Allow all DQ constraints to be generated from an Analyzer

src/main/scala/com/amazon/deequ/checks/Check.scala

@@ -1083,6 +1083,12 @@ object Check {
   /** A common assertion function checking if the value is 1 */
   val IsOne: Double => Boolean = { _ == 1.0 }
 
+  def fromConstraint(constraint: Constraint,
+                     description: String,
+                     checkLevel: CheckLevel.Value = CheckLevel.Error): Check = {
+    Check(checkLevel, description, constraints = Seq(constraint))
+  }
+
   /**
     * Common assertion function checking if the value can be considered as normal (that no
     * anomalies were detected), given the anomaly detection strategy and details on how to retrieve

src/main/scala/com/amazon/deequ/constraints/Constraint.scala

@@ -114,6 +114,10 @@ object Constraint {
 
     val size = Size(where)
 
+    fromAnalyzer(size, assertion, hint)
+  }
+
+  def fromAnalyzer(size: Size, assertion: Long => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[NumMatches, Double, Long](size,
       assertion, Some(_.toLong), hint)
 
@@ -194,10 +198,16 @@ object Constraint {
 
     val completeness = Completeness(column, where)
 
+    this.fromAnalyzer(completeness, assertion, hint)
+  }
+
+  def fromAnalyzer(completeness: Completeness,
+                   assertion: Double => Boolean,
+                   hint: Option[String] = None): Constraint = {
     val constraint = AnalysisBasedConstraint[NumMatchesAndCount, Double, Double](
       completeness, assertion, hint = hint)
 
-    new RowLevelConstraint(constraint, s"CompletenessConstraint($completeness)", s"Completeness-$column")
+    new RowLevelConstraint(constraint, s"CompletenessConstraint($completeness)", s"Completeness-${completeness.column}")
   }
 
   /**
@@ -238,12 +248,16 @@ object Constraint {
 
     val uniqueness = Uniqueness(columns, where)
 
+    fromAnalyzer(uniqueness, assertion, hint)
+  }
+
+  def fromAnalyzer(uniqueness: Uniqueness, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[FrequenciesAndNumRows, Double, Double](
       uniqueness, assertion, hint = hint)
 
     new RowLevelGroupedConstraint(constraint,
       s"UniquenessConstraint($uniqueness)",
-      columns)
+      uniqueness.columns)
   }
 
   /**
@@ -264,6 +278,10 @@ object Constraint {
 
     val distinctness = Distinctness(columns, where)
 
+    fromAnalyzer(distinctness, assertion, hint)
+  }
+
+  def fromAnalyzer(distinctness: Distinctness, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[FrequenciesAndNumRows, Double, Double](
       distinctness, assertion, hint = hint)
 
@@ -287,12 +305,20 @@ object Constraint {
     : Constraint = {
 
     val uniqueValueRatio = UniqueValueRatio(columns, where)
+    fromAnalyzer(uniqueValueRatio, assertion, hint)
+  }
+
+  def fromAnalyzer(
+      uniqueValueRatio: UniqueValueRatio,
+      assertion: Double => Boolean,
+      hint: Option[String])
+    : Constraint = {
     val constraint = AnalysisBasedConstraint[FrequenciesAndNumRows, Double, Double](
       uniqueValueRatio, assertion, hint = hint)
 
     new RowLevelGroupedConstraint(constraint,
       s"UniqueValueRatioConstraint($uniqueValueRatio",
-      columns)
+      uniqueValueRatio.columns)
   }
 
   /**
@@ -314,15 +340,18 @@ object Constraint {
 
     val compliance = Compliance(name, column, where, columns)
 
+    fromAnalyzer(compliance, assertion, hint)
+  }
+
+  private def fromAnalyzer(compliance: Compliance, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[NumMatchesAndCount, Double, Double](
       compliance, assertion, hint = hint)
 
