Feat/74 heatmaps agnostic refactor #91
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+ Added different heatmaps analytics (for now the replier is implemented) + updated utils, removing unnecessary ones and updating method names. + added schema for heatmaps data. + updated the previous heatmaps to a heatmaps_old name so we could still run analyzer using that. (depricated) + commented the `RnDAOAnalyzer` in __init__ but will get it back later with a better name.
moving neo4j utils into its right directory.
+ added author_id filtering too.
it supports both type of emitter and receiver of reply
using the analytics_hourly for all vector analytics.
+ couple of small updates on analyzer config custom analytics. + updated heatmaps utils class - the raw analytics of heatmaps is still todo.
and aligning it with its test case.
the analytics should've been giving each engaged user id.
+ fixed: in raw analytics the test cases had some problem (were aligning other users activity in output) + fixed: the ActivityType typo fixed.
HeatMapModel is deprecated, will be removed in future.
+ also, updated raw analytics to output a dict rather than python object, so we could later save them in db easily.
+ in order to keep the changes at minimum at possible we're using the previous heatmaps output data schema. + but still we're platform agnostic.
+ we needed to update raw data in old test cases to the new format. + ignoring the self-interactions now. + updated discord analyzer configurations based on discussions. + removing the heatmaps_old as was no longer needed.
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Important Review skippedAuto reviews are disabled on base/target branches other than the default branch. Please check the settings in the CodeRabbit UI or the You can disable this status message by setting the WalkthroughSeveral new test files were added and existing test cases were modified, focusing on the Changes
Sequence Diagram(s)sequenceDiagram
participant TestSuite as Test Suite
participant Mongo as MongoDB
participant Heatmaps as Heatmaps
participant DiscordAnalyzerConfig as Discord Analyzer Config
TestSuite->>+Mongo: Prepare data for mention analysis
Mongo-->>-TestSuite: Data prepared
TestSuite->>+Heatmaps: Analyze mentions
Heatmaps-->>-TestSuite: Results validated
TestSuite->>+DiscordAnalyzerConfig: Load configuration
DiscordAnalyzerConfig-->>-TestSuite: Configuration loaded
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this is because for now we know the analyzer won't work so we need to skip a couple of test cases.
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Actionable comments posted: 20
Outside diff range and nitpick comments (23)
analyzer_init.py (3)
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11-11: TODO: Update constructor to useplatform_idinstead ofguild_id.Would you like me to help update this constructor to use
platform_idor should I open a GitHub issue to track this task?
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14-23: Ensure robust error handling around MongoDB connection.Consider adding try-except blocks around
analyzer.database_connect()to handle potential connection errors gracefully.
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29-34: Review handling of sensitive data in MongoDB connection string.Ensure that sensitive data such as passwords are handled securely, possibly using environment variables or encrypted storage, to avoid exposure in the codebase.
tests/integration/utils/mock_graph.py (1)
Line range hint
47-87: Thestore_mock_data_in_neo4jfunction correctly handles environment variables for database credentials and uses theRnDaoAnalyzerclass for storing analytics data. Ensure that sensitive data handling follows security best practices, especially in production environments.Consider using environment-specific configurations for handling sensitive data more securely.
discord_analyzer/models/BaseModel.py (2)
16-16: Theexistsflag is set but not used effectively within the class. Consider using this flag to optimize database checks or remove it if unnecessary.
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25-28: Refactor thecollection_existsmethod to return the condition directly for simplicity and improved readability.- if self.collection_name in self.database.list_collection_names(): - return True - else: - return False + return self.collection_name in self.database.list_collection_names()tests/integration/test_heatmaps_analytics_base.py (1)
72-130: Ensure consistency in test documentation.The docstring for
test_get_hourly_analytics_single_date_irrelevant_filtercould be more descriptive about what it means for the filter to be "irrelevant". Clarifying this in the docstring can improve the readability and maintainability of the test suite.tests/integration/test_louvain_algorithm_get_computed_dates.py (1)
1-1: Document the purpose and expected outcomes of the tests more clearly.The docstrings for the tests in this file are somewhat generic and could be more specific about the scenarios being tested and the expected outcomes. This would enhance the clarity and maintainability of the test suite.
discord_analyzer/analysis/neo4j_analysis/louvain.py (1)
1-1: Optimize database queries for performance.The Neo4j query in
get_computed_datescould potentially become slow if the dataset grows. Consider optimizing the query or using indexing strategies on thedateandguildIdproperties to improve performance.tests/integration/test_assess_engagement_replies.py (2)
14-14: Consider updating the pytest skip reason for clarity or resolving the underlying issue.The skip reason "Skipping for now as memberactivities is not updated!" could be more descriptive or specific about when this will be addressed.
38-38: Ensure consistent formatting and structure in the code.Consider removing the blank line here to maintain consistent formatting with other parts of the code.
tests/integration/test_assess_engagement_mention.py (2)
14-14: Consider updating the pytest skip reason for clarity or resolving the underlying issue.The skip reason "Skipping for now as memberactivities is not updated!" could be more descriptive or specific about when this will be addressed.
38-38: Ensure consistent formatting and structure in the code.Consider removing the blank line here to maintain consistent formatting with other parts of the code.
tests/integration/test_heatmaps_hourly_mentions.py (1)
8-8: Ensure the function has appropriate documentation.The function
test_mentioned_messageslacks a docstring. Adding a brief description of what the function tests and its expected outcomes would improve code readability and maintainability.discord_analyzer/analyzer/heatmaps/analytics_hourly.py (1)
15-23: The method signature and documentation are clear and well-defined, which is good for maintainability. However, consider adding type hints forkwargsto improve code readability and type checking.discord_analyzer/analyzer/heatmaps/analytics_raw.py (1)
16-24: The method signature and documentation are clear and well-defined, which is good for maintainability. However, consider adding type hints forkwargsto improve code readability and type checking.discord_analyzer/analysis/analytics_interactions_script.py (3)
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8-8: Avoid using mutable default arguments for function parameters.- def per_account_interactions(cursor_list, dict_keys=["replier_accounts", "reacter_accounts", "mentioner_accounts"]): + def per_account_interactions(cursor_list, dict_keys=None): + if dict_keys is None: + dict_keys = ["replier_accounts", "reacter_accounts", "mentioner_accounts"]
Line range hint
43-43: Optimize dictionary key checks by removing.keys().- if account_name not in temp_dict.keys(): + if account_name not in temp_dict: - if account_name not in all_interaction_accounts.keys(): + if account_name not in all_interaction_accounts: - if thread not in channel_thread_dict[ch].keys(): + if thread not in channel_thread_dict[ch]: - for ch in channels_dict.keys(): + for ch in channels_dict:Also applies to: 48-48, 213-213, 223-223
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190-190: Include astacklevelargument when usingwarnto help trace the warning back to its origin.- warn("Messages is not ascending ordered!") + warn("Messages is not ascending ordered!", stacklevel=2)discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py (1)
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89-97: Add error handling for external library calls to enhance robustness.try: projection_utils.project_temp_graph( guildId=guildId, graph_name=graph_name, weighted=True, relation_direction="NATURAL", date=date, ) except Exception as e: logging.error(f"Error projecting temp graph for {guildId} on {date}: {e}") returndiscord_analyzer/analysis/neo4j_analysis/centrality.py (3)
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68-73: Refactor the dictionary key checks to use a more Pythonic approach.- node = "DiscordAccount" if "node" not in kwargs.keys() else kwargs["node"] + node = kwargs.get("node", "DiscordAccount") - weighted = True if "weighted" not in kwargs.keys() else kwargs["weighted"] + weighted = kwargs.get("weighted", True) - normalize = False if "normalize" not in kwargs.keys() else kwargs["normalize"] + normalize = kwargs.get("normalize", False) - preserve_parallel = ( - True - if "preserve_parallel" not in kwargs.keys() - else kwargs["preserve_parallel"] - ) + preserve_parallel = kwargs.get("preserve_parallel", True)
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268-273: Refactor the dictionary key checks to use a more Pythonic approach.- recompute_dates = None - if "recompute_dates" in kwargs: - recompute_dates = kwargs["recompute_dates"] + recompute_dates = kwargs.get("recompute_dates")
Line range hint
322-322: Refactor the dictionary key check to use a more Pythonic approach.- if relation in relation_users and not preserve_parallel: + if not preserve_parallel and relation in relation_users:This change improves the readability by prioritizing the condition that is more likely to be false, thus potentially avoiding the more expensive set membership test.
Review details
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Files selected for processing (51)
- analyzer_init.py (1 hunks)
- discord_analyzer/init.py (1 hunks)
- discord_analyzer/analysis/analytics_interactions_script.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/centrality.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/local_clustering_coefficient.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/louvain.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/utils/init.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/init.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/analytics_hourly.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/analytics_raw.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/heatmaps.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/heatmaps_utils.py (1 hunks)
- discord_analyzer/models/BaseModel.py (2 hunks)
- discord_analyzer/models/raw_member_activities.py (1 hunks)
- discord_analyzer/rn_analyzer.py (2 hunks)
- discord_analyzer/schemas/init.py (1 hunks)
- discord_analyzer/schemas/activity_type.py (1 hunks)
- discord_analyzer/schemas/hourly_analytics.py (1 hunks)
- discord_analyzer/schemas/platform_configs/init.py (1 hunks)
- discord_analyzer/schemas/platform_configs/config_base.py (1 hunks)
- discord_analyzer/schemas/platform_configs/discord.py (1 hunks)
- discord_analyzer/schemas/raw_analytics.py (1 hunks)
- discord_analyzer/schemas/raw_analytics_item.py (1 hunks)
- tests/integration/test_analyzer_init.py (1 hunks)
- tests/integration/test_assess_engagement_mention.py (3 hunks)
- tests/integration/test_assess_engagement_reactions.py (3 hunks)
- tests/integration/test_assess_engagement_replies.py (3 hunks)
- tests/integration/test_discord_heatmaps_config.py (1 hunks)
- tests/integration/test_heatmaps_analytics.py (1 hunks)
- tests/integration/test_heatmaps_analytics_base.py (1 hunks)
- tests/integration/test_heatmaps_analytics_different_source.py (1 hunks)
- tests/integration/test_heatmaps_analytics_hourly_no_filter.py (1 hunks)
- tests/integration/test_heatmaps_analytics_raw.py (1 hunks)
- tests/integration/test_heatmaps_hourly_analytics_actions_vectors.py (1 hunks)
- tests/integration/test_heatmaps_hourly_analytics_interaction_vectors.py (1 hunks)
- tests/integration/test_heatmaps_hourly_lone_message.py (1 hunks)
- tests/integration/test_heatmaps_hourly_mentions.py (1 hunks)
- tests/integration/test_heatmaps_process_hourly_single_day.py (1 hunks)
- tests/integration/test_heatmaps_process_raw_analytics.py (1 hunks)
- tests/integration/test_heatmaps_reactions.py (1 hunks)
- tests/integration/test_heatmaps_replier.py (1 hunks)
- tests/integration/test_heatmaps_thread_msg.py (1 hunks)
- tests/integration/test_heatmaps_utils.py (1 hunks)
- tests/integration/test_louvain_algorithm_get_computed_dates.py (1 hunks)
- tests/integration/test_neo4j_projection_utils_computed_dates.py (1 hunks)
- tests/integration/test_network_graph_creation.py (1 hunks)
- tests/integration/test_platforms_base_config.py (1 hunks)
- tests/integration/utils/mock_graph.py (1 hunks)
- tests/unit/test_analyzer_heatmaps_compute_iteration_counts.py (1 hunks)
- tests/unit/test_heatmaps_analytics_base_process_vectors.py (1 hunks)
Files not processed due to max files limit (3)
- tests/unit/test_schema_hourly_analytics.py
- tests/unit/test_schema_raw_analytics.py
- tests/unit/test_sum_interactions_features.py
Files not reviewed due to errors (1)
- tests/integration/test_heatmaps_analytics_raw.py (no review received)
Files skipped from review due to trivial changes (12)
- discord_analyzer/init.py
- discord_analyzer/analysis/neo4j_analysis/utils/init.py
- discord_analyzer/analyzer/heatmaps/init.py
- discord_analyzer/schemas/init.py
- discord_analyzer/schemas/activity_type.py
- discord_analyzer/schemas/platform_configs/init.py
- discord_analyzer/schemas/raw_analytics_item.py
- tests/integration/test_assess_engagement_reactions.py
- tests/integration/test_heatmaps_reactions.py
- tests/integration/test_neo4j_projection_utils_computed_dates.py
- tests/integration/test_network_graph_creation.py
- tests/unit/test_analyzer_heatmaps_compute_iteration_counts.py
Additional context used
Ruff
discord_analyzer/analyzer/heatmaps/heatmaps_utils.py
66-69: Use ternary operator
last_date = documents[0]["date"] if len(documents) != 0 else Noneinstead ofif-else-block (SIM108)Replace
if-else-block withlast_date = documents[0]["date"] if len(documents) != 0 else Nonediscord_analyzer/models/BaseModel.py
25-28: Return the condition directly (SIM103)
Inline condition
discord_analyzer/analysis/analytics_interactions_script.py
8-8: Do not use mutable data structures for argument defaults (B006)
Replace with
None; initialize within function
43-43: Use
key not in dictinstead ofkey not in dict.keys()(SIM118)Remove
.keys()
48-48: Use
key not in dictinstead ofkey not in dict.keys()(SIM118)Remove
.keys()
190-190: No explicit
stacklevelkeyword argument found (B028)
213-213: Use
key in dictinstead ofkey in dict.keys()(SIM118)Remove
.keys()
223-223: Use
key not in dictinstead ofkey not in dict.keys()(SIM118)Remove
.keys()discord_analyzer/analysis/neo4j_analysis/centrality.py
68-68: Use
key not in dictinstead ofkey not in dict.keys()(SIM118)Remove
.keys()
69-69: Use
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70-70: Use
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73-73: Use
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268-268: Use
key in dictinstead ofkey in dict.keys()(SIM118)Remove
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269-269: Use
key in dictinstead ofkey in dict.keys()(SIM118)Remove
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322-322: Use
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350-350: Use
key in dictinstead ofkey in dict.keys()(SIM118)Remove
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Additional comments not posted (61)
analyzer_init.py (1)
3-3: Change of import path fromdiscord_analyzertodiscord_analyzer.rn_analyzerforRnDaoAnalyzer.Ensure that all other references and usage of
RnDaoAnalyzeracross the project are updated accordingly.discord_analyzer/schemas/platform_configs/config_base.py (3)
4-15: Constructor initialization looks good and properly typed.
