(arguments) +102 except TimeoutError: +103 msg = f'Timeout ({TIMEOUT}s) reached for RMLMapper' +104 self._logger.warning(msg) 105 -106 def execute_mapping(self, -107 mapping_file: str, -108 output_file: str, -109 serialization: str, -110 rdb_username: Optional[str] = None, -111 rdb_password: Optional[str] = None, -112 rdb_host: Optional[str] = None, -113 rdb_port: Optional[int] = None, -114 rdb_name: Optional[str] = None, -115 rdb_type: Optional[str] = None) -> bool: -116 """Execute a mapping file with RMLMapper. -117 -118 N-Quads and N-Triples are currently supported as serialization -119 format for RMLMapper. -120 -121 Parameters -122 ---------- -123 mapping_file : str -124 Path to the mapping file to execute. -125 output_file : str -126 Name of the output file to store the triples in. -127 serialization : str -128 Serialization format to use. -129 rdb_username : Optional[str] -130 Username for the database, required when a database is used as -131 source. -132 rdb_password : Optional[str] -133 Password for the database, required when a database is used as -134 source. -135 rdb_host : Optional[str] -136 Hostname for the database, required when a database is used as -137 source. -138 rdb_port : Optional[int] -139 Port for the database, required when a database is used as source. -140 rdb_name : Optional[str] -141 Database name for the database, required when a database is used as -142 source. -143 rdb_type : Optional[str] -144 Database type, required when a database is used as source. -145 -146 Returns -147 ------- -148 success : bool -149 Whether the execution was successfull or not. -150 """ -151 arguments = ['-m', os.path.join('/data/shared/', mapping_file), -152 '-s', serialization, -153 '-o', os.path.join('/data/shared/', output_file), -154 '-d'] # Enable duplicate removal -155 -156 if rdb_username is not None and rdb_password is not None \ -157 and rdb_host is not None and rdb_port is not None \ -158 and rdb_name is not None and rdb_type is not None: -159 -160 arguments.append('-u') -161 arguments.append(rdb_username) -162 arguments.append('-p') -163 arguments.append(rdb_password) -164 -165 parameters = '' -166 if rdb_type == 'MySQL': -167 protocol = 'jdbc:mysql' -168 parameters = '?allowPublicKeyRetrieval=true&useSSL=false' -169 elif rdb_type == 'PostgreSQL': -170 protocol = 'jdbc:postgresql' -171 else: -172 raise ValueError(f'Unknown RDB type: "{rdb_type}"') -173 rdb_dsn = f'\'{protocol}://{rdb_host}:{rdb_port}/' + \ -174 f'{rdb_name}{parameters}\'' -175 arguments.append('-dsn') -176 arguments.append(rdb_dsn) -177 -178 return self.execute(arguments) +106 return False +107 +108 def execute_mapping(self, +109 mapping_file: str, +110 output_file: str, +111 serialization: str, +112 rdb_username: Optional[str] = None, +113 rdb_password: Optional[str] = None, +114 rdb_host: Optional[str] = None, +115 rdb_port: Optional[int] = None, +116 rdb_name: Optional[str] = None, +117 rdb_type: Optional[str] = None) -> bool: +118 """Execute a mapping file with RMLMapper. +119 +120 N-Quads and N-Triples are currently supported as serialization +121 format for RMLMapper. +122 +123 Parameters +124 ---------- +125 mapping_file : str +126 Path to the mapping file to execute. +127 output_file : str +128 Name of the output file to store the triples in. +129 serialization : str +130 Serialization format to use. +131 rdb_username : Optional[str] +132 Username for the database, required when a database is used as +133 source. +134 rdb_password : Optional[str] +135 Password for the database, required when a database is used as +136 source. +137 rdb_host : Optional[str] +138 Hostname for the database, required when a database is used as +139 source. +140 rdb_port : Optional[int] +141 Port for the database, required when a database is used as source. +142 rdb_name : Optional[str] +143 Database name for the database, required when a database is used as +144 source. +145 rdb_type : Optional[str] +146 Database type, required when a database is used as source. +147 +148 Returns +149 ------- +150 success : bool +151 Whether the execution was successfull or not. +152 """ +153 arguments = ['-m', os.path.join('/data/shared/', mapping_file), +154 '-s', serialization, +155 '-o', os.path.join('/data/shared/', output_file), +156 '-d'] # Enable duplicate removal +157 +158 if rdb_username is not None and rdb_password is not None \ +159 and rdb_host is not None and rdb_port is not None \ +160 and rdb_name is not None and rdb_type is not None: +161 +162 arguments.append('-u') +163 arguments.append(rdb_username) +164 arguments.append('-p') +165 arguments.append(rdb_password) +166 +167 parameters = '' +168 if rdb_type == 'MySQL': +169 protocol = 'jdbc:mysql' +170 parameters = '?allowPublicKeyRetrieval=true&useSSL=false' +171 elif rdb_type == 'PostgreSQL': +172 protocol = 'jdbc:postgresql' +173 else: +174 raise ValueError(f'Unknown RDB type: "{rdb_type}"') +175 rdb_dsn = f'\'{protocol}://{rdb_host}:{rdb_port}/' + \ +176 f'{rdb_name}{parameters}\'' +177 arguments.append('-dsn') +178 arguments.append(rdb_dsn) +179 +180 return self.execute(arguments) @@ -266,7 +268,7 @@

    VERSION = -'6.2.1' +'6.0.0'
    @@ -292,13 +294,13 @@

    class - RMLMapper: + RMLMapper(bench_executor.container.Container):
    - 
     23class RMLMapper():
+            
     23class RMLMapper(Container):
  24    """RMLMapper container for executing R2RML and RML mappings."""
  25
  26    def __init__(self, data_path: str, config_path: str, directory: str,
@@ -322,139 +324,141 @@ 
    
  44        self._verbose = verbose
  45
  46        os.makedirs(os.path.join(self._data_path, 'rmlmapper'), exist_ok=True)
- 47
- 48    @property
- 49    def root_mount_directory(self) -> str:
- 50        """Subdirectory in the root directory of the case for RMLMapper.
+ 47        super().__init__(f'kgconstruct/rmlmapper:v{VERSION}', 'RMLMapper',
+ 48                         self._logger,
+ 49                         volumes=[f'{self._data_path}/rmlmapper:/data',
+ 50                                  f'{self._data_path}/shared:/data/shared'])
  51
- 52        Returns
- 53        -------
- 54        subdirectory : str
- 55            Subdirectory of the root directory for RMLMapper.
- 56
- 57        """
- 58        return __name__.lower()
- 59
- 60    @timeout(TIMEOUT)
- 61    def _execute_with_timeout(self, arguments: list) -> bool:
- 62        """Execute a mapping with a provided timeout.
+ 52    @property
+ 53    def root_mount_directory(self) -> str:
+ 54        """Subdirectory in the root directory of the case for RMLMapper.
+ 55
+ 56        Returns
+ 57        -------
+ 58        subdirectory : str
+ 59            Subdirectory of the root directory for RMLMapper.
+ 60
+ 61        """
+ 62        return __name__.lower()
  63
- 64        Returns
- 65        -------
- 66        success : bool
- 67            Whether the execution was successfull or not.
- 68        """
- 69        # Set Java heap to 90% of available memory instead of the default 1/4
- 70        max_heap = int(psutil.virtual_memory().total * 0.9)
- 71
- 72        # Execute command
- 73        cmd = f'java -Xmx{max_heap} -Xms{max_heap}' + \
- 74              ' -jar rmlmapper.jar'
- 75        if self._verbose:
- 76            cmd += ' -vvvvvvvvvvvvv'
- 77        cmd += f' {" ".join(arguments)}'
- 78
- 79        self._logger.debug(f'Executing RMLMapper with arguments '
- 80                           f'{" ".join(arguments)}')
- 81
- 82        exitcode, output = subprocess.getstatusoutput(cmd)
- 83        self._logger.debug(output)
- 84        return exitcode == 0
+ 64    @timeout(TIMEOUT)
+ 65    def _execute_with_timeout(self, arguments: list) -> bool:
+ 66        """Execute a mapping with a provided timeout.
+ 67
+ 68        Returns
+ 69        -------
+ 70        success : bool
+ 71            Whether the execution was successfull or not.
+ 72        """
+ 73        # Set Java heap to 1/2 of available memory instead of the default 1/4
+ 74        max_heap = int(psutil.virtual_memory().total * (1/2))
+ 75
+ 76        # Execute command
+ 77        cmd = f'java -Xmx{max_heap} -Xms{max_heap}' + \
+ 78              ' -jar /rmlmapper/rmlmapper.jar'
+ 79        if self._verbose:
+ 80            cmd += ' -vvvvvvvvvvvvv'
+ 81        cmd += f' {" ".join(arguments)}'
+ 82
+ 83        self._logger.debug(f'Executing RMLMapper with arguments '
+ 84                           f'{" ".join(arguments)}')
  85
- 86    def execute(self, arguments: list) -> bool:
- 87        """Execute RMLMapper with given arguments.
- 88
- 89        Parameters
- 90        ----------
- 91        arguments : list
- 92            Arguments to supply to RMLMapper.
- 93
- 94        Returns
- 95        -------
- 96        success : bool
- 97            Whether the execution succeeded or not.
- 98        """
- 99        try:
-100            return self._execute_with_timeout(arguments)
-101        except TimeoutError:
-102            msg = f'Timeout ({TIMEOUT}s) reached for RMLMapper'
-103            self._logger.warning(msg)
-104
-105        return False
+ 86        return self.run_and_wait_for_exit(cmd)
+ 87
+ 88    def execute(self, arguments: list) -> bool:
+ 89        """Execute RMLMapper with given arguments.
+ 90
+ 91        Parameters
+ 92        ----------
+ 93        arguments : list
+ 94            Arguments to supply to RMLMapper.
+ 95
+ 96        Returns
+ 97        -------
+ 98        success : bool
+ 99            Whether the execution succeeded or not.
+100        """
+101        try:
+102            return self._execute_with_timeout(arguments)
+103        except TimeoutError:
+104            msg = f'Timeout ({TIMEOUT}s) reached for RMLMapper'
+105            self._logger.warning(msg)
 106
-107    def execute_mapping(self,
-108                        mapping_file: str,
-109                        output_file: str,
-110                        serialization: str,
-111                        rdb_username: Optional[str] = None,
-112                        rdb_password: Optional[str] = None,
-113                        rdb_host: Optional[str] = None,
-114                        rdb_port: Optional[int] = None,
-115                        rdb_name: Optional[str] = None,
-116                        rdb_type: Optional[str] = None) -> bool:
-117        """Execute a mapping file with RMLMapper.
-118
-119        N-Quads and N-Triples are currently supported as serialization
-120        format for RMLMapper.
-121
-122        Parameters
-123        ----------
-124        mapping_file : str
-125            Path to the mapping file to execute.
-126        output_file : str
-127            Name of the output file to store the triples in.
-128        serialization : str
-129            Serialization format to use.
-130        rdb_username : Optional[str]
-131            Username for the database, required when a database is used as
-132            source.
-133        rdb_password : Optional[str]
-134            Password for the database, required when a database is used as
-135            source.
-136        rdb_host : Optional[str]
-137            Hostname for the database, required when a database is used as
-138            source.
-139        rdb_port : Optional[int]
-140            Port for the database, required when a database is used as source.
-141        rdb_name : Optional[str]
-142            Database name for the database, required when a database is used as
-143            source.
-144        rdb_type : Optional[str]
-145            Database type, required when a database is used as source.
-146
-147        Returns
-148        -------
-149        success : bool
-150            Whether the execution was successfull or not.
-151        """
-152        arguments = ['-m', os.path.join('/data/shared/', mapping_file),
-153                     '-s', serialization,
-154                     '-o', os.path.join('/data/shared/', output_file),
-155                     '-d']  # Enable duplicate removal
-156
-157        if rdb_username is not None and rdb_password is not None \
-158                and rdb_host is not None and rdb_port is not None \
-159                and rdb_name is not None and rdb_type is not None:
-160
-161            arguments.append('-u')
-162            arguments.append(rdb_username)
-163            arguments.append('-p')
-164            arguments.append(rdb_password)
-165
-166            parameters = ''
-167            if rdb_type == 'MySQL':
-168                protocol = 'jdbc:mysql'
-169                parameters = '?allowPublicKeyRetrieval=true&useSSL=false'
-170            elif rdb_type == 'PostgreSQL':
-171                protocol = 'jdbc:postgresql'
-172            else:
-173                raise ValueError(f'Unknown RDB type: "{rdb_type}"')
-174            rdb_dsn = f'\'{protocol}://{rdb_host}:{rdb_port}/' + \
-175                      f'{rdb_name}{parameters}\''
-176            arguments.append('-dsn')
-177            arguments.append(rdb_dsn)
-178
-179        return self.execute(arguments)
+107        return False
+108
+109    def execute_mapping(self,
+110                        mapping_file: str,
+111                        output_file: str,
+112                        serialization: str,
+113                        rdb_username: Optional[str] = None,
+114                        rdb_password: Optional[str] = None,
+115                        rdb_host: Optional[str] = None,
+116                        rdb_port: Optional[int] = None,
+117                        rdb_name: Optional[str] = None,
+118                        rdb_type: Optional[str] = None) -> bool:
+119        """Execute a mapping file with RMLMapper.
+120
+121        N-Quads and N-Triples are currently supported as serialization
+122        format for RMLMapper.
+123
+124        Parameters
+125        ----------
+126        mapping_file : str
+127            Path to the mapping file to execute.
+128        output_file : str
+129            Name of the output file to store the triples in.
+130        serialization : str
+131            Serialization format to use.
+132        rdb_username : Optional[str]
+133            Username for the database, required when a database is used as
+134            source.
+135        rdb_password : Optional[str]
+136            Password for the database, required when a database is used as
+137            source.
+138        rdb_host : Optional[str]
+139            Hostname for the database, required when a database is used as
+140            source.
+141        rdb_port : Optional[int]
+142            Port for the database, required when a database is used as source.
+143        rdb_name : Optional[str]
+144            Database name for the database, required when a database is used as
+145            source.
+146        rdb_type : Optional[str]
+147            Database type, required when a database is used as source.
+148
+149        Returns
+150        -------
+151        success : bool
+152            Whether the execution was successfull or not.
+153        """
+154        arguments = ['-m', os.path.join('/data/shared/', mapping_file),
+155                     '-s', serialization,
+156                     '-o', os.path.join('/data/shared/', output_file),
+157                     '-d']  # Enable duplicate removal
+158
+159        if rdb_username is not None and rdb_password is not None \
+160                and rdb_host is not None and rdb_port is not None \
+161                and rdb_name is not None and rdb_type is not None:
+162
+163            arguments.append('-u')
+164            arguments.append(rdb_username)
+165            arguments.append('-p')
+166            arguments.append(rdb_password)
+167
+168            parameters = ''
+169            if rdb_type == 'MySQL':
+170                protocol = 'jdbc:mysql'
+171                parameters = '?allowPublicKeyRetrieval=true&useSSL=false'
+172            elif rdb_type == 'PostgreSQL':
+173                protocol = 'jdbc:postgresql'
+174            else:
+175                raise ValueError(f'Unknown RDB type: "{rdb_type}"')
+176            rdb_dsn = f'\'{protocol}://{rdb_host}:{rdb_port}/' + \
+177                      f'{rdb_name}{parameters}\''
+178            arguments.append('-dsn')
+179            arguments.append(rdb_dsn)
+180
+181        return self.execute(arguments)
 
    
 
 
@@ -493,6 +497,10 @@ 
    
 44        self._verbose = verbose
 45
 46        os.makedirs(os.path.join(self._data_path, 'rmlmapper'), exist_ok=True)
+47        super().__init__(f'kgconstruct/rmlmapper:v{VERSION}', 'RMLMapper',
+48                         self._logger,
+49                         volumes=[f'{self._data_path}/rmlmapper:/data',
+50                                  f'{self._data_path}/shared:/data/shared'])
    @@ -523,17 +531,17 @@

    Parameters
    - 
    48    @property
-49    def root_mount_directory(self) -> str:
-50        """Subdirectory in the root directory of the case for RMLMapper.
-51
-52        Returns
-53        -------
-54        subdirectory : str
-55            Subdirectory of the root directory for RMLMapper.
-56
-57        """
-58        return __name__.lower()
+            
    52    @property
+53    def root_mount_directory(self) -> str:
+54        """Subdirectory in the root directory of the case for RMLMapper.
+55
+56        Returns
+57        -------
+58        subdirectory : str
+59            Subdirectory of the root directory for RMLMapper.
+60
+61        """
+62        return __name__.lower()
 
    
 
 
@@ -560,26 +568,26 @@ 
    Returns
    - 
     86    def execute(self, arguments: list) -> bool:
- 87        """Execute RMLMapper with given arguments.
- 88
- 89        Parameters
- 90        ----------
- 91        arguments : list
- 92            Arguments to supply to RMLMapper.
- 93
- 94        Returns
- 95        -------
- 96        success : bool
- 97            Whether the execution succeeded or not.
- 98        """
- 99        try:
-100            return self._execute_with_timeout(arguments)
-101        except TimeoutError:
-102            msg = f'Timeout ({TIMEOUT}s) reached for RMLMapper'
-103            self._logger.warning(msg)
-104
-105        return False
+            
     88    def execute(self, arguments: list) -> bool:
+ 89        """Execute RMLMapper with given arguments.
+ 90
+ 91        Parameters
+ 92        ----------
+ 93        arguments : list
+ 94            Arguments to supply to RMLMapper.
+ 95
+ 96        Returns
+ 97        -------
+ 98        success : bool
+ 99            Whether the execution succeeded or not.
+100        """
+101        try:
+102            return self._execute_with_timeout(arguments)
+103        except TimeoutError:
+104            msg = f'Timeout ({TIMEOUT}s) reached for RMLMapper'
+105            self._logger.warning(msg)
+106
+107        return False
 
    
 
 
@@ -613,79 +621,79 @@ 
    Returns
    - 
    107    def execute_mapping(self,
-108                        mapping_file: str,
-109                        output_file: str,
-110                        serialization: str,
-111                        rdb_username: Optional[str] = None,
-112                        rdb_password: Optional[str] = None,
-113                        rdb_host: Optional[str] = None,
-114                        rdb_port: Optional[int] = None,
-115                        rdb_name: Optional[str] = None,
-116                        rdb_type: Optional[str] = None) -> bool:
-117        """Execute a mapping file with RMLMapper.
-118
-119        N-Quads and N-Triples are currently supported as serialization
-120        format for RMLMapper.
-121
-122        Parameters
-123        ----------
-124        mapping_file : str
-125            Path to the mapping file to execute.
-126        output_file : str
-127            Name of the output file to store the triples in.
-128        serialization : str
-129            Serialization format to use.
-130        rdb_username : Optional[str]
-131            Username for the database, required when a database is used as
-132            source.
-133        rdb_password : Optional[str]
-134            Password for the database, required when a database is used as
-135            source.
-136        rdb_host : Optional[str]
-137            Hostname for the database, required when a database is used as
-138            source.
-139        rdb_port : Optional[int]
-140            Port for the database, required when a database is used as source.
-141        rdb_name : Optional[str]
-142            Database name for the database, required when a database is used as
-143            source.
-144        rdb_type : Optional[str]
-145            Database type, required when a database is used as source.
-146
-147        Returns
-148        -------
-149        success : bool
-150            Whether the execution was successfull or not.
-151        """
-152        arguments = ['-m', os.path.join('/data/shared/', mapping_file),
-153                     '-s', serialization,
-154                     '-o', os.path.join('/data/shared/', output_file),
-155                     '-d']  # Enable duplicate removal
-156
-157        if rdb_username is not None and rdb_password is not None \
-158                and rdb_host is not None and rdb_port is not None \
-159                and rdb_name is not None and rdb_type is not None:
-160
-161            arguments.append('-u')
-162            arguments.append(rdb_username)
-163            arguments.append('-p')
-164            arguments.append(rdb_password)
-165
-166            parameters = ''
-167            if rdb_type == 'MySQL':
-168                protocol = 'jdbc:mysql'
-169                parameters = '?allowPublicKeyRetrieval=true&useSSL=false'
-170            elif rdb_type == 'PostgreSQL':
-171                protocol = 'jdbc:postgresql'
-172            else:
-173                raise ValueError(f'Unknown RDB type: "{rdb_type}"')
-174            rdb_dsn = f'\'{protocol}://{rdb_host}:{rdb_port}/' + \
-175                      f'{rdb_name}{parameters}\''
-176            arguments.append('-dsn')
-177            arguments.append(rdb_dsn)
-178
-179        return self.execute(arguments)
+            
    109    def execute_mapping(self,
+110                        mapping_file: str,
+111                        output_file: str,
+112                        serialization: str,
+113                        rdb_username: Optional[str] = None,
+114                        rdb_password: Optional[str] = None,
+115                        rdb_host: Optional[str] = None,
+116                        rdb_port: Optional[int] = None,
+117                        rdb_name: Optional[str] = None,
+118                        rdb_type: Optional[str] = None) -> bool:
+119        """Execute a mapping file with RMLMapper.
+120
+121        N-Quads and N-Triples are currently supported as serialization
+122        format for RMLMapper.
+123
+124        Parameters
+125        ----------
+126        mapping_file : str
+127            Path to the mapping file to execute.
+128        output_file : str
+129            Name of the output file to store the triples in.
+130        serialization : str
+131            Serialization format to use.
+132        rdb_username : Optional[str]
+133            Username for the database, required when a database is used as
+134            source.
+135        rdb_password : Optional[str]
+136            Password for the database, required when a database is used as
+137            source.
+138        rdb_host : Optional[str]
+139            Hostname for the database, required when a database is used as
+140            source.
+141        rdb_port : Optional[int]
+142            Port for the database, required when a database is used as source.
+143        rdb_name : Optional[str]
+144            Database name for the database, required when a database is used as
+145            source.
+146        rdb_type : Optional[str]
+147            Database type, required when a database is used as source.
+148
+149        Returns
+150        -------
+151        success : bool
+152            Whether the execution was successfull or not.
+153        """
+154        arguments = ['-m', os.path.join('/data/shared/', mapping_file),
+155                     '-s', serialization,
+156                     '-o', os.path.join('/data/shared/', output_file),
+157                     '-d']  # Enable duplicate removal
+158
+159        if rdb_username is not None and rdb_password is not None \
+160                and rdb_host is not None and rdb_port is not None \
+161                and rdb_name is not None and rdb_type is not None:
+162
+163            arguments.append('-u')
+164            arguments.append(rdb_username)
+165            arguments.append('-p')
+166            arguments.append(rdb_password)
+167
+168            parameters = ''
+169            if rdb_type == 'MySQL':
+170                protocol = 'jdbc:mysql'
+171                parameters = '?allowPublicKeyRetrieval=true&useSSL=false'
+172            elif rdb_type == 'PostgreSQL':
+173                protocol = 'jdbc:postgresql'
+174            else:
+175                raise ValueError(f'Unknown RDB type: "{rdb_type}"')
+176            rdb_dsn = f'\'{protocol}://{rdb_host}:{rdb_port}/' + \
+177                      f'{rdb_name}{parameters}\''
+178            arguments.append('-dsn')
+179            arguments.append(rdb_dsn)
+180
+181        return self.execute(arguments)
 
    
 
 
@@ -731,6 +739,21 @@ 
    Returns
    +
    +
    Inherited Members
    +
    + +
    +
    + \ No newline at end of file diff --git a/docs/execution-framework/bench_executor/rmlstreamer.html b/docs/execution-framework/bench_executor/rmlstreamer.html index 1bd5d06..17d8160 100644 --- a/docs/execution-framework/bench_executor/rmlstreamer.html +++ b/docs/execution-framework/bench_executor/rmlstreamer.html @@ -119,7 +119,7 @@

    24 25VERSION = '2.5.0' # standalone mode with RDB support 26TIMEOUT = 6 * 3600 # 6 hours - 27IMAGE = f'blindreviewing/rmlstreamer:v{VERSION}' + 27IMAGE = f'kgconstruct/rmlstreamer:v{VERSION}' 28 29 30class RMLStreamer(Container): @@ -416,7 +416,7 @@

    IMAGE = -'blindreviewing/rmlstreamer:v2.5.0' +'kgconstruct/rmlstreamer:v2.5.0'
    diff --git a/docs/execution-framework/bench_executor/sdmrdfizer.html b/docs/execution-framework/bench_executor/sdmrdfizer.html index e985a99..e90b2a8 100644 --- a/docs/execution-framework/bench_executor/sdmrdfizer.html +++ b/docs/execution-framework/bench_executor/sdmrdfizer.html @@ -114,7 +114,7 @@

    20R2RML = Namespace('http://www.w3.org/ns/r2rml#') 21RML = Namespace('http://semweb.mmlab.be/ns/rml#') 22D2RQ = Namespace('http://www.wiwiss.fu-berlin.de/suhl/bizer/D2RQ/0.1#') - 23IMAGE = f'blindreviewing/sdm-rdfizer:v{VERSION}' + 23IMAGE = f'kgconstruct/sdm-rdfizer:v{VERSION}' 24 25 26class SDMRDFizer(Container): @@ -420,7 +420,7 @@

