feature: 单元格补全策略调整

README.md

@@ -23,7 +23,7 @@ decision_table = {
         "rows": [ # 行对应的值
             ["[0..70]", '"boy"'],
             ["(70..80]", '"boy"'],
-            ["(80..90]", '"boy"'],  # 对于实际场景中，如果希望一行表示多列表达式，则直接用字符串类型进行描述，形如 'score in (80..90] and sex="boy"'
+            ["(80..90]", '"boy"'],  # 对于实际场景中，如果希望【单行表示多列表达式】，则直接用字符串类型进行描述，形如 'score in (80..90] and sex="boy"'
             ["(90..100]", '"boy"'],
             ["[0..60]", '"girl"'],
             ["(60..70]", '"girl"'],
@@ -47,6 +47,26 @@ decision_table = {
 }
 ```
 
+其中，输入表默认会将单元格中的表达式作为整体表达式进行真值判定，同时支持一些快捷填写方式（仅在未使用【单行表示多列表达式】的情况下)：
+
+| 快捷填写方式 | 补全后表达式（假设列名为 x） | 
+| --- | --- |
+| ">=10" | "x>=10" |
+| ">10" | "x>10" |
+| "<=10" | "x<=10" |
+| "<10" | "x<10" |
+| "[1..2]" | "x in [1..2]" |
+| "(1..2]" | "x in (1..2]" |
+| '"boy"' | 'x="boy"' |
+| "1" | "x=1" |
+| "1.2" | "x=1.2" |
+| "-1" | "x=-1" |
+| "-2.3" | "x=-2.3" |
+| "true" | "x=true" |
+| "false" | "x=false" |
+| "null" | "x=null" |
+
+
 ### 3. 调用函数进行决策
 
 ``` python

bkflow_dmn/__version__.py

@@ -1,3 +1,3 @@
 # -*- coding: utf-8 -*-
 
-__version__ = "0.1.1"
+__version__ = "0.2.0"

bkflow_dmn/data_model.py

@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+import re
 from enum import Enum
 from typing import List, Union
 
@@ -94,31 +95,52 @@ def hit_policy_value(self):
     @property
     def feel_exp_of_inputs(self):
         col_ids = [col.id for col in self.inputs.cols]
-        operator_prefix = {
-            ">": "",
-            "<": "",
-            "[": " in ",
-            "(": " in ",
-        }
-        or_operator = ","
-
         result = []
         for row in self.inputs.rows:
             if isinstance(row, str):
                 result.append([row])
                 continue
-            row_exps = []
+            row_result = []
             for idx, unit in enumerate(row):
                 pured_unit = unit.strip()
                 if pured_unit == "":
                     continue
-                unit_exps = []
-                vals = [val.strip() for val in pured_unit.split(or_operator) if val.strip()]
-                for val in vals:
-                    if val[0] in operator_prefix:
-                        unit_exps.append(f"{col_ids[idx]}{operator_prefix[val[0]]}{val}")
-                    else:
-                        unit_exps.append(f"{col_ids[idx]}={val}")
-                row_exps.append(f'({" or ".join(unit_exps)})' if len(unit_exps) > 1 else unit_exps[0])
-            result.append(row_exps)
+                handler = TableUnitHandler(unit_exp=pured_unit, col_id=col_ids[idx])
+                row_result.append(handler.get_handled_exp())
+            result.append(row_result)
         return result
+
+
+class TableUnitHandler:
+    OPERATOR_PATTERNS = {
+        r"^>(.*?)": "",
+        r"^<(.*?)": "",
+        r"[\[\(](.*?)\.\.(.*?)[\]\)]": " in ",
+        r"\"(.*?)\"": "=",
+        r"-?\d+(\.\d+)?": "=",
+        r"true": "=",
+        r"false": "=",
+        r"null": "=",
+    }
+    OR_OPERATOR = ","
+
+    def __init__(self, unit_exp: str, col_id: str):
+        self.exp = unit_exp
+        self.col_id = col_id
+
+    def get_handled_exp(self):
+        exp_splices = [exp.strip() for exp in self.exp.split(self.OR_OPERATOR)]
+        union_patterns = "|".join(self.OPERATOR_PATTERNS.keys())
+
+        # 不能进行自动补全的情况
+        if any([re.fullmatch(union_patterns, exp) is None for exp in exp_splices]):
+            return self.exp
+
+        handled_exp_splices = []
+        for exp in exp_splices:
+            for pattern, operator in self.OPERATOR_PATTERNS.items():
+                if re.fullmatch(pattern, exp):
+                    handled_exp_splices.append(f"{self.col_id}{operator}{exp}")
+                    break
+
+        return " or ".join(handled_exp_splices)