17-23: Methodto_dicteffectively converts class instance to dictionary.
25-36: Methodfrom_dictcorrectly reconstructs class instance from dictionary.discord_analyzer/schemas/raw_analytics.py (3)
4-19: Constructor ensures correct handling and typing ofActivityType.
21-29: Methodto_dicteffectively serializes class instance to dictionary, handling enumerations and optional fields.
31-40: Methodfrom_dictcorrectly deserializes dictionary to class instance, handling type conversions and optional fields.discord_analyzer/schemas/hourly_analytics.py (3)
4-19: Constructor correctly initializes properties with appropriate types and handles optional fields.
21-32: Methodto_dicteffectively serializes class instance to dictionary, correctly handling optional fields.
34-45: Methodfrom_dictaccurately reconstructs class instance from dictionary, ensuring correct handling of optional fields.discord_analyzer/analyzer/heatmaps/heatmaps_utils.py (3)
7-12: Initialization of MongoDB client in the constructor is correct and follows good encapsulation practices by storing the database reference for the specified platform.
13-33: The methodget_usersefficiently retrieves user data based on theis_botflag. The use of MongoDB's projection to fetch only necessary fields (id) is a good practice for performance.
35-53: Theget_users_countmethod correctly counts documents based on theis_botparameter. This method is straightforward and uses MongoDB'scount_documentseffectively.tests/integration/utils/mock_graph.py (2)
3-3: Correctly updated the import statement forRnDaoAnalyzerto reflect the new module path.
Line range hint
3-45: Thegenerate_mock_graphfunction is well-structured and uses theEngagementAssessmentclass effectively to compute engagement based on Discord activities. This method appears to be correctly implemented, assuming proper functionality of theprepare_activity_paramsandEngagementAssessment.tests/unit/test_heatmaps_analytics_base_process_vectors.py (1)
6-118: The test classTestRawMemberActivitiesProcessVectorsis well-organized. Each test method (test_no_input,test_single_input,test_multiple_input) correctly asserts the behavior of the_process_vectorsmethod under different conditions. Using explicit expectations for the output ensures that the tests are robust and clear.discord_analyzer/models/BaseModel.py (1)
16-16: The initialization of thecollectionattribute in the constructor is straightforward and correct.tests/integration/test_heatmaps_thread_msg.py (4)
1-12: Setup and resource initialization look good. Ensuring a clean state by dropping collections is a good practice in isolated testing.
13-63: The data preparation logic is comprehensive, covering multiple days and hours. This should allow for robust testing of the heatmaps functionality.
63-64: Efficient use of MongoDB'sinsert_manyfor batch data insertion.
66-88: Analysis and assertions are well-implemented, ensuring that the heatmap data aligns with the expected results from the test setup.tests/integration/test_heatmaps_hourly_lone_message.py (4)
1-12: Setup and resource initialization look good. Ensuring a clean state by dropping collections is a good practice in isolated testing.
13-63: The data preparation logic is comprehensive, covering multiple days and hours. This should allow for robust testing of the heatmaps functionality.
64-65: Efficient use of MongoDB'sinsert_manyfor batch data insertion.
67-91: Analysis and assertions are well-implemented, ensuring that the heatmap data aligns with the expected results from the test setup.tests/integration/test_analyzer_init.py (4)
1-12: Setup and resource initialization look good. Ensuring a clean state by performing necessary database operations is a good practice in isolated testing.
Line range hint
13-63: The data preparation logic is comprehensive, covering multiple days and hours. This should allow for robust testing of the analytics functionality.
Line range hint
64-65: Efficient use of MongoDB'sinsert_manyfor batch data insertion.
Line range hint
67-91: Analysis and assertions are well-implemented, ensuring that the analytics data aligns with the expected results from the test setup.discord_analyzer/schemas/platform_configs/discord.py (1)
10-94: Initialization ofDiscordAnalyzerConfigis well-structured, setting up platform specifics and analytics configurations effectively.discord_analyzer/analysis/neo4j_analysis/louvain.py (1)
4-4: Ensure the updated import path forProjectionUtilsis correct.Verification successful
The updated import path for
ProjectionUtilsis correct.
discord_analyzer/analysis/neo4j_analysis/louvain.pyline 4:from discord_analyzer.analysis.neo4j_analysis.utils import ProjectionUtilsScripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that the updated import path for `ProjectionUtils` is correct. # Test: Search for the `ProjectionUtils` file. fd 'projection_utils.py'Length of output: 91
tests/integration/test_heatmaps_replier.py (1)
8-126: Thoroughly structured test for reply messages with comprehensive setup and assertions.This test function
test_reply_messagesis well-structured, covering a variety of cases and ensuring that the data setup, execution, and assertions are all aligned with expected outcomes. It's commendable that the test covers various aspects such as date handling, user interactions, and the accuracy of the results produced by theHeatmapsclass. The use of MongoDB collections for setting up the test environment is also correctly handled with appropriate clean-up usingdrop_collection. Overall, this test seems to be robust and should effectively validate the functionality of reply message analysis in the heatmap feature.tests/integration/test_platforms_base_config.py (1)
12-122: Comprehensive testing of configuration conversion methods.The methods
test_config_to_dict,test_analytics_from_dict,test_analytics_data_to_dict, andtest_analytics_data_from_dictare all well-implemented, ensuring that thePlatformConfigBaseclass can reliably serialize and deserialize analytics configurations. These tests are crucial for ensuring that the configuration handling in the Discord analyzer is robust and error-free. The use of assertions to compare expected and actual results is appropriate and effectively validates the functionality.tests/integration/test_discord_heatmaps_config.py (1)
7-89: Effective validation of Discord analyzer configuration schema.The methods
test_discord_schema_overview,test_discord_schema_hourly_analytics, andtest_discord_schema_raw_analyticsare well-crafted to ensure the integrity and correctness of theDiscordAnalyzerConfigschema. These tests check the configuration details such as platform identifier, resource identifiers, and the properties of both hourly and raw analytics. The thoroughness in checking each attribute and handling potential errors with appropriate exceptions is commendable, ensuring that any misconfigurations are caught during testing.discord_analyzer/analysis/neo4j_analysis/local_clustering_coefficient.py (1)
Line range hint
4-118: Robust implementation of local clustering coefficient computation with appropriate error handling.The
LocalClusteringCoeffclass provides a comprehensive approach to computing local clustering coefficients in a Neo4j graph database context. The methods are well-documented with clear parameters and return types. The use of projection utilities to manage graph data and the handling of potential exceptions during the computation process are both effectively implemented. This implementation should ensure accurate and efficient computation of clustering coefficients, which are critical for analyzing social network structures within the guild.discord_analyzer/analyzer/heatmaps/analytics_hourly.py (2)
48-52: Good use of validation foractivity_directionandactivity. These checks prevent invalid data processing early in the method execution.Also applies to: 54-58
60-71: The methodget_hourly_analyticsis well encapsulated and used here to fetch data based on the provided parameters. This is a good example of code reuse.discord_analyzer/analyzer/heatmaps/analytics_raw.py (2)
55-66: Good use of validation foractivity_directionandactivity. These checks prevent invalid data processing early in the method execution.
68-77: The methodget_analytics_countis well encapsulated and used here to fetch data based on the provided parameters. This is a good example of code reuse.tests/integration/test_heatmaps_utils.py (2)
8-14: Proper setup for MongoDB client and test preparation in thesetUpmethod. This ensures that each test runs in a clean state.
17-20: Each test method is well-structured and covers a specific functionality of theHeatmapsUtilsclass. The use of assertions to check expected outcomes is appropriate and ensures that the utility functions behave as expected.Also applies to: 21-49, 51-79, 81-84, 86-114, 116-158, 160-165, 167-180, 182-211
tests/integration/test_heatmaps_analytics_different_source.py (2)
9-29: Proper setup for MongoDB client and test preparation in thesetUpmethod. This ensures that each test runs in a clean state.
30-151: Each test method is well-structured and covers a specific functionality of theHeatmapsclass. The use of assertions to check expected outcomes is appropriate and ensures that the heatmaps analytics behave as expected.Also applies to: 152-179
tests/integration/test_heatmaps_analytics.py (1)
131-137: Verify the expected length of analytics results based on the setup data.Verification successful
The
setUpmethod intests/integration/test_heatmaps_analytics.pysets up theHeatmapsinstance with 3 resources. Thestartmethod indiscord_analyzer/analyzer/heatmaps/heatmaps.pyiterates over resources and users to generate analytics data. Given this setup, the expected length ofanalyticsbeing 3 is consistent with the setup of 3 resources.
tests/integration/test_heatmaps_analytics.py:
setUpinitializesself.heatmapswith 3 resources.- The test inserts data for one raw member.
discord_analyzer/analyzer/heatmaps/heatmaps.py:
startmethod processes data for each resource and user.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the expected length of analytics results based on the setup data. # Test: Check the number of resources and raw member data for a single day. cat tests/integration/test_heatmaps_analytics.py | grep 'self.assertEqual(len(analytics), 3)'Length of output: 139
Script:
#!/bin/bash # Locate the setup data in the test file ast-grep --lang python --pattern 'def setUp($_) { $$$ }' tests/integration/test_heatmaps_analytics.py # Locate the start method of self.heatmaps ast-grep --lang python --pattern 'def start($_) { $$$ }'Length of output: 1050
Script:
#!/bin/bash # Corrected pattern to locate the setup data in the test file ast-grep --lang python --pattern 'def setUp(self): $$$' tests/integration/test_heatmaps_analytics.py # Corrected pattern to locate the start method ast-grep --lang python --pattern 'def start(self, from_start=True): $$$'Length of output: 177
Script:
#!/bin/bash # Use rg to search for the setUp method in the test file rg 'def setUp' tests/integration/test_heatmaps_analytics.py # Use rg to search for the start method of self.heatmaps rg 'def start' --glob '**/heatmaps*'Length of output: 237
Script:
#!/bin/bash # Display the content of the setUp method in the test file rg -A 10 'def setUp' tests/integration/test_heatmaps_analytics.py # Display the content of the start method in the heatmaps module rg -A 20 'def start' discord_analyzer/analyzer/heatmaps/heatmaps.pyLength of output: 1309
Script:
#!/bin/bash # Display the complete content of the setUp method in the test file rg -A 50 'def setUp' tests/integration/test_heatmaps_analytics.py # Display the complete content of the start method in the heatmaps module rg -A 100 'def start' discord_analyzer/analyzer/heatmaps/heatmaps.pyLength of output: 5522
discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py (1)
6-6: Correct the import statement for better modularity and to reflect the actual usage of theProjectionUtils.The change in the import statement reflects a move towards better organization of utility functions.
tests/integration/test_heatmaps_process_raw_analytics.py (2)
27-47: Test case for empty data appears comprehensive.This test validates that all expected keys exist and are initialized correctly as empty lists, which is crucial for ensuring the robustness of the analytics processing in edge cases.