    IMAGE = -'blindreviewing/sdm-rdfizer:v4.6.6.5' +'kgconstruct/sdm-rdfizer:v4.6.6.5'
    diff --git a/docs/execution-framework/bench_executor/virtuoso.html b/docs/execution-framework/bench_executor/virtuoso.html index f9d18b4..b2791fc 100644 --- a/docs/execution-framework/bench_executor/virtuoso.html +++ b/docs/execution-framework/bench_executor/virtuoso.html @@ -192,7 +192,7 @@

    77 'VIRT_Parameters_MaxVectorSize': MAX_VECTOR_SIZE, 78 'VIRT_Parameters_NumberOfBuffers': number_of_buffers, 79 'VIRT_Parameters_MaxDirtyBuffers': max_dirty_buffers} - 80 super().__init__(f'blindreviewing/virtuoso:v{VERSION}', + 80 super().__init__(f'kgconstruct/virtuoso:v{VERSION}', 81 'Virtuoso', self._logger, 82 ports={'8890': '8890', '1111': '1111'}, 83 environment=environment, @@ -550,7 +550,7 @@

    78 'VIRT_Parameters_MaxVectorSize': MAX_VECTOR_SIZE, 79 'VIRT_Parameters_NumberOfBuffers': number_of_buffers, 80 'VIRT_Parameters_MaxDirtyBuffers': max_dirty_buffers} - 81 super().__init__(f'blindreviewing/virtuoso:v{VERSION}', + 81 super().__init__(f'kgconstruct/virtuoso:v{VERSION}', 82 'Virtuoso', self._logger, 83 ports={'8890': '8890', '1111': '1111'}, 84 environment=environment, @@ -814,7 +814,7 @@

    78 'VIRT_Parameters_MaxVectorSize': MAX_VECTOR_SIZE, 79 'VIRT_Parameters_NumberOfBuffers': number_of_buffers, 80 'VIRT_Parameters_MaxDirtyBuffers': max_dirty_buffers} -81 super().__init__(f'blindreviewing/virtuoso:v{VERSION}', +81 super().__init__(f'kgconstruct/virtuoso:v{VERSION}', 82 'Virtuoso', self._logger, 83 ports={'8890': '8890', '1111': '1111'}, 84 environment=environment, diff --git a/docs/execution-framework/bench_executor/yarrrml.html b/docs/execution-framework/bench_executor/yarrrml.html index 22efeae..c4595e8 100644 --- a/docs/execution-framework/bench_executor/yarrrml.html +++ b/docs/execution-framework/bench_executor/yarrrml.html @@ -115,7 +115,7 @@

    38 self._logger = Logger(__name__, directory, verbose) 39 40 os.makedirs(os.path.join(self._data_path, 'yarrrml'), exist_ok=True) -41 super().__init__(f'blindreviewing/yarrrml:v{VERSION}', 'YARRRML', +41 super().__init__(f'kgconstruct/yarrrml:v{VERSION}', 'YARRRML', 42 self._logger, 43 volumes=[f'{self._data_path}/yarrrml:/data', 44 f'{self._data_path}/shared:/data/shared']) @@ -217,7 +217,7 @@

    39 self._logger = Logger(__name__, directory, verbose) 40 41 os.makedirs(os.path.join(self._data_path, 'yarrrml'), exist_ok=True) -42 super().__init__(f'blindreviewing/yarrrml:v{VERSION}', 'YARRRML', +42 super().__init__(f'kgconstruct/yarrrml:v{VERSION}', 'YARRRML', 43 self._logger, 44 volumes=[f'{self._data_path}/yarrrml:/data', 45 f'{self._data_path}/shared:/data/shared']) @@ -306,7 +306,7 @@

    39 self._logger = Logger(__name__, directory, verbose) 40 41 os.makedirs(os.path.join(self._data_path, 'yarrrml'), exist_ok=True) -42 super().__init__(f'blindreviewing/yarrrml:v{VERSION}', 'YARRRML', +42 super().__init__(f'kgconstruct/yarrrml:v{VERSION}', 'YARRRML', 43 self._logger, 44 volumes=[f'{self._data_path}/yarrrml:/data', 45 f'{self._data_path}/shared:/data/shared']) diff --git a/docs/execution-framework/search.js b/docs/execution-framework/search.js index 99515d4..a89bf93 100644 --- a/docs/execution-framework/search.js +++ b/docs/execution-framework/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. 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t=[],n=e.length,i=this._queue.length,o=0;n>o;o++){for(var r=e[o],s=0;i>s&&(r=this._queue[s](r,o,e),void 0!==r&&null!==r);s++);void 0!==r&&null!==r&&t.push(r)}return t},t.Pipeline.prototype.reset=function(){this._queue=[]},t.Pipeline.prototype.get=function(){return this._queue},t.Pipeline.prototype.toJSON=function(){return this._queue.map(function(e){return t.Pipeline.warnIfFunctionNotRegistered(e),e.label})},t.Index=function(){this._fields=[],this._ref="id",this.pipeline=new t.Pipeline,this.documentStore=new t.DocumentStore,this.index={},this.eventEmitter=new t.EventEmitter,this._idfCache={},this.on("add","remove","update",function(){this._idfCache={}}.bind(this))},t.Index.prototype.on=function(){var e=Array.prototype.slice.call(arguments);return this.eventEmitter.addListener.apply(this.eventEmitter,e)},t.Index.prototype.off=function(e,t){return this.eventEmitter.removeListener(e,t)},t.Index.load=function(e){e.version!==t.version&&t.utils.warn("version mismatch: current "+t.version+" 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u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var i=this.index[t].getDocFreq(e),o=1+Math.log(this.documentStore.length/(i+1));return this._idfCache[n]=o,o},t.Index.prototype.getFields=function(){return this._fields.slice()},t.Index.prototype.search=function(e,n){if(!e)return[];e="string"==typeof e?{any:e}:JSON.parse(JSON.stringify(e));var i=null;null!=n&&(i=JSON.stringify(n));for(var o=new t.Configuration(i,this.getFields()).get(),r={},s=Object.keys(e),u=0;u0&&t.push(e);for(var i in n)"docs"!==i&&"df"!==i&&this.expandToken(e+i,t,n[i]);return t},t.InvertedIndex.prototype.toJSON=function(){return{root:this.root}},t.Configuration=function(e,n){var e=e||"";if(void 0==n||null==n)throw new Error("fields should not be null");this.config={};var i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();oThis module holds the Collector class which is responsible for collecting\nmetrics during the execution of a case. It also collects hardware information\nfor provenance reasons when comparing results from cases.

    \n\n

    The following metrics are collected:

    \n\n

    General

    \n\n
      \n
    • name: name of the case being executed.
      • \n
    • index: incremental index for each collected sample.
      • \n
    • step: Number of the step of a collected sample.
      • \n
    • timestamp: The time when the sample was collected.
      • \n
    • version: format version of the collected version, currently v2.
      • \n
    \n\n

    CPU

    \n\n
      \n
    • cpu_user: CPU time spent in userspace.
      • \n
    • cpu_system: CPU time spent in kernelspace.
      • \n
    • cpu_user_system: sum of CPU time userspace and kernelspace.
      • \n
    • cpu_idle: CPU time spent in idle mode.
      • \n
    • cpu_iowait: Time that the CPU has to wait for IO operations to complete.
      • \n
    \n\n

    Memory

    \n\n
      \n
    • memory_ram: Amount of RAM memory in use.
      • \n
    • memory_swap: Amount of SWAP memory in use.
      • \n
    • memory_ram_swap: Sum of the RAM and SWAP memory in use.
      • \n
    \n\n

    Disk

    \n\n
      \n
    • disk_read_count: Number of disk reads.
      • \n
    • disk_write_count: Number of disk writes.
      • \n
    • disk_read_bytes: Number of bytes read from disk.
      • \n
    • disk_write_bytes: Number of bytes written to disk.
      • \n
    • disk_read_time: Time spent to read from disk.
      • \n
    • disk_write_time: Time spent to write to disk.
      • \n
    • disk_busy_time: Time that the disk is busy and all actions are pending.
      • \n
    \n\n

    Network

    \n\n
      \n
    • network_received_count: Number of network packets received.
      • \n
    • network_sent_count: Number of network packets sent.
      • \n
    • network_received_bytes: Number of bytes received over network.
      • \n
    • network_sent_bytes: Number of bytes sent over network.
      • \n
    • network_received_error: Number of errors occured during receiving over\nnetwork.
      • \n
    • network_sent_error: Number of errors occured during sending over network.
      • \n
    • network_received_drop: Number of packets dropped during receiving over\nnetwork.
      • \n
    • network_sent_drop: Number of packets dropped during sending over network.
      • \n
    \n"}, "bench_executor.collector.CASE_INFO_FILE_NAME": {"fullname": "bench_executor.collector.CASE_INFO_FILE_NAME", "modulename": "bench_executor.collector", "qualname": "CASE_INFO_FILE_NAME", "kind": "variable", "doc": "

    \n", "annotation": ": str", "default_value": "'case-info.txt'"}, "bench_executor.collector.METRICS_FILE_NAME": {"fullname": "bench_executor.collector.METRICS_FILE_NAME", "modulename": "bench_executor.collector", "qualname": "METRICS_FILE_NAME", "kind": "variable", "doc": "

    \n", "annotation": ": str", "default_value": "'metrics.csv'"}, "bench_executor.collector.METRICS_VERSION": {"fullname": "bench_executor.collector.METRICS_VERSION", "modulename": "bench_executor.collector", "qualname": "METRICS_VERSION", "kind": "variable", "doc": "

    \n", "annotation": ": int", "default_value": "3"}, "bench_executor.collector.FIELDNAMES": {"fullname": "bench_executor.collector.FIELDNAMES", "modulename": "bench_executor.collector", "qualname": "FIELDNAMES", "kind": "variable", "doc": "

    \n", "annotation": ": List[str]", "default_value": "['name', 'run', 'index', 'step', 'timestamp', 'version', 'cpu_user', 'cpu_system', 'cpu_user_system', 'cpu_idle', 'cpu_iowait', 'memory_ram', 'memory_swap', 'memory_ram_swap', 'disk_read_count', 'disk_write_count', 'disk_read_bytes', 'disk_write_bytes', 'disk_read_time', 'disk_write_time', 'disk_busy_time', 'network_received_count', 'network_sent_count', 'network_received_bytes', 'network_sent_bytes', 'network_received_error', 'network_sent_error', 'network_received_drop', 'network_sent_drop']"}, "bench_executor.collector.ROUND": {"fullname": "bench_executor.collector.ROUND", "modulename": "bench_executor.collector", "qualname": "ROUND", "kind": "variable", "doc": "

    \n", "annotation": ": int", "default_value": "4"}, "bench_executor.collector.step_id": {"fullname": "bench_executor.collector.step_id", "modulename": "bench_executor.collector", "qualname": "step_id", "kind": "variable", "doc": "

    \n", "annotation": ": int", "default_value": "1"}, "bench_executor.collector.Collector": {"fullname": "bench_executor.collector.Collector", "modulename": "bench_executor.collector", "qualname": "Collector", "kind": "class", "doc": "

    Collect metrics samples at a given interval for a run of a case.

    \n"}, "bench_executor.collector.Collector.__init__": {"fullname": "bench_executor.collector.Collector.__init__", "modulename": "bench_executor.collector", "qualname": "Collector.__init__", "kind": "function", "doc": "

    Create an instance of the Collector class.

    \n\n

    Instantiating this class will automatically generate a case-info.txt\nfile which describes the hardware used during collection of the\nmetrics. The file describes:

    \n\n
      \n
    • Case:\n
        \n
      • Name of the case.
        • \n
      • Timestamp when started.
        • \n
      • Directory of the case.
        • \n
      • Number of the run.
        • \n
      • Number of steps in a case.
        • \n
      • \n
    • Hardware:\n
        \n
      • CPU name.
        • \n
      • Number of CPU cores.
        • \n
      • Minimum and maximum CPU core frequency.
        • \n
      • Amount of RAM and SWAP memory
        • \n
      • Available disk storage.
        • \n
      • Available network interfaces and their link speed.
        • \n
      • \n
    • Docker:\n
        \n
      • Version of the Docker daemon
        • \n
      • Docker root directory
        • \n
      • Docker storage driver
        • \n
      • Docker CgroupFS driver and version
        • \n
      • \n
    \n\n
    Parameters
    \n\n
      \n
    • case_name (str):\nName of the case being executed.
      • \n
    • results_run_path (str):\nPath to the results directory of the run currently being executed.
      • \n
    • sample_interval (float):\nSample interval in seconds for collecting metrics.
      • \n
    • number_of_steps (int):\nThe number of steps of the case that is being executed.
      • \n
    • run_id (int):\nThe number of the run that is being executed.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(\tcase_name: str,\tresults_run_path: str,\tsample_interval: float,\tnumber_of_steps: int,\trun_id: int,\tdirectory: str,\tverbose: bool)"}, "bench_executor.collector.Collector.name": {"fullname": "bench_executor.collector.Collector.name", "modulename": "bench_executor.collector", "qualname": "Collector.name", "kind": "variable", "doc": "

    Name of the class: Collector

    \n"}, "bench_executor.collector.Collector.next_step": {"fullname": "bench_executor.collector.Collector.next_step", "modulename": "bench_executor.collector", "qualname": "Collector.next_step", "kind": "function", "doc": "

    Increment the step number by one.

    \n\n

    The step number must always be equal or lower than the number of steps\nin the case.

    \n", "signature": "(self):", "funcdef": "def"}, "bench_executor.collector.Collector.stop": {"fullname": "bench_executor.collector.Collector.stop", "modulename": "bench_executor.collector", "qualname": "Collector.stop", "kind": "function", "doc": "

    End metrics collection.

    \n\n

    Signal the metrics collection thread to stop collecting any metrics.

    \n", "signature": "(self):", "funcdef": "def"}, "bench_executor.collector.scputimes": {"fullname": "bench_executor.collector.scputimes", "modulename": "bench_executor.collector", "qualname": "scputimes", "kind": "class", "doc": "

    scputimes()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.scputimes.__init__": {"fullname": "bench_executor.collector.scputimes.__init__", "modulename": "bench_executor.collector", "qualname": "scputimes.__init__", "kind": "function", "doc": "

    Create new instance of scputimes()

    \n", "signature": "()"}, "bench_executor.collector.sswap": {"fullname": "bench_executor.collector.sswap", "modulename": "bench_executor.collector", "qualname": "sswap", "kind": "class", "doc": "

    sswap()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.sswap.__init__": {"fullname": "bench_executor.collector.sswap.__init__", "modulename": "bench_executor.collector", "qualname": "sswap.__init__", "kind": "function", "doc": "

    Create new instance of sswap()

    \n", "signature": "()"}, "bench_executor.collector.svmem": {"fullname": "bench_executor.collector.svmem", "modulename": "bench_executor.collector", "qualname": "svmem", "kind": "class", "doc": "

    svmem()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.svmem.__init__": {"fullname": "bench_executor.collector.svmem.__init__", "modulename": "bench_executor.collector", "qualname": "svmem.__init__", "kind": "function", "doc": "

    Create new instance of svmem()

    \n", "signature": "()"}, "bench_executor.collector.sdiskio": {"fullname": "bench_executor.collector.sdiskio", "modulename": "bench_executor.collector", "qualname": "sdiskio", "kind": "class", "doc": "

    sdiskio()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.sdiskio.__init__": {"fullname": "bench_executor.collector.sdiskio.__init__", "modulename": "bench_executor.collector", "qualname": "sdiskio.__init__", "kind": "function", "doc": "

    Create new instance of sdiskio()

    \n", "signature": "()"}, "bench_executor.collector.snetio": {"fullname": "bench_executor.collector.snetio", "modulename": "bench_executor.collector", "qualname": "snetio", "kind": "class", "doc": "

    snetio()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.snetio.__init__": {"fullname": "bench_executor.collector.snetio.__init__", "modulename": "bench_executor.collector", "qualname": "snetio.__init__", "kind": "function", "doc": "

    Create new instance of snetio()

    \n", "signature": "()"}, "bench_executor.container": {"fullname": "bench_executor.container", "modulename": "bench_executor.container", "kind": "module", "doc": "

    This module holds the Container and ContainerManager classes. The Container\nclass is responsible for abstracting the Docker containers and allow running\ncontainers easily and make sure they are initialized before using them.\nThe Containermanager class allows to create container networks, list all\nrunning containers and stop them.

    \n"}, "bench_executor.container.WAIT_TIME": {"fullname": "bench_executor.container.WAIT_TIME", "modulename": "bench_executor.container", "qualname": "WAIT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "1"}, "bench_executor.container.TIMEOUT_TIME": {"fullname": "bench_executor.container.TIMEOUT_TIME", "modulename": "bench_executor.container", "qualname": "TIMEOUT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "600"}, "bench_executor.container.NETWORK_NAME": {"fullname": "bench_executor.container.NETWORK_NAME", "modulename": "bench_executor.container", "qualname": "NETWORK_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'bench_executor'"}, "bench_executor.container.ContainerManager": {"fullname": "bench_executor.container.ContainerManager", "modulename": "bench_executor.container", "qualname": "ContainerManager", "kind": "class", "doc": "

    Manage containers and networks.

    \n"}, "bench_executor.container.ContainerManager.__init__": {"fullname": "bench_executor.container.ContainerManager.__init__", "modulename": "bench_executor.container", "qualname": "ContainerManager.__init__", "kind": "function", "doc": "

    Creates an instance of the ContainerManager class.

    \n", "signature": "(docker: bench_executor.docker.Docker)"}, "bench_executor.container.ContainerManager.create_network": {"fullname": "bench_executor.container.ContainerManager.create_network", "modulename": "bench_executor.container", "qualname": "ContainerManager.create_network", "kind": "function", "doc": "

    Create a container network.

    \n\n
    Parameters
    \n\n
      \n
    • name (str):\nName of the network
      • \n
    \n", "signature": "(self, name: str):", "funcdef": "def"}, "bench_executor.container.Container": {"fullname": "bench_executor.container.Container", "modulename": "bench_executor.container", "qualname": "Container", "kind": "class", "doc": "

    Container abstracts a Docker container

    \n\n

    Abstract how to run a command in a container, start or stop a container,\nor retrieve logs. Also allow to wait for a certain log entry to appear or\nexit successfully.

    \n"}, "bench_executor.container.Container.__init__": {"fullname": "bench_executor.container.Container.__init__", "modulename": "bench_executor.container", "qualname": "Container.__init__", "kind": "function", "doc": "

    Creates an instance of the Container class.

    \n\n
    Parameters
    \n\n
      \n
    • container (str):\nContainer ID.
      • \n
    • name (str):\nPretty name of the container.
      • \n
    • logger (Logger):\nLogger class to use for container logs.
      • \n
    • ports (dict):\nPorts mapping of the container onto the host.
      • \n
    • volumes (list):\nVolumes mapping of the container onto the host.
      • \n
    \n", "signature": "(\tcontainer: str,\tname: str,\tlogger: bench_executor.logger.Logger,\tports: dict = {},\tenvironment: dict = {},\tvolumes: List[str] = [])"}, "bench_executor.container.Container.started": {"fullname": "bench_executor.container.Container.started", "modulename": "bench_executor.container", "qualname": "Container.started", "kind": "variable", "doc": "

    Indicates if the container is already started

    \n", "annotation": ": bool"}, "bench_executor.container.Container.name": {"fullname": "bench_executor.container.Container.name", "modulename": "bench_executor.container", "qualname": "Container.name", "kind": "variable", "doc": "

    The pretty name of the container

    \n", "annotation": ": str"}, "bench_executor.container.Container.run": {"fullname": "bench_executor.container.Container.run", "modulename": "bench_executor.container", "qualname": "Container.run", "kind": "function", "doc": "

    Run the container.

    \n\n

    This is used for containers which are long running to provide services\nsuch as a database or endpoint.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nThe command to execute in the container, optionally and defaults to\nno command.
      • \n
    • detach (bool):\nIf the container may run in the background, default True.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether running the container was successfull or not.
      • \n
    \n", "signature": "(self, command: str = '', detach=True) -> bool:", "funcdef": "def"}, "bench_executor.container.Container.exec": {"fullname": "bench_executor.container.Container.exec", "modulename": "bench_executor.container", "qualname": "Container.exec", "kind": "function", "doc": "

    Execute a command in the container.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nThe command to execute in the container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the command was executed successfully or not.
      • \n
    • logs (list):\nThe logs of the container for executing the command.
      • \n
    \n", "signature": "(self, command: str) -> Tuple[bool, List[str]]:", "funcdef": "def"}, "bench_executor.container.Container.run_and_wait_for_log": {"fullname": "bench_executor.container.Container.run_and_wait_for_log", "modulename": "bench_executor.container", "qualname": "Container.run_and_wait_for_log", "kind": "function", "doc": "

    Run the container and wait for a log line to appear.

    \n\n

    This blocks until the container's log contains the log_line.

    \n\n
    Parameters
    \n\n
      \n
    • log_line (str):\nThe log line to wait for in the logs.
      • \n
    • command (str):\nThe command to execute in the container, optionally and defaults to\nno command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the container exited with status code 0 or not.
      • \n
    \n", "signature": "(self, log_line: str, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.container.Container.run_and_wait_for_exit": {"fullname": "bench_executor.container.Container.run_and_wait_for_exit", "modulename": "bench_executor.container", "qualname": "Container.run_and_wait_for_exit", "kind": "function", "doc": "

    Run the container and wait for exit

    \n\n

    This blocks until the container exit and gives a status code.

    \n\n

    Parameters

    \n\n
    \n\n

    command : str\n The command to execute in the container, optionally and defaults to\n no command.

    \n\n

    Returns

    \n\n
    \n\n

    success : bool\n Whether the container exited with status code 0 or not.

    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.container.Container.stop": {"fullname": "bench_executor.container.Container.stop", "modulename": "bench_executor.container", "qualname": "Container.stop", "kind": "function", "doc": "

    Stop a running container

    \n\n

    Stops the container and removes it, including its volumes.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether stopping the container was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.docker": {"fullname": "bench_executor.docker", "modulename": "bench_executor.docker", "kind": "module", "doc": "

    This module holds the Docker class which implements the necessary API calls\nfor the Container class to control Docker containers. The docker-py module\nwhich is similar has serious issues with resource leaking for years.

    \n"}, "bench_executor.docker.Docker": {"fullname": "bench_executor.docker.Docker", "modulename": "bench_executor.docker", "qualname": "Docker", "kind": "class", "doc": "

    Client for the Docker CLI.

    \n"}, "bench_executor.docker.Docker.__init__": {"fullname": "bench_executor.docker.Docker.__init__", "modulename": "bench_executor.docker", "qualname": "Docker.__init__", "kind": "function", "doc": "

    Creates an instance of the Docker class.

    \n", "signature": "(logger: bench_executor.logger.Logger)"}, "bench_executor.docker.Docker.exec": {"fullname": "bench_executor.docker.Docker.exec", "modulename": "bench_executor.docker", "qualname": "Docker.exec", "kind": "function", "doc": "

    Execute a command inside a running Docker container.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    • command (str):\nCommand to execute inside the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • status_code (int):\nThe exit status code of the executed command.
      • \n
    \n", "signature": "(self, container_id: str, command: str) -> int:", "funcdef": "def"}, "bench_executor.docker.Docker.wait": {"fullname": "bench_executor.docker.Docker.wait", "modulename": "bench_executor.docker", "qualname": "Docker.wait", "kind": "function", "doc": "

    Wait for Docker container to exit.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • status_code (int):\nThe exit status code of the Docker container.
      • \n
    \n", "signature": "(self, container_id: str) -> int:", "funcdef": "def"}, "bench_executor.docker.Docker.stop": {"fullname": "bench_executor.docker.Docker.stop", "modulename": "bench_executor.docker", "qualname": "Docker.stop", "kind": "function", "doc": "

    Stop a running Docker container.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if stopping the container was successful.
      • \n
    \n", "signature": "(self, container_id: str) -> bool:", "funcdef": "def"}, "bench_executor.docker.Docker.logs": {"fullname": "bench_executor.docker.Docker.logs", "modulename": "bench_executor.docker", "qualname": "Docker.logs", "kind": "function", "doc": "

    Retrieve the logs of a container.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • logs (List[str]):\nList of loglines from the container.
      • \n
    \n", "signature": "(self, container_id: str) -> List[str]:", "funcdef": "def"}, "bench_executor.docker.Docker.pull": {"fullname": "bench_executor.docker.Docker.pull", "modulename": "bench_executor.docker", "qualname": "Docker.pull", "kind": "function", "doc": "

    Pull a Docker image from DockerHub or other registries.

    \n\n

    If the image exists locally, pulling will be skipped without\nthe force flag.

    \n\n
    Parameters
    \n\n
      \n
    • image (str):\nName of the Docker container image.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if starting the container was successful.
      • \n
    \n", "signature": "(self, image: str) -> bool:", "funcdef": "def"}, "bench_executor.docker.Docker.run": {"fullname": "bench_executor.docker.Docker.run", "modulename": "bench_executor.docker", "qualname": "Docker.run", "kind": "function", "doc": "

    Start a Docker container.

