Constraint list support

Author: Calvin Wang

pydeequ/checks.py

@@ -98,16 +98,20 @@ def __init__(self, spark_session: SparkSession, level: CheckLevel, description:
                                              getattr(self._check_java_class, 'apply$default$3')()
                                              )
         self.constraints = constraints if constraints else []
-        for constraint in self.constraints:
-            self.addConstraint(constraint)
+
+    def addConstraints(self, constraints: list):
+        self.constraints.extend(constraints)
+        for constraint in constraints:
+            self._Check = constraint._Check
 
     def addConstraint(self, constraint):
         """
         Returns a new Check object with the given constraints added to the constraints list.
         :param Constraint constraint: new constraint to be added.
         :return: new Check object
         """
-        raise NotImplementedError("Private factory method for other check methods")
+        self.constraints.append(constraint)
+        self._Check = constraint._Check
 
     def addFilterableContstraint(self, creationFunc):
         """ Adds a constraint that can subsequently be replaced with a filtered version

tests/test_checks.py

@@ -31,6 +31,28 @@ def tearDownClass(cls):
         cls.spark.sparkContext._gateway.shutdown_callback_server()
         cls.spark.stop()
 
+    def testCheckConstraints(self):
+        check = Check(self.spark, CheckLevel.Warning, "test list constraints")
+        check.addConstraints([check.isComplete('c'),
+                            check.isUnique('b')])
+        check.addConstraint(check.hasSize(lambda x: x == 3.0))
+
+        result = VerificationSuite(self.spark).onData(self.df) \
+            .addCheck(check) \
+            .run()
+
+        result_df = VerificationResult.checkResultsAsDataFrame(self.spark, result)
+
+        check2 = Check(self.spark, CheckLevel.Warning, "test list constraints")
+
+        result2 = VerificationSuite(self.spark).onData(self.df) \
+            .addCheck(check2.isComplete('c').isUnique('b').hasSize(lambda x: x == 3.0)) \
+            .run()
+
+        result_df2 = VerificationResult.checkResultsAsDataFrame(self.spark, result2)
+
+        self.assertEqual(result_df.select('constraint').collect(), result_df2.select('constraint').collect())
+
     def test_initializer(self):
         # TODO verify that it does more than run
         check = Check(self.spark, CheckLevel.Warning, "test initializer")