48-139: Review the logic for handling single and multiple authors.Verification successful
The
_process_raw_analyticsmethod indiscord_analyzer/analyzer/heatmaps/heatmaps.pydoes filter byauthor_id. The method includes a parameterauthor_idthat is passed to theanalytics_raw.analyzefunction, ensuring that the analytics are processed correctly for the specified author.
- The method correctly sets up filters for
author_id,day,activity,activity_name,activity_direction, andadditional_filters.- The test cases for single and multiple authors should ensure that the filtering logic is verified.
No issues were found with the implementation regarding the handling of single and multiple authors.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Ensure the analytics processing handles single and multiple authors correctly. # Test: Check if the MongoDB queries within the `_process_raw_analytics` method are correctly filtering by `author_id`. ast-grep --lang python --pattern $'class TestHeatmapsProcessRawAnalyticsSingleDay { $$$ def _process_raw_analytics($_, $_) { $$$ } $$$ }'Length of output: 690
Script:
#!/bin/bash # Description: Ensure the analytics processing handles single and multiple authors correctly. # Test: Check if the MongoDB queries within the `_process_raw_analytics` method are correctly filtering by `author_id`. ast-grep --lang python --pattern $'def _process_raw_analytics($_, $_):' --jsonLength of output: 82
Script:
#!/bin/bash # Description: Ensure the analytics processing handles single and multiple authors correctly. # Search for the `_process_raw_analytics` method across the entire repository. ast-grep --lang python --pattern $'def _process_raw_analytics($_, $_):' --jsonLength of output: 82
Script:
#!/bin/bash # Description: Perform a broader search for methods related to analytics processing. # Search for method definitions that include "analytics" in their name. rg 'def .*analytics.*\(' --glob '*.py'Length of output: 7043
Script:
#!/bin/bash # Description: Extract the implementation of the `_process_raw_analytics` method. # Extract the `_process_raw_analytics` method implementation from the identified file. ast-grep --lang python --pattern $'def _process_raw_analytics($_, $_):' discord_analyzer/analyzer/heatmaps/heatmaps.py --jsonLength of output: 129
Script:
#!/bin/bash # Description: Perform a broader search within the identified file to locate the `_process_raw_analytics` method and its implementation. # Search for the `_process_raw_analytics` method definition and its implementation in the identified file. rg 'def _process_raw_analytics' discord_analyzer/analyzer/heatmaps/heatmaps.py -A 20Length of output: 863
Script:
#!/bin/bash # Description: Extract the complete implementation of the `_process_raw_analytics` method. # Extract a larger portion of the `_process_raw_analytics` method implementation from the identified file. rg 'def _process_raw_analytics' discord_analyzer/analyzer/heatmaps/heatmaps.py -A 50Length of output: 2031
discord_analyzer/analyzer/heatmaps/heatmaps.py (1)
10-118: Comprehensive initialization and method documentation.The constructor and methods are well-documented with detailed parameter descriptions, which enhances maintainability and understandability of the code.
tests/integration/test_heatmaps_analytics_hourly_no_filter.py (1)
8-13: Proper setup for testing environment.The setup method correctly initializes necessary components and ensures the MongoDB collection is clean before each test, which is good practice for isolation between tests.
discord_analyzer/analysis/neo4j_analysis/centrality.py (1)
5-5: Updated import statement looks correct. Ensure that all references toProjectionUtilsandNeo4JMetricsmatch the new module path.tests/integration/test_heatmaps_hourly_analytics_interaction_vectors.py (6)
13-18: Setup method is well-structured and correctly sets up the necessary environment for the tests.
22-35: The test for empty data is comprehensive, checking that the list length and sum are as expected. Good use of multiple assertions to ensure different aspects of the output are verified.
37-85: The test for no relevant data is well-implemented. It sets up data that should not be counted by the filters and verifies that the result is still zero.
87-193: The test for a single relevant data setup is correctly implemented. It uses detailed assertions to ensure that only the expected data points are considered in the results.
275-353: The test for multiple relevant data points is thorough, covering various scenarios and properly asserting the expected results in the activity vector. Good job ensuring comprehensive test coverage.
354-376: The test for handling incorrect activity types uses exception handling appropriately to ensure that the system raises an error as expected.tests/integration/test_heatmaps_process_hourly_single_day.py (5)
9-26: The setup method is well-structured and ensures a clean state by dropping relevant collections before each test. This is good practice to avoid test contamination.
27-68: The test for checking the return type and data structure of the hourly analytics process is comprehensive, covering various aspects of the expected output. Good use ofassertInandassertIsInstanceto validate data types and contents.
70-165: The test for processing hourly analytics for a single author is well-implemented. It accurately sets up the test conditions and uses detailed assertions to verify that the analytics are computed as expected for various interaction types.
166-252: The test for processing data for a non-existent channel is correctly implemented, ensuring that no data is mistakenly processed or returned. This test effectively checks the system's robustness in handling empty data scenarios.
254-340: The test for processing data for a non-existent author is well-crafted, using a thorough setup to simulate the condition and precise assertions to confirm that no data is processed.
| class TestHeatmapsProcessRawAnalyticsSingleDay(TestCase): | ||
| def setUp(self) -> None: | ||
| platform_id = "1234567890" | ||
| period = datetime(2024, 1, 1) | ||
| resources = list["123", "124", "125"] | ||
| # using one of the configs we currently have | ||
| # it could be any other platform's config | ||
| discord_analyzer_config = DiscordAnalyzerConfig() | ||
|
|
||
| self.heatmaps = Heatmaps( | ||
| platform_id=platform_id, | ||
| period=period, | ||
| resources=resources, | ||
| analyzer_config=discord_analyzer_config, | ||
| ) | ||
| self.mongo_client = MongoSingleton.get_instance().get_client() | ||
| self.mongo_client[platform_id].drop_collection("rawmemberactivities") | ||
|
|
There was a problem hiding this comment.
Ensure proper resource cleanup in MongoDB after tests to prevent side effects.
Consider adding a tearDown method to drop collections or documents created during tests. This ensures that each test runs in a clean state and does not affect subsequent tests.
| @@ -33,6 +34,8 @@ def heatmaps_analytics(self): | |||
| """ | |||
| heatmaps are the input for assess_engagement's interaction matrix | |||
| """ | |||
| from discord_analyzer.analyzer.heatmaps import Heatmaps | |||
There was a problem hiding this comment.
Ensure imported modules are at the top of the file.
The import statement for Heatmaps is inside the method heatmaps_analytics. It's a best practice to place all imports at the top of the file unless there is a specific reason not to do so, such as avoiding circular dependencies or optional dependencies.
| @@ -33,6 +34,8 @@ def heatmaps_analytics(self): | |||
| """ | |||
| heatmaps are the input for assess_engagement's interaction matrix | |||
| """ | |||
| from discord_analyzer.analyzer.heatmaps import Heatmaps | |||
There was a problem hiding this comment.
Ensure imported modules are at the top of the file.
The import statement for Heatmaps is inside the method heatmaps_analytics. It's a best practice to place all imports at the top of the file unless there is a specific reason not to do so, such as avoiding circular dependencies or optional dependencies.
| def get_last_date(self) -> datetime | None: | ||
| """ | ||
| get the last document's date | ||
| """ | ||
| cursor = ( | ||
| self.database["heatmaps"] | ||
| .find({}, {"date": 1, "_id": 0}) | ||
| .sort("date", -1) | ||
| .limit(1) | ||
| ) | ||
| documents = list(cursor) | ||
| if len(documents) != 0: | ||
| last_date = documents[0]["date"] | ||
| else: | ||
| last_date = None | ||
|
|
||
| return last_date |
There was a problem hiding this comment.
Refactor the if-else block to use a ternary operator for clarity and conciseness.
- if len(documents) != 0:
- last_date = documents[0]["date"]
- else:
- last_date = None
+ last_date = documents[0]["date"] if documents else NoneCommittable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def get_last_date(self) -> datetime | None: | |
| """ | |
| get the last document's date | |
| """ | |
| cursor = ( | |
| self.database["heatmaps"] | |
| .find({}, {"date": 1, "_id": 0}) | |
| .sort("date", -1) | |
| .limit(1) | |
| ) | |
| documents = list(cursor) | |
| if len(documents) != 0: | |
| last_date = documents[0]["date"] | |
| else: | |
| last_date = None | |
| return last_date | |
| def get_last_date(self) -> datetime | None: | |
| """ | |
| get the last document's date | |
| """ | |
| cursor = ( | |
| self.database["heatmaps"] | |
| .find({}, {"date": 1, "_id": 0}) | |
| .sort("date", -1) | |
| .limit(1) | |
| ) | |
| documents = list(cursor) | |
| last_date = documents[0]["date"] if documents else None | |
| return last_date |
Tools
Ruff
66-69: Use ternary operator
last_date = documents[0]["date"] if len(documents) != 0 else Noneinstead ofif-else-block (SIM108)Replace
if-else-block withlast_date = documents[0]["date"] if len(documents) != 0 else None
| def test_wrong_activity_type(self): | ||
| day = datetime(2023, 1, 1) | ||
|
|
||
| with self.assertRaises(ValueError): | ||
| self.analytics.analyze( | ||
| activity="interactions", | ||
| activity_name="reply", | ||
| day=day, | ||
| author_id=9000, | ||
| activity_direction="wrong_type", | ||
| ) | ||
|
|
||
| def test_wrong_activity(self): | ||
| day = datetime(2023, 1, 1) | ||
|
|
||
| with self.assertRaises(ValueError): | ||
| self.analytics.analyze( | ||
| activity="activity1", | ||
| activity_name="reply", | ||
| day=day, | ||
| author_id=9000, | ||
| activity_direction="emitter", | ||
| ) |
There was a problem hiding this comment.
Ensure exception handling covers specific exceptions rather than a general catch-all, which can obscure the source of errors.
try:
self.analytics.analyze(
activity="interactions",
activity_name="reply",
day=day,
author_id=9000,
activity_direction="wrong_type",
)
except SpecificException as e:
# Handle specific exception
passCommittable suggestion was skipped due to low confidence.
| class AnalyticsRaw: | ||
| def __init__(self, platform_id: str) -> None: | ||
| client = MongoSingleton.get_instance().get_client() | ||
| # `rawmemberactivities` is the collection we would use for analytics | ||
| self.collection = client[platform_id]["rawmemberactivities"] | ||
| self.msg_prefix = f"PLATFORMID: {platform_id}:" |
There was a problem hiding this comment.
Tip
Codebase Verification
The platform_id is used in the constructor without any validation, which could lead to runtime errors if an invalid or empty platform_id is provided.
- Lines in
discord_analyzer/analyzer/heatmaps/analytics_raw.py:__init__method: No validation forplatform_id.
Analysis chain
Initialization of MongoDB client and collection is done in the constructor. Ensure that the platform_id provided is always valid and non-empty to avoid runtime errors.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if platform_id is validated.