    \n\n
    Parameters
    \n\n
      \n
    • image (str):\nName of the Docker container image.
      • \n
    • command (str):\nCommand to execute in the Docker container.
      • \n
    • name (str):\nCanonical name to assign to the container.
      • \n
    • detach (bool):\nWhether to detach from the container or not.
      • \n
    • ports (dict):\nPorts to expose from the container to the host.
      • \n
    • network (str):\nName of the Docker network to attach the container to.
      • \n
    • environment (dict):\nEnvironment variables to set.
      • \n
    • volumes (List[str]):\nVolumes to mount on the container from the host.
      • \n
    • must_pull (bool):\nWhether the image should be pulled first, default is True.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if starting the container was successful.
      • \n
    • container_id (str):\nID of the container that was started.
      • \n
    \n", "signature": "(\tself,\timage: str,\tcommand: str,\tname: str,\tdetach: bool,\tports: dict,\tnetwork: str,\tenvironment: dict,\tvolumes: List[str],\tmust_pull: bool = True) -> Tuple[bool, str]:", "funcdef": "def"}, "bench_executor.docker.Docker.create_network": {"fullname": "bench_executor.docker.Docker.create_network", "modulename": "bench_executor.docker", "qualname": "Docker.create_network", "kind": "function", "doc": "

    Create a Docker container network.

    \n\n

    If the network already exist, it will not be recreated.

    \n\n
    Parameters
    \n\n
      \n
    • network (str):\nName of the network.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if the network was created
      • \n
    \n", "signature": "(self, network: str) -> bool:", "funcdef": "def"}, "bench_executor.docker.Docker.info": {"fullname": "bench_executor.docker.Docker.info", "modulename": "bench_executor.docker", "qualname": "Docker.info", "kind": "function", "doc": "

    Dump the Docker daemon system information.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if the command succeed.
      • \n
    • info (dict):\nDocker daemon system information as dictionary.
      • \n
    \n", "signature": "(self) -> Tuple[bool, dict]:", "funcdef": "def"}, "bench_executor.executor": {"fullname": "bench_executor.executor", "modulename": "bench_executor.executor", "kind": "module", "doc": "

    This module holds the Executor class which is responsible for executing a case,\ncollecting metrics, and exposing this functionality to the CLI.\nAll features of this tool can be accessed through the Executor class, other\nclasses should not be used directly.

    \n"}, "bench_executor.executor.METADATA_FILE": {"fullname": "bench_executor.executor.METADATA_FILE", "modulename": "bench_executor.executor", "qualname": "METADATA_FILE", "kind": "variable", "doc": "

    \n", "default_value": "'metadata.json'"}, "bench_executor.executor.SCHEMA_FILE": {"fullname": "bench_executor.executor.SCHEMA_FILE", "modulename": "bench_executor.executor", "qualname": "SCHEMA_FILE", "kind": "variable", "doc": "

    \n", "default_value": "'metadata.schema'"}, "bench_executor.executor.CONFIG_DIR": {"fullname": "bench_executor.executor.CONFIG_DIR", "modulename": "bench_executor.executor", "qualname": "CONFIG_DIR", "kind": "variable", "doc": "

    \n", "default_value": "'/home/dylan/Projects/KROWN/execution-framework/bench_executor/config'"}, "bench_executor.executor.WAIT_TIME": {"fullname": "bench_executor.executor.WAIT_TIME", "modulename": "bench_executor.executor", "qualname": "WAIT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "15"}, "bench_executor.executor.CHECKPOINT_FILE_NAME": {"fullname": "bench_executor.executor.CHECKPOINT_FILE_NAME", "modulename": "bench_executor.executor", "qualname": "CHECKPOINT_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'.done'"}, "bench_executor.executor.Executor": {"fullname": "bench_executor.executor.Executor", "modulename": "bench_executor.executor", "qualname": "Executor", "kind": "class", "doc": "

    Executor class executes a case.

    \n"}, "bench_executor.executor.Executor.__init__": {"fullname": "bench_executor.executor.Executor.__init__", "modulename": "bench_executor.executor", "qualname": "Executor.__init__", "kind": "function", "doc": "

    Create an instance of the Executor class.

    \n\n
    Parameters
    \n\n
      \n
    • main_directory (str):\nThe root directory of all the cases to execute.
      • \n
    • verbose (bool):\nEnables verbose logs.
      • \n
    • process_cb (function):\nCallback to call when a step is completed of the case. By default,\na dummy callback is provided if the argument is missing.
      • \n
    \n", "signature": "(\tmain_directory: str,\tverbose: bool = False,\tprogress_cb=<function _progress_cb>)"}, "bench_executor.executor.Executor.main_directory": {"fullname": "bench_executor.executor.Executor.main_directory", "modulename": "bench_executor.executor", "qualname": "Executor.main_directory", "kind": "variable", "doc": "

    The main directory of all the cases.

    \n\n
    Returns
    \n\n
      \n
    • main_directory (str):\nThe path to the main directory of the cases.
      • \n
    \n", "annotation": ": str"}, "bench_executor.executor.Executor.stats": {"fullname": "bench_executor.executor.Executor.stats", "modulename": "bench_executor.executor", "qualname": "Executor.stats", "kind": "function", "doc": "

    Generate statistics for a case.

    \n\n

    Generate statistics for an executed case. The case must be executed\nbefore to succeed.

    \n\n
    Parameters
    \n\n
      \n
    • case (dict):\nThe case to generate statistics for.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the statistics are generated with success or not.
      • \n
    \n", "signature": "(self, case: dict) -> bool:", "funcdef": "def"}, "bench_executor.executor.Executor.clean": {"fullname": "bench_executor.executor.Executor.clean", "modulename": "bench_executor.executor", "qualname": "Executor.clean", "kind": "function", "doc": "

    Clean a case.

    \n\n

    Clean up all results and metrics for a case to start it fresh.

    \n\n
    Parameters
    \n\n
      \n
    • case (dict):\nThe case to clean.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the cleaning of the case succeeded or not.
      • \n
    \n", "signature": "(self, case: dict) -> bool:", "funcdef": "def"}, "bench_executor.executor.Executor.run": {"fullname": "bench_executor.executor.Executor.run", "modulename": "bench_executor.executor", "qualname": "Executor.run", "kind": "function", "doc": "

    Execute a case.

    \n\n

    Execute all steps of a case while collecting metrics and logs.\nThe metrics are collected at a given interval and for a specific run of\nthe case to allow multiple executions of the same case. Checkpoints of\nruns can be enabled to allow the executor to restart where it stopped\nin case of a failure, electricity blackout, etc.

    \n\n
    Parameters
    \n\n
      \n
    • case (dict):\nThe case to execute.
      • \n
    • interval (float):\nThe sample interval for the metrics collection.
      • \n
    • run (int):\nThe run number of the case.
      • \n
    • checkpoint (bool):\nEnable checkpoints after each run to allow restarts.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the case was executed successfully or not.
      • \n
    \n", "signature": "(self, case: dict, interval: float, run: int, checkpoint: bool) -> bool:", "funcdef": "def"}, "bench_executor.executor.Executor.list": {"fullname": "bench_executor.executor.Executor.list", "modulename": "bench_executor.executor", "qualname": "Executor.list", "kind": "function", "doc": "

    List all cases in a root directory.

    \n\n

    Retrieve a list of all discovered valid cases in a given directory.\nCases which do not pass the validation, are excluded and their\nvalidation errors are reported through logging.

    \n\n
    Returns
    \n\n
      \n
    • cases (list):\nList of discovered cases.
      • \n
    \n", "signature": "(self) -> list:", "funcdef": "def"}, "bench_executor.fuseki": {"fullname": "bench_executor.fuseki", "modulename": "bench_executor.fuseki", "kind": "module", "doc": "

    Apache Jena Fuseki is a SPARQL server. It can run as an operating system\nservice, as a Java web application (WAR file), and as a standalone server.

    \n\n

    Website: https://jena.apache.org/documentation/fuseki2/

    \n"}, "bench_executor.fuseki.VERSION": {"fullname": "bench_executor.fuseki.VERSION", "modulename": "bench_executor.fuseki", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'4.6.1'"}, "bench_executor.fuseki.CMD_ARGS": {"fullname": "bench_executor.fuseki.CMD_ARGS", "modulename": "bench_executor.fuseki", "qualname": "CMD_ARGS", "kind": "variable", "doc": "

    \n", "default_value": "'--tdb2 --update --loc /fuseki/databases/DB /ds'"}, "bench_executor.fuseki.Fuseki": {"fullname": "bench_executor.fuseki.Fuseki", "modulename": "bench_executor.fuseki", "qualname": "Fuseki", "kind": "class", "doc": "

    Fuseki container for executing SPARQL queries.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.fuseki.Fuseki.__init__": {"fullname": "bench_executor.fuseki.Fuseki.__init__", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.__init__", "kind": "function", "doc": "

    Creates an instance of the Fuseki class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.fuseki.Fuseki.initialization": {"fullname": "bench_executor.fuseki.Fuseki.initialization", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.initialization", "kind": "function", "doc": "

    Initialize Fuseki's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.root_mount_directory": {"fullname": "bench_executor.fuseki.Fuseki.root_mount_directory", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Fuseki.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Fuseki.
      • \n
    \n", "annotation": ": str"}, "bench_executor.fuseki.Fuseki.headers": {"fullname": "bench_executor.fuseki.Fuseki.headers", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.headers", "kind": "variable", "doc": "

    HTTP headers of SPARQL queries for serialization formats.

    \n\n

    Only supported serialization formats are included in the dictionary.\nCurrently, the following formats are supported:

    \n\n
      \n
    • N-Triples
      • \n
    • Turtle
      • \n
    • CSV
      • \n
    • RDF/JSON
      • \n
    • RDF/XML
      • \n
    • JSON-LD
      • \n
    \n\n
    Returns
    \n\n
      \n
    • headers (dict):\nDictionary of headers to use for each serialization format.
      • \n
    \n", "annotation": ": Dict[str, Dict[str, str]]"}, "bench_executor.fuseki.Fuseki.wait_until_ready": {"fullname": "bench_executor.fuseki.Fuseki.wait_until_ready", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.wait_until_ready", "kind": "function", "doc": "

    Wait until Fuseki is ready to execute SPARQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the Fuseki container, optionally, defaults to\nno command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the Fuseki was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.load": {"fullname": "bench_executor.fuseki.Fuseki.load", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.load", "kind": "function", "doc": "

    Load an RDF file into Fuseki.

    \n\n

    Currently, only N-Triples files are supported.

    \n\n
    Parameters
    \n\n
      \n
    • rdf_file (str):\nName of the RDF file to load.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the loading was successfull or not.
      • \n
    \n", "signature": "(self, rdf_file: str) -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.stop": {"fullname": "bench_executor.fuseki.Fuseki.stop", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.stop", "kind": "function", "doc": "

    Stop Fuseki.

    \n\n

    Drops all triples in Fuseki before stopping its container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether stopping Fuseki was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.endpoint": {"fullname": "bench_executor.fuseki.Fuseki.endpoint", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.endpoint", "kind": "variable", "doc": "

    SPARQL endpoint URL

    \n"}, "bench_executor": {"fullname": "bench_executor", "modulename": "bench_executor", "kind": "module", "doc": "

    bench_executor module allows you to execute benchmark scenarios\nwith multiple runs and automatically collect metrics.

    \n"}, "bench_executor.logger": {"fullname": "bench_executor.logger", "modulename": "bench_executor.logger", "kind": "module", "doc": "

    This module contains the Logger class which is responsible for logging.\nThis class is a small wrapper around the Python logging module to automatically\nconfigure the loggers and handle unittest logging.

    \n"}, "bench_executor.logger.LOG_FILE_NAME": {"fullname": "bench_executor.logger.LOG_FILE_NAME", "modulename": "bench_executor.logger", "qualname": "LOG_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'log.txt'"}, "bench_executor.logger.LOGGER_FORMAT_FILE": {"fullname": "bench_executor.logger.LOGGER_FORMAT_FILE", "modulename": "bench_executor.logger", "qualname": "LOGGER_FORMAT_FILE", "kind": "variable", "doc": "

    \n", "default_value": "'[%(asctime)s] %(levelname)-8s %(message)-s'"}, "bench_executor.logger.LOGGER_FORMAT_CONSOLE": {"fullname": "bench_executor.logger.LOGGER_FORMAT_CONSOLE", "modulename": "bench_executor.logger", "qualname": "LOGGER_FORMAT_CONSOLE", "kind": "variable", "doc": "

    \n", "default_value": "'%(levelname)s: %(message)s'"}, "bench_executor.logger.Logger": {"fullname": "bench_executor.logger.Logger", "modulename": "bench_executor.logger", "qualname": "Logger", "kind": "class", "doc": "

    Log messages to a log file and console.

    \n"}, "bench_executor.logger.Logger.__init__": {"fullname": "bench_executor.logger.Logger.__init__", "modulename": "bench_executor.logger", "qualname": "Logger.__init__", "kind": "function", "doc": "

    Creates an instance of the Logger class.

    \n\n

    During unittests, the UNITTEST environment variable is set which\ndisables the console logger.

    \n\n
    Parameters
    \n\n
      \n
    • name (str):\nName of the logger
      • \n
    • directory (str):\nThe path to the directory where the logs must be stored.
      • \n
    • verbose (bool):\nEnable verbose logs
      • \n
    \n", "signature": "(name: str, directory: str, verbose: bool)"}, "bench_executor.logger.Logger.verbose": {"fullname": "bench_executor.logger.Logger.verbose", "modulename": "bench_executor.logger", "qualname": "Logger.verbose", "kind": "variable", "doc": "

    Verbose logging enabled.

    \n\n
    Returns
    \n\n
      \n
    • verbose (bool):\nVerbose logging enabled or not.
      • \n
    \n", "annotation": ": bool"}, "bench_executor.logger.Logger.debug": {"fullname": "bench_executor.logger.Logger.debug", "modulename": "bench_executor.logger", "qualname": "Logger.debug", "kind": "function", "doc": "

    Log a message with level DEBUG.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.logger.Logger.info": {"fullname": "bench_executor.logger.Logger.info", "modulename": "bench_executor.logger", "qualname": "Logger.info", "kind": "function", "doc": "

    Log a message with level INFO.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.logger.Logger.warning": {"fullname": "bench_executor.logger.Logger.warning", "modulename": "bench_executor.logger", "qualname": "Logger.warning", "kind": "function", "doc": "

    Log a message with level WARNING.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.logger.Logger.error": {"fullname": "bench_executor.logger.Logger.error", "modulename": "bench_executor.logger", "qualname": "Logger.error", "kind": "function", "doc": "

    Log a message with level ERROR.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.morphkgc": {"fullname": "bench_executor.morphkgc", "modulename": "bench_executor.morphkgc", "kind": "module", "doc": "

    Morph-KGC is an engine that constructs RDF and RDF-star knowledge graphs\nfrom heterogeneous data sources with the R2RML, RML and RML-star mapping\nlanguages.

    \n\n

    Website: https://morph-kgc.readthedocs.io/
    \nRepository: https://github.com/oeg-upm/morph-kgc

    \n"}, "bench_executor.morphkgc.VERSION": {"fullname": "bench_executor.morphkgc.VERSION", "modulename": "bench_executor.morphkgc", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'2.2.0'"}, "bench_executor.morphkgc.TIMEOUT": {"fullname": "bench_executor.morphkgc.TIMEOUT", "modulename": "bench_executor.morphkgc", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.morphkgc.MorphKGC": {"fullname": "bench_executor.morphkgc.MorphKGC", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC", "kind": "class", "doc": "

    Morph-KGC container for executing R2RML, RML, and RML-star mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.morphkgc.MorphKGC.__init__": {"fullname": "bench_executor.morphkgc.MorphKGC.__init__", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.__init__", "kind": "function", "doc": "

    Creates an instance of the MorphKGC class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.morphkgc.MorphKGC.root_mount_directory": {"fullname": "bench_executor.morphkgc.MorphKGC.root_mount_directory", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Morph-KGC.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Morph-KGC.
      • \n
    \n", "annotation": ": str"}, "bench_executor.morphkgc.MorphKGC.execute": {"fullname": "bench_executor.morphkgc.MorphKGC.execute", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.execute", "kind": "function", "doc": "

    Execute Morph-KGC with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to Morph-KGC.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.morphkgc.MorphKGC.execute_mapping": {"fullname": "bench_executor.morphkgc.MorphKGC.execute_mapping", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with Morph-KGC.

    \n\n

    Morph-KGC can transform SQL relational databases (MySQL, PostgreSQL,\nOracle, Microsoft SQL Server, MariaDB, SQLite), tabular (CSV, TSV,\nExcel, Parquet, Feather, ORC, Stata, SAS, SPSS, ODS) and\nhierarchical files (JSON, XML).

    \n\n

    Morph-KGC currently only supports N-Quads and N-Triples in RDF and\nRDF-Star. RDF and RDF-Star output is done automatically, you can use\nthe same serialization format (ntriples, nquads) for both RDF\nand RDF-Star output.

    \n\n

    Morph-KGC can generate all triples in a single file or spread it\namong multiple files.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    • multiple_files (bool):\nIf the generated triples must be stored in multiple files, default\na single file.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None,\tmultiple_files: bool = False) -> bool:", "funcdef": "def"}, "bench_executor.morphrdb": {"fullname": "bench_executor.morphrdb", "modulename": "bench_executor.morphrdb", "kind": "module", "doc": "

    Morph-RDB (formerly called ODEMapster) is an RDB2RDF engine developed by\nthe Ontology Engineering Group, which follows the R2RML specification.

    \n\n

    Website: https://oeg.fi.upm.es/index.php/en/technologies/315-morph-rdb/index.html
    \nRepository: https://github.com/oeg-upm/morph-rdb

    \n"}, "bench_executor.morphrdb.VERSION": {"fullname": "bench_executor.morphrdb.VERSION", "modulename": "bench_executor.morphrdb", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'3.12.5'"}, "bench_executor.morphrdb.TIMEOUT": {"fullname": "bench_executor.morphrdb.TIMEOUT", "modulename": "bench_executor.morphrdb", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.morphrdb.MorphRDB": {"fullname": "bench_executor.morphrdb.MorphRDB", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB", "kind": "class", "doc": "

    Morph-RDB container for executing R2RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.morphrdb.MorphRDB.__init__": {"fullname": "bench_executor.morphrdb.MorphRDB.__init__", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.__init__", "kind": "function", "doc": "

    Creates an instance of the MorphRDB class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.morphrdb.MorphRDB.root_mount_directory": {"fullname": "bench_executor.morphrdb.MorphRDB.root_mount_directory", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Morph-RDB.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Morph-RDB.
      • \n
    \n", "annotation": ": str"}, "bench_executor.morphrdb.MorphRDB.execute": {"fullname": "bench_executor.morphrdb.MorphRDB.execute", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.execute", "kind": "function", "doc": "

    Execute Morph-KGC with the given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nAdditional arguments to supply to Morph-KGC.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.morphrdb.MorphRDB.execute_mapping": {"fullname": "bench_executor.morphrdb.MorphRDB.execute_mapping", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with Morph-RDB.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for Morph-RDB. Only relational databases are supported by\nMorph-RDB, thus the relational database parameters are mandantory.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (str):\nUsername for the database.
      • \n
    • rdb_password (str):\nPassword for the database.
      • \n
    • rdb_host (str):\nHostname for the database.
      • \n
    • rdb_port (int):\nPort for the database.
      • \n
    • rdb_name (str):\nDatabase name for the database.
      • \n
    • rdb_type (str):\nDatabase type.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: str,\trdb_password: str,\trdb_host: str,\trdb_port: int,\trdb_name: str,\trdb_type: str) -> bool:", "funcdef": "def"}, "bench_executor.mysql": {"fullname": "bench_executor.mysql", "modulename": "bench_executor.mysql", "kind": "module", "doc": "

    MySQL is an open-source relational database management system developed by\nOracle Corporation.

    \n\n

    Website: https://www.mysql.com/
    \nRepository: https://github.com/mysql/mysql-server

    \n"}, "bench_executor.mysql.VERSION": {"fullname": "bench_executor.mysql.VERSION", "modulename": "bench_executor.mysql", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'8.0'"}, "bench_executor.mysql.HOST": {"fullname": "bench_executor.mysql.HOST", "modulename": "bench_executor.mysql", "qualname": "HOST", "kind": "variable", "doc": "

    \n", "default_value": "'localhost'"}, "bench_executor.mysql.USER": {"fullname": "bench_executor.mysql.USER", "modulename": "bench_executor.mysql", "qualname": "USER", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.mysql.PASSWORD": {"fullname": "bench_executor.mysql.PASSWORD", "modulename": "bench_executor.mysql", "qualname": "PASSWORD", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.mysql.DB": {"fullname": "bench_executor.mysql.DB", "modulename": "bench_executor.mysql", "qualname": "DB", "kind": "variable", "doc": "

    \n", "default_value": "'db'"}, "bench_executor.mysql.PORT": {"fullname": "bench_executor.mysql.PORT", "modulename": "bench_executor.mysql", "qualname": "PORT", "kind": "variable", "doc": "

    \n", "default_value": "'3306'"}, "bench_executor.mysql.CLEAR_TABLES_TIMEOUT": {"fullname": "bench_executor.mysql.CLEAR_TABLES_TIMEOUT", "modulename": "bench_executor.mysql", "qualname": "CLEAR_TABLES_TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "300"}, "bench_executor.mysql.MySQL": {"fullname": "bench_executor.mysql.MySQL", "modulename": "bench_executor.mysql", "qualname": "MySQL", "kind": "class", "doc": "

    MySQL container for executing SQL queries.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.mysql.MySQL.__init__": {"fullname": "bench_executor.mysql.MySQL.__init__", "modulename": "bench_executor.mysql", "qualname": "MySQL.__init__", "kind": "function", "doc": "

    Creates an instance of the MySQL class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.mysql.MySQL.initialization": {"fullname": "bench_executor.mysql.MySQL.initialization", "modulename": "bench_executor.mysql", "qualname": "MySQL.initialization", "kind": "function", "doc": "

    Initialize MySQL's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.root_mount_directory": {"fullname": "bench_executor.mysql.MySQL.root_mount_directory", "modulename": "bench_executor.mysql", "qualname": "MySQL.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for MySQL.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for MySQL.
      • \n
    \n", "annotation": ": str"}, "bench_executor.mysql.MySQL.wait_until_ready": {"fullname": "bench_executor.mysql.MySQL.wait_until_ready", "modulename": "bench_executor.mysql", "qualname": "MySQL.wait_until_ready", "kind": "function", "doc": "

    Wait until MySQL is ready to execute SQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the MySQL container, optionally, defaults to\nno command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the MySQL was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.load": {"fullname": "bench_executor.mysql.MySQL.load", "modulename": "bench_executor.mysql", "qualname": "MySQL.load", "kind": "function", "doc": "

    Load a single CSV file into MySQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_file (str):\nName of the CSV file.
      • \n
    • table (str):\nName of the table.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_file: str, table: str) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.load_multiple": {"fullname": "bench_executor.mysql.MySQL.load_multiple", "modulename": "bench_executor.mysql", "qualname": "MySQL.load_multiple", "kind": "function", "doc": "

    Load multiple CSV files into MySQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_files (list):\nList of CSV files to load. Each entry consist of a file and\ntable key.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_files: List[dict]) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.load_sql_schema": {"fullname": "bench_executor.mysql.MySQL.load_sql_schema", "modulename": "bench_executor.mysql", "qualname": "MySQL.load_sql_schema", "kind": "function", "doc": "

    Execute SQL schema with MySQL.

    \n\n

    Executes a .sql file with MySQL.\nIf the data is not loaded by the .sql file but only the schema is\nprovided through the .sql file, a list of CSV files can be provided to\nload them as well.

    \n\n
    Parameters
    \n\n
      \n
    • schema_file (str):\nName of the .sql file.
      • \n
    • csv_files (List[Tuple[str, str]]):\nList of CSV file names to load in the tables created with the .sql\nfile, may also be an empty list. Each entry contains a Tuple with\nthe name of the CSV file and the table name.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, schema_file: str, csv_files: List[Tuple[str, str]]) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.stop": {"fullname": "bench_executor.mysql.MySQL.stop", "modulename": "bench_executor.mysql", "qualname": "MySQL.stop", "kind": "function", "doc": "

    Stop MySQL\nClears all tables and stops the MySQL container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.ontop": {"fullname": "bench_executor.ontop", "modulename": "bench_executor.ontop", "kind": "module", "doc": "

    Ontop is a Virtual Knowledge Graph system. It exposes the content of\narbitrary relational databases as knowledge graphs. These graphs are virtual,\nwhich means that data remains in the data sources instead of being moved\nto another database.

    \n\n

    Website: https://ontop-vkg.org
    \nRepository: https://github.com/ontop/ontop

    \n"}, "bench_executor.ontop.VERSION": {"fullname": "bench_executor.ontop.VERSION", "modulename": "bench_executor.ontop", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'5.0.0'"}, "bench_executor.ontop.TIMEOUT": {"fullname": "bench_executor.ontop.TIMEOUT", "modulename": "bench_executor.ontop", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.ontop.R2RML": {"fullname": "bench_executor.ontop.R2RML", "modulename": "bench_executor.ontop", "qualname": "R2RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.w3.org/ns/r2rml#')"}, "bench_executor.ontop.Ontop": {"fullname": "bench_executor.ontop.Ontop", "modulename": "bench_executor.ontop", "qualname": "Ontop", "kind": "class", "doc": "

    Ontop container super class for OntopMaterialize and OntopVirtualize.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.ontop.Ontop.__init__": {"fullname": "bench_executor.ontop.Ontop.__init__", "modulename": "bench_executor.ontop", "qualname": "Ontop.__init__", "kind": "function", "doc": "

    Creates an instance of the Ontop class.