release.md

@@ -1,5 +1,8 @@
 # Release Notes
 
+# 0.2.0
+    - 单元格补全策略调整
+
 # 0.1.1
     - 规则配置支持单行跨列规则
 

tests/data.py

@@ -30,7 +30,6 @@
     },
 }
 
-
 UNIQUE_SCORE_MULTI_ROW_FORMAT_TEST_TABLE = {
     "title": "testing",
     "hit_policy": "Unique",
@@ -62,7 +61,6 @@
     },
 }
 
-
 UNIQUE_TEST_DATA = [
     (UNIQUE_SCORE_TEST_TABLE, {"score": 10, "sex": "boy"}, [{"level": "bad"}]),
     (UNIQUE_SCORE_TEST_TABLE, {"score": 80, "sex": "boy"}, [{"level": "good"}]),
@@ -78,7 +76,6 @@
     (UNIQUE_SCORE_MULTI_ROW_FORMAT_TEST_TABLE, {"score": 84, "sex": "girl"}, [{"level": "good++"}]),
 ]
 
-
 ANY_SCORE_TEST_TABLE = {
     "title": "testing",
     "hit_policy": "Any",

tests/test_single_table_decision.py

@@ -2,6 +2,7 @@
 import pytest
 
 from bkflow_dmn.api import decide_single_table
+from bkflow_dmn.data_model import SingleDecisionTable
 from tests.data import (
     UNIQUE_TEST_DATA,
     ANY_TEST_DATA,
@@ -34,6 +35,63 @@ def test_single_table_decision_strict_mode(single_table, facts, expected):
     assert result == expected
 
 
+def test_single_table_inputs_autocomplete():
+    rows = [
+        [">=10"],
+        [">10"],
+        ["[1..2]"],
+        ["(1..2]"],
+        ["<=10"],
+        ["<10"],
+        ['"boy"'],
+        ["1"],
+        ["-1"],
+        ["1.2"],
+        ["-2.3"],
+        ["true"],
+        ["false"],
+        ["null"],
+        ["1 and 1"],
+        ["before(x, [2..3])"],
+        ["< 10, > 20"],
+        ["<10, >20"],
+    ]
+    TEST_TABLE = {
+        "title": "testing",
+        "hit_policy": "Unique",
+        "inputs": {
+            "cols": [{"id": "input"}],
+            "rows": rows,
+        },
+        "outputs": {
+            "cols": [{"id": "output"}],
+            "rows": [[1]] * len(rows),
+        },
+    }
+    table = SingleDecisionTable(**TEST_TABLE)
+    auto_completed_inputs = table.feel_exp_of_inputs
+    assert auto_completed_inputs == [
+        ["input>=10"],
+        ["input>10"],
+        ["input in [1..2]"],
+        ["input in (1..2]"],
+        ["input<=10"],
+        ["input<10"],
+        ['input="boy"'],
+        ["input=1"],
+        ["input=-1"],
+        ["input=1.2"],
+        ["input=-2.3"],
+        ["input=true"],
+        ["input=false"],
+        ["input=null"],
+        ["1 and 1"],
+        ["before(x, [2..3])"],
+        ["input< 10 or input> 20"],
+        ["input<10 or input>20"],
+    ]
+
+
 @pytest.mark.parametrize(
     "single_table, facts, expected",
     test_data,