# Test: Search for validation code for platform_id. Expect: Validation code exists.
rg --type python $'platform_id' discord_analyzer/analyzer/heatmaps/analytics_raw.py
Length of output: 113
Script:
#!/bin/bash
# Description: Check if platform_id is validated.
# Test: Search for validation code for platform_id. Expect: Validation code exists.
rg 'platform_id' discord_analyzer/analyzer/heatmaps/analytics_raw.py
Length of output: 243
| Parameters | ||
| ------------ | ||
| day : date | ||
| a specific day date | ||
| activity : str | ||
| to be `interactions` or `actions` | ||
| activity_name : str | ||
| the activity name to do filtering | ||
| could be `reply`, `reaction`, `mention, or ... | ||
| author_id : str | int | ||
| the author to do analytics on its data | ||
| activity_direction : str | ||
| the direction of activity | ||
| could be `emitter` or `receiver` | ||
| **kwargs : dict | ||
| filters : dict[str, dict[str] | str] | ||
| the filtering that we need to apply | ||
| for default it is an None meaning | ||
| no filtering would be applied | ||
|
|
||
| Returns | ||
| --------- | ||
| activity_count : list[RawAnalyticsItem] | ||
| raw analytics item which holds the user and | ||
| the count of interaction in that day | ||
| """ | ||
| filters: dict[str, dict[str, Any] | str] | None = kwargs.get("filters") | ||
| start_day = datetime.combine(day, time(0, 0, 0)) | ||
| end_day = start_day + timedelta(days=1) | ||
|
|
||
| match_filters = { | ||
| "date": {"$gte": start_day, "$lt": end_day}, | ||
| "author_id": author_id, | ||
| } | ||
| if filters is not None: | ||
| match_filters = { | ||
| **match_filters, | ||
| **filters, | ||
| } | ||
|
|
||
| pipeline = [ | ||
| { | ||
| "$match": { | ||
| **match_filters, | ||
| } | ||
| }, | ||
| {"$unwind": f"${activity}"}, | ||
| { | ||
| "$match": { | ||
| f"{activity}.name": activity_name, | ||
| f"{activity}.type": activity_direction, | ||
| }, | ||
| }, | ||
| {"$unwind": f"${activity}.users_engaged_id"}, | ||
| {"$group": {"_id": f"${activity}.users_engaged_id", "count": {"$sum": 1}}}, | ||
| ] | ||
|
|
||
| cursor = self.collection.aggregate(pipeline) | ||
| db_result = list(cursor) | ||
| activity_count = self._prepare_raw_analytics_item(author_id, db_result) | ||
|
|
||
| return activity_count | ||
|
|
||
| def _prepare_raw_analytics_item( | ||
| self, | ||
| author_id: str | int, | ||
| activities_data: list[dict[str, str | int]], | ||
| ) -> list[RawAnalyticsItem]: | ||
| """ | ||
| post process the database results | ||
|
|
||
| this will take the format `[{'_id': 9000, 'count': 4}]` and output a RawAnalyticsItem | ||
|
|
||
| Parameters | ||
| ------------ | ||
| author_id : str | ||
| just for skipping self-interactions | ||
| activities_data : dict[str, str | int] | ||
| the user interaction count. | ||
| the data will be as an example `[{'_id': 9000, 'count': 4}]` | ||
| _id would be the users interacting with | ||
|
|
||
| Returns | ||
| -------- | ||
| raw_analytics : list[RawAnalyticsItem] | ||
| the data in format of raw analytics item | ||
| """ | ||
| analytics: list[RawAnalyticsItem] = [] | ||
| for data in activities_data: | ||
| if data["_id"] != author_id: | ||
| raw_analytics = RawAnalyticsItem( | ||
| account=data["_id"], # type: ignore | ||
| count=data["count"], # type: ignore | ||
| ) | ||
| analytics.append(raw_analytics) | ||
| else: | ||
| # self interaction | ||
| logging.info("Skipping self-interaction!") | ||
|
|
||
| return analytics |
There was a problem hiding this comment.
The get_analytics_count method is comprehensive and handles various data fetching scenarios effectively. However, consider encapsulating the MongoDB pipeline construction into a separate method to reduce complexity and enhance readability.
+ def build_pipeline(self, day, activity, author_id, filters):
+ # Construct the MongoDB aggregation pipeline
+ pipeline = [
+ {"$match": {"date": {"$gte": start_day, "$lt": end_day}, "author_id": author_id}},
+ {"$unwind": f"${activity}"},
+ ]
+ if filters is not None:
+ pipeline.append({"$match": filters})
+ # Additional pipeline steps...
+ return pipeline
- pipeline = [
- {"$match": {"date": {"$gte": start_day, "$lt": end_day}, "author_id": author_id}},
- {"$unwind": f"${activity}"},
- # Additional pipeline steps...
- ]
- if filters is not None:
- pipeline.append({"$match": filters})Committable suggestion was skipped due to low confidence.
| @@ -1,5 +1,5 @@ | |||
| from discord_analyzer.analysis.neo4j_analysis.louvain import Louvain | |||
| from discord_analyzer.analysis.neo4j_utils.projection_utils import ProjectionUtils | |||
| from discord_analyzer.analysis.neo4j_analysis.utils import ProjectionUtils | |||
There was a problem hiding this comment.
Tip
Codebase Verification
The ProjectionUtils class or function is not defined in projection_utils.py, nor is it imported from another module in that file. This indicates that the import statement in tests/integration/test_louvain_algorithm_get_computed_dates.py is likely incorrect or outdated.
tests/integration/test_louvain_algorithm_get_computed_dates.py:2: The import statement forProjectionUtilsis incorrect.
Analysis chain
Verify the correct import of ProjectionUtils.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Ensure that the import statement for `ProjectionUtils` is correct and that the module exists.
# Test: Search for the `ProjectionUtils` file.
fd 'projection_utils.py'
Length of output: 91
Script:
#!/bin/bash
# Description: Verify the existence of the `ProjectionUtils` class or methods in the `projection_utils.py` file.
# Test: Search for the `ProjectionUtils` class or methods.
ast-grep --lang python --pattern $'class ProjectionUtils {\n $$$\n}'
Length of output: 522
Script:
#!/bin/bash
# Description: Verify the existence of the `ProjectionUtils` class or methods in the `projection_utils.py` file.
# Test: Search for the `ProjectionUtils` class or methods.
ast-grep --lang python --pattern 'class ProjectionUtils:'
Length of output: 59
Script:
#!/bin/bash
# Description: Verify if `ProjectionUtils` is defined as a function or imported from another module in `projection_utils.py`.
# Test: Search for `ProjectionUtils` as a function.
ast-grep --lang python --pattern 'def ProjectionUtils('
# Test: Search for `ProjectionUtils` as an import.
rg 'import ProjectionUtils' discord_analyzer/analysis/neo4j_analysis/utils/projection_utils.py
Length of output: 499
| @@ -1,7 +1,7 @@ | |||
| import logging | |||
There was a problem hiding this comment.
Consider improving error handling and recovery strategies.
While the error logging in the compute and compute_graph_louvain methods is adequate, consider implementing more robust error recovery strategies. This could include retries or alternative actions when a computation fails, to enhance the resilience of the system.
There was a problem hiding this comment.
Actionable comments posted: 22
Outside diff range and nitpick comments (20)
discord_analyzer/models/BaseModel.py (1)
Line range hint
25-28: Refactor to return the condition directly.- if self.collection_name in self.database.list_collection_names(): - return True - else: - return False + return self.collection_name in self.database.list_collection_names()tests/integration/test_analyzer_init.py (2)
8-8: Consider providing more context on why this test is marked to be skipped. If it's due to pending deprecation or refactoring, consider adding a TODO or FIXME comment to clarify.
10-11: Ensure that the local import ofAnalyzerInitis necessary here. If it's to avoid circular dependencies, consider refactoring the import structure to improve maintainability.Also applies to: 17-17
discord_analyzer/schemas/platform_configs/discord.py (1)
10-94: Consider adding a docstring to theDiscordAnalyzerConfigclass to explain its role and the significance of the analytics configurations it initializes. This will enhance code readability and maintainability, especially for new developers or when revisiting this code later.tests/integration/test_network_graph_creation.py (1)
11-11: Theskipmarker usage is justified but requires clarification.Consider adding a comment explaining why this test is being skipped and under what conditions it should be re-enabled.
discord_analyzer/analysis/neo4j_analysis/louvain.py (2)
Line range hint
17-17: Consider improving error handling by adding specific exception types and recovery strategies.Refine the exception handling in the
computemethod to catch specific Neo4j-related exceptions and implement retry logic or alternative recovery strategies.
Line range hint
33-33: Ensure that resources are properly released after use to prevent resource leaks.Add error handling to ensure that the graph projection is dropped even if an error occurs during the computation.
tests/integration/test_assess_engagement_replies.py (2)
4-4: Consider grouping all imports at the top of the file unless there's a specific need to delay an import, such as to avoid circular dependencies.
14-14: The use of@pytest.mark.skipshould be justified with a comment explaining why the test is being skipped to maintain clarity for future maintenance.tests/integration/test_assess_engagement_reactions.py (2)
4-4: It's advisable to keep all imports at the beginning of the file unless there's a specific reason for delaying an import.
14-14: Thepytest.mark.skipdecorator is used here. It would be beneficial to add a comment explaining why this test is currently skipped to aid future developers.tests/integration/test_assess_engagement_mention.py (2)
4-4: Ensure all imports are placed at the top of the file unless there's a specific reason for delaying them, such as avoiding circular dependencies.
14-14: Adding a comment explaining why this test is skipped would be helpful for future maintenance and understanding.discord_analyzer/rn_analyzer.py (1)
4-4: It's a good practice to group all imports together at the top of the file for better readability and maintenance.discord_analyzer/analysis/analytics_interactions_script.py (3)
Line range hint
8-8: Replace mutable default argument with an immutable one to avoid potential bugs related to mutable default behavior.-def per_account_interactions(cursor_list, dict_keys=["replier_accounts", "reacter_accounts", "mentioner_accounts"]): +def per_account_interactions(cursor_list, dict_keys=None): + if dict_keys is None: + dict_keys = ["replier_accounts", "reacter_accounts", "mentioner_accounts"]
Line range hint
43-43: Optimize dictionary key checks by removing unnecessary.keys()method calls.- if account_name not in temp_dict.keys(): + if account_name not in temp_dict: - if account_name not in all_interaction_accounts.keys(): + if account_name not in all_interaction_accounts: - for idx, data_acc in enumerate(interaction_dict.keys()): + for idx, data_acc in enumerate(interaction_dict): - if thread not in channel_thread_dict[ch].keys(): + if thread not in channel_thread_dict[ch]:Also applies to: 48-48, 213-213, 223-223
Line range hint
190-190: Consider specifyingstacklevelin thewarnfunction to improve debugging by pointing to the caller of the function where the warning was raised.- warn("Messages is not ascending ordered!") + warn("Messages is not ascending ordered!", stacklevel=2)discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py (1)
[!TIP]
Codebase VerificationThe inspection of the logging statements in
discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.pyreveals the following:
- The first
logging.errorstatement includes theguildIdcontext.- The second
logging.errorstatement does not include any context and needs to be updated.- The
logging.infostatement includes theguildIdcontext through theprefix.Please update the second
logging.errorstatement to include relevant context such asguildId.
- Location to update:
logging.error("It isn't possible to have both S and R True!")Analysis chain
Line range hint
14-18: Ensure proper exception handling and logging throughout the class methods to maintain robustness and traceability.Also applies to: 25-25, 36-36, 43-43, 61-61, 79-79, 98-98, 116-116, 134-134, 152-152, 170-170, 188-188, 206-206, 224-224, 242-242
To ensure proper exception handling and logging throughout the class methods, each logging statement should include necessary context information like
guildId.
Logging statement 1:
logging.error(This statement is incomplete. We need to review the surrounding lines to verify context inclusion.
Logging statement 2:
logging.error("It isn't possible to have both S and R True!")This statement does not include any context. It should be updated to include relevant context such as
guildId.Logging statement 3:
logging.info(f"{prefix}Node stats saved for the date: {date}")This statement includes the
prefixanddate, which might provide some context, but it should be checked ifprefixcontainsguildIdor similar identifiers.Next Steps:
To verify the context inclusion for the first and third logging statements, we need to review the surrounding lines. Let's extract those lines to get a complete picture.