    \n\n
    Parameters
    \n\n
      \n
    • name (str):\nPretty name of the container.
      • \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • logger (Logger):\nLogger to use for log messages.
      • \n
    • mode (str):\nOntop mode: materialize or endpoint
      • \n
    \n", "signature": "(\tname: str,\tdata_path: str,\tlogger: bench_executor.logger.Logger,\tmode: str)"}, "bench_executor.ontop.Ontop.root_mount_directory": {"fullname": "bench_executor.ontop.Ontop.root_mount_directory", "modulename": "bench_executor.ontop", "qualname": "Ontop.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Ontop.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Ontop.
      • \n
    \n", "annotation": ": str"}, "bench_executor.ontop.Ontop.endpoint": {"fullname": "bench_executor.ontop.Ontop.endpoint", "modulename": "bench_executor.ontop", "qualname": "Ontop.endpoint", "kind": "variable", "doc": "

    SPARQL endpoint URL for Ontop.

    \n\n
    Returns
    \n\n
      \n
    • url (str):\nSPARQL endpoint URL.
      • \n
    \n", "annotation": ": str"}, "bench_executor.ontop.Ontop.headers": {"fullname": "bench_executor.ontop.Ontop.headers", "modulename": "bench_executor.ontop", "qualname": "Ontop.headers", "kind": "variable", "doc": "

    HTTP headers of SPARQL queries for serialization formats.

    \n\n

    Only supported serialization formats are included in the dictionary.\nCurrently, the following formats are supported:

    \n\n
      \n
    • N-Triples
      • \n
    • N-Quads
      • \n
    • Turtle
      • \n
    • CSV
      • \n
    • RDF/JSON
      • \n
    • RDF/XML
      • \n
    • JSON-LD
      • \n
    \n\n
    Returns
    \n\n
      \n
    • headers (dict):\nDictionary of headers to use for each serialization format.
      • \n
    \n", "annotation": ": dict"}, "bench_executor.ontop.OntopVirtualize": {"fullname": "bench_executor.ontop.OntopVirtualize", "modulename": "bench_executor.ontop", "qualname": "OntopVirtualize", "kind": "class", "doc": "

    OntopVirtualize container for setting up an Ontop SPARQL endpoint.

    \n", "bases": "Ontop"}, "bench_executor.ontop.OntopVirtualize.__init__": {"fullname": "bench_executor.ontop.OntopVirtualize.__init__", "modulename": "bench_executor.ontop", "qualname": "OntopVirtualize.__init__", "kind": "function", "doc": "

    Creates an instance of the OntopVirtualize class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.ontop.OntopVirtualize.execute_mapping": {"fullname": "bench_executor.ontop.OntopVirtualize.execute_mapping", "modulename": "bench_executor.ontop", "qualname": "OntopVirtualize.execute_mapping", "kind": "function", "doc": "

    Start an Ontop SPARQL endpoint with a mapping.

    \n\n

    Only relational databases are supported by\nOntop, thus the relational database parameters are mandantory.\nOntop SPARQL endpoint supports the following serialization formats:

    \n\n
      \n
    • N-Triples (Ontop v5+)
      • \n
    • N-Quads (Ontop v5+)
      • \n
    • Turtle
      • \n
    • RDF/JSON
      • \n
    • JSON-LD
      • \n
    • CSV
      • \n
    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (str):\nUsername for the database.
      • \n
    • rdb_password (str):\nPassword for the database.
      • \n
    • rdb_host (str):\nHostname for the database.
      • \n
    • rdb_port (int):\nPort for the database.
      • \n
    • rdb_name (str):\nDatabase name for the database.
      • \n
    • rdb_type (str):\nDatabase type.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\tserialization: str,\trdb_username: str,\trdb_password: str,\trdb_host: str,\trdb_port: int,\trdb_name: str,\trdb_type: str) -> bool:", "funcdef": "def"}, "bench_executor.ontop.OntopMaterialize": {"fullname": "bench_executor.ontop.OntopMaterialize", "modulename": "bench_executor.ontop", "qualname": "OntopMaterialize", "kind": "class", "doc": "

    OntopMaterialize container to execute a R2RML mapping.

    \n", "bases": "Ontop"}, "bench_executor.ontop.OntopMaterialize.__init__": {"fullname": "bench_executor.ontop.OntopMaterialize.__init__", "modulename": "bench_executor.ontop", "qualname": "OntopMaterialize.__init__", "kind": "function", "doc": "

    Creates an instance of the OntopMaterialize class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.ontop.OntopMaterialize.execute_mapping": {"fullname": "bench_executor.ontop.OntopMaterialize.execute_mapping", "modulename": "bench_executor.ontop", "qualname": "OntopMaterialize.execute_mapping", "kind": "function", "doc": "

    Execute a R2RML mapping with Ontop

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nfor Ontop materialize. Only relational databases are supported by\nOntop, thus the relational database parameters are mandantory.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in. This is not used\nfor OntopVirtualize.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (str):\nUsername for the database.
      • \n
    • rdb_password (str):\nPassword for the database.
      • \n
    • rdb_host (str):\nHostname for the database.
      • \n
    • rdb_port (int):\nPort for the database.
      • \n
    • rdb_name (str):\nDatabase name for the database.
      • \n
    • rdb_type (str):\nDatabase type.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: str,\trdb_password: str,\trdb_host: str,\trdb_port: int,\trdb_name: str,\trdb_type: str) -> bool:", "funcdef": "def"}, "bench_executor.postgresql": {"fullname": "bench_executor.postgresql", "modulename": "bench_executor.postgresql", "kind": "module", "doc": "

    PostgreSQL is an open-source relational database developed by The PostgreSQL\nGlobal Development Group.

    \n\n

    Website: https://www.postgresql.org/
    \nRepository: https://git.postgresql.org/gitweb/?p=postgresql.git

    \n"}, "bench_executor.postgresql.VERSION": {"fullname": "bench_executor.postgresql.VERSION", "modulename": "bench_executor.postgresql", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'14.5'"}, "bench_executor.postgresql.HOST": {"fullname": "bench_executor.postgresql.HOST", "modulename": "bench_executor.postgresql", "qualname": "HOST", "kind": "variable", "doc": "

    \n", "default_value": "'localhost'"}, "bench_executor.postgresql.USER": {"fullname": "bench_executor.postgresql.USER", "modulename": "bench_executor.postgresql", "qualname": "USER", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.postgresql.PASSWORD": {"fullname": "bench_executor.postgresql.PASSWORD", "modulename": "bench_executor.postgresql", "qualname": "PASSWORD", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.postgresql.DB": {"fullname": "bench_executor.postgresql.DB", "modulename": "bench_executor.postgresql", "qualname": "DB", "kind": "variable", "doc": "

    \n", "default_value": "'db'"}, "bench_executor.postgresql.PORT": {"fullname": "bench_executor.postgresql.PORT", "modulename": "bench_executor.postgresql", "qualname": "PORT", "kind": "variable", "doc": "

    \n", "default_value": "'5432'"}, "bench_executor.postgresql.WAIT_TIME": {"fullname": "bench_executor.postgresql.WAIT_TIME", "modulename": "bench_executor.postgresql", "qualname": "WAIT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "3"}, "bench_executor.postgresql.CLEAR_TABLES_TIMEOUT": {"fullname": "bench_executor.postgresql.CLEAR_TABLES_TIMEOUT", "modulename": "bench_executor.postgresql", "qualname": "CLEAR_TABLES_TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "300"}, "bench_executor.postgresql.PostgreSQL": {"fullname": "bench_executor.postgresql.PostgreSQL", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL", "kind": "class", "doc": "

    PostgreSQL container for executing SQL queries

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.postgresql.PostgreSQL.__init__": {"fullname": "bench_executor.postgresql.PostgreSQL.__init__", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.__init__", "kind": "function", "doc": "

    Creates an instance of the PostgreSQL class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.postgresql.PostgreSQL.initialization": {"fullname": "bench_executor.postgresql.PostgreSQL.initialization", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.initialization", "kind": "function", "doc": "

    Initialize PostgreSQL's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.root_mount_directory": {"fullname": "bench_executor.postgresql.PostgreSQL.root_mount_directory", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for PostgreSQL.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for PostgreSQL.
      • \n
    \n", "annotation": ": str"}, "bench_executor.postgresql.PostgreSQL.wait_until_ready": {"fullname": "bench_executor.postgresql.PostgreSQL.wait_until_ready", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.wait_until_ready", "kind": "function", "doc": "

    Wait until PostgreSQL is ready to execute SQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the PostgreSQL container, optionally,\ndefaults to no command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the PostgreSQL was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.load": {"fullname": "bench_executor.postgresql.PostgreSQL.load", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.load", "kind": "function", "doc": "

    Load a single CSV file into PostgreSQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_file (str):\nName of the CSV file.
      • \n
    • table (str):\nName of the table.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_file: str, table: str) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.load_multiple": {"fullname": "bench_executor.postgresql.PostgreSQL.load_multiple", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.load_multiple", "kind": "function", "doc": "

    Load multiple CSV files into PostgreSQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_files (list):\nList of CSV files to load. Each entry consist of a file and\ntable key.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_files: List[dict]) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.load_sql_schema": {"fullname": "bench_executor.postgresql.PostgreSQL.load_sql_schema", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.load_sql_schema", "kind": "function", "doc": "

    Execute SQL schema with PostgreSQL.

    \n\n

    Executes a .sql file with PostgreSQL.\nIf the data is not loaded by the .sql file but only the schema is\nprovided through the .sql file, a list of CSV files can be provided to\nload them as well.

    \n\n
    Parameters
    \n\n
      \n
    • schema_file (str):\nName of the .sql file.
      • \n
    • csv_files (List[Tuple[str, str]]]):\nList of CSV file names to load in the tables created with the .sql\nfile, may also be an empty list. Each entry contains a Tuple of the\nCSV file name and the table name.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, schema_file: str, csv_files: List[Tuple[str, str]]) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.stop": {"fullname": "bench_executor.postgresql.PostgreSQL.stop", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.stop", "kind": "function", "doc": "

    Stop PostgreSQL\nClears all tables and stops the PostgreSQL container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.query": {"fullname": "bench_executor.query", "modulename": "bench_executor.query", "kind": "module", "doc": "

    Query executes SPARQL queries on endpoints by posting the SPARQL query over\nHTTP onto the endpoint. It applies timeouts to these queries automatically and\nchecks if the results are empty or not.

    \n"}, "bench_executor.query.TIMEOUT": {"fullname": "bench_executor.query.TIMEOUT", "modulename": "bench_executor.query", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "3600"}, "bench_executor.query.Query": {"fullname": "bench_executor.query.Query", "modulename": "bench_executor.query", "qualname": "Query", "kind": "class", "doc": "

    Execute a query on a SPARQL endpoint.

    \n"}, "bench_executor.query.Query.__init__": {"fullname": "bench_executor.query.Query.__init__", "modulename": "bench_executor.query", "qualname": "Query.__init__", "kind": "function", "doc": "

    Creates an instance of the Query class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.query.Query.name": {"fullname": "bench_executor.query.Query.name", "modulename": "bench_executor.query", "qualname": "Query.name", "kind": "variable", "doc": "

    Name of the class: Query

    \n"}, "bench_executor.query.Query.root_mount_directory": {"fullname": "bench_executor.query.Query.root_mount_directory", "modulename": "bench_executor.query", "qualname": "Query.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Query.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Query.
      • \n
    \n", "annotation": ": str"}, "bench_executor.query.Query.execute_and_save": {"fullname": "bench_executor.query.Query.execute_and_save", "modulename": "bench_executor.query", "qualname": "Query.execute_and_save", "kind": "function", "doc": "

    Executes a SPARQL query and save the results.

    \n\n

    The results are saved to the results_file path.

    \n\n
    Parameters
    \n\n
      \n
    • query (str):\nThe query to execute.
      • \n
    • sparql_endpoint (str):\nThe URL of the SPARQL endpoint.
      • \n
    • results_file (str):\nPath to the file where the results may be stored.
      • \n
    • expect_empty (bool):\nWhether the expected results are empty or not.
      • \n
    • headers (dict):\nHTTP headers to supply when posting the query.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(\tself,\tquery: str,\tsparql_endpoint: str,\tresults_file: str,\texpect_empty: bool = False,\theaders: dict = {}) -> bool:", "funcdef": "def"}, "bench_executor.query.Query.execute_from_file": {"fullname": "bench_executor.query.Query.execute_from_file", "modulename": "bench_executor.query", "qualname": "Query.execute_from_file", "kind": "function", "doc": "

    Executes a SPARQL query from file.

    \n\n

    The results are saved to the results_file path.

    \n\n
    Parameters
    \n\n
      \n
    • query_file (str):\nPath to the file containing the query.
      • \n
    • sparql_endpoint (str):\nThe URL of the SPARQL endpoint.
      • \n
    • expect_empty (bool):\nWhether the expected results are empty or not.
      • \n
    • headers (dict):\nHTTP headers to supply when posting the query.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • results (str):\nThe HTTP response as string of the SPARQL endpoint, unless it has\nno results.
      • \n
    \n\n
    Raises
    \n\n
      \n
    • Exception (Exception):\nPass through the exception from the Python's request module\nregarding HTTP status codes.
      • \n
    \n", "signature": "(\tself,\tquery_file: str,\tsparql_endpoint: str,\texpect_empty: bool = False,\theaders: dict = {}) -> str:", "funcdef": "def"}, "bench_executor.query.Query.execute_from_file_and_save": {"fullname": "bench_executor.query.Query.execute_from_file_and_save", "modulename": "bench_executor.query", "qualname": "Query.execute_from_file_and_save", "kind": "function", "doc": "

    Executes a SPARQL query from file and save the results.

    \n\n

    The results are saved to the results_file path.

    \n\n
    Parameters
    \n\n
      \n
    • query_file (str):\nPath to the file containing the query.
      • \n
    • sparql_endpoint (str):\nThe URL of the SPARQL endpoint.
      • \n
    • results_file (str):\nPath to the file where the results may be stored.
      • \n
    • expect_empty (bool):\nWhether the expected results are empty or not.
      • \n
    • headers (dict):\nHTTP headers to supply when posting the query.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n\n
    Raises
    \n\n
      \n
    • FileNotFoundError (Exception):\nIf the query file cannot be found.
      • \n
    \n", "signature": "(\tself,\tquery_file: str,\tsparql_endpoint: str,\tresults_file: str,\texpect_empty: bool = False,\theaders: dict = {}) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper": {"fullname": "bench_executor.rmlmapper", "modulename": "bench_executor.rmlmapper", "kind": "module", "doc": "

    The RMLMapper executes RML rules to generate high quality Linked Data\nfrom multiple originally (semi-)structured data sources.

    \n\n

    Website: https://rml.io
    \nRepository: https://github.com/RMLio/rmlmapper-java

    \n"}, "bench_executor.rmlmapper.VERSION": {"fullname": "bench_executor.rmlmapper.VERSION", "modulename": "bench_executor.rmlmapper", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'6.2.1'"}, "bench_executor.rmlmapper.TIMEOUT": {"fullname": "bench_executor.rmlmapper.TIMEOUT", "modulename": "bench_executor.rmlmapper", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.rmlmapper.RMLMapper": {"fullname": "bench_executor.rmlmapper.RMLMapper", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper", "kind": "class", "doc": "

    RMLMapper container for executing R2RML and RML mappings.

    \n"}, "bench_executor.rmlmapper.RMLMapper.__init__": {"fullname": "bench_executor.rmlmapper.RMLMapper.__init__", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.__init__", "kind": "function", "doc": "

    Creates an instance of the RMLMapper class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.rmlmapper.RMLMapper.root_mount_directory": {"fullname": "bench_executor.rmlmapper.RMLMapper.root_mount_directory", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for RMLMapper.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for RMLMapper.
      • \n
    \n", "annotation": ": str"}, "bench_executor.rmlmapper.RMLMapper.execute": {"fullname": "bench_executor.rmlmapper.RMLMapper.execute", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.execute", "kind": "function", "doc": "

    Execute RMLMapper with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to RMLMapper.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper.RMLMapper.execute_mapping": {"fullname": "bench_executor.rmlmapper.RMLMapper.execute_mapping", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with RMLMapper.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for RMLMapper.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper_docker": {"fullname": "bench_executor.rmlmapper_docker", "modulename": "bench_executor.rmlmapper_docker", "kind": "module", "doc": "

    The RMLMapper executes RML rules to generate high quality Linked Data\nfrom multiple originally (semi-)structured data sources.

    \n\n

    Website: https://rml.io
    \nRepository: https://github.com/RMLio/rmlmapper-java

    \n"}, "bench_executor.rmlmapper_docker.VERSION": {"fullname": "bench_executor.rmlmapper_docker.VERSION", "modulename": "bench_executor.rmlmapper_docker", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'6.0.0'"}, "bench_executor.rmlmapper_docker.TIMEOUT": {"fullname": "bench_executor.rmlmapper_docker.TIMEOUT", "modulename": "bench_executor.rmlmapper_docker", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.rmlmapper_docker.RMLMapperDocker": {"fullname": "bench_executor.rmlmapper_docker.RMLMapperDocker", "modulename": "bench_executor.rmlmapper_docker", "qualname": "RMLMapperDocker", "kind": "class", "doc": "

    RMLMapper container for executing R2RML and RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.rmlmapper_docker.RMLMapperDocker.__init__": {"fullname": "bench_executor.rmlmapper_docker.RMLMapperDocker.__init__", "modulename": "bench_executor.rmlmapper_docker", "qualname": "RMLMapperDocker.__init__", "kind": "function", "doc": "

    Creates an instance of the RMLMapper class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.rmlmapper_docker.RMLMapperDocker.root_mount_directory": {"fullname": "bench_executor.rmlmapper_docker.RMLMapperDocker.root_mount_directory", "modulename": "bench_executor.rmlmapper_docker", "qualname": "RMLMapperDocker.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for RMLMapper.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for RMLMapper.
      • \n
    \n", "annotation": ": str"}, "bench_executor.rmlmapper_docker.RMLMapperDocker.execute": {"fullname": "bench_executor.rmlmapper_docker.RMLMapperDocker.execute", "modulename": "bench_executor.rmlmapper_docker", "qualname": "RMLMapperDocker.execute", "kind": "function", "doc": "

    Execute RMLMapper with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to RMLMapper.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper_docker.RMLMapperDocker.execute_mapping": {"fullname": "bench_executor.rmlmapper_docker.RMLMapperDocker.execute_mapping", "modulename": "bench_executor.rmlmapper_docker", "qualname": "RMLMapperDocker.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with RMLMapper.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for RMLMapper.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.rmlstreamer": {"fullname": "bench_executor.rmlstreamer", "modulename": "bench_executor.rmlstreamer", "kind": "module", "doc": "

    The RMLStreamer executes RML rules to generate high quality Linked Data\nfrom multiple originally (semi-)structured data sources in a streaming way.

    \n\n

    Website: https://rml.io
    \nRepository: https://github.com/RMLio/RMLStreamer

    \n"}, "bench_executor.rmlstreamer.R2RML": {"fullname": "bench_executor.rmlstreamer.R2RML", "modulename": "bench_executor.rmlstreamer", "qualname": "R2RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.w3.org/ns/r2rml#')"}, "bench_executor.rmlstreamer.RML": {"fullname": "bench_executor.rmlstreamer.RML", "modulename": "bench_executor.rmlstreamer", "qualname": "RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://semweb.mmlab.be/ns/rml#')"}, "bench_executor.rmlstreamer.D2RQ": {"fullname": "bench_executor.rmlstreamer.D2RQ", "modulename": "bench_executor.rmlstreamer", "qualname": "D2RQ", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.wiwiss.fu-berlin.de/suhl/bizer/D2RQ/0.1#')"}, "bench_executor.rmlstreamer.VERSION": {"fullname": "bench_executor.rmlstreamer.VERSION", "modulename": "bench_executor.rmlstreamer", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'2.5.0'"}, "bench_executor.rmlstreamer.TIMEOUT": {"fullname": "bench_executor.rmlstreamer.TIMEOUT", "modulename": "bench_executor.rmlstreamer", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.rmlstreamer.IMAGE": {"fullname": "bench_executor.rmlstreamer.IMAGE", "modulename": "bench_executor.rmlstreamer", "qualname": "IMAGE", "kind": "variable", "doc": "

    \n", "default_value": "'blindreviewing/rmlstreamer:v2.5.0'"}, "bench_executor.rmlstreamer.RMLStreamer": {"fullname": "bench_executor.rmlstreamer.RMLStreamer", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer", "kind": "class", "doc": "

    RMLStreamer container for executing RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.rmlstreamer.RMLStreamer.__init__": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.__init__", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.__init__", "kind": "function", "doc": "

    Creates an instance of the RMLStreamer class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.rmlstreamer.RMLStreamer.root_mount_directory": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.root_mount_directory", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for RMLStreamer.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for RMLStreamer.
      • \n
    \n", "annotation": ": str"}, "bench_executor.rmlstreamer.RMLStreamer.execute": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.execute", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.execute", "kind": "function", "doc": "

    Execute RMLStreamer with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to RMLStreamer.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.rmlstreamer.RMLStreamer.execute_mapping": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.execute_mapping", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with RMLStreamer.

    \n\n

    N-Quads/N-Triples is the only currently supported as serialization\nformat for RMLStreamer.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.sdmrdfizer": {"fullname": "bench_executor.sdmrdfizer", "modulename": "bench_executor.sdmrdfizer", "kind": "module", "doc": "

    SDM-RDFizer is an efficient RML-Compliant engine for knowledge graph\nconstruction.

    \n\n

    Repository: https://github.com/SDM-TIB/SDM-RDFizer

    \n"}, "bench_executor.sdmrdfizer.VERSION": {"fullname": "bench_executor.sdmrdfizer.VERSION", "modulename": "bench_executor.sdmrdfizer", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'4.6.6.5'"}, "bench_executor.sdmrdfizer.TIMEOUT": {"fullname": "bench_executor.sdmrdfizer.TIMEOUT", "modulename": "bench_executor.sdmrdfizer", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.sdmrdfizer.R2RML": {"fullname": "bench_executor.sdmrdfizer.R2RML", "modulename": "bench_executor.sdmrdfizer", "qualname": "R2RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.w3.org/ns/r2rml#')"}, "bench_executor.sdmrdfizer.RML": {"fullname": "bench_executor.sdmrdfizer.RML", "modulename": "bench_executor.sdmrdfizer", "qualname": "RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://semweb.mmlab.be/ns/rml#')"}, "bench_executor.sdmrdfizer.D2RQ": {"fullname": "bench_executor.sdmrdfizer.D2RQ", "modulename": "bench_executor.sdmrdfizer", "qualname": "D2RQ", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.wiwiss.fu-berlin.de/suhl/bizer/D2RQ/0.1#')"}, "bench_executor.sdmrdfizer.IMAGE": {"fullname": "bench_executor.sdmrdfizer.IMAGE", "modulename": "bench_executor.sdmrdfizer", "qualname": "IMAGE", "kind": "variable", "doc": "

    \n", "default_value": "'blindreviewing/sdm-rdfizer:v4.6.6.5'"}, "bench_executor.sdmrdfizer.SDMRDFizer": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer", "kind": "class", "doc": "

    SDMRDFizer container for executing RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.sdmrdfizer.SDMRDFizer.__init__": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.__init__", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.__init__", "kind": "function", "doc": "

    Creates an instance of the SDMRDFizer class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.sdmrdfizer.SDMRDFizer.root_mount_directory": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.root_mount_directory", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for SDM-RDFizer.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for SDM-RDFizer.
      • \n
    \n", "annotation": ": str"}, "bench_executor.sdmrdfizer.SDMRDFizer.execute": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.execute", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.execute", "kind": "function", "doc": "

    Execute SDM-RDFizer with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to SDM-RDFizer.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.sdmrdfizer.SDMRDFizer.execute_mapping": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.execute_mapping", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with SDM-RDFizer.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for RMLMapper.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.stats": {"fullname": "bench_executor.stats", "modulename": "bench_executor.stats", "kind": "module", "doc": "

    This module holds the Stats class which is responsible for generating\nstaticstics from executed cases. It will automatically aggregate all runs of an\nexecuted case to generate an aggregated.csv and summary.csv files which can\nbe used to compare various cases with each other.

