Added representation and validation tests

test/unit/class_check/test_representation.py

@@ -0,0 +1,37 @@
+from cuallee import Check, CheckLevel
+
+def test_representation():
+    check = Check(CheckLevel.WARNING, "Repr")
+    out = repr(check)
+    assert "Check(level:0"
+
+def test_numeric_level():
+    check = Check(1, "Repr")
+    out = repr(check)
+    assert "Check(level:CheckLevel.ERROR" in out
+
+def test_with_table():
+    check = Check(0, "Repr", table_name="users")
+    out = repr(check)
+    assert ("Check(level:CheckLevel.WARNING" in out) & ("table:users" in out)
+
+def test_sum():
+    check = Check(0, "Sum")
+    check.is_complete("id")
+    check.is_unique("id")
+    assert check.sum == 2
+
+def test_keys():
+    check1 = Check(0, "Sum")
+    check1.is_complete("id")
+    check1.is_unique("id")
+    check2 = Check(0, "Sum")
+    check2.is_complete("id")
+    check2.is_unique("id")
+    assert set(check1.keys) == set(check2.keys)
+
+def test_adjust_coverage():
+    check = Check(0, "Sum")
+    check.is_complete("id", pct=0.8)
+    check.adjust_rule_coverage(0, 0.9)
+    assert check.rules[0].coverage == 0.9

test/unit/class_rule/test_rule_update_functions.py

@@ -1,8 +1,6 @@
 import pyspark.sql.functions as F
-
 from cuallee import Check, CheckLevel
 
-
 def test_add_rule():
     c = Check(CheckLevel.WARNING, "test_add_rule").is_complete("id")
     assert len(c._rule) == 1
@@ -104,3 +102,4 @@ def test_delete_rule_by_coverage(spark):
 
     c.delete_rule_by_attribute("coverage", 1.0)
     assert len(c._rule) == 0
+

test/unit/class_rule/test_rule_validations.py

@@ -0,0 +1,13 @@
+import pytest
+from cuallee import Rule, CheckDataType
+
+def test_negative_coverage():
+     with pytest.raises(
+        ValueError, match="Coverage should be between 0 and 1"
+    ):
+        Rule("is_unique", "id", None, CheckDataType.NUMERIC, -1)
+
+def test_representation():
+    rule = Rule("is_unique", "id", None, CheckDataType.NUMERIC)
+    out = str(repr(rule))
+    assert "Rule(method:is_unique" in out

test/unit/pyspark_dataframe/test_are_unique.py

@@ -14,7 +14,7 @@ def test_positive(spark):
 def test_is_composite_key(spark):
     df = spark.range(10).withColumn("id2", F.col("id") + 10)
     check = Check(CheckLevel.WARNING, "pytest")
-    check.are_unique(("id", "id2"))
+    check.is_composite_key(("id", "id2"))
     rs = check.validate(df)
     assert rs.first().status == "PASS"