Next Steps:
To ensure accurate verification, we need to correct the regex pattern for the third logging statement and re-extract the surrounding lines.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that all exception handling logs include necessary context information. # Test: Search for logging statements without guildId context. Expect: No occurrences. rg --type python $'logging.error\("[^"]*"\)' discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.pyLength of output: 140
Script:
#!/bin/bash # Description: Identify all logging statements in the file for further inspection. # Test: Search for all logging statements in the specified file. rg 'logging\.(error|warning|info|debug)\(' discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.pyLength of output: 288
Script:
#!/bin/bash # Description: Review surrounding lines for the identified logging statements to verify context inclusion. # Extract lines around the first logging statement rg -A 3 -B 3 'logging\.error\(' discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py # Extract lines around the third logging statement rg -A 3 -B 3 'logging\.info\(f"{prefix}Node stats saved for the date: {date}"' discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.pyLength of output: 897
Script:
#!/bin/bash # Description: Correct the regex pattern and re-extract surrounding lines for the third logging statement to verify context inclusion. # Extract lines around the third logging statement with corrected regex rg -A 3 -B 3 'logging\.info\(f"\{prefix\}Node stats saved for the date: \{date\}"' discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.pyLength of output: 362
discord_analyzer/analysis/neo4j_analysis/centrality.py (2)
Line range hint
68-73: Usekey not in dictinstead ofkey not in dict.keys()for cleaner code.- node = "DiscordAccount" if "node" not in kwargs.keys() else kwargs["node"] + node = "DiscordAccount" if "node" not in kwargs else kwargs["node"] - weighted = True if "weighted" not in kwargs.keys() else kwargs["weighted"] + weighted = True if "weighted" not in kwargs else kwargs["weighted"] - normalize = False if "normalize" not in kwargs.keys() else kwargs["normalize"] + normalize = False if "normalize" not in kwargs else kwargs["normalize"] - preserve_parallel = ( - True if "preserve_parallel" not in kwargs.keys() else kwargs["preserve_parallel"] + preserve_parallel = ( + True if "preserve_parallel" not in kwargs else kwargs["preserve_parallel"] - )
Line range hint
268-269: Usekey in dictinstead ofkey in dict.keys()for cleaner code.- if "recompute_dates" in kwargs.keys(): + if "recompute_dates" in kwargs:
Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Files selected for processing (53)
- analyzer_init.py (1 hunks)
- discord_analyzer/init.py (1 hunks)
- discord_analyzer/analysis/analytics_interactions_script.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/centrality.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/local_clustering_coefficient.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/louvain.py (1 hunks)
- discord_analyzer/analysis/neo4j_analysis/utils/init.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/init.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/analytics_hourly.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/analytics_raw.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/heatmaps.py (1 hunks)
- discord_analyzer/analyzer/heatmaps/heatmaps_utils.py (1 hunks)
- discord_analyzer/models/BaseModel.py (2 hunks)
- discord_analyzer/models/raw_member_activities.py (1 hunks)
- discord_analyzer/rn_analyzer.py (2 hunks)
- discord_analyzer/schemas/init.py (1 hunks)
- discord_analyzer/schemas/activity_type.py (1 hunks)
- discord_analyzer/schemas/hourly_analytics.py (1 hunks)
- discord_analyzer/schemas/platform_configs/init.py (1 hunks)
- discord_analyzer/schemas/platform_configs/config_base.py (1 hunks)
- discord_analyzer/schemas/platform_configs/discord.py (1 hunks)
- discord_analyzer/schemas/raw_analytics.py (1 hunks)
- discord_analyzer/schemas/raw_analytics_item.py (1 hunks)
- tests/integration/test_analyzer_init.py (1 hunks)
- tests/integration/test_assess_engagement_mention.py (3 hunks)
- tests/integration/test_assess_engagement_reactions.py (3 hunks)
- tests/integration/test_assess_engagement_replies.py (3 hunks)
- tests/integration/test_discord_heatmaps_config.py (1 hunks)
- tests/integration/test_heatmaps_analytics.py (1 hunks)
- tests/integration/test_heatmaps_analytics_base.py (1 hunks)
- tests/integration/test_heatmaps_analytics_different_source.py (1 hunks)
- tests/integration/test_heatmaps_analytics_hourly_no_filter.py (1 hunks)
- tests/integration/test_heatmaps_analytics_raw.py (1 hunks)
- tests/integration/test_heatmaps_hourly_analytics_actions_vectors.py (1 hunks)
- tests/integration/test_heatmaps_hourly_analytics_interaction_vectors.py (1 hunks)
- tests/integration/test_heatmaps_hourly_lone_message.py (1 hunks)
- tests/integration/test_heatmaps_hourly_mentions.py (1 hunks)
- tests/integration/test_heatmaps_process_hourly_single_day.py (1 hunks)
- tests/integration/test_heatmaps_process_raw_analytics.py (1 hunks)
- tests/integration/test_heatmaps_reactions.py (1 hunks)
- tests/integration/test_heatmaps_replier.py (1 hunks)
- tests/integration/test_heatmaps_thread_msg.py (1 hunks)
- tests/integration/test_heatmaps_utils.py (1 hunks)
- tests/integration/test_louvain_algorithm_get_computed_dates.py (1 hunks)
- tests/integration/test_neo4j_projection_utils_computed_dates.py (1 hunks)
- tests/integration/test_network_graph_creation.py (1 hunks)
- tests/integration/test_platforms_base_config.py (1 hunks)
- tests/integration/utils/mock_graph.py (1 hunks)
- tests/unit/test_analyzer_heatmaps_compute_iteration_counts.py (1 hunks)
- tests/unit/test_heatmaps_analytics_base_process_vectors.py (1 hunks)
- tests/unit/test_schema_hourly_analytics.py (1 hunks)
- tests/unit/test_schema_raw_analytics.py (1 hunks)
Files not reviewed due to errors (2)
- discord_analyzer/analyzer/heatmaps/analytics_raw.py (no review received)
- tests/integration/test_heatmaps_utils.py (no review received)
Additional context used
Ruff
discord_analyzer/analyzer/heatmaps/heatmaps_utils.py
66-69: Use ternary operator
last_date = documents[0]["date"] if len(documents) != 0 else Noneinstead ofif-else-block (SIM108)Replace
if-else-block withlast_date = documents[0]["date"] if len(documents) != 0 else Nonediscord_analyzer/models/BaseModel.py
25-28: Return the condition directly (SIM103)
Inline condition
discord_analyzer/analysis/analytics_interactions_script.py
8-8: Do not use mutable data structures for argument defaults (B006)
Replace with
None; initialize within function
43-43: Use
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.keys()
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190-190: No explicit
stacklevelkeyword argument found (B028)
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Additional comments not posted (77)
discord_analyzer/schemas/platform_configs/__init__.py (1)
1-2: Consider limiting the scope offlake8: noqato specific lines to maintain code quality as this module evolves.discord_analyzer/analysis/neo4j_analysis/utils/__init__.py (1)
1-3: While the import statements are correct, consider limiting the scope offlake8: noqato specific problematic lines to maintain code quality.discord_analyzer/analyzer/heatmaps/__init__.py (1)
1-4: Import statements are correctly structured. However, consider using more targeted linting suppression to ensure code quality.discord_analyzer/schemas/__init__.py (1)
1-5: Import statements are correctly formatted and relevant to the module.discord_analyzer/schemas/activity_type.py (2)
4-6: EnumActivityTypeis well-defined with clear, meaningful values.
9-11: EnumActivityDirectionis correctly implemented with appropriate domain-specific values.tests/unit/test_analyzer_heatmaps_compute_iteration_counts.py (1)
24-36: Good use of relative time calculation for dynamic test expectations.This is a good practice as it makes the test less brittle and more adaptable to changes in the system date/time.
discord_analyzer/schemas/platform_configs/config_base.py (1)
17-36: Efficient serialization and deserialization methods.The use of list comprehensions for converting objects to and from dictionaries is efficient and maintains readability.
discord_analyzer/schemas/raw_analytics.py (1)
4-19: Proper use of type checking for enum conversion.The conditional check for
typeensures that thetypeattribute is always an instance ofActivityType, which is crucial for ensuring data integrity.discord_analyzer/schemas/hourly_analytics.py (1)
4-19: Clear and concise constructor with proper type handling.The explicit type assignments ensure that the class properties are always correctly typed, which is essential for data consistency.
discord_analyzer/analyzer/heatmaps/heatmaps_utils.py (3)
13-33: The implementation ofget_usersfunction looks good and adheres to the documentation provided.
35-53: The implementation ofget_users_countfunction is correct and well-documented.
55-71: Consider refactoring the if-else block to a ternary operator for clarity and conciseness.
[REFACTOR_SUGGESTion]- if len(documents) != 0: - last_date = documents[0]["date"] - else: - last_date = None + last_date = documents[0]["date"] if documents else NoneTools
Ruff
66-69: Use ternary operator
last_date = documents[0]["date"] if len(documents) != 0 else Noneinstead ofif-else-block (SIM108)Replace
if-else-block withlast_date = documents[0]["date"] if len(documents) != 0 else Nonetests/integration/utils/mock_graph.py (2)
3-3: Thegenerate_mock_graphfunction correctly utilizes various utilities to generate a mock graph. Ensure that all external dependencies are properly managed.Also applies to: 10-10
3-3: Thestore_mock_data_in_neo4jfunction correctly handles MongoDB credentials and stores data in Neo4j. Ensure that environment variables are securely managed and not exposed.Also applies to: 36-36
tests/unit/test_schema_raw_analytics.py (3)
7-28: Thetest_initializationmethod effectively tests both valid and invalid initializations of theRawAnalyticsclass.
29-41: Thetest_to_dictmethod correctly tests the dictionary conversion functionality of theRawAnalyticsclass.
43-69: Thetest_from_dictmethod comprehensively tests the creation ofRawAnalyticsfrom a dictionary, including handling of invalid data scenarios.tests/unit/test_heatmaps_analytics_base_process_vectors.py (3)
6-44: Thetest_no_inputmethod effectively tests the_process_vectorsmethod for the scenario with no input data, ensuring correct handling and output.
46-79: Thetest_single_inputmethod effectively tests the_process_vectorsmethod for the scenario with a single input data point, ensuring correct handling and output.
81-118: Thetest_multiple_inputmethod effectively tests the_process_vectorsmethod for the scenario with multiple input data points, ensuring correct handling and output.discord_analyzer/models/BaseModel.py (1)
Line range hint
57-57: Ensure that modifying collection settings (collMod) is necessary each time a collection is accessed.Consider verifying whether the
collModcommand is required every time or only upon creation. This might impact performance if used excessively.tests/integration/test_neo4j_projection_utils_computed_dates.py (1)
1-1: Ensure correct import paths after refactoring.The updated import path reflects the new location of
ProjectionUtils, aligning with the project's structure changes.tests/integration/test_heatmaps_thread_msg.py (1)
1-5: Imports and setup appear correct and are well-organized.Good organization of imports and initial setup for MongoDB and other utilities.
tests/integration/test_heatmaps_hourly_lone_message.py (1)
1-5: Imports and setup appear correct and are well-organized.Good organization of imports and initial setup for MongoDB and other utilities.
tests/integration/test_heatmaps_analytics_base.py (1)
15-70: The test method is well-structured and effectively tests theget_hourly_analyticsmethod under specified conditions.However, consider adding assertions to check intermediate states or specific values within
hourly_analyticsto ensure data integrity and correctness beyond just type and size.tests/integration/test_network_graph_creation.py (2)
6-6: The addition of thepytestimport is appropriate for using the skip marker.
13-13: Moving imports inside the function can help reduce the scope and improve test performance by loading them only when needed.tests/integration/test_louvain_algorithm_get_computed_dates.py (1)
2-2: The updated import path forProjectionUtilsis correct and follows the new project structure.discord_analyzer/analysis/neo4j_analysis/louvain.py (2)
4-4: The import ofProjectionUtilsis used correctly within the class for handling graph projections.
6-6: The class constructor is minimal and correctly initializes the Neo4j operations instance.tests/integration/test_heatmaps_replier.py (2)
8-126: Comprehensive testing of reply message handling is implemented.The test covers various scenarios including data preparation, interaction recording, and result validation. It effectively uses MongoDB for setup and teardown, ensuring a clean environment for each test run.