    \n\n
      \n
    • aggregated.csv: For each run of a case, the median execution time of each\nstep is calculated. For each step, the results of the run with the median\nexecution time is used to assemble the aggregated results.
      • \n
    • summary.csv: The summary is similar to the previous file, but provides a\nsingle result for each step to immediately see how long the step took, how\nmany samples are provided for the step, etc.
      • \n
    \n"}, "bench_executor.stats.METRICS_AGGREGATED_FILE_NAME": {"fullname": "bench_executor.stats.METRICS_AGGREGATED_FILE_NAME", "modulename": "bench_executor.stats", "qualname": "METRICS_AGGREGATED_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'aggregated.csv'"}, "bench_executor.stats.METRICS_SUMMARY_FILE_NAME": {"fullname": "bench_executor.stats.METRICS_SUMMARY_FILE_NAME", "modulename": "bench_executor.stats", "qualname": "METRICS_SUMMARY_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'summary.csv'"}, "bench_executor.stats.METRICS_STATS_FILE_NAME": {"fullname": "bench_executor.stats.METRICS_STATS_FILE_NAME", "modulename": "bench_executor.stats", "qualname": "METRICS_STATS_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'stats.csv'"}, "bench_executor.stats.FIELDNAMES_STRING": {"fullname": "bench_executor.stats.FIELDNAMES_STRING", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_STRING", "kind": "variable", "doc": "

    \n", "default_value": "['name']"}, "bench_executor.stats.FIELDNAMES_FLOAT": {"fullname": "bench_executor.stats.FIELDNAMES_FLOAT", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_FLOAT", "kind": "variable", "doc": "

    \n", "default_value": "['timestamp', 'cpu_user', 'cpu_system', 'cpu_idle', 'cpu_iowait', 'cpu_user_system']"}, "bench_executor.stats.FIELDNAMES_INT": {"fullname": "bench_executor.stats.FIELDNAMES_INT", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_INT", "kind": "variable", "doc": "

    \n", "default_value": "['run', 'index', 'step', 'version', 'memory_ram', 'memory_swap', 'memory_ram_swap', 'disk_read_count', 'disk_write_count', 'disk_read_bytes', 'disk_write_bytes', 'disk_read_time', 'disk_write_time', 'disk_busy_time', 'network_received_count', 'network_sent_count', 'network_received_bytes', 'network_sent_bytes', 'network_received_error', 'network_sent_error', 'network_received_drop', 'network_sent_drop']"}, "bench_executor.stats.FIELDNAMES_SUMMARY": {"fullname": "bench_executor.stats.FIELDNAMES_SUMMARY", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_SUMMARY", "kind": "variable", "doc": "

    \n", "default_value": "['name', 'run', 'number_of_samples', 'step', 'duration', 'version', 'cpu_user_diff', 'cpu_system_diff', 'cpu_user_system_diff', 'cpu_idle_diff', 'cpu_iowait_diff', 'memory_ram_max', 'memory_swap_max', 'memory_ram_swap_max', 'memory_ram_min', 'memory_swap_min', 'memory_ram_swap_min', 'disk_read_count_diff', 'disk_write_count_diff', 'disk_read_bytes_diff', 'disk_write_bytes_diff', 'disk_read_time_diff', 'disk_write_time_diff', 'disk_busy_time_diff', 'network_received_count_diff', 'network_sent_count_diff', 'network_received_bytes_diff', 'network_sent_bytes_diff', 'network_received_error_diff', 'network_sent_error_diff', 'network_received_drop_diff', 'network_sent_drop_diff']"}, "bench_executor.stats.ROUND": {"fullname": "bench_executor.stats.ROUND", "modulename": "bench_executor.stats", "qualname": "ROUND", "kind": "variable", "doc": "

    \n", "default_value": "4"}, "bench_executor.stats.Stats": {"fullname": "bench_executor.stats.Stats", "modulename": "bench_executor.stats", "qualname": "Stats", "kind": "class", "doc": "

    Generate statistics for an executed case.

    \n"}, "bench_executor.stats.Stats.__init__": {"fullname": "bench_executor.stats.Stats.__init__", "modulename": "bench_executor.stats", "qualname": "Stats.__init__", "kind": "function", "doc": "

    Create an instance of the Stats class.

    \n\n
    Parameters
    \n\n
      \n
    • results_path (str):\nThe path to the results directory of the case
      • \n
    • number_of_steps (int):\nThe number of steps of the case
      • \n
    • directory (str):\nThe path to the directory where the logs must be stored.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(\tresults_path: str,\tnumber_of_steps: int,\tdirectory: str,\tverbose: bool)"}, "bench_executor.stats.Stats.statistics": {"fullname": "bench_executor.stats.Stats.statistics", "modulename": "bench_executor.stats", "qualname": "Stats.statistics", "kind": "function", "doc": "

    Calculate basic statistics on the steps by aggregating them from\nall runs and applying standard deviation, median, min, max, mean for\neach measured metric.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the standard deviation calculation was successfully or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.stats.Stats.aggregate": {"fullname": "bench_executor.stats.Stats.aggregate", "modulename": "bench_executor.stats", "qualname": "Stats.aggregate", "kind": "function", "doc": "

    Aggregate the metrics of the different runs of a case.

    \n\n

    Find the median execution time of each step across all runs and extract\nthe step from the run which has this median execution time to assemble\nan aggregated version and summary version of the case's metrics.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the aggregation was successfully or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.virtuoso": {"fullname": "bench_executor.virtuoso", "modulename": "bench_executor.virtuoso", "kind": "module", "doc": "

    Virtuoso is a secure and high-performance platform for modern data access,\nintegration, virtualization, and multi-model data management (tables & graphs)\nbased on innovative support of existing open standards\n(e.g., SQL, SPARQL, and GraphQL).

    \n\n

    Website: https://virtuoso.openlinksw.com/
    \nRepository: https://github.com/openlink/virtuoso-opensource

    \n"}, "bench_executor.virtuoso.VERSION": {"fullname": "bench_executor.virtuoso.VERSION", "modulename": "bench_executor.virtuoso", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'7.2.7'"}, "bench_executor.virtuoso.MAX_ROWS": {"fullname": "bench_executor.virtuoso.MAX_ROWS", "modulename": "bench_executor.virtuoso", "qualname": "MAX_ROWS", "kind": "variable", "doc": "

    \n", "default_value": "'10000000'"}, "bench_executor.virtuoso.QUERY_TIMEOUT": {"fullname": "bench_executor.virtuoso.QUERY_TIMEOUT", "modulename": "bench_executor.virtuoso", "qualname": "QUERY_TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "'0'"}, "bench_executor.virtuoso.MAX_VECTOR_SIZE": {"fullname": "bench_executor.virtuoso.MAX_VECTOR_SIZE", "modulename": "bench_executor.virtuoso", "qualname": "MAX_VECTOR_SIZE", "kind": "variable", "doc": "

    \n", "default_value": "'3000000'"}, "bench_executor.virtuoso.PASSWORD": {"fullname": "bench_executor.virtuoso.PASSWORD", "modulename": "bench_executor.virtuoso", "qualname": "PASSWORD", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.virtuoso.NUMBER_OF_BUFFERS_PER_GB": {"fullname": "bench_executor.virtuoso.NUMBER_OF_BUFFERS_PER_GB", "modulename": "bench_executor.virtuoso", "qualname": "NUMBER_OF_BUFFERS_PER_GB", "kind": "variable", "doc": "

    \n", "default_value": "85000"}, "bench_executor.virtuoso.MAX_DIRTY_BUFFERS_PER_GB": {"fullname": "bench_executor.virtuoso.MAX_DIRTY_BUFFERS_PER_GB", "modulename": "bench_executor.virtuoso", "qualname": "MAX_DIRTY_BUFFERS_PER_GB", "kind": "variable", "doc": "

    \n", "default_value": "65000"}, "bench_executor.virtuoso.Virtuoso": {"fullname": "bench_executor.virtuoso.Virtuoso", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso", "kind": "class", "doc": "

    Virtuoso container to execute SPARQL queries

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.virtuoso.Virtuoso.__init__": {"fullname": "bench_executor.virtuoso.Virtuoso.__init__", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.__init__", "kind": "function", "doc": "

    Creates an instance of the Virtuoso class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.virtuoso.Virtuoso.initialization": {"fullname": "bench_executor.virtuoso.Virtuoso.initialization", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.initialization", "kind": "function", "doc": "

    Initialize Virtuoso's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.root_mount_directory": {"fullname": "bench_executor.virtuoso.Virtuoso.root_mount_directory", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Virtuoso.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Virtuoso.
      • \n
    \n", "annotation": ": str"}, "bench_executor.virtuoso.Virtuoso.wait_until_ready": {"fullname": "bench_executor.virtuoso.Virtuoso.wait_until_ready", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.wait_until_ready", "kind": "function", "doc": "

    Wait until Virtuoso is ready to execute SPARQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the Virtuoso container, optionally, defaults\nto no command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the Virtuoso was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.load": {"fullname": "bench_executor.virtuoso.Virtuoso.load", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.load", "kind": "function", "doc": "

    Load an RDF file into Virtuoso.

    \n\n

    Currently, only N-Triples files are supported.

    \n\n
    Parameters
    \n\n
      \n
    • rdf_file (str):\nName of the RDF file to load.
      • \n
    • rdf_dir (str):\nName of the directory where RDF file(s) are stored.\nDefault root of the data directory.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the loading was successfull or not.
      • \n
    \n", "signature": "(self, rdf_file: str, rdf_dir: str = '') -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.load_parallel": {"fullname": "bench_executor.virtuoso.Virtuoso.load_parallel", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.load_parallel", "kind": "function", "doc": "

    Load an RDF file into Virtuoso in parallel.

    \n\n

    Currently, only N-Triples files are supported.

    \n\n
    Parameters
    \n\n
      \n
    • rdf_file (str):\nName of the RDF file to load.
      • \n
    • cores (int):\nNumber of CPU cores for loading.
      • \n
    • rdf_dir (str):\nName of the directory where RDF file(s) are stored.\nDefault root of the data directory.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the loading was successfull or not.
      • \n
    \n", "signature": "(self, rdf_file: str, cores: int, rdf_dir: str = '') -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.stop": {"fullname": "bench_executor.virtuoso.Virtuoso.stop", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.stop", "kind": "function", "doc": "

    Stop Virtuoso.

    \n\n

    Drops all triples in Virtuoso before stopping its container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether stopping Virtuoso was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.endpoint": {"fullname": "bench_executor.virtuoso.Virtuoso.endpoint", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.endpoint", "kind": "variable", "doc": "

    SPARQL endpoint URL

    \n", "annotation": ": str"}, "bench_executor.virtuoso.Virtuoso.headers": {"fullname": "bench_executor.virtuoso.Virtuoso.headers", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.headers", "kind": "variable", "doc": "

    HTTP headers of SPARQL queries for serialization formats.

    \n\n

    Only supported serialization formats are included in the dictionary.\nCurrently, the following formats are supported:

    \n\n
      \n
    • N-Triples
      • \n
    • Turtle
      • \n
    • CSV
      • \n
    • RDF/JSON
      • \n
    • RDF/XML
      • \n
    • JSON-LD
      • \n
    \n\n
    Returns
    \n\n
      \n
    • headers (dict):\nDictionary of headers to use for each serialization format.
      • \n
    \n", "annotation": ": Dict[str, Dict[str, str]]"}, "bench_executor.yarrrml": {"fullname": "bench_executor.yarrrml", "modulename": "bench_executor.yarrrml", "kind": "module", "doc": "

    YARRRML is a human readable text-based representation for declarative\nLinked Data generation rules.

    \n\n

    Website: https://rml.io/yarrrml/
    \nRepository: https://github.com/RMLio/yarrrml-parser

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    \n", "default_value": "'1.3.6'"}, "bench_executor.yarrrml.YARRRML": {"fullname": "bench_executor.yarrrml.YARRRML", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML", "kind": "class", "doc": "

    YARRRML container to transform YARRRML mappings into RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.yarrrml.YARRRML.__init__": {"fullname": "bench_executor.yarrrml.YARRRML.__init__", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML.__init__", "kind": "function", "doc": "

    Creates an instance of the YARRRML class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.yarrrml.YARRRML.root_mount_directory": {"fullname": "bench_executor.yarrrml.YARRRML.root_mount_directory", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for YARRRML.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for YARRRML.
      • \n
    \n", "annotation": ": str"}, "bench_executor.yarrrml.YARRRML.transform_mapping": {"fullname": "bench_executor.yarrrml.YARRRML.transform_mapping", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML.transform_mapping", "kind": "function", "doc": "

    Transform a YARRRML mapping into a RML mapping.

    \n\n
    Parameters
    \n\n
      \n
    • yarrrml_file (str):\nName of the YARRRML mapping file.
      • \n
    • mapping_file (str):\nName of the RML mapping file.
      • \n
    • r2rml (bool):\nWhether the RML mapping file must be R2RML compatible.
      • \n
    • pretty (bool):\nWhether the generated mapping file must be pretty or not.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the YARRRML was initialized successfull or not.
      • \n
    \n", "signature": "(\tself,\tyarrrml_file: str,\tmapping_file: str,\tr2rml: bool = False,\tpretty: bool = True) -> bool:", "funcdef": "def"}}, "docInfo": {"bench_executor.collector": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 482}, "bench_executor.collector.CASE_INFO_FILE_NAME": {"qualname": 4, "fullname": 7, "annotation": 2, "default_value": 7, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.METRICS_FILE_NAME": {"qualname": 3, "fullname": 6, "annotation": 2, "default_value": 6, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.METRICS_VERSION": {"qualname": 2, "fullname": 5, "annotation": 2, "default_value": 1, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.FIELDNAMES": {"qualname": 1, "fullname": 4, "annotation": 2, "default_value": 129, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.ROUND": {"qualname": 1, "fullname": 4, "annotation": 2, 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    This module holds the Collector class which is responsible for collecting\nmetrics during the execution of a case. It also collects hardware information\nfor provenance reasons when comparing results from cases.

    \n\n

    The following metrics are collected:

    \n\n

    General

    \n\n
      \n
    • name: name of the case being executed.
      • \n
    • index: incremental index for each collected sample.
      • \n
    • step: Number of the step of a collected sample.
      • \n
    • timestamp: The time when the sample was collected.
      • \n
    • version: format version of the collected version, currently v2.
      • \n
    \n\n

    CPU

    \n\n
      \n
    • cpu_user: CPU time spent in userspace.
      • \n
    • cpu_system: CPU time spent in kernelspace.
      • \n
    • cpu_user_system: sum of CPU time userspace and kernelspace.
      • \n
    • cpu_idle: CPU time spent in idle mode.
      • \n
    • cpu_iowait: Time that the CPU has to wait for IO operations to complete.
      • \n
    \n\n

    Memory

    \n\n
      \n
    • memory_ram: Amount of RAM memory in use.
      • \n
    • memory_swap: Amount of SWAP memory in use.
      • \n
    • memory_ram_swap: Sum of the RAM and SWAP memory in use.
      • \n
    \n\n

    Disk

    \n\n
      \n
    • disk_read_count: Number of disk reads.
      • \n
    • disk_write_count: Number of disk writes.
      • \n
    • disk_read_bytes: Number of bytes read from disk.
      • \n
    • disk_write_bytes: Number of bytes written to disk.
      • \n
    • disk_read_time: Time spent to read from disk.
      • \n
    • disk_write_time: Time spent to write to disk.
      • \n
    • disk_busy_time: Time that the disk is busy and all actions are pending.
      • \n
    \n\n

    Network

    \n\n
      \n
    • network_received_count: Number of network packets received.
      • \n
    • network_sent_count: Number of network packets sent.
      • \n
    • network_received_bytes: Number of bytes received over network.
      • \n
    • network_sent_bytes: Number of bytes sent over network.
      • \n
    • network_received_error: Number of errors occured during receiving over\nnetwork.
      • \n
    • network_sent_error: Number of errors occured during sending over network.
      • \n
    • network_received_drop: Number of packets dropped during receiving over\nnetwork.
      • \n
    • network_sent_drop: Number of packets dropped during sending over network.
      • \n
    \n"}, "bench_executor.collector.CASE_INFO_FILE_NAME": {"fullname": "bench_executor.collector.CASE_INFO_FILE_NAME", "modulename": "bench_executor.collector", "qualname": "CASE_INFO_FILE_NAME", "kind": "variable", "doc": "

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    \n", "annotation": ": List[str]", "default_value": "['name', 'run', 'index', 'step', 'timestamp', 'version', 'cpu_user', 'cpu_system', 'cpu_user_system', 'cpu_idle', 'cpu_iowait', 'memory_ram', 'memory_swap', 'memory_ram_swap', 'disk_read_count', 'disk_write_count', 'disk_read_bytes', 'disk_write_bytes', 'disk_read_time', 'disk_write_time', 'disk_busy_time', 'network_received_count', 'network_sent_count', 'network_received_bytes', 'network_sent_bytes', 'network_received_error', 'network_sent_error', 'network_received_drop', 'network_sent_drop']"}, "bench_executor.collector.ROUND": {"fullname": "bench_executor.collector.ROUND", "modulename": "bench_executor.collector", "qualname": "ROUND", "kind": "variable", "doc": "

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    Collect metrics samples at a given interval for a run of a case.

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    Create an instance of the Collector class.

    \n\n

    Instantiating this class will automatically generate a case-info.txt\nfile which describes the hardware used during collection of the\nmetrics. The file describes:

    \n\n
      \n
    • Case:\n
        \n
      • Name of the case.
        • \n
      • Timestamp when started.
        • \n
      • Directory of the case.
        • \n
      • Number of the run.
        • \n
      • Number of steps in a case.
        • \n
      • \n
    • Hardware:\n
        \n
      • CPU name.
        • \n
      • Number of CPU cores.
        • \n
      • Minimum and maximum CPU core frequency.
        • \n
      • Amount of RAM and SWAP memory
        • \n
      • Available disk storage.
        • \n
      • Available network interfaces and their link speed.
        • \n
      • \n
    • Docker:\n
        \n
      • Version of the Docker daemon
        • \n
      • Docker root directory
        • \n
      • Docker storage driver
        • \n
      • Docker CgroupFS driver and version
        • \n
      • \n
    \n\n
    Parameters
    \n\n
      \n
    • case_name (str):\nName of the case being executed.
      • \n
    • results_run_path (str):\nPath to the results directory of the run currently being executed.
      • \n
    • sample_interval (float):\nSample interval in seconds for collecting metrics.
      • \n
    • number_of_steps (int):\nThe number of steps of the case that is being executed.
      • \n
    • run_id (int):\nThe number of the run that is being executed.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
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    Name of the class: Collector

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    Increment the step number by one.

    \n\n

    The step number must always be equal or lower than the number of steps\nin the case.

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    End metrics collection.

    \n\n

    Signal the metrics collection thread to stop collecting any metrics.

    \n", "signature": "(self):", "funcdef": "def"}, "bench_executor.collector.scputimes": {"fullname": "bench_executor.collector.scputimes", "modulename": "bench_executor.collector", "qualname": "scputimes", "kind": "class", "doc": "

    scputimes()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.scputimes.__init__": {"fullname": "bench_executor.collector.scputimes.__init__", "modulename": "bench_executor.collector", "qualname": "scputimes.__init__", "kind": "function", "doc": "

    Create new instance of scputimes()

    \n", "signature": "()"}, "bench_executor.collector.sswap": {"fullname": "bench_executor.collector.sswap", "modulename": "bench_executor.collector", "qualname": "sswap", "kind": "class", "doc": "

    sswap()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.sswap.__init__": {"fullname": "bench_executor.collector.sswap.__init__", "modulename": "bench_executor.collector", "qualname": "sswap.__init__", "kind": "function", "doc": "

    Create new instance of sswap()

    \n", "signature": "()"}, "bench_executor.collector.svmem": {"fullname": "bench_executor.collector.svmem", "modulename": "bench_executor.collector", "qualname": "svmem", "kind": "class", "doc": "

    svmem()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.svmem.__init__": {"fullname": "bench_executor.collector.svmem.__init__", "modulename": "bench_executor.collector", "qualname": "svmem.__init__", "kind": "function", "doc": "

    Create new instance of svmem()

    \n", "signature": "()"}, "bench_executor.collector.sdiskio": {"fullname": "bench_executor.collector.sdiskio", "modulename": "bench_executor.collector", "qualname": "sdiskio", "kind": "class", "doc": "

    sdiskio()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.sdiskio.__init__": {"fullname": "bench_executor.collector.sdiskio.__init__", "modulename": "bench_executor.collector", "qualname": "sdiskio.__init__", "kind": "function", "doc": "

    Create new instance of sdiskio()

    \n", "signature": "()"}, "bench_executor.collector.snetio": {"fullname": "bench_executor.collector.snetio", "modulename": "bench_executor.collector", "qualname": "snetio", "kind": "class", "doc": "

    snetio()

    \n", "bases": "builtins.tuple"}, "bench_executor.collector.snetio.__init__": {"fullname": "bench_executor.collector.snetio.__init__", "modulename": "bench_executor.collector", "qualname": "snetio.__init__", "kind": "function", "doc": "

    Create new instance of snetio()

    \n", "signature": "()"}, "bench_executor.container": {"fullname": "bench_executor.container", "modulename": "bench_executor.container", "kind": "module", "doc": "

    This module holds the Container and ContainerManager classes. The Container\nclass is responsible for abstracting the Docker containers and allow running\ncontainers easily and make sure they are initialized before using them.\nThe Containermanager class allows to create container networks, list all\nrunning containers and stop them.

    \n"}, "bench_executor.container.WAIT_TIME": {"fullname": "bench_executor.container.WAIT_TIME", "modulename": "bench_executor.container", "qualname": "WAIT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "1"}, "bench_executor.container.TIMEOUT_TIME": {"fullname": "bench_executor.container.TIMEOUT_TIME", "modulename": "bench_executor.container", "qualname": "TIMEOUT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "600"}, "bench_executor.container.NETWORK_NAME": {"fullname": "bench_executor.container.NETWORK_NAME", "modulename": "bench_executor.container", "qualname": "NETWORK_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'bench_executor'"}, "bench_executor.container.ContainerManager": {"fullname": "bench_executor.container.ContainerManager", "modulename": "bench_executor.container", "qualname": "ContainerManager", "kind": "class", "doc": "

    Manage containers and networks.

    \n"}, "bench_executor.container.ContainerManager.__init__": {"fullname": "bench_executor.container.ContainerManager.__init__", "modulename": "bench_executor.container", "qualname": "ContainerManager.__init__", "kind": "function", "doc": "

    Creates an instance of the ContainerManager class.

    \n", "signature": "(docker: bench_executor.docker.Docker)"}, "bench_executor.container.ContainerManager.create_network": {"fullname": "bench_executor.container.ContainerManager.create_network", "modulename": "bench_executor.container", "qualname": "ContainerManager.create_network", "kind": "function", "doc": "

    Create a container network.

    \n\n
    Parameters
    \n\n
      \n
    • name (str):\nName of the network
      • \n
    \n", "signature": "(self, name: str):", "funcdef": "def"}, "bench_executor.container.Container": {"fullname": "bench_executor.container.Container", "modulename": "bench_executor.container", "qualname": "Container", "kind": "class", "doc": "

    Container abstracts a Docker container

    \n\n

    Abstract how to run a command in a container, start or stop a container,\nor retrieve logs. Also allow to wait for a certain log entry to appear or\nexit successfully.

    \n"}, "bench_executor.container.Container.__init__": {"fullname": "bench_executor.container.Container.__init__", "modulename": "bench_executor.container", "qualname": "Container.__init__", "kind": "function", "doc": "

    Creates an instance of the Container class.

    \n\n
    Parameters
    \n\n
      \n
    • container (str):\nContainer ID.
      • \n
    • name (str):\nPretty name of the container.
      • \n
    • logger (Logger):\nLogger class to use for container logs.
      • \n
    • ports (dict):\nPorts mapping of the container onto the host.
      • \n
    • volumes (list):\nVolumes mapping of the container onto the host.
      • \n
    \n", "signature": "(\tcontainer: str,\tname: str,\tlogger: bench_executor.logger.Logger,\tports: dict = {},\tenvironment: dict = {},\tvolumes: List[str] = [])"}, "bench_executor.container.Container.started": {"fullname": "bench_executor.container.Container.started", "modulename": "bench_executor.container", "qualname": "Container.started", "kind": "variable", "doc": "

    Indicates if the container is already started

    \n", "annotation": ": bool"}, "bench_executor.container.Container.name": {"fullname": "bench_executor.container.Container.name", "modulename": "bench_executor.container", "qualname": "Container.name", "kind": "variable", "doc": "

    The pretty name of the container

    \n", "annotation": ": str"}, "bench_executor.container.Container.run": {"fullname": "bench_executor.container.Container.run", "modulename": "bench_executor.container", "qualname": "Container.run", "kind": "function", "doc": "

    Run the container.

    \n\n

    This is used for containers which are long running to provide services\nsuch as a database or endpoint.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nThe command to execute in the container, optionally and defaults to\nno command.
      • \n
    • detach (bool):\nIf the container may run in the background, default True.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether running the container was successfull or not.
      • \n
    \n", "signature": "(self, command: str = '', detach=True) -> bool:", "funcdef": "def"}, "bench_executor.container.Container.exec": {"fullname": "bench_executor.container.Container.exec", "modulename": "bench_executor.container", "qualname": "Container.exec", "kind": "function", "doc": "

    Execute a command in the container.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nThe command to execute in the container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the command was executed successfully or not.
      • \n
    • logs (list):\nThe logs of the container for executing the command.
      • \n
    \n", "signature": "(self, command: str) -> Tuple[bool, List[str]]:", "funcdef": "def"}, "bench_executor.container.Container.run_and_wait_for_log": {"fullname": "bench_executor.container.Container.run_and_wait_for_log", "modulename": "bench_executor.container", "qualname": "Container.run_and_wait_for_log", "kind": "function", "doc": "

    Run the container and wait for a log line to appear.

    \n\n

    This blocks until the container's log contains the log_line.

    \n\n
    Parameters
    \n\n
      \n
    • log_line (str):\nThe log line to wait for in the logs.
      • \n
    • command (str):\nThe command to execute in the container, optionally and defaults to\nno command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the container exited with status code 0 or not.
      • \n
    \n", "signature": "(self, log_line: str, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.container.Container.run_and_wait_for_exit": {"fullname": "bench_executor.container.Container.run_and_wait_for_exit", "modulename": "bench_executor.container", "qualname": "Container.run_and_wait_for_exit", "kind": "function", "doc": "

    Run the container and wait for exit

    \n\n

    This blocks until the container exit and gives a status code.

    \n\n

    Parameters

    \n\n
    \n\n

    command : str\n The command to execute in the container, optionally and defaults to\n no command.

    \n\n

    Returns

    \n\n
    \n\n

    success : bool\n Whether the container exited with status code 0 or not.

    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.container.Container.stop": {"fullname": "bench_executor.container.Container.stop", "modulename": "bench_executor.container", "qualname": "Container.stop", "kind": "function", "doc": "

    Stop a running container

    \n\n

    Stops the container and removes it, including its volumes.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether stopping the container was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.docker": {"fullname": "bench_executor.docker", "modulename": "bench_executor.docker", "kind": "module", "doc": "

    This module holds the Docker class which implements the necessary API calls\nfor the Container class to control Docker containers. The docker-py module\nwhich is similar has serious issues with resource leaking for years.

    \n"}, "bench_executor.docker.Docker": {"fullname": "bench_executor.docker.Docker", "modulename": "bench_executor.docker", "qualname": "Docker", "kind": "class", "doc": "

    Client for the Docker CLI.

    \n"}, "bench_executor.docker.Docker.__init__": {"fullname": "bench_executor.docker.Docker.__init__", "modulename": "bench_executor.docker", "qualname": "Docker.__init__", "kind": "function", "doc": "

    Creates an instance of the Docker class.

    \n", "signature": "(logger: bench_executor.logger.Logger)"}, "bench_executor.docker.Docker.exec": {"fullname": "bench_executor.docker.Docker.exec", "modulename": "bench_executor.docker", "qualname": "Docker.exec", "kind": "function", "doc": "

    Execute a command inside a running Docker container.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    • command (str):\nCommand to execute inside the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • status_code (int):\nThe exit status code of the executed command.
      • \n
    \n", "signature": "(self, container_id: str, command: str) -> int:", "funcdef": "def"}, "bench_executor.docker.Docker.wait": {"fullname": "bench_executor.docker.Docker.wait", "modulename": "bench_executor.docker", "qualname": "Docker.wait", "kind": "function", "doc": "

    Wait for Docker container to exit.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • status_code (int):\nThe exit status code of the Docker container.
      • \n
    \n", "signature": "(self, container_id: str) -> int:", "funcdef": "def"}, "bench_executor.docker.Docker.stop": {"fullname": "bench_executor.docker.Docker.stop", "modulename": "bench_executor.docker", "qualname": "Docker.stop", "kind": "function", "doc": "

    Stop a running Docker container.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if stopping the container was successful.
      • \n
    \n", "signature": "(self, container_id: str) -> bool:", "funcdef": "def"}, "bench_executor.docker.Docker.logs": {"fullname": "bench_executor.docker.Docker.logs", "modulename": "bench_executor.docker", "qualname": "Docker.logs", "kind": "function", "doc": "

    Retrieve the logs of a container.

    \n\n
    Parameters
    \n\n
      \n
    • container_id (str):\nID of the Docker container.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • logs (List[str]):\nList of loglines from the container.
      • \n
    \n", "signature": "(self, container_id: str) -> List[str]:", "funcdef": "def"}, "bench_executor.docker.Docker.pull": {"fullname": "bench_executor.docker.Docker.pull", "modulename": "bench_executor.docker", "qualname": "Docker.pull", "kind": "function", "doc": "

    Pull a Docker image from DockerHub or other registries.

    \n\n

    If the image exists locally, pulling will be skipped without\nthe force flag.

    \n\n
    Parameters
    \n\n
      \n
    • image (str):\nName of the Docker container image.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if starting the container was successful.
      • \n
    \n", "signature": "(self, image: str) -> bool:", "funcdef": "def"}, "bench_executor.docker.Docker.run": {"fullname": "bench_executor.docker.Docker.run", "modulename": "bench_executor.docker", "qualname": "Docker.run", "kind": "function", "doc": "

    Start a Docker container.

    \n\n
    Parameters
    \n\n
      \n
    • image (str):\nName of the Docker container image.
      • \n
    • command (str):\nCommand to execute in the Docker container.
      • \n
    • name (str):\nCanonical name to assign to the container.
      • \n
    • detach (bool):\nWhether to detach from the container or not.
      • \n
    • ports (dict):\nPorts to expose from the container to the host.
      • \n
    • network (str):\nName of the Docker network to attach the container to.
      • \n
    • environment (dict):\nEnvironment variables to set.
      • \n
    • volumes (List[str]):\nVolumes to mount on the container from the host.
      • \n
    • must_pull (bool):\nWhether the image should be pulled first, default is True.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if starting the container was successful.
      • \n
    • container_id (str):\nID of the container that was started.
      • \n
    \n", "signature": "(\tself,\timage: str,\tcommand: str,\tname: str,\tdetach: bool,\tports: dict,\tnetwork: str,\tenvironment: dict,\tvolumes: List[str],\tmust_pull: bool = True) -> Tuple[bool, str]:", "funcdef": "def"}, "bench_executor.docker.Docker.create_network": {"fullname": "bench_executor.docker.Docker.create_network", "modulename": "bench_executor.docker", "qualname": "Docker.create_network", "kind": "function", "doc": "

    Create a Docker container network.

    \n\n

    If the network already exist, it will not be recreated.

    \n\n
    Parameters
    \n\n
      \n
    • network (str):\nName of the network.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if the network was created
      • \n
    \n", "signature": "(self, network: str) -> bool:", "funcdef": "def"}, "bench_executor.docker.Docker.info": {"fullname": "bench_executor.docker.Docker.info", "modulename": "bench_executor.docker", "qualname": "Docker.info", "kind": "function", "doc": "

    Dump the Docker daemon system information.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nTrue if the command succeed.
      • \n
    • info (dict):\nDocker daemon system information as dictionary.
      • \n
    \n", "signature": "(self) -> Tuple[bool, dict]:", "funcdef": "def"}, "bench_executor.executor": {"fullname": "bench_executor.executor", "modulename": "bench_executor.executor", "kind": "module", "doc": "

    This module holds the Executor class which is responsible for executing a case,\ncollecting metrics, and exposing this functionality to the CLI.\nAll features of this tool can be accessed through the Executor class, other\nclasses should not be used directly.

    \n"}, "bench_executor.executor.METADATA_FILE": {"fullname": "bench_executor.executor.METADATA_FILE", "modulename": "bench_executor.executor", "qualname": "METADATA_FILE", "kind": "variable", "doc": "

    \n", "default_value": "'metadata.json'"}, "bench_executor.executor.SCHEMA_FILE": {"fullname": "bench_executor.executor.SCHEMA_FILE", "modulename": "bench_executor.executor", "qualname": "SCHEMA_FILE", "kind": "variable", "doc": "

    \n", "default_value": "'metadata.schema'"}, "bench_executor.executor.CONFIG_DIR": {"fullname": "bench_executor.executor.CONFIG_DIR", "modulename": "bench_executor.executor", "qualname": "CONFIG_DIR", "kind": "variable", "doc": "

    \n", "default_value": "'/home/dylan/Projects/KROWN/execution-framework/bench_executor/config'"}, "bench_executor.executor.WAIT_TIME": {"fullname": "bench_executor.executor.WAIT_TIME", "modulename": "bench_executor.executor", "qualname": "WAIT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "15"}, "bench_executor.executor.CHECKPOINT_FILE_NAME": {"fullname": "bench_executor.executor.CHECKPOINT_FILE_NAME", "modulename": "bench_executor.executor", "qualname": "CHECKPOINT_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'.done'"}, "bench_executor.executor.Executor": {"fullname": "bench_executor.executor.Executor", "modulename": "bench_executor.executor", "qualname": "Executor", "kind": "class", "doc": "

    Executor class executes a case.

    \n"}, "bench_executor.executor.Executor.__init__": {"fullname": "bench_executor.executor.Executor.__init__", "modulename": "bench_executor.executor", "qualname": "Executor.__init__", "kind": "function", "doc": "

    Create an instance of the Executor class.

    \n\n
    Parameters
    \n\n
      \n
    • main_directory (str):\nThe root directory of all the cases to execute.
      • \n
    • verbose (bool):\nEnables verbose logs.
      • \n
    • process_cb (function):\nCallback to call when a step is completed of the case. By default,\na dummy callback is provided if the argument is missing.
      • \n
    \n", "signature": "(\tmain_directory: str,\tverbose: bool = False,\tprogress_cb=<function _progress_cb>)"}, "bench_executor.executor.Executor.main_directory": {"fullname": "bench_executor.executor.Executor.main_directory", "modulename": "bench_executor.executor", "qualname": "Executor.main_directory", "kind": "variable", "doc": "

    The main directory of all the cases.

    \n\n
    Returns
    \n\n
      \n
    • main_directory (str):\nThe path to the main directory of the cases.
      • \n
    \n", "annotation": ": str"}, "bench_executor.executor.Executor.stats": {"fullname": "bench_executor.executor.Executor.stats", "modulename": "bench_executor.executor", "qualname": "Executor.stats", "kind": "function", "doc": "

    Generate statistics for a case.

    \n\n

    Generate statistics for an executed case. The case must be executed\nbefore to succeed.

    \n\n
    Parameters
    \n\n
      \n
    • case (dict):\nThe case to generate statistics for.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the statistics are generated with success or not.
      • \n
    \n", "signature": "(self, case: dict) -> bool:", "funcdef": "def"}, "bench_executor.executor.Executor.clean": {"fullname": "bench_executor.executor.Executor.clean", "modulename": "bench_executor.executor", "qualname": "Executor.clean", "kind": "function", "doc": "

    Clean a case.

    \n\n

    Clean up all results and metrics for a case to start it fresh.

    \n\n
    Parameters
    \n\n
      \n
    • case (dict):\nThe case to clean.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the cleaning of the case succeeded or not.
      • \n
    \n", "signature": "(self, case: dict) -> bool:", "funcdef": "def"}, "bench_executor.executor.Executor.run": {"fullname": "bench_executor.executor.Executor.run", "modulename": "bench_executor.executor", "qualname": "Executor.run", "kind": "function", "doc": "

    Execute a case.

    \n\n

    Execute all steps of a case while collecting metrics and logs.\nThe metrics are collected at a given interval and for a specific run of\nthe case to allow multiple executions of the same case. Checkpoints of\nruns can be enabled to allow the executor to restart where it stopped\nin case of a failure, electricity blackout, etc.

    \n\n
    Parameters
    \n\n
      \n
    • case (dict):\nThe case to execute.
      • \n
    • interval (float):\nThe sample interval for the metrics collection.
      • \n
    • run (int):\nThe run number of the case.
      • \n
    • checkpoint (bool):\nEnable checkpoints after each run to allow restarts.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the case was executed successfully or not.
      • \n
    \n", "signature": "(self, case: dict, interval: float, run: int, checkpoint: bool) -> bool:", "funcdef": "def"}, "bench_executor.executor.Executor.list": {"fullname": "bench_executor.executor.Executor.list", "modulename": "bench_executor.executor", "qualname": "Executor.list", "kind": "function", "doc": "

    List all cases in a root directory.

    \n\n

    Retrieve a list of all discovered valid cases in a given directory.\nCases which do not pass the validation, are excluded and their\nvalidation errors are reported through logging.

    \n\n
    Returns
    \n\n
      \n
    • cases (list):\nList of discovered cases.
      • \n
    \n", "signature": "(self) -> list:", "funcdef": "def"}, "bench_executor.fuseki": {"fullname": "bench_executor.fuseki", "modulename": "bench_executor.fuseki", "kind": "module", "doc": "

    Apache Jena Fuseki is a SPARQL server. It can run as an operating system\nservice, as a Java web application (WAR file), and as a standalone server.

    \n\n

    Website: https://jena.apache.org/documentation/fuseki2/

    \n"}, "bench_executor.fuseki.VERSION": {"fullname": "bench_executor.fuseki.VERSION", "modulename": "bench_executor.fuseki", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'4.6.1'"}, "bench_executor.fuseki.CMD_ARGS": {"fullname": "bench_executor.fuseki.CMD_ARGS", "modulename": "bench_executor.fuseki", "qualname": "CMD_ARGS", "kind": "variable", "doc": "

    \n", "default_value": "'--tdb2 --update --loc /fuseki/databases/DB /ds'"}, "bench_executor.fuseki.Fuseki": {"fullname": "bench_executor.fuseki.Fuseki", "modulename": "bench_executor.fuseki", "qualname": "Fuseki", "kind": "class", "doc": "

    Fuseki container for executing SPARQL queries.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.fuseki.Fuseki.__init__": {"fullname": "bench_executor.fuseki.Fuseki.__init__", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.__init__", "kind": "function", "doc": "

    Creates an instance of the Fuseki class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.fuseki.Fuseki.initialization": {"fullname": "bench_executor.fuseki.Fuseki.initialization", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.initialization", "kind": "function", "doc": "

    Initialize Fuseki's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.root_mount_directory": {"fullname": "bench_executor.fuseki.Fuseki.root_mount_directory", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Fuseki.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Fuseki.
      • \n
    \n", "annotation": ": str"}, "bench_executor.fuseki.Fuseki.headers": {"fullname": "bench_executor.fuseki.Fuseki.headers", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.headers", "kind": "variable", "doc": "

    HTTP headers of SPARQL queries for serialization formats.

    \n\n

    Only supported serialization formats are included in the dictionary.\nCurrently, the following formats are supported:

    \n\n
      \n
    • N-Triples
      • \n
    • Turtle
      • \n
    • CSV
      • \n
    • RDF/JSON
      • \n
    • RDF/XML
      • \n
    • JSON-LD
      • \n
    \n\n
    Returns
    \n\n
      \n
    • headers (dict):\nDictionary of headers to use for each serialization format.
      • \n
    \n", "annotation": ": Dict[str, Dict[str, str]]"}, "bench_executor.fuseki.Fuseki.wait_until_ready": {"fullname": "bench_executor.fuseki.Fuseki.wait_until_ready", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.wait_until_ready", "kind": "function", "doc": "

    Wait until Fuseki is ready to execute SPARQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the Fuseki container, optionally, defaults to\nno command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the Fuseki was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.load": {"fullname": "bench_executor.fuseki.Fuseki.load", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.load", "kind": "function", "doc": "

    Load an RDF file into Fuseki.

    \n\n

    Currently, only N-Triples files are supported.

    \n\n
    Parameters
    \n\n
      \n
    • rdf_file (str):\nName of the RDF file to load.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the loading was successfull or not.
      • \n
    \n", "signature": "(self, rdf_file: str) -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.stop": {"fullname": "bench_executor.fuseki.Fuseki.stop", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.stop", "kind": "function", "doc": "

    Stop Fuseki.

    \n\n

    Drops all triples in Fuseki before stopping its container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether stopping Fuseki was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.fuseki.Fuseki.endpoint": {"fullname": "bench_executor.fuseki.Fuseki.endpoint", "modulename": "bench_executor.fuseki", "qualname": "Fuseki.endpoint", "kind": "variable", "doc": "

    SPARQL endpoint URL

    \n"}, "bench_executor": {"fullname": "bench_executor", "modulename": "bench_executor", "kind": "module", "doc": "

    bench_executor module allows you to execute benchmark scenarios\nwith multiple runs and automatically collect metrics.

    \n"}, "bench_executor.logger": {"fullname": "bench_executor.logger", "modulename": "bench_executor.logger", "kind": "module", "doc": "

    This module contains the Logger class which is responsible for logging.\nThis class is a small wrapper around the Python logging module to automatically\nconfigure the loggers and handle unittest logging.

    \n"}, "bench_executor.logger.LOG_FILE_NAME": {"fullname": "bench_executor.logger.LOG_FILE_NAME", "modulename": "bench_executor.logger", "qualname": "LOG_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'log.txt'"}, "bench_executor.logger.LOGGER_FORMAT_FILE": {"fullname": "bench_executor.logger.LOGGER_FORMAT_FILE", "modulename": "bench_executor.logger", "qualname": "LOGGER_FORMAT_FILE", "kind": "variable", "doc": "

    \n", "default_value": "'[%(asctime)s] %(levelname)-8s %(message)-s'"}, "bench_executor.logger.LOGGER_FORMAT_CONSOLE": {"fullname": "bench_executor.logger.LOGGER_FORMAT_CONSOLE", "modulename": "bench_executor.logger", "qualname": "LOGGER_FORMAT_CONSOLE", "kind": "variable", "doc": "

    \n", "default_value": "'%(levelname)s: %(message)s'"}, "bench_executor.logger.Logger": {"fullname": "bench_executor.logger.Logger", "modulename": "bench_executor.logger", "qualname": "Logger", "kind": "class", "doc": "

    Log messages to a log file and console.

    \n"}, "bench_executor.logger.Logger.__init__": {"fullname": "bench_executor.logger.Logger.__init__", "modulename": "bench_executor.logger", "qualname": "Logger.__init__", "kind": "function", "doc": "

    Creates an instance of the Logger class.

    \n\n

    During unittests, the UNITTEST environment variable is set which\ndisables the console logger.

    \n\n
    Parameters
    \n\n
      \n
    • name (str):\nName of the logger
      • \n
    • directory (str):\nThe path to the directory where the logs must be stored.
      • \n
    • verbose (bool):\nEnable verbose logs
      • \n
    \n", "signature": "(name: str, directory: str, verbose: bool)"}, "bench_executor.logger.Logger.verbose": {"fullname": "bench_executor.logger.Logger.verbose", "modulename": "bench_executor.logger", "qualname": "Logger.verbose", "kind": "variable", "doc": "

    Verbose logging enabled.

    \n\n
    Returns
    \n\n
      \n
    • verbose (bool):\nVerbose logging enabled or not.
      • \n
    \n", "annotation": ": bool"}, "bench_executor.logger.Logger.debug": {"fullname": "bench_executor.logger.Logger.debug", "modulename": "bench_executor.logger", "qualname": "Logger.debug", "kind": "function", "doc": "

    Log a message with level DEBUG.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.logger.Logger.info": {"fullname": "bench_executor.logger.Logger.info", "modulename": "bench_executor.logger", "qualname": "Logger.info", "kind": "function", "doc": "

    Log a message with level INFO.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.logger.Logger.warning": {"fullname": "bench_executor.logger.Logger.warning", "modulename": "bench_executor.logger", "qualname": "Logger.warning", "kind": "function", "doc": "

    Log a message with level WARNING.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.logger.Logger.error": {"fullname": "bench_executor.logger.Logger.error", "modulename": "bench_executor.logger", "qualname": "Logger.error", "kind": "function", "doc": "

    Log a message with level ERROR.

    \n", "signature": "(self, msg):", "funcdef": "def"}, "bench_executor.morphkgc": {"fullname": "bench_executor.morphkgc", "modulename": "bench_executor.morphkgc", "kind": "module", "doc": "

    Morph-KGC is an engine that constructs RDF and RDF-star knowledge graphs\nfrom heterogeneous data sources with the R2RML, RML and RML-star mapping\nlanguages.

    \n\n

    Website: https://morph-kgc.readthedocs.io/
    \nRepository: https://github.com/oeg-upm/morph-kgc

    \n"}, "bench_executor.morphkgc.VERSION": {"fullname": "bench_executor.morphkgc.VERSION", "modulename": "bench_executor.morphkgc", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'2.2.0'"}, "bench_executor.morphkgc.TIMEOUT": {"fullname": "bench_executor.morphkgc.TIMEOUT", "modulename": "bench_executor.morphkgc", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.morphkgc.MorphKGC": {"fullname": "bench_executor.morphkgc.MorphKGC", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC", "kind": "class", "doc": "

    Morph-KGC container for executing R2RML, RML, and RML-star mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.morphkgc.MorphKGC.__init__": {"fullname": "bench_executor.morphkgc.MorphKGC.__init__", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.__init__", "kind": "function", "doc": "

    Creates an instance of the MorphKGC class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.morphkgc.MorphKGC.root_mount_directory": {"fullname": "bench_executor.morphkgc.MorphKGC.root_mount_directory", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Morph-KGC.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Morph-KGC.
      • \n
    \n", "annotation": ": str"}, "bench_executor.morphkgc.MorphKGC.execute": {"fullname": "bench_executor.morphkgc.MorphKGC.execute", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.execute", "kind": "function", "doc": "

    Execute Morph-KGC with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to Morph-KGC.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.morphkgc.MorphKGC.execute_mapping": {"fullname": "bench_executor.morphkgc.MorphKGC.execute_mapping", "modulename": "bench_executor.morphkgc", "qualname": "MorphKGC.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with Morph-KGC.

    \n\n

    Morph-KGC can transform SQL relational databases (MySQL, PostgreSQL,\nOracle, Microsoft SQL Server, MariaDB, SQLite), tabular (CSV, TSV,\nExcel, Parquet, Feather, ORC, Stata, SAS, SPSS, ODS) and\nhierarchical files (JSON, XML).

    \n\n

    Morph-KGC currently only supports N-Quads and N-Triples in RDF and\nRDF-Star. RDF and RDF-Star output is done automatically, you can use\nthe same serialization format (ntriples, nquads) for both RDF\nand RDF-Star output.

    \n\n

    Morph-KGC can generate all triples in a single file or spread it\namong multiple files.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    • multiple_files (bool):\nIf the generated triples must be stored in multiple files, default\na single file.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None,\tmultiple_files: bool = False) -> bool:", "funcdef": "def"}, "bench_executor.morphrdb": {"fullname": "bench_executor.morphrdb", "modulename": "bench_executor.morphrdb", "kind": "module", "doc": "

    Morph-RDB (formerly called ODEMapster) is an RDB2RDF engine developed by\nthe Ontology Engineering Group, which follows the R2RML specification.

    \n\n

    Website: https://oeg.fi.upm.es/index.php/en/technologies/315-morph-rdb/index.html
    \nRepository: https://github.com/oeg-upm/morph-rdb

    \n"}, "bench_executor.morphrdb.VERSION": {"fullname": "bench_executor.morphrdb.VERSION", "modulename": "bench_executor.morphrdb", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'3.12.5'"}, "bench_executor.morphrdb.TIMEOUT": {"fullname": "bench_executor.morphrdb.TIMEOUT", "modulename": "bench_executor.morphrdb", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.morphrdb.MorphRDB": {"fullname": "bench_executor.morphrdb.MorphRDB", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB", "kind": "class", "doc": "

    Morph-RDB container for executing R2RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.morphrdb.MorphRDB.__init__": {"fullname": "bench_executor.morphrdb.MorphRDB.__init__", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.__init__", "kind": "function", "doc": "

    Creates an instance of the MorphRDB class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.morphrdb.MorphRDB.root_mount_directory": {"fullname": "bench_executor.morphrdb.MorphRDB.root_mount_directory", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Morph-RDB.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Morph-RDB.
      • \n
    \n", "annotation": ": str"}, "bench_executor.morphrdb.MorphRDB.execute": {"fullname": "bench_executor.morphrdb.MorphRDB.execute", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.execute", "kind": "function", "doc": "

    Execute Morph-KGC with the given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nAdditional arguments to supply to Morph-KGC.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.morphrdb.MorphRDB.execute_mapping": {"fullname": "bench_executor.morphrdb.MorphRDB.execute_mapping", "modulename": "bench_executor.morphrdb", "qualname": "MorphRDB.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with Morph-RDB.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for Morph-RDB. Only relational databases are supported by\nMorph-RDB, thus the relational database parameters are mandantory.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (str):\nUsername for the database.
      • \n
    • rdb_password (str):\nPassword for the database.
      • \n
    • rdb_host (str):\nHostname for the database.
      • \n
    • rdb_port (int):\nPort for the database.
      • \n
    • rdb_name (str):\nDatabase name for the database.
      • \n
    • rdb_type (str):\nDatabase type.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: str,\trdb_password: str,\trdb_host: str,\trdb_port: int,\trdb_name: str,\trdb_type: str) -> bool:", "funcdef": "def"}, "bench_executor.mysql": {"fullname": "bench_executor.mysql", "modulename": "bench_executor.mysql", "kind": "module", "doc": "

    MySQL is an open-source relational database management system developed by\nOracle Corporation.