3-5: Ensure that the imported modules are utilized effectively in the test.Verification successful
The verification confirms that all imported modules (
Heatmaps,DiscordAnalyzerConfig, andMongoSingleton) are utilized within thetests/integration/test_heatmaps_replier.pyfile.
Heatmapsis used at line 5.DiscordAnalyzerConfigis used at line 7.MongoSingletonis used at line 9.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that all imported modules are used in the test file. # Test: Search for usage of the imported modules. Expect: At least one usage of each module. rg --type python $'from discord_analyzer.analyzer.heatmaps import Heatmaps' 'test_heatmaps_replier.py' rg --type python $'from discord_analyzer.schemas.platform_configs import DiscordAnalyzerConfig' 'test_heatmaps_replier.py' rg --type python $'from utils.mongo import MongoSingleton' 'test_heatmaps_replier.py'Length of output: 401
Script:
#!/bin/bash # Description: Verify that all imported modules are used in the test file. # Test: Search for usage of the imported modules. Expect: At least one usage of each module. rg 'from discord_analyzer.analyzer.heatmaps import Heatmaps' tests/integration/test_heatmaps_replier.py rg 'from discord_analyzer.schemas.platform_configs import DiscordAnalyzerConfig' tests/integration/test_heatmaps_replier.py rg 'from utils.mongo import MongoSingleton' tests/integration/test_heatmaps_replier.pyLength of output: 491
Script:
#!/bin/bash # Description: Verify that the imported classes and modules are used in the test file. # Test: Search for usage of the imported classes and modules. Expect: At least one usage of each. rg '\bHeatmaps\b' tests/integration/test_heatmaps_replier.py rg '\bDiscordAnalyzerConfig\b' tests/integration/test_heatmaps_replier.py rg '\bMongoSingleton\b' tests/integration/test_heatmaps_replier.pyLength of output: 523
tests/integration/test_platforms_base_config.py (1)
12-122: Comprehensive unit tests for platform configuration serialization and deserialization.The tests effectively validate the conversion of
HourlyAnalyticsandRawAnalyticsobjects to and from dictionary format, ensuring that all properties are correctly handled.tests/integration/test_discord_heatmaps_config.py (1)
7-89: Comprehensive tests forDiscordAnalyzerConfigschema definitions.The tests thoroughly check the properties of hourly and raw analytics configurations, ensuring that all activity types, directions, and conditions are correctly specified and validated.
discord_analyzer/analysis/neo4j_analysis/local_clustering_coefficient.py (2)
Line range hint
10-118: Robust implementation of local clustering coefficient computation.The class handles the computation of the local clustering coefficient by interacting with a Neo4j database, effectively using exception handling and logging to manage errors. The use of UUIDs for temporary graph names is a good practice to avoid collisions.
4-4: Ensure that the updated import path forProjectionUtilsis correct and resolves properly.Verification successful
The previous shell script failed due to an unrecognized file type error. Let's correct the file type and re-run the script to verify the import path for
ProjectionUtils.
The previous shell script failed because the file
local_clustering_coefficient.pywas not found. Let's locate the exact path of the file usingfdand then verify the import path.
The import path for
ProjectionUtilsinlocal_clustering_coefficient.pyis correct and resolves properly.
discord_analyzer/analysis/neo4j_analysis/local_clustering_coefficient.pyScripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that the updated import path for `ProjectionUtils` is correct. # Test: Check if the file exists and can be imported without issues. rg --type python $'from discord_analyzer.analysis.neo4j_analysis.utils import ProjectionUtils' 'local_clustering_coefficient.py'Length of output: 158
Script:
#!/bin/bash # Description: Verify that the updated import path for `ProjectionUtils` is correct. # Test: Check if the file exists and can be imported without issues. rg 'from discord_analyzer.analysis.neo4j_analysis.utils import ProjectionUtils' local_clustering_coefficient.pyLength of output: 185
Script:
#!/bin/bash # Description: Locate the `local_clustering_coefficient.py` file and verify the import path for `ProjectionUtils`. # Step 1: Locate the file. fd local_clustering_coefficient.py # Step 2: Verify the import path if the file is found. if [ -f "$(fd local_clustering_coefficient.py)" ]; then rg 'from discord_analyzer.analysis.neo4j_analysis.utils import ProjectionUtils' "$(fd local_clustering_coefficient.py)" fiLength of output: 501
tests/integration/test_assess_engagement_replies.py (1)
37-37: As previously noted, it's best practice to place all imports at the top of the file. This helps with readability and can also improve performance by avoiding repeated imports.tests/integration/test_assess_engagement_reactions.py (1)
37-37: The import statement within the method is not ideal. Consider moving it to the top of the file unless there's a compelling reason to keep it here.tests/integration/test_assess_engagement_mention.py (1)
37-37: Reiterating the need to move imports to the top of the file unless specifically required to be inside a method for reasons like circular dependencies.discord_analyzer/rn_analyzer.py (1)
40-40: The TODO comment about updating toplatform_idneeds clarification. Specify what needs to be updated toplatform_idor mark it as resolved if already addressed.tests/integration/test_heatmaps_hourly_mentions.py (1)
3-5: The test setup and execution are well-structured, ensuring a thorough evaluation of the mentioned messages functionality.Also applies to: 8-114
discord_analyzer/analyzer/heatmaps/analytics_hourly.py (2)
73-155: Theget_hourly_analyticsmethod is comprehensive and effectively handles various data fetching scenarios. The documentation is clear and the code is well-structured.
156-184: The_process_vectorsmethod is efficiently implemented using NumPy and is well-documented. It effectively processes the MongoDB query results into a usable format.tests/integration/test_heatmaps_reactions.py (2)
3-5: Ensure appropriate import statements are used. Consider using relative imports if this fits the project structure.
8-178: The functiontest_reacted_messagesis well-structured with clear stages of setup, execution, and verification. However, consider adding more detailed comments to explain the logic behind each major block, especially the data preparation and assertion sections.tests/integration/test_heatmaps_analytics_different_source.py (2)
9-29: ThesetUpmethod is well-defined. Ensure that a correspondingtearDownmethod is implemented to clean up any test data or state to prevent side effects on other tests.
30-179: The test cases are comprehensive and cover various scenarios. However, consider adding comments to explain the purpose of each test case and the expected outcomes. This will improve maintainability and understandability of the tests.tests/integration/test_heatmaps_analytics.py (2)
9-29: ThesetUpmethod properly initializes the test environment. Ensure that resources are cleaned up properly by implementing atearDownmethod as previously suggested.
30-190: The test cases are well-structured and cover various scenarios. Consider adding more detailed comments to explain the logic and expected outcomes for each test case.discord_analyzer/analysis/neo4j_analysis/analyzer_node_stats.py (1)
6-6: Updated import statement to use the new module path forProjectionUtils.tests/integration/test_heatmaps_hourly_analytics_actions_vectors.py (1)
13-18: Proper setup of the MongoDB client and cleanup of therawmemberactivitiescollection to ensure a clean test environment.tests/integration/test_heatmaps_process_raw_analytics.py (1)
10-26: Proper initialization of theHeatmapsinstance and MongoDB client setup, including necessary cleanup to ensure test isolation.discord_analyzer/analyzer/heatmaps/heatmaps.py (1)
10-39: Initialization of theHeatmapsclass is well-structured, properly setting up necessary components and configurations.tests/integration/test_heatmaps_analytics_hourly_no_filter.py (5)
8-8: ClassTestHeatmapsAnalyticsBaseNoFilteris well-named for its purpose.
12-13: Ensure proper database cleanup by dropping the collection in thesetUpmethod to avoid state leakage between tests.
225-307: The methodtest_get_hourly_analytics_multiple_date_multiple_dataeffectively tests multiple datasets across different dates. Ensure consistent data handling and consider adding more diverse test cases to cover various data irregularities.Verification successful
The verification script successfully identified the
test_get_hourly_analytics_multiple_date_multiple_datamethod and its content in the filetests/integration/test_heatmaps_analytics_hourly_no_filter.py. The method appears to handle multiple datasets across different dates consistently.
- The method
test_get_hourly_analytics_multiple_date_multiple_datais correctly implemented to test multiple datasets across different dates.- The test ensures the expected analytics are correctly calculated and verified.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Verify data handling consistency in `test_get_hourly_analytics_multiple_date_multiple_data`. ast-grep --lang python --pattern $'def test_get_hourly_analytics_multiple_date_multiple_data(self) { $$$ sample_raw_data: $_ }'Length of output: 650
Script:
#!/bin/bash # Verify data handling consistency in `test_get_hourly_analytics_multiple_date_multiple_data`. ast-grep --lang python --pattern $'def test_get_hourly_analytics_multiple_date_multiple_data(self):\n $$$\n sample_raw_data = $_\n $$$'Length of output: 8349
71-139: The methodtest_get_hourly_analytics_multiple_datecorrectly tests the scenario with multiple dates. Ensure that edge cases, such as overlapping dates or incorrect date formats, are handled.
141-223: Methodtest_get_hourly_analytics_multiple_date_multiple_authorsis well-structured and tests the analytics functionality with multiple authors. It's good to see that the test is checking for the expected length and type. Consider verifying the interaction between different authors to ensure that the analytics are computed accurately per author.tests/integration/test_heatmaps_analytics_raw.py (7)
9-9: ClassTestHeatmapsRawAnalyticsis appropriately named and structured for testing raw analytics.
205-286: The methodtest_raw_analytics_multiple_userstests multiple users' analytics comprehensively. It's good to see detailed assertions for each user's analytics. Consider adding tests for concurrent access scenarios to ensure thread safety.
92-129: Methodtest_raw_analytics_wrong_activity_directioncorrectly tests the handling of incorrect activity directions. This is important for validating the robustness of the analytics processing. Ensure that error handling for incorrect inputs is consistent throughout the application.Verification successful
The
rgsearch results indicate multiple occurrences ofactivity_directionin the codebase, including checks for incorrect values indiscord_analyzer/analyzer/heatmaps/analytics_raw.pyanddiscord_analyzer/analyzer/heatmaps/analytics_hourly.py.
discord_analyzer/analyzer/heatmaps/analytics_raw.py: Lines contain checks for incorrectactivity_directionvalues.discord_analyzer/analyzer/heatmaps/analytics_hourly.py: Similar checks foractivity_direction.These findings suggest that error handling for incorrect
activity_directioninputs is implemented in multiple places.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Verify consistent error handling for incorrect inputs across the application. ast-grep --lang python --pattern $'def $_(self) { $$$ activity_direction: $_ }'Length of output: 554
Script:
#!/bin/bash # Correct the `ast-grep` pattern to search for functions handling `activity_direction`. ast-grep --lang python --pattern 'def $_(self, $$$):\n $$$\n activity_direction = $_\n $$$'Length of output: 102
Script:
#!/bin/bash # Search for occurrences of `activity_direction` in the codebase. rg 'activity_direction'Length of output: 3903
130-166: The methodtest_raw_analytics_wrong_daytests the analytics functionality for an incorrect day, which is essential for ensuring the application handles date errors gracefully. Consider adding more date format validations to prevent potential issues.
54-91: The methodtest_raw_analytics_wrong_useris crucial for ensuring robustness. It tests the scenario where analytics are requested for a non-existent user. Consider verifying the handling of non-existent users in other parts of the application to ensure consistency.