    \n\n

    Website: https://www.mysql.com/
    \nRepository: https://github.com/mysql/mysql-server

    \n"}, "bench_executor.mysql.VERSION": {"fullname": "bench_executor.mysql.VERSION", "modulename": "bench_executor.mysql", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'8.0'"}, "bench_executor.mysql.HOST": {"fullname": "bench_executor.mysql.HOST", "modulename": "bench_executor.mysql", "qualname": "HOST", "kind": "variable", "doc": "

    \n", "default_value": "'localhost'"}, "bench_executor.mysql.USER": {"fullname": "bench_executor.mysql.USER", "modulename": "bench_executor.mysql", "qualname": "USER", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.mysql.PASSWORD": {"fullname": "bench_executor.mysql.PASSWORD", "modulename": "bench_executor.mysql", "qualname": "PASSWORD", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.mysql.DB": {"fullname": "bench_executor.mysql.DB", "modulename": "bench_executor.mysql", "qualname": "DB", "kind": "variable", "doc": "

    \n", "default_value": "'db'"}, "bench_executor.mysql.PORT": {"fullname": "bench_executor.mysql.PORT", "modulename": "bench_executor.mysql", "qualname": "PORT", "kind": "variable", "doc": "

    \n", "default_value": "'3306'"}, "bench_executor.mysql.CLEAR_TABLES_TIMEOUT": {"fullname": "bench_executor.mysql.CLEAR_TABLES_TIMEOUT", "modulename": "bench_executor.mysql", "qualname": "CLEAR_TABLES_TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "300"}, "bench_executor.mysql.MySQL": {"fullname": "bench_executor.mysql.MySQL", "modulename": "bench_executor.mysql", "qualname": "MySQL", "kind": "class", "doc": "

    MySQL container for executing SQL queries.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.mysql.MySQL.__init__": {"fullname": "bench_executor.mysql.MySQL.__init__", "modulename": "bench_executor.mysql", "qualname": "MySQL.__init__", "kind": "function", "doc": "

    Creates an instance of the MySQL class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.mysql.MySQL.initialization": {"fullname": "bench_executor.mysql.MySQL.initialization", "modulename": "bench_executor.mysql", "qualname": "MySQL.initialization", "kind": "function", "doc": "

    Initialize MySQL's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.root_mount_directory": {"fullname": "bench_executor.mysql.MySQL.root_mount_directory", "modulename": "bench_executor.mysql", "qualname": "MySQL.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for MySQL.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for MySQL.
      • \n
    \n", "annotation": ": str"}, "bench_executor.mysql.MySQL.wait_until_ready": {"fullname": "bench_executor.mysql.MySQL.wait_until_ready", "modulename": "bench_executor.mysql", "qualname": "MySQL.wait_until_ready", "kind": "function", "doc": "

    Wait until MySQL is ready to execute SQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the MySQL container, optionally, defaults to\nno command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the MySQL was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.load": {"fullname": "bench_executor.mysql.MySQL.load", "modulename": "bench_executor.mysql", "qualname": "MySQL.load", "kind": "function", "doc": "

    Load a single CSV file into MySQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_file (str):\nName of the CSV file.
      • \n
    • table (str):\nName of the table.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_file: str, table: str) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.load_multiple": {"fullname": "bench_executor.mysql.MySQL.load_multiple", "modulename": "bench_executor.mysql", "qualname": "MySQL.load_multiple", "kind": "function", "doc": "

    Load multiple CSV files into MySQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_files (list):\nList of CSV files to load. Each entry consist of a file and\ntable key.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_files: List[dict]) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.load_sql_schema": {"fullname": "bench_executor.mysql.MySQL.load_sql_schema", "modulename": "bench_executor.mysql", "qualname": "MySQL.load_sql_schema", "kind": "function", "doc": "

    Execute SQL schema with MySQL.

    \n\n

    Executes a .sql file with MySQL.\nIf the data is not loaded by the .sql file but only the schema is\nprovided through the .sql file, a list of CSV files can be provided to\nload them as well.

    \n\n
    Parameters
    \n\n
      \n
    • schema_file (str):\nName of the .sql file.
      • \n
    • csv_files (List[Tuple[str, str]]):\nList of CSV file names to load in the tables created with the .sql\nfile, may also be an empty list. Each entry contains a Tuple with\nthe name of the CSV file and the table name.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, schema_file: str, csv_files: List[Tuple[str, str]]) -> bool:", "funcdef": "def"}, "bench_executor.mysql.MySQL.stop": {"fullname": "bench_executor.mysql.MySQL.stop", "modulename": "bench_executor.mysql", "qualname": "MySQL.stop", "kind": "function", "doc": "

    Stop MySQL\nClears all tables and stops the MySQL container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.ontop": {"fullname": "bench_executor.ontop", "modulename": "bench_executor.ontop", "kind": "module", "doc": "

    Ontop is a Virtual Knowledge Graph system. It exposes the content of\narbitrary relational databases as knowledge graphs. These graphs are virtual,\nwhich means that data remains in the data sources instead of being moved\nto another database.

    \n\n

    Website: https://ontop-vkg.org
    \nRepository: https://github.com/ontop/ontop

    \n"}, "bench_executor.ontop.VERSION": {"fullname": "bench_executor.ontop.VERSION", "modulename": "bench_executor.ontop", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'5.0.0'"}, "bench_executor.ontop.TIMEOUT": {"fullname": "bench_executor.ontop.TIMEOUT", "modulename": "bench_executor.ontop", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.ontop.R2RML": {"fullname": "bench_executor.ontop.R2RML", "modulename": "bench_executor.ontop", "qualname": "R2RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.w3.org/ns/r2rml#')"}, "bench_executor.ontop.Ontop": {"fullname": "bench_executor.ontop.Ontop", "modulename": "bench_executor.ontop", "qualname": "Ontop", "kind": "class", "doc": "

    Ontop container super class for OntopMaterialize and OntopVirtualize.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.ontop.Ontop.__init__": {"fullname": "bench_executor.ontop.Ontop.__init__", "modulename": "bench_executor.ontop", "qualname": "Ontop.__init__", "kind": "function", "doc": "

    Creates an instance of the Ontop class.

    \n\n
    Parameters
    \n\n
      \n
    • name (str):\nPretty name of the container.
      • \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • logger (Logger):\nLogger to use for log messages.
      • \n
    • mode (str):\nOntop mode: materialize or endpoint
      • \n
    \n", "signature": "(\tname: str,\tdata_path: str,\tlogger: bench_executor.logger.Logger,\tmode: str)"}, "bench_executor.ontop.Ontop.root_mount_directory": {"fullname": "bench_executor.ontop.Ontop.root_mount_directory", "modulename": "bench_executor.ontop", "qualname": "Ontop.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Ontop.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Ontop.
      • \n
    \n", "annotation": ": str"}, "bench_executor.ontop.Ontop.endpoint": {"fullname": "bench_executor.ontop.Ontop.endpoint", "modulename": "bench_executor.ontop", "qualname": "Ontop.endpoint", "kind": "variable", "doc": "

    SPARQL endpoint URL for Ontop.

    \n\n
    Returns
    \n\n
      \n
    • url (str):\nSPARQL endpoint URL.
      • \n
    \n", "annotation": ": str"}, "bench_executor.ontop.Ontop.headers": {"fullname": "bench_executor.ontop.Ontop.headers", "modulename": "bench_executor.ontop", "qualname": "Ontop.headers", "kind": "variable", "doc": "

    HTTP headers of SPARQL queries for serialization formats.

    \n\n

    Only supported serialization formats are included in the dictionary.\nCurrently, the following formats are supported:

    \n\n
      \n
    • N-Triples
      • \n
    • N-Quads
      • \n
    • Turtle
      • \n
    • CSV
      • \n
    • RDF/JSON
      • \n
    • RDF/XML
      • \n
    • JSON-LD
      • \n
    \n\n
    Returns
    \n\n
      \n
    • headers (dict):\nDictionary of headers to use for each serialization format.
      • \n
    \n", "annotation": ": dict"}, "bench_executor.ontop.OntopVirtualize": {"fullname": "bench_executor.ontop.OntopVirtualize", "modulename": "bench_executor.ontop", "qualname": "OntopVirtualize", "kind": "class", "doc": "

    OntopVirtualize container for setting up an Ontop SPARQL endpoint.

    \n", "bases": "Ontop"}, "bench_executor.ontop.OntopVirtualize.__init__": {"fullname": "bench_executor.ontop.OntopVirtualize.__init__", "modulename": "bench_executor.ontop", "qualname": "OntopVirtualize.__init__", "kind": "function", "doc": "

    Creates an instance of the OntopVirtualize class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.ontop.OntopVirtualize.execute_mapping": {"fullname": "bench_executor.ontop.OntopVirtualize.execute_mapping", "modulename": "bench_executor.ontop", "qualname": "OntopVirtualize.execute_mapping", "kind": "function", "doc": "

    Start an Ontop SPARQL endpoint with a mapping.

    \n\n

    Only relational databases are supported by\nOntop, thus the relational database parameters are mandantory.\nOntop SPARQL endpoint supports the following serialization formats:

    \n\n
      \n
    • N-Triples (Ontop v5+)
      • \n
    • N-Quads (Ontop v5+)
      • \n
    • Turtle
      • \n
    • RDF/JSON
      • \n
    • JSON-LD
      • \n
    • CSV
      • \n
    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (str):\nUsername for the database.
      • \n
    • rdb_password (str):\nPassword for the database.
      • \n
    • rdb_host (str):\nHostname for the database.
      • \n
    • rdb_port (int):\nPort for the database.
      • \n
    • rdb_name (str):\nDatabase name for the database.
      • \n
    • rdb_type (str):\nDatabase type.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\tserialization: str,\trdb_username: str,\trdb_password: str,\trdb_host: str,\trdb_port: int,\trdb_name: str,\trdb_type: str) -> bool:", "funcdef": "def"}, "bench_executor.ontop.OntopMaterialize": {"fullname": "bench_executor.ontop.OntopMaterialize", "modulename": "bench_executor.ontop", "qualname": "OntopMaterialize", "kind": "class", "doc": "

    OntopMaterialize container to execute a R2RML mapping.

    \n", "bases": "Ontop"}, "bench_executor.ontop.OntopMaterialize.__init__": {"fullname": "bench_executor.ontop.OntopMaterialize.__init__", "modulename": "bench_executor.ontop", "qualname": "OntopMaterialize.__init__", "kind": "function", "doc": "

    Creates an instance of the OntopMaterialize class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.ontop.OntopMaterialize.execute_mapping": {"fullname": "bench_executor.ontop.OntopMaterialize.execute_mapping", "modulename": "bench_executor.ontop", "qualname": "OntopMaterialize.execute_mapping", "kind": "function", "doc": "

    Execute a R2RML mapping with Ontop

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nfor Ontop materialize. Only relational databases are supported by\nOntop, thus the relational database parameters are mandantory.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in. This is not used\nfor OntopVirtualize.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (str):\nUsername for the database.
      • \n
    • rdb_password (str):\nPassword for the database.
      • \n
    • rdb_host (str):\nHostname for the database.
      • \n
    • rdb_port (int):\nPort for the database.
      • \n
    • rdb_name (str):\nDatabase name for the database.
      • \n
    • rdb_type (str):\nDatabase type.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: str,\trdb_password: str,\trdb_host: str,\trdb_port: int,\trdb_name: str,\trdb_type: str) -> bool:", "funcdef": "def"}, "bench_executor.postgresql": {"fullname": "bench_executor.postgresql", "modulename": "bench_executor.postgresql", "kind": "module", "doc": "

    PostgreSQL is an open-source relational database developed by The PostgreSQL\nGlobal Development Group.

    \n\n

    Website: https://www.postgresql.org/
    \nRepository: https://git.postgresql.org/gitweb/?p=postgresql.git

    \n"}, "bench_executor.postgresql.VERSION": {"fullname": "bench_executor.postgresql.VERSION", "modulename": "bench_executor.postgresql", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'14.5'"}, "bench_executor.postgresql.HOST": {"fullname": "bench_executor.postgresql.HOST", "modulename": "bench_executor.postgresql", "qualname": "HOST", "kind": "variable", "doc": "

    \n", "default_value": "'localhost'"}, "bench_executor.postgresql.USER": {"fullname": "bench_executor.postgresql.USER", "modulename": "bench_executor.postgresql", "qualname": "USER", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.postgresql.PASSWORD": {"fullname": "bench_executor.postgresql.PASSWORD", "modulename": "bench_executor.postgresql", "qualname": "PASSWORD", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.postgresql.DB": {"fullname": "bench_executor.postgresql.DB", "modulename": "bench_executor.postgresql", "qualname": "DB", "kind": "variable", "doc": "

    \n", "default_value": "'db'"}, "bench_executor.postgresql.PORT": {"fullname": "bench_executor.postgresql.PORT", "modulename": "bench_executor.postgresql", "qualname": "PORT", "kind": "variable", "doc": "

    \n", "default_value": "'5432'"}, "bench_executor.postgresql.WAIT_TIME": {"fullname": "bench_executor.postgresql.WAIT_TIME", "modulename": "bench_executor.postgresql", "qualname": "WAIT_TIME", "kind": "variable", "doc": "

    \n", "default_value": "3"}, "bench_executor.postgresql.CLEAR_TABLES_TIMEOUT": {"fullname": "bench_executor.postgresql.CLEAR_TABLES_TIMEOUT", "modulename": "bench_executor.postgresql", "qualname": "CLEAR_TABLES_TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "300"}, "bench_executor.postgresql.PostgreSQL": {"fullname": "bench_executor.postgresql.PostgreSQL", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL", "kind": "class", "doc": "

    PostgreSQL container for executing SQL queries

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.postgresql.PostgreSQL.__init__": {"fullname": "bench_executor.postgresql.PostgreSQL.__init__", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.__init__", "kind": "function", "doc": "

    Creates an instance of the PostgreSQL class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.postgresql.PostgreSQL.initialization": {"fullname": "bench_executor.postgresql.PostgreSQL.initialization", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.initialization", "kind": "function", "doc": "

    Initialize PostgreSQL's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.root_mount_directory": {"fullname": "bench_executor.postgresql.PostgreSQL.root_mount_directory", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for PostgreSQL.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for PostgreSQL.
      • \n
    \n", "annotation": ": str"}, "bench_executor.postgresql.PostgreSQL.wait_until_ready": {"fullname": "bench_executor.postgresql.PostgreSQL.wait_until_ready", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.wait_until_ready", "kind": "function", "doc": "

    Wait until PostgreSQL is ready to execute SQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the PostgreSQL container, optionally,\ndefaults to no command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the PostgreSQL was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.load": {"fullname": "bench_executor.postgresql.PostgreSQL.load", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.load", "kind": "function", "doc": "

    Load a single CSV file into PostgreSQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_file (str):\nName of the CSV file.
      • \n
    • table (str):\nName of the table.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_file: str, table: str) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.load_multiple": {"fullname": "bench_executor.postgresql.PostgreSQL.load_multiple", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.load_multiple", "kind": "function", "doc": "

    Load multiple CSV files into PostgreSQL.

    \n\n
    Parameters
    \n\n
      \n
    • csv_files (list):\nList of CSV files to load. Each entry consist of a file and\ntable key.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, csv_files: List[dict]) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.load_sql_schema": {"fullname": "bench_executor.postgresql.PostgreSQL.load_sql_schema", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.load_sql_schema", "kind": "function", "doc": "

    Execute SQL schema with PostgreSQL.

    \n\n

    Executes a .sql file with PostgreSQL.\nIf the data is not loaded by the .sql file but only the schema is\nprovided through the .sql file, a list of CSV files can be provided to\nload them as well.

    \n\n
    Parameters
    \n\n
      \n
    • schema_file (str):\nName of the .sql file.
      • \n
    • csv_files (List[Tuple[str, str]]]):\nList of CSV file names to load in the tables created with the .sql\nfile, may also be an empty list. Each entry contains a Tuple of the\nCSV file name and the table name.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self, schema_file: str, csv_files: List[Tuple[str, str]]) -> bool:", "funcdef": "def"}, "bench_executor.postgresql.PostgreSQL.stop": {"fullname": "bench_executor.postgresql.PostgreSQL.stop", "modulename": "bench_executor.postgresql", "qualname": "PostgreSQL.stop", "kind": "function", "doc": "

    Stop PostgreSQL\nClears all tables and stops the PostgreSQL container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.query": {"fullname": "bench_executor.query", "modulename": "bench_executor.query", "kind": "module", "doc": "

    Query executes SPARQL queries on endpoints by posting the SPARQL query over\nHTTP onto the endpoint. It applies timeouts to these queries automatically and\nchecks if the results are empty or not.

    \n"}, "bench_executor.query.TIMEOUT": {"fullname": "bench_executor.query.TIMEOUT", "modulename": "bench_executor.query", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "3600"}, "bench_executor.query.Query": {"fullname": "bench_executor.query.Query", "modulename": "bench_executor.query", "qualname": "Query", "kind": "class", "doc": "

    Execute a query on a SPARQL endpoint.

    \n"}, "bench_executor.query.Query.__init__": {"fullname": "bench_executor.query.Query.__init__", "modulename": "bench_executor.query", "qualname": "Query.__init__", "kind": "function", "doc": "

    Creates an instance of the Query class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.query.Query.name": {"fullname": "bench_executor.query.Query.name", "modulename": "bench_executor.query", "qualname": "Query.name", "kind": "variable", "doc": "

    Name of the class: Query

    \n"}, "bench_executor.query.Query.root_mount_directory": {"fullname": "bench_executor.query.Query.root_mount_directory", "modulename": "bench_executor.query", "qualname": "Query.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Query.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Query.
      • \n
    \n", "annotation": ": str"}, "bench_executor.query.Query.execute_and_save": {"fullname": "bench_executor.query.Query.execute_and_save", "modulename": "bench_executor.query", "qualname": "Query.execute_and_save", "kind": "function", "doc": "

    Executes a SPARQL query and save the results.

    \n\n

    The results are saved to the results_file path.

    \n\n
    Parameters
    \n\n
      \n
    • query (str):\nThe query to execute.
      • \n
    • sparql_endpoint (str):\nThe URL of the SPARQL endpoint.
      • \n
    • results_file (str):\nPath to the file where the results may be stored.
      • \n
    • expect_empty (bool):\nWhether the expected results are empty or not.
      • \n
    • headers (dict):\nHTTP headers to supply when posting the query.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(\tself,\tquery: str,\tsparql_endpoint: str,\tresults_file: str,\texpect_empty: bool = False,\theaders: dict = {}) -> bool:", "funcdef": "def"}, "bench_executor.query.Query.execute_from_file": {"fullname": "bench_executor.query.Query.execute_from_file", "modulename": "bench_executor.query", "qualname": "Query.execute_from_file", "kind": "function", "doc": "

    Executes a SPARQL query from file.

    \n\n

    The results are saved to the results_file path.

    \n\n
    Parameters
    \n\n
      \n
    • query_file (str):\nPath to the file containing the query.
      • \n
    • sparql_endpoint (str):\nThe URL of the SPARQL endpoint.
      • \n
    • expect_empty (bool):\nWhether the expected results are empty or not.
      • \n
    • headers (dict):\nHTTP headers to supply when posting the query.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • results (str):\nThe HTTP response as string of the SPARQL endpoint, unless it has\nno results.
      • \n
    \n\n
    Raises
    \n\n
      \n
    • Exception (Exception):\nPass through the exception from the Python's request module\nregarding HTTP status codes.
      • \n
    \n", "signature": "(\tself,\tquery_file: str,\tsparql_endpoint: str,\texpect_empty: bool = False,\theaders: dict = {}) -> str:", "funcdef": "def"}, "bench_executor.query.Query.execute_from_file_and_save": {"fullname": "bench_executor.query.Query.execute_from_file_and_save", "modulename": "bench_executor.query", "qualname": "Query.execute_from_file_and_save", "kind": "function", "doc": "

    Executes a SPARQL query from file and save the results.

    \n\n

    The results are saved to the results_file path.

    \n\n
    Parameters
    \n\n
      \n
    • query_file (str):\nPath to the file containing the query.
      • \n
    • sparql_endpoint (str):\nThe URL of the SPARQL endpoint.
      • \n
    • results_file (str):\nPath to the file where the results may be stored.
      • \n
    • expect_empty (bool):\nWhether the expected results are empty or not.
      • \n
    • headers (dict):\nHTTP headers to supply when posting the query.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n\n
    Raises
    \n\n
      \n
    • FileNotFoundError (Exception):\nIf the query file cannot be found.
      • \n
    \n", "signature": "(\tself,\tquery_file: str,\tsparql_endpoint: str,\tresults_file: str,\texpect_empty: bool = False,\theaders: dict = {}) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper": {"fullname": "bench_executor.rmlmapper", "modulename": "bench_executor.rmlmapper", "kind": "module", "doc": "

    The RMLMapper executes RML rules to generate high quality Linked Data\nfrom multiple originally (semi-)structured data sources.

    \n\n

    Website: https://rml.io
    \nRepository: https://github.com/RMLio/rmlmapper-java

    \n"}, "bench_executor.rmlmapper.VERSION": {"fullname": "bench_executor.rmlmapper.VERSION", "modulename": "bench_executor.rmlmapper", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'6.0.0'"}, "bench_executor.rmlmapper.TIMEOUT": {"fullname": "bench_executor.rmlmapper.TIMEOUT", "modulename": "bench_executor.rmlmapper", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.rmlmapper.RMLMapper": {"fullname": "bench_executor.rmlmapper.RMLMapper", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper", "kind": "class", "doc": "

    RMLMapper container for executing R2RML and RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.rmlmapper.RMLMapper.__init__": {"fullname": "bench_executor.rmlmapper.RMLMapper.__init__", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.__init__", "kind": "function", "doc": "

    Creates an instance of the RMLMapper class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.rmlmapper.RMLMapper.root_mount_directory": {"fullname": "bench_executor.rmlmapper.RMLMapper.root_mount_directory", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for RMLMapper.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for RMLMapper.
      • \n
    \n", "annotation": ": str"}, "bench_executor.rmlmapper.RMLMapper.execute": {"fullname": "bench_executor.rmlmapper.RMLMapper.execute", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.execute", "kind": "function", "doc": "

    Execute RMLMapper with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to RMLMapper.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper.RMLMapper.execute_mapping": {"fullname": "bench_executor.rmlmapper.RMLMapper.execute_mapping", "modulename": "bench_executor.rmlmapper", "qualname": "RMLMapper.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with RMLMapper.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for RMLMapper.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper_jar": {"fullname": "bench_executor.rmlmapper_jar", "modulename": "bench_executor.rmlmapper_jar", "kind": "module", "doc": "

    The RMLMapper executes RML rules to generate high quality Linked Data\nfrom multiple originally (semi-)structured data sources.

    \n\n

    Website: https://rml.io
    \nRepository: https://github.com/RMLio/rmlmapper-java

    \n"}, "bench_executor.rmlmapper_jar.VERSION": {"fullname": "bench_executor.rmlmapper_jar.VERSION", "modulename": "bench_executor.rmlmapper_jar", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'6.2.1'"}, "bench_executor.rmlmapper_jar.TIMEOUT": {"fullname": "bench_executor.rmlmapper_jar.TIMEOUT", "modulename": "bench_executor.rmlmapper_jar", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.rmlmapper_jar.RMLMapperJar": {"fullname": "bench_executor.rmlmapper_jar.RMLMapperJar", "modulename": "bench_executor.rmlmapper_jar", "qualname": "RMLMapperJar", "kind": "class", "doc": "

    RMLMapper container for executing R2RML and RML mappings.

    \n"}, "bench_executor.rmlmapper_jar.RMLMapperJar.__init__": {"fullname": "bench_executor.rmlmapper_jar.RMLMapperJar.__init__", "modulename": "bench_executor.rmlmapper_jar", "qualname": "RMLMapperJar.__init__", "kind": "function", "doc": "

    Creates an instance of the RMLMapper class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.rmlmapper_jar.RMLMapperJar.root_mount_directory": {"fullname": "bench_executor.rmlmapper_jar.RMLMapperJar.root_mount_directory", "modulename": "bench_executor.rmlmapper_jar", "qualname": "RMLMapperJar.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for RMLMapper.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for RMLMapper.
      • \n
    \n", "annotation": ": str"}, "bench_executor.rmlmapper_jar.RMLMapperJar.execute": {"fullname": "bench_executor.rmlmapper_jar.RMLMapperJar.execute", "modulename": "bench_executor.rmlmapper_jar", "qualname": "RMLMapperJar.execute", "kind": "function", "doc": "

    Execute RMLMapper with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to RMLMapper.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.rmlmapper_jar.RMLMapperJar.execute_mapping": {"fullname": "bench_executor.rmlmapper_jar.RMLMapperJar.execute_mapping", "modulename": "bench_executor.rmlmapper_jar", "qualname": "RMLMapperJar.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with RMLMapper.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for RMLMapper.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.rmlstreamer": {"fullname": "bench_executor.rmlstreamer", "modulename": "bench_executor.rmlstreamer", "kind": "module", "doc": "

    The RMLStreamer executes RML rules to generate high quality Linked Data\nfrom multiple originally (semi-)structured data sources in a streaming way.

    \n\n

    Website: https://rml.io
    \nRepository: https://github.com/RMLio/RMLStreamer

    \n"}, "bench_executor.rmlstreamer.R2RML": {"fullname": "bench_executor.rmlstreamer.R2RML", "modulename": "bench_executor.rmlstreamer", "qualname": "R2RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.w3.org/ns/r2rml#')"}, "bench_executor.rmlstreamer.RML": {"fullname": "bench_executor.rmlstreamer.RML", "modulename": "bench_executor.rmlstreamer", "qualname": "RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://semweb.mmlab.be/ns/rml#')"}, "bench_executor.rmlstreamer.D2RQ": {"fullname": "bench_executor.rmlstreamer.D2RQ", "modulename": "bench_executor.rmlstreamer", "qualname": "D2RQ", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.wiwiss.fu-berlin.de/suhl/bizer/D2RQ/0.1#')"}, "bench_executor.rmlstreamer.VERSION": {"fullname": "bench_executor.rmlstreamer.VERSION", "modulename": "bench_executor.rmlstreamer", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'2.5.0'"}, "bench_executor.rmlstreamer.TIMEOUT": {"fullname": "bench_executor.rmlstreamer.TIMEOUT", "modulename": "bench_executor.rmlstreamer", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.rmlstreamer.IMAGE": {"fullname": "bench_executor.rmlstreamer.IMAGE", "modulename": "bench_executor.rmlstreamer", "qualname": "IMAGE", "kind": "variable", "doc": "

    \n", "default_value": "'kgconstruct/rmlstreamer:v2.5.0'"}, "bench_executor.rmlstreamer.RMLStreamer": {"fullname": "bench_executor.rmlstreamer.RMLStreamer", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer", "kind": "class", "doc": "

    RMLStreamer container for executing RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.rmlstreamer.RMLStreamer.__init__": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.__init__", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.__init__", "kind": "function", "doc": "

    Creates an instance of the RMLStreamer class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.rmlstreamer.RMLStreamer.root_mount_directory": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.root_mount_directory", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for RMLStreamer.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for RMLStreamer.
      • \n
    \n", "annotation": ": str"}, "bench_executor.rmlstreamer.RMLStreamer.execute": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.execute", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.execute", "kind": "function", "doc": "

    Execute RMLStreamer with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to RMLStreamer.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.rmlstreamer.RMLStreamer.execute_mapping": {"fullname": "bench_executor.rmlstreamer.RMLStreamer.execute_mapping", "modulename": "bench_executor.rmlstreamer", "qualname": "RMLStreamer.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with RMLStreamer.

    \n\n

    N-Quads/N-Triples is the only currently supported as serialization\nformat for RMLStreamer.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.sdmrdfizer": {"fullname": "bench_executor.sdmrdfizer", "modulename": "bench_executor.sdmrdfizer", "kind": "module", "doc": "

    SDM-RDFizer is an efficient RML-Compliant engine for knowledge graph\nconstruction.

    \n\n

    Repository: https://github.com/SDM-TIB/SDM-RDFizer

    \n"}, "bench_executor.sdmrdfizer.VERSION": {"fullname": "bench_executor.sdmrdfizer.VERSION", "modulename": "bench_executor.sdmrdfizer", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'4.6.6.5'"}, "bench_executor.sdmrdfizer.TIMEOUT": {"fullname": "bench_executor.sdmrdfizer.TIMEOUT", "modulename": "bench_executor.sdmrdfizer", "qualname": "TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "21600"}, "bench_executor.sdmrdfizer.R2RML": {"fullname": "bench_executor.sdmrdfizer.R2RML", "modulename": "bench_executor.sdmrdfizer", "qualname": "R2RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.w3.org/ns/r2rml#')"}, "bench_executor.sdmrdfizer.RML": {"fullname": "bench_executor.sdmrdfizer.RML", "modulename": "bench_executor.sdmrdfizer", "qualname": "RML", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://semweb.mmlab.be/ns/rml#')"}, "bench_executor.sdmrdfizer.D2RQ": {"fullname": "bench_executor.sdmrdfizer.D2RQ", "modulename": "bench_executor.sdmrdfizer", "qualname": "D2RQ", "kind": "variable", "doc": "

    \n", "default_value": "Namespace('http://www.wiwiss.fu-berlin.de/suhl/bizer/D2RQ/0.1#')"}, "bench_executor.sdmrdfizer.IMAGE": {"fullname": "bench_executor.sdmrdfizer.IMAGE", "modulename": "bench_executor.sdmrdfizer", "qualname": "IMAGE", "kind": "variable", "doc": "

    \n", "default_value": "'kgconstruct/sdm-rdfizer:v4.6.6.5'"}, "bench_executor.sdmrdfizer.SDMRDFizer": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer", "kind": "class", "doc": "

    SDMRDFizer container for executing RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.sdmrdfizer.SDMRDFizer.__init__": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.__init__", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.__init__", "kind": "function", "doc": "

    Creates an instance of the SDMRDFizer class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.sdmrdfizer.SDMRDFizer.root_mount_directory": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.root_mount_directory", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for SDM-RDFizer.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for SDM-RDFizer.
      • \n
    \n", "annotation": ": str"}, "bench_executor.sdmrdfizer.SDMRDFizer.execute": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.execute", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.execute", "kind": "function", "doc": "

    Execute SDM-RDFizer with given arguments.

    \n\n
    Parameters
    \n\n
      \n
    • arguments (list):\nArguments to supply to SDM-RDFizer.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution succeeded or not.
      • \n
    \n", "signature": "(self, arguments: list) -> bool:", "funcdef": "def"}, "bench_executor.sdmrdfizer.SDMRDFizer.execute_mapping": {"fullname": "bench_executor.sdmrdfizer.SDMRDFizer.execute_mapping", "modulename": "bench_executor.sdmrdfizer", "qualname": "SDMRDFizer.execute_mapping", "kind": "function", "doc": "

    Execute a mapping file with SDM-RDFizer.

    \n\n

    N-Quads and N-Triples are currently supported as serialization\nformat for RMLMapper.

    \n\n
    Parameters
    \n\n
      \n
    • mapping_file (str):\nPath to the mapping file to execute.
      • \n
    • output_file (str):\nName of the output file to store the triples in.
      • \n
    • serialization (str):\nSerialization format to use.
      • \n
    • rdb_username (Optional[str]):\nUsername for the database, required when a database is used as\nsource.
      • \n
    • rdb_password (Optional[str]):\nPassword for the database, required when a database is used as\nsource.
      • \n
    • rdb_host (Optional[str]):\nHostname for the database, required when a database is used as\nsource.
      • \n
    • rdb_port (Optional[int]):\nPort for the database, required when a database is used as source.
      • \n
    • rdb_name (Optional[str]):\nDatabase name for the database, required when a database is used as\nsource.
      • \n
    • rdb_type (Optional[str]):\nDatabase type, required when a database is used as source.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the execution was successfull or not.
      • \n
    \n", "signature": "(\tself,\tmapping_file: str,\toutput_file: str,\tserialization: str,\trdb_username: Optional[str] = None,\trdb_password: Optional[str] = None,\trdb_host: Optional[str] = None,\trdb_port: Optional[int] = None,\trdb_name: Optional[str] = None,\trdb_type: Optional[str] = None) -> bool:", "funcdef": "def"}, "bench_executor.stats": {"fullname": "bench_executor.stats", "modulename": "bench_executor.stats", "kind": "module", "doc": "

    This module holds the Stats class which is responsible for generating\nstaticstics from executed cases. It will automatically aggregate all runs of an\nexecuted case to generate an aggregated.csv and summary.csv files which can\nbe used to compare various cases with each other.

    \n\n
      \n
    • aggregated.csv: For each run of a case, the median execution time of each\nstep is calculated. For each step, the results of the run with the median\nexecution time is used to assemble the aggregated results.
      • \n
    • summary.csv: The summary is similar to the previous file, but provides a\nsingle result for each step to immediately see how long the step took, how\nmany samples are provided for the step, etc.
      • \n
    \n"}, "bench_executor.stats.METRICS_AGGREGATED_FILE_NAME": {"fullname": "bench_executor.stats.METRICS_AGGREGATED_FILE_NAME", "modulename": "bench_executor.stats", "qualname": "METRICS_AGGREGATED_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'aggregated.csv'"}, "bench_executor.stats.METRICS_SUMMARY_FILE_NAME": {"fullname": "bench_executor.stats.METRICS_SUMMARY_FILE_NAME", "modulename": "bench_executor.stats", "qualname": "METRICS_SUMMARY_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'summary.csv'"}, "bench_executor.stats.METRICS_STATS_FILE_NAME": {"fullname": "bench_executor.stats.METRICS_STATS_FILE_NAME", "modulename": "bench_executor.stats", "qualname": "METRICS_STATS_FILE_NAME", "kind": "variable", "doc": "

    \n", "default_value": "'stats.csv'"}, "bench_executor.stats.FIELDNAMES_STRING": {"fullname": "bench_executor.stats.FIELDNAMES_STRING", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_STRING", "kind": "variable", "doc": "

    \n", "default_value": "['name']"}, "bench_executor.stats.FIELDNAMES_FLOAT": {"fullname": "bench_executor.stats.FIELDNAMES_FLOAT", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_FLOAT", "kind": "variable", "doc": "

    \n", "default_value": "['timestamp', 'cpu_user', 'cpu_system', 'cpu_idle', 'cpu_iowait', 'cpu_user_system']"}, "bench_executor.stats.FIELDNAMES_INT": {"fullname": "bench_executor.stats.FIELDNAMES_INT", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_INT", "kind": "variable", "doc": "

    \n", "default_value": "['run', 'index', 'step', 'version', 'memory_ram', 'memory_swap', 'memory_ram_swap', 'disk_read_count', 'disk_write_count', 'disk_read_bytes', 'disk_write_bytes', 'disk_read_time', 'disk_write_time', 'disk_busy_time', 'network_received_count', 'network_sent_count', 'network_received_bytes', 'network_sent_bytes', 'network_received_error', 'network_sent_error', 'network_received_drop', 'network_sent_drop']"}, "bench_executor.stats.FIELDNAMES_SUMMARY": {"fullname": "bench_executor.stats.FIELDNAMES_SUMMARY", "modulename": "bench_executor.stats", "qualname": "FIELDNAMES_SUMMARY", "kind": "variable", "doc": "

    \n", "default_value": "['name', 'run', 'number_of_samples', 'step', 'duration', 'version', 'cpu_user_diff', 'cpu_system_diff', 'cpu_user_system_diff', 'cpu_idle_diff', 'cpu_iowait_diff', 'memory_ram_max', 'memory_swap_max', 'memory_ram_swap_max', 'memory_ram_min', 'memory_swap_min', 'memory_ram_swap_min', 'disk_read_count_diff', 'disk_write_count_diff', 'disk_read_bytes_diff', 'disk_write_bytes_diff', 'disk_read_time_diff', 'disk_write_time_diff', 'disk_busy_time_diff', 'network_received_count_diff', 'network_sent_count_diff', 'network_received_bytes_diff', 'network_sent_bytes_diff', 'network_received_error_diff', 'network_sent_error_diff', 'network_received_drop_diff', 'network_sent_drop_diff']"}, "bench_executor.stats.ROUND": {"fullname": "bench_executor.stats.ROUND", "modulename": "bench_executor.stats", "qualname": "ROUND", "kind": "variable", "doc": "

    \n", "default_value": "4"}, "bench_executor.stats.Stats": {"fullname": "bench_executor.stats.Stats", "modulename": "bench_executor.stats", "qualname": "Stats", "kind": "class", "doc": "

    Generate statistics for an executed case.

    \n"}, "bench_executor.stats.Stats.__init__": {"fullname": "bench_executor.stats.Stats.__init__", "modulename": "bench_executor.stats", "qualname": "Stats.__init__", "kind": "function", "doc": "

    Create an instance of the Stats class.

    \n\n
    Parameters
    \n\n
      \n
    • results_path (str):\nThe path to the results directory of the case
      • \n
    • number_of_steps (int):\nThe number of steps of the case
      • \n
    • directory (str):\nThe path to the directory where the logs must be stored.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(\tresults_path: str,\tnumber_of_steps: int,\tdirectory: str,\tverbose: bool)"}, "bench_executor.stats.Stats.statistics": {"fullname": "bench_executor.stats.Stats.statistics", "modulename": "bench_executor.stats", "qualname": "Stats.statistics", "kind": "function", "doc": "

    Calculate basic statistics on the steps by aggregating them from\nall runs and applying standard deviation, median, min, max, mean for\neach measured metric.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the standard deviation calculation was successfully or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.stats.Stats.aggregate": {"fullname": "bench_executor.stats.Stats.aggregate", "modulename": "bench_executor.stats", "qualname": "Stats.aggregate", "kind": "function", "doc": "

    Aggregate the metrics of the different runs of a case.

    \n\n

    Find the median execution time of each step across all runs and extract\nthe step from the run which has this median execution time to assemble\nan aggregated version and summary version of the case's metrics.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the aggregation was successfully or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.virtuoso": {"fullname": "bench_executor.virtuoso", "modulename": "bench_executor.virtuoso", "kind": "module", "doc": "

    Virtuoso is a secure and high-performance platform for modern data access,\nintegration, virtualization, and multi-model data management (tables & graphs)\nbased on innovative support of existing open standards\n(e.g., SQL, SPARQL, and GraphQL).

    \n\n

    Website: https://virtuoso.openlinksw.com/
    \nRepository: https://github.com/openlink/virtuoso-opensource

    \n"}, "bench_executor.virtuoso.VERSION": {"fullname": "bench_executor.virtuoso.VERSION", "modulename": "bench_executor.virtuoso", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'7.2.7'"}, "bench_executor.virtuoso.MAX_ROWS": {"fullname": "bench_executor.virtuoso.MAX_ROWS", "modulename": "bench_executor.virtuoso", "qualname": "MAX_ROWS", "kind": "variable", "doc": "

    \n", "default_value": "'10000000'"}, "bench_executor.virtuoso.QUERY_TIMEOUT": {"fullname": "bench_executor.virtuoso.QUERY_TIMEOUT", "modulename": "bench_executor.virtuoso", "qualname": "QUERY_TIMEOUT", "kind": "variable", "doc": "

    \n", "default_value": "'0'"}, "bench_executor.virtuoso.MAX_VECTOR_SIZE": {"fullname": "bench_executor.virtuoso.MAX_VECTOR_SIZE", "modulename": "bench_executor.virtuoso", "qualname": "MAX_VECTOR_SIZE", "kind": "variable", "doc": "

    \n", "default_value": "'3000000'"}, "bench_executor.virtuoso.PASSWORD": {"fullname": "bench_executor.virtuoso.PASSWORD", "modulename": "bench_executor.virtuoso", "qualname": "PASSWORD", "kind": "variable", "doc": "

    \n", "default_value": "'root'"}, "bench_executor.virtuoso.NUMBER_OF_BUFFERS_PER_GB": {"fullname": "bench_executor.virtuoso.NUMBER_OF_BUFFERS_PER_GB", "modulename": "bench_executor.virtuoso", "qualname": "NUMBER_OF_BUFFERS_PER_GB", "kind": "variable", "doc": "

    \n", "default_value": "85000"}, "bench_executor.virtuoso.MAX_DIRTY_BUFFERS_PER_GB": {"fullname": "bench_executor.virtuoso.MAX_DIRTY_BUFFERS_PER_GB", "modulename": "bench_executor.virtuoso", "qualname": "MAX_DIRTY_BUFFERS_PER_GB", "kind": "variable", "doc": "

    \n", "default_value": "65000"}, "bench_executor.virtuoso.Virtuoso": {"fullname": "bench_executor.virtuoso.Virtuoso", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso", "kind": "class", "doc": "

    Virtuoso container to execute SPARQL queries

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.virtuoso.Virtuoso.__init__": {"fullname": "bench_executor.virtuoso.Virtuoso.__init__", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.__init__", "kind": "function", "doc": "

    Creates an instance of the Virtuoso class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.virtuoso.Virtuoso.initialization": {"fullname": "bench_executor.virtuoso.Virtuoso.initialization", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.initialization", "kind": "function", "doc": "

    Initialize Virtuoso's database.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the initialization was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.root_mount_directory": {"fullname": "bench_executor.virtuoso.Virtuoso.root_mount_directory", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for Virtuoso.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for Virtuoso.
      • \n
    \n", "annotation": ": str"}, "bench_executor.virtuoso.Virtuoso.wait_until_ready": {"fullname": "bench_executor.virtuoso.Virtuoso.wait_until_ready", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.wait_until_ready", "kind": "function", "doc": "

    Wait until Virtuoso is ready to execute SPARQL queries.

    \n\n
    Parameters
    \n\n
      \n
    • command (str):\nCommand to execute in the Virtuoso container, optionally, defaults\nto no command.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the Virtuoso was initialized successfull or not.
      • \n
    \n", "signature": "(self, command: str = '') -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.load": {"fullname": "bench_executor.virtuoso.Virtuoso.load", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.load", "kind": "function", "doc": "

    Load an RDF file into Virtuoso.

    \n\n

    Currently, only N-Triples files are supported.

    \n\n
    Parameters
    \n\n
      \n
    • rdf_file (str):\nName of the RDF file to load.
      • \n
    • rdf_dir (str):\nName of the directory where RDF file(s) are stored.\nDefault root of the data directory.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the loading was successfull or not.
      • \n
    \n", "signature": "(self, rdf_file: str, rdf_dir: str = '') -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.load_parallel": {"fullname": "bench_executor.virtuoso.Virtuoso.load_parallel", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.load_parallel", "kind": "function", "doc": "

    Load an RDF file into Virtuoso in parallel.

    \n\n

    Currently, only N-Triples files are supported.

    \n\n
    Parameters
    \n\n
      \n
    • rdf_file (str):\nName of the RDF file to load.
      • \n
    • cores (int):\nNumber of CPU cores for loading.
      • \n
    • rdf_dir (str):\nName of the directory where RDF file(s) are stored.\nDefault root of the data directory.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the loading was successfull or not.
      • \n
    \n", "signature": "(self, rdf_file: str, cores: int, rdf_dir: str = '') -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.stop": {"fullname": "bench_executor.virtuoso.Virtuoso.stop", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.stop", "kind": "function", "doc": "

    Stop Virtuoso.

    \n\n

    Drops all triples in Virtuoso before stopping its container.

    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether stopping Virtuoso was successfull or not.
      • \n
    \n", "signature": "(self) -> bool:", "funcdef": "def"}, "bench_executor.virtuoso.Virtuoso.endpoint": {"fullname": "bench_executor.virtuoso.Virtuoso.endpoint", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.endpoint", "kind": "variable", "doc": "

    SPARQL endpoint URL

    \n", "annotation": ": str"}, "bench_executor.virtuoso.Virtuoso.headers": {"fullname": "bench_executor.virtuoso.Virtuoso.headers", "modulename": "bench_executor.virtuoso", "qualname": "Virtuoso.headers", "kind": "variable", "doc": "

    HTTP headers of SPARQL queries for serialization formats.

    \n\n

    Only supported serialization formats are included in the dictionary.\nCurrently, the following formats are supported:

    \n\n
      \n
    • N-Triples
      • \n
    • Turtle
      • \n
    • CSV
      • \n
    • RDF/JSON
      • \n
    • RDF/XML
      • \n
    • JSON-LD
      • \n
    \n\n
    Returns
    \n\n
      \n
    • headers (dict):\nDictionary of headers to use for each serialization format.
      • \n
    \n", "annotation": ": Dict[str, Dict[str, str]]"}, "bench_executor.yarrrml": {"fullname": "bench_executor.yarrrml", "modulename": "bench_executor.yarrrml", "kind": "module", "doc": "

    YARRRML is a human readable text-based representation for declarative\nLinked Data generation rules.

    \n\n

    Website: https://rml.io/yarrrml/
    \nRepository: https://github.com/RMLio/yarrrml-parser

    \n"}, "bench_executor.yarrrml.VERSION": {"fullname": "bench_executor.yarrrml.VERSION", "modulename": "bench_executor.yarrrml", "qualname": "VERSION", "kind": "variable", "doc": "

    \n", "default_value": "'1.3.6'"}, "bench_executor.yarrrml.YARRRML": {"fullname": "bench_executor.yarrrml.YARRRML", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML", "kind": "class", "doc": "

    YARRRML container to transform YARRRML mappings into RML mappings.

    \n", "bases": "bench_executor.container.Container"}, "bench_executor.yarrrml.YARRRML.__init__": {"fullname": "bench_executor.yarrrml.YARRRML.__init__", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML.__init__", "kind": "function", "doc": "

    Creates an instance of the YARRRML class.

    \n\n
    Parameters
    \n\n
      \n
    • data_path (str):\nPath to the data directory of the case.
      • \n
    • config_path (str):\nPath to the config directory of the case.
      • \n
    • directory (str):\nPath to the directory to store logs.
      • \n
    • verbose (bool):\nEnable verbose logs.
      • \n
    \n", "signature": "(data_path: str, config_path: str, directory: str, verbose: bool)"}, "bench_executor.yarrrml.YARRRML.root_mount_directory": {"fullname": "bench_executor.yarrrml.YARRRML.root_mount_directory", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML.root_mount_directory", "kind": "variable", "doc": "

    Subdirectory in the root directory of the case for YARRRML.

    \n\n
    Returns
    \n\n
      \n
    • subdirectory (str):\nSubdirectory of the root directory for YARRRML.
      • \n
    \n", "annotation": ": str"}, "bench_executor.yarrrml.YARRRML.transform_mapping": {"fullname": "bench_executor.yarrrml.YARRRML.transform_mapping", "modulename": "bench_executor.yarrrml", "qualname": "YARRRML.transform_mapping", "kind": "function", "doc": "

    Transform a YARRRML mapping into a RML mapping.

    \n\n
    Parameters
    \n\n
      \n
    • yarrrml_file (str):\nName of the YARRRML mapping file.
      • \n
    • mapping_file (str):\nName of the RML mapping file.
      • \n
    • r2rml (bool):\nWhether the RML mapping file must be R2RML compatible.
      • \n
    • pretty (bool):\nWhether the generated mapping file must be pretty or not.
      • \n
    \n\n
    Returns
    \n\n
      \n
    • success (bool):\nWhether the YARRRML was initialized successfull or not.
      • \n
    \n", "signature": "(\tself,\tyarrrml_file: str,\tmapping_file: str,\tr2rml: bool = False,\tpretty: bool = True) -> bool:", "funcdef": "def"}}, "docInfo": {"bench_executor.collector": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 482}, "bench_executor.collector.CASE_INFO_FILE_NAME": {"qualname": 4, "fullname": 7, "annotation": 2, "default_value": 7, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.METRICS_FILE_NAME": {"qualname": 3, "fullname": 6, "annotation": 2, "default_value": 6, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.METRICS_VERSION": {"qualname": 2, "fullname": 5, "annotation": 2, "default_value": 1, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.FIELDNAMES": {"qualname": 1, "fullname": 4, "annotation": 2, "default_value": 129, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.ROUND": {"qualname": 1, "fullname": 4, "annotation": 2, "default_value": 1, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.step_id": {"qualname": 2, "fullname": 5, "annotation": 2, "default_value": 1, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.collector.Collector": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 16}, "bench_executor.collector.Collector.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 88, "bases": 0, "doc": 298}, "bench_executor.collector.Collector.name": {"qualname": 2, "fullname": 5, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 7}, "bench_executor.collector.Collector.next_step": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 11, "bases": 0, "doc": 29}, "bench_executor.collector.Collector.stop": {"qualname": 2, "fullname": 5, "annotation": 0, "default_value": 0, "signature": 11, "bases": 0, "doc": 19}, "bench_executor.collector.scputimes": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 2, "doc": 4}, "bench_executor.collector.scputimes.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 4, "bases": 0, "doc": 8}, "bench_executor.collector.sswap": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 2, "doc": 4}, "bench_executor.collector.sswap.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 4, "bases": 0, "doc": 8}, "bench_executor.collector.svmem": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 2, "doc": 4}, "bench_executor.collector.svmem.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 4, "bases": 0, "doc": 8}, "bench_executor.collector.sdiskio": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 2, "doc": 4}, "bench_executor.collector.sdiskio.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 4, "bases": 0, "doc": 8}, "bench_executor.collector.snetio": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 2, "doc": 4}, "bench_executor.collector.snetio.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 4, "bases": 0, "doc": 8}, "bench_executor.container": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 50}, "bench_executor.container.WAIT_TIME": {"qualname": 2, "fullname": 5, "annotation": 0, "default_value": 1, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.container.TIMEOUT_TIME": {"qualname": 2, "fullname": 5, "annotation": 0, "default_value": 1, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.container.NETWORK_NAME": {"qualname": 2, "fullname": 5, "annotation": 0, "default_value": 6, "signature": 0, "bases": 0, "doc": 3}, "bench_executor.container.ContainerManager": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 7}, "bench_executor.container.ContainerManager.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 25, "bases": 0, "doc": 10}, "bench_executor.container.ContainerManager.create_network": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 21, "bases": 0, "doc": 25}, "bench_executor.container.Container": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 41}, "bench_executor.container.Container.__init__": {"qualname": 3, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 108, "bases": 0, "doc": 87}, "bench_executor.container.Container.started": {"qualname": 2, "fullname": 5, "annotation": 2, "default_value": 0, "signature": 0, "bases": 0, "doc": 9}, 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