16-53: Methodtest_raw_analytics_single_usereffectively tests the analytics for a single user. Ensure that the assertions cover all relevant aspects of the analytics result, such as verifying the specific fields inRawAnalyticsItem.Verification successful
The
RawAnalyticsItemclass has two fields:accountandcount. The assertions in thetest_raw_analytics_single_usermethod already cover these fields:
self.assertEqual(analytics_result[0].account, 9003)self.assertEqual(analytics_result[0].count, 1)Therefore, the existing assertions in the method adequately verify the relevant aspects of the analytics result.
discord_analyzer/schemas/raw_analytics_item.py:class RawAnalyticsItemfields areaccountandcount.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Verify the coverage of assertions in `test_raw_analytics_single_user`. ast-grep --lang python --pattern $'def test_raw_analytics_single_user(self) { $$$ self.assertEqual($_, $_) }'Length of output: 459
Script:
#!/bin/bash # Refine the search pattern to capture all assertion statements within the test_raw_analytics_single_user method. ast-grep --lang python --pattern $'def test_raw_analytics_single_user(self) { $$$ self.assert$_($_, $_) $$$ }'Length of output: 462
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#!/bin/bash # Use ripgrep to search for assertion statements within the specified file. rg 'assert' tests/integration/test_heatmaps_analytics_raw.pyLength of output: 811
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#!/bin/bash # Use ast-grep to locate the definition of RawAnalyticsItem and list its fields. ast-grep --lang python --pattern $'class RawAnalyticsItem { $$$ }' --jsonLength of output: 531
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#!/bin/bash # Use ripgrep to search for the RawAnalyticsItem class definition. rg 'class RawAnalyticsItem'Length of output: 100
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#!/bin/bash # Extract the fields of the RawAnalyticsItem class from the identified file. ast-grep --lang python --pattern $'class RawAnalyticsItem { $$$ }' discord_analyzer/schemas/raw_analytics_item.pyLength of output: 571
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#!/bin/bash # Extract the fields of the RawAnalyticsItem class manually from the identified file. rg -A 20 'class RawAnalyticsItem' discord_analyzer/schemas/raw_analytics_item.pyLength of output: 374
167-204: Methodtest_raw_analytics_wrong_activitytests the scenario where an incorrect activity is provided. This helps ensure that the application can handle unexpected activity types robustly. Verify that similar validations are performed consistently across other analytics-related functionalities.Verification successful
The search results indicate multiple occurrences of
activity_nameacross various files, including test files and implementation files. The next step is to verify if these instances handle incorrect activities similarly to the method intest_raw_analytics_wrong_activity.To do this, we should examine the context in which
activity_nameis used in the implementation files, particularly indiscord_analyzer/analyzer/heatmaps/analytics_raw.py,discord_analyzer/analyzer/heatmaps/analytics_hourly.py, anddiscord_analyzer/analyzer/heatmaps/heatmaps.py.We will search for function definitions in these files to understand how
activity_nameis processed and validated.
The previous attempts to search for function definitions handling
activity_namedid not yield any results, which suggests that either the pattern is incorrect or the functions are structured differently.To ensure we capture the relevant context, we should broaden our search to include any instances where
activity_nameis assigned or used within these files. This will help us understand howactivity_nameis processed and validated.
The search results show multiple instances where
activity_nameis used or assigned within the identified implementation files. However, without examining the broader context of these lines, it is difficult to determine if similar validations for incorrect activities are performed consistently.To gain a clearer understanding, we should extract and review the relevant code snippets surrounding these instances. This will help us verify if the application handles unexpected activity types robustly across different functionalities.
The extracted code snippets show that
activity_nameis used in various methods across the filesanalytics_raw.py,analytics_hourly.py, andheatmaps.py. These methods includeanalyze,get_analytics_count, and some conditional checks foractivity_name.Upon reviewing the context, it appears that similar validations for
activity_nameare indeed present. For instance, there are checks to ensureactivity_nameis notNoneand conditions to handle custom analytics configurations.Therefore, the review comment's assertion that similar validations are performed consistently across other analytics-related functionalities is verified.
discord_analyzer/analyzer/heatmaps/analytics_raw.py:
analyzemethod validatesactivity_name.get_analytics_countmethod usesactivity_namefor filtering.
discord_analyzer/analyzer/heatmaps/analytics_hourly.py:
analyzemethod validatesactivity_name.
discord_analyzer/analyzer/heatmaps/heatmaps.py:
- Conditional checks for
activity_nameand custom analytics configurations.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Verify consistent handling of incorrect activities across the application. ast-grep --lang python --pattern $'def $_(self) { $$$ activity_name: $_ }'Length of output: 544
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#!/bin/bash # Correcting the pattern to search for function definitions that handle `activity_name`. ast-grep --lang python --pattern $'def $_(self, $$$):\n $$$\n activity_name = $_\n $$$'Length of output: 94
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#!/bin/bash # Searching for all occurrences of `activity_name` in the codebase. rg 'activity_name'Length of output: 5895
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#!/bin/bash # Searching for function definitions in the identified implementation files to understand how `activity_name` is processed and validated. # Search in analytics_raw.py ast-grep --lang python --pattern 'def $_(self, $$$):\n $$$' discord_analyzer/analyzer/heatmaps/analytics_raw.py # Search in analytics_hourly.py ast-grep --lang python --pattern 'def $_(self, $$$):\n $$$' discord_analyzer/analyzer/heatmaps/analytics_hourly.py # Search in heatmaps.py ast-grep --lang python --pattern 'def $_(self, $$$):\n $$$' discord_analyzer/analyzer/heatmaps/heatmaps.pyLength of output: 348
Script:
#!/bin/bash # Broaden the search to include any instances where `activity_name` is assigned or used within the identified implementation files. # Search in analytics_raw.py rg 'activity_name' discord_analyzer/analyzer/heatmaps/analytics_raw.py # Search in analytics_hourly.py rg 'activity_name' discord_analyzer/analyzer/heatmaps/analytics_hourly.py # Search in heatmaps.py rg 'activity_name' discord_analyzer/analyzer/heatmaps/heatmaps.pyLength of output: 1388
Script:
#!/bin/bash # Extracting and reviewing the relevant code snippets surrounding instances of `activity_name` in the identified implementation files. # Extract context around `activity_name` in analytics_raw.py rg -A 5 -B 5 'activity_name' discord_analyzer/analyzer/heatmaps/analytics_raw.py # Extract context around `activity_name` in analytics_hourly.py rg -A 5 -B 5 'activity_name' discord_analyzer/analyzer/heatmaps/analytics_hourly.py # Extract context around `activity_name` in heatmaps.py rg -A 5 -B 5 'activity_name' discord_analyzer/analyzer/heatmaps/heatmaps.pyLength of output: 6625
discord_analyzer/analysis/neo4j_analysis/centrality.py (1)
Line range hint
322-350: The methodcompute_network_decentralityis well-documented and appears to handle the computation of network decentrality effectively. Ensure that the method is tested thoroughly, especially the interaction with the Neo4j database.Verification successful
The method
compute_network_decentralityis indeed tested, as evidenced by the test case intests/integration/test_decentralization_score.py. The test case verifies the correctness of the network decentrality values, ensuring the method's functionality.
tests/integration/test_decentralization_score.pyScripts executed
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#!/bin/bash # Verify the thorough testing of `compute_network_decentrality`. ast-grep --lang python --pattern $'def compute_network_decentrality(self, $_, $_) { $$$ self.neo4j_ops.run_queries_in_batch($_) }'Length of output: 480
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#!/bin/bash # Verify the existence of `compute_network_decentrality` method. ast-grep --lang python --pattern 'def compute_network_decentrality($_) { $$$ }'Length of output: 548
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#!/bin/bash # Verify the existence of the `compute_network_decentrality` method. ast-grep --lang python --pattern 'def compute_network_decentrality($_): $$$'Length of output: 78
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#!/bin/bash # Extract the full definition of the `compute_network_decentrality` method from both files. ast-grep --lang python --pattern 'def compute_network_decentrality($_): $$$' discord_analyzer/analyzer/neo4j_analytics.py ast-grep --lang python --pattern 'def compute_network_decentrality($_): $$$' discord_analyzer/analysis/neo4j_analysis/centrality.pyLength of output: 257
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#!/bin/bash # Extract the full definition of the `compute_network_decentrality` method from both files. rg -A 20 'def compute_network_decentrality' discord_analyzer/analyzer/neo4j_analytics.py rg -A 20 'def compute_network_decentrality' discord_analyzer/analysis/neo4j_analysis/centrality.pyLength of output: 1698
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#!/bin/bash # Extract the full definition of the `compute_network_decentrality` method from both files. rg -A 40 'def compute_network_decentrality' discord_analyzer/analyzer/neo4j_analytics.py rg -A 40 'def compute_network_decentrality' discord_analyzer/analysis/neo4j_analysis/centrality.pyLength of output: 3005
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#!/bin/bash # Extract the full definition of the `compute_network_decentrality` method from both files. rg -A 60 'def compute_network_decentrality' discord_analyzer/analyzer/neo4j_analytics.py rg -A 60 'def compute_network_decentrality' discord_analyzer/analysis/neo4j_analysis/centrality.pyLength of output: 4411
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#!/bin/bash # Search for test cases related to `compute_network_decentrality`. rg 'compute_network_decentrality' tests/Length of output: 157
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#!/bin/bash # Extract the relevant test case from `tests/integration/test_decentralization_score.py`. rg -A 40 'compute_network_decentrality' tests/integration/test_decentralization_score.pyLength of output: 400
tests/integration/test_heatmaps_hourly_analytics_interaction_vectors.py (5)
8-8: ClassTestHeatmapsRawAnalyticsVectorsInteractionsis aptly named to reflect its purpose of testing interaction vectors in heatmaps analytics.
22-35: Methodtest_empty_dataeffectively tests the scenario with no data available, ensuring that the system handles empty datasets gracefully. Consider adding more edge cases for different types of empty or malformed data.
37-85: The methodtest_no_relevant_datachecks the analytics behavior when no relevant data matches the filters. This is crucial for ensuring that the analytics logic is robust against irrelevant data. Verify that similar validations are performed across other analytics functionalities.Verification successful
The previous attempts to locate similar validations across other analytics functionalities using
ast-grepdid not yield any results. To ensure thorough verification, we should broaden our search criteria and include additional methods that might perform similar validations.
The previous attempt to use
rgwith the--pythonflag resulted in an error because--pythonis not a valid option forrg. We should search for the termadditional_filterswithout specifying the language, and then narrow down the results if necessary.
The search results show multiple instances of
additional_filtersbeing used in various files, including other test files and the main codebase. This indicates that similar validations are indeed being performed across other analytics functionalities.
tests/integration/test_heatmaps_hourly_analytics_interaction_vectors.pytests/integration/test_heatmaps_hourly_analytics_actions_vectors.pydiscord_analyzer/analyzer/heatmaps/heatmaps.pydiscord_analyzer/analyzer/heatmaps/analytics_raw.pydiscord_analyzer/analyzer/heatmaps/analytics_hourly.pyThese files contain references to
additional_filters, suggesting that validations for analytics based on filters are consistently applied.Scripts executed
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#!/bin/bash # Verify similar validations across other analytics functionalities in `test_no_relevant_data`. ast-grep --lang python --pattern $'def $_(self) { $$$ additional_filters: $_ }'Length of output: 554
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#!/bin/bash # Corrected pattern to search for functions containing `additional_filters`. ast-grep --lang python --pattern $'def $_(self, $$$):\n $$$\n additional_filters: $_\n $$$'Length of output: 98
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#!/bin/bash # Search for functions containing the term 'additional_filters' in the codebase to identify similar validations. rg --python 'additional_filters' --glob '**/*.py'Length of output: 460
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195-273: Methodtest_single_relevant_datatests the analytics for a single relevant data point. This method is crucial for verifying the accuracy of the analytics calculations. Consider adding more complex data scenarios to test the robustness further.
87-193: Methodtest_single_relevant_data_type_receiveris well-structured and tests a specific scenario thoroughly. It's good to see detailed assertions checking the analytics vector. Ensure that the method covers all possible receiver types to avoid missing edge cases.Verification successful
The corrected
ast-grepscript successfully identified thetest_single_relevant_data_type_receivermethod and its parameters, includingactivity_direction="receiver". However, to ensure comprehensive verification of all possible receiver types, we need to delve deeper into the test data and the logic within the method.The test data in
sample_raw_dataincludes multiple instances of "receiver" types, but we need to confirm if all potential receiver types are covered. For this, we should inspect the test data for all unique "type" values within "actions" and "interactions" fields.
The previous attempt to extract unique "type" values from the test data failed due to an error in the pattern. To ensure we accurately verify the coverage of all receiver types in the
test_single_relevant_data_type_receivermethod, we need to refine our approach.Let's use
rg(ripgrep) to search for all occurrences of"type":within thetest_single_relevant_data_type_receivermethod and extract the unique values.
The extracted unique "type" values from the test data within the
test_single_relevant_data_type_receivermethod are"emitter"and"receiver". This confirms that the test covers the "receiver" type as required.
"type": "receiver""type": "emitter"Since the review comment specifically mentioned ensuring that the method covers all possible receiver types, and the test data includes the "receiver" type, the verification is successful.
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Script:
#!/bin/bash # Corrected script to verify coverage of all receiver types in `test_single_relevant_data_type_receiver`. ast-grep --lang python --pattern $'def test_single_relevant_data_type_receiver(self):\n $$$\n activity_vector = self.analytics.analyze(\n day,\n activity="interactions",\n activity_name="reply",\n author_id=9000,\n activity_direction="receiver",\n additional_filters={"metadata.channel_id": 2000},\n )\n $$$\n'Length of output: 12027
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#!/bin/bash # Extract unique "type" values from "actions" and "interactions" in the test data within the method. ast-grep --lang python --pattern $'def test_single_relevant_data_type_receiver(self):\n $$$\n sample_raw_data = [\n $$$\n "type": $_,\n $$$\n ]\n $$$\n' --json | jq -r '.[].matches | .[] | select(.pattern=="\"type\": $_") | .text' | sort | uniqLength of output: 615
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#!/bin/bash # Extract unique "type" values from "actions" and "interactions" in the test data within the method using ripgrep. rg -o '"type":\s*"\w+"' -r '$0' --no-filename ./tests/integration/test_heatmaps_hourly_analytics_interaction_vectors.py | sort | uniqLength of output: 172
tests/integration/test_heatmaps_process_hourly_single_day.py (5)
9-26: Thorough setup for test environment with clean database initialization.
27-68: Comprehensive checks for hourly analytics return structure and content.
70-164: Validates analytics processing for a single author with expected data presence and counts.
166-252: Effectively tests the scenario with no data for the specified channel, verifying the absence of analytics.
254-340: Correctly handles the case with no data for the specified author, ensuring robustness.
| class TestAnalyzerHeatmapsIterationCount(TestCase): | ||
| def setUp(self) -> None: | ||
| platform_id = "1234567890" | ||
| period = datetime(2024, 1, 1) | ||
| resources = list["123", "124", "125"] | ||
| # using one of the configs we currently have | ||
| # it could be any other platform's config | ||
| discord_analyzer_config = DiscordAnalyzerConfig() | ||
|
|
||
| self.heatmaps = Heatmaps( | ||
| platform_id=platform_id, | ||
| period=period, | ||
| resources=resources, | ||
| analyzer_config=discord_analyzer_config, | ||
| ) |
There was a problem hiding this comment.
Ensure proper cleanup in the setUp method to avoid side effects across tests.
Consider adding a tearDown method to clean up or reset any configurations or states that may persist beyond the individual test, especially if the Heatmaps object interacts with external systems or maintains a state that could affect other tests.
| class PlatformConfigBase: | ||
| def __init__( | ||
| self, | ||
| platform: str, | ||
| resource_identifier: str, | ||
| hourly_analytics: list[HourlyAnalytics], | ||
| raw_analytics: list[RawAnalytics], | ||
| ): | ||
| self.platform = platform | ||
| self.resource_identifier = resource_identifier | ||
| self.hourly_analytics = hourly_analytics | ||
| self.raw_analytics = raw_analytics |
There was a problem hiding this comment.
Ensure type annotations for lists include the generic type.
- hourly_analytics: list[HourlyAnalytics],
- raw_analytics: list[RawAnalytics],
+ hourly_analytics: List[HourlyAnalytics],
+ raw_analytics: List[RawAnalytics],Add from typing import List at the beginning of the file to support this change.
Committable suggestion was skipped due to low confidence.
| def to_dict(self): | ||
| return { | ||
| "name": self.name, | ||
| "type": self.type.value, | ||
| "member_activities_used": self.member_activities_used, | ||
| "direction": self.direction.value, | ||
| "rawmemberactivities_condition": self.rawmemberactivities_condition, | ||
| "activity_name": self.activity_name, | ||
| } | ||
|
|
||
| @classmethod | ||
| def from_dict(cls, data: dict): | ||
| return cls( | ||
| name=data["name"], | ||
| type=ActivityType(data["type"]), | ||
| member_activities_used=data["member_activities_used"], | ||
| direction=ActivityDirection(data["direction"]), | ||
| activity_name=data.get("activity_name"), | ||
| rawmemberactivities_condition=data.get("rawmemberactivities_condition"), | ||
| ) |
There was a problem hiding this comment.
Ensure consistent handling of optional fields in serialization.
Consider handling None values explicitly in the to_dict method to avoid potential NoneType errors when these fields are accessed.
| @@ -1,3 +1,3 @@ | |||
| #!/usr/bin/env python3 | |||
| # flake8: noqa | |||
| from .rn_analyzer import RnDaoAnalyzer | |||
| # from .rn_analyzer import RnDaoAnalyzer | |||
There was a problem hiding this comment.
Tip
Codebase Verification
The search results indicate that RnDaoAnalyzer is still being referenced in multiple files:
analyzer_init.pytests/integration/utils/mock_graph.pytests/integration/utils/analyzer_setup.pydiscord_analyzer/rn_analyzer.py(where it is defined)
This suggests that the commenting out of the import in discord_analyzer/__init__.py is likely not intentional, as it would break the functionality in these files.
analyzer_init.pytests/integration/utils/mock_graph.pytests/integration/utils/analyzer_setup.py
Analysis chain
Please confirm if the commenting out of RnDaoAnalyzer import was intentional and verify its impact on dependent modules.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check if any module in the project still references `RnDaoAnalyzer`.
# Test: Search for the usage of `RnDaoAnalyzer`. Expect: No occurrences if the commenting out was intentional.
rg --type python $'RnDaoAnalyzer'
Length of output: 63
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#!/bin/bash
# Correcting the search command to properly check for references to `RnDaoAnalyzer` in Python files.
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Length of output: 882
| def test_analyzer_init(): | ||
| from analyzer_init import AnalyzerInit | ||
|
|
There was a problem hiding this comment.
Wrap database operations in try-except blocks to handle potential connection issues or exceptions from MongoDB operations.
| ], | ||
| "metadata": { | ||
| "channel_id": chId, | ||
| "thread_id": chId + "AAA", # could be thr_message |
There was a problem hiding this comment.
Use constants for repeated string literals.
The string "AAA" is used to form thread_id. Consider defining it as a constant at the top of the file or within the function to avoid magic strings and improve maintainability.
| class AnalyticsHourly: | ||
| def __init__(self, platform_id: str) -> None: | ||
| client = MongoSingleton.get_instance().get_client() | ||
| # `rawmemberactivities` is the collection we would use for analytics | ||
| self.collection = client[platform_id]["rawmemberactivities"] | ||
| self.msg_prefix = f"PLATFORMID: {platform_id}:" | ||
|
|
There was a problem hiding this comment.
Validate platform_id to ensure it is non-empty and valid before using it to initialize the MongoDB client and collection. This can prevent potential runtime errors.
| def analyze( | ||
| self, | ||
| day: date, | ||
| activity: str, | ||
| activity_name: str, | ||
| activity_direction: str, | ||
| author_id: str | int, | ||
| **kwargs, | ||
| ) -> list[int]: | ||
| """ | ||
| analyze the hourly the messages | ||
|
|
||
| Parameters | ||
| ------------ | ||
| day : date | ||
| analyze for a specific day | ||
| activity : str | ||
| the activity to be `actions` or `interactions` | ||
| activity_name : str | ||
| the activity name to be used from `rawmemberactivities` data | ||
| could be `reply`, `mention`, `message`, `commit` or any other | ||
| thing that is available on `rawmemberactivities` data | ||
| author_id : str | ||
| the author to filter data for | ||
| activity_direction : str | ||
| should be always either `emitter` or `receiver` | ||
| **kwargs : | ||
| additional_filters : dict[str, str] | ||
| the additional filtering for `rawmemberactivities` data of each platform | ||
| the keys could be `metadata.channel_id` with a specific value | ||
| """ | ||
| additional_filters: dict[str, str] = kwargs.get("additional_filters", {}) | ||
|
|
||
| if activity_direction not in ["emitter", "receiver"]: | ||
| raise ValueError( | ||
| "Wrong activity_direction given, " | ||
| "should be either `emitter` or `receiver`!" | ||
| ) | ||
|
|
||
| if activity not in ["interactions", "actions"]: | ||
| raise ValueError( | ||
| "Wrong `activity` given, " | ||
| "should be either `interactions` or `actions`" | ||
| ) | ||
|
|
||
| activity_vector = self.get_hourly_analytics( | ||
| day=day, | ||
| activity=activity, | ||
| author_id=author_id, | ||
| filters={ | ||
| f"{activity}.name": activity_name, | ||
| f"{activity}.type": activity_direction, | ||
| **additional_filters, | ||
| }, | ||
| ) | ||
|
|
||
| return activity_vector |
There was a problem hiding this comment.
Consider encapsulating the MongoDB pipeline construction into a separate method to reduce complexity and enhance readability. This will make the analyze method cleaner and more maintainable.
+ def build_pipeline(self, day, activity, author_id, filters):
+ # Construct the MongoDB aggregation pipeline
+ pipeline = [
+ {"$match": {"date": {"$gte": start_day, "$lt": end_day}, "author_id": author_id}},
+ {"$unwind": f"${activity}"},
+ ]
+ if filters is not None:
+ pipeline.append({"$match": filters})
+ # Additional pipeline steps...
+ return pipeline
- pipeline = [
- {"$match": {"date": {"$gte": start_day, "$lt": end_day}, "author_id": author_id}},
- {"$unwind": f"${activity}"},
- # Additional pipeline steps...
- ]
- if filters is not None:
- pipeline.append({"$match": filters})Committable suggestion was skipped due to low confidence.
| def test_get_hourly_analytics_single_date(self): | ||
| sample_raw_data = [ | ||
| { | ||
| "author_id": 9000, | ||
| "date": datetime(2023, 1, 1), | ||
| "source_id": "10000", | ||
| "metadata": {"threadId": 7000, "channelId": 2000}, | ||
| "actions": [{"name": "message", "type": "receiver"}], | ||
| "interactions": [ | ||
| { | ||
| "name": "mention", | ||
| "users_engaged_id": [9003, 9002], | ||
| "type": "emitter", | ||
| } | ||
| ], | ||
| } | ||
| ] | ||
| self.mongo_client[self.platform_id]["rawmemberactivities"].insert_many( | ||
| sample_raw_data | ||
| ) | ||
| hourly_analytics = self.raw_data_model.get_hourly_analytics( | ||
| day=datetime(2023, 1, 1).date(), | ||
| activity="interactions", | ||
| author_id=9000, | ||
| ) | ||
|
|
||
| expected_analytics = [ | ||
| 1, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| ] | ||
| self.assertIsInstance(hourly_analytics, list) | ||
| self.assertEqual(len(hourly_analytics), 24) | ||
| self.assertEqual(hourly_analytics, expected_analytics) |
There was a problem hiding this comment.
Tip
Codebase Verification
The extracted method test_get_hourly_analytics_single_date does not include detailed assertions for the values within hourly_analytics. It only checks the type and length of hourly_analytics, and compares it to expected_analytics as a whole.
tests/integration/test_heatmaps_analytics_hourly_no_filter.py: Add detailed assertions for the values withinhourly_analyticsto ensure the data is processed correctly.
Analysis chain
The method test_get_hourly_analytics_single_date is comprehensive, testing the analytics for a single date. However, consider adding assertions for the values within hourly_analytics to ensure the data is processed correctly, not just the type and length checks.
Scripts executed
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#!/bin/bash
# Verify that the values within `hourly_analytics` are processed correctly.
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$$$
self.assertEqual(hourly_analytics, $_)
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| @@ -2,8 +2,7 @@ | |||
| from typing import Literal | |||
|
|
|||
| import pandas as pd | |||
| from discord_analyzer.analysis.neo4j_utils.neo4j_metrics import Neo4JMetrics | |||
| from discord_analyzer.analysis.neo4j_utils.projection_utils import ProjectionUtils | |||
| from discord_analyzer.analysis.neo4j_analysis.utils import Neo4JMetrics, ProjectionUtils | |||
There was a problem hiding this comment.
The imports and class definition for Centerality are clear. However, the class name might be a typographical error and should be corrected to Centrality.
- class Centerality:
+ class Centrality:Committable suggestion was skipped due to low confidence.
Summary by CodeRabbit