-//    new NamedConstraint(constraint, s"ComplianceConstraint($compliance)")
     val sparkAssertion = org.apache.spark.sql.functions.udf(assertion)
     new RowLevelAssertedConstraint(
       constraint,
       s"ComplianceConstraint($compliance)",
-      s"ColumnsCompliance-$column",
+      s"ColumnsCompliance-${compliance.predicate}",
       sparkAssertion)
   }
 
@@ -346,6 +375,16 @@ object Constraint {
 
     val patternMatch = PatternMatch(column, pattern, where)
 
+    fromAnalyzer(patternMatch, pattern, assertion, name, hint)
+  }
+
+  def fromAnalyzer(
+                    patternMatch: PatternMatch,
+                    pattern: Regex,
+                    assertion: Double => Boolean,
+                    name: Option[String],
+                    hint: Option[String]): Constraint = {
+    val column: String = patternMatch.column
     val constraint = AnalysisBasedConstraint[NumMatchesAndCount, Double, Double](
       patternMatch, assertion, hint = hint)
 
@@ -375,6 +414,10 @@ object Constraint {
 
     val entropy = Entropy(column, where)
 
+    fromAnalyzer(entropy, assertion, hint)
+  }
+
+  def fromAnalyzer(entropy: Entropy, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[FrequenciesAndNumRows, Double, Double](
       entropy, assertion, hint = hint)
 
@@ -401,6 +444,14 @@ object Constraint {
 
     val mutualInformation = MutualInformation(Seq(columnA, columnB), where)
 
+    fromAnalyzer(mutualInformation, assertion, hint)
+  }
+
+  def fromAnalyzer(
+      mutualInformation: MutualInformation,
+      assertion: Double => Boolean,
+      hint: Option[String])
+    : Constraint = {
     val constraint = AnalysisBasedConstraint[FrequenciesAndNumRows, Double, Double](
       mutualInformation, assertion, hint = hint)
 
@@ -427,6 +478,10 @@ object Constraint {
 
     val approxQuantile = ApproxQuantile(column, quantile, where = where)
 
+    fromAnalyzer(approxQuantile, assertion, hint)
+  }
+
+  def fromAnalyzer(approxQuantile: ApproxQuantile, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[ApproxQuantileState, Double, Double](
       approxQuantile, assertion, hint = hint)
 
@@ -450,6 +505,11 @@ object Constraint {
 
     val maxLength = MaxLength(column, where, analyzerOptions)
 
+    fromAnalyzer(maxLength, assertion, hint)
+  }
+
+  def fromAnalyzer(maxLength: MaxLength, assertion: Double => Boolean, hint: Option[String]): Constraint = {
+    val column: String = maxLength.column
     val constraint = AnalysisBasedConstraint[MaxState, Double, Double](maxLength, assertion,
       hint = hint)
 
@@ -479,6 +539,11 @@ object Constraint {
 
     val minLength = MinLength(column, where, analyzerOptions)
 
+    fromAnalyzer(minLength, assertion, hint)
+  }
+
+  def fromAnalyzer(minLength: MinLength, assertion: Double => Boolean, hint: Option[String]): Constraint = {
+    val column: String = minLength.column
     val constraint = AnalysisBasedConstraint[MinState, Double, Double](minLength, assertion,
       hint = hint)
 
@@ -508,6 +573,11 @@ object Constraint {
 
     val minimum = Minimum(column, where)
 
+    fromAnalyzer(minimum, assertion, hint)
+  }
+
+  def fromAnalyzer(minimum: Minimum, assertion: Double => Boolean, hint: Option[String]): Constraint = {
+    val column: String = minimum.column
     val constraint = AnalysisBasedConstraint[MinState, Double, Double](minimum, assertion,
       hint = hint)
 
@@ -535,6 +605,11 @@ object Constraint {
 
     val maximum = Maximum(column, where)
 
+    fromAnalyzer(maximum, assertion, hint)
+  }
+
+  def fromAnalyzer(maximum: Maximum, assertion: Double => Boolean, hint: Option[String]): Constraint = {
+    val column: String = maximum.column
     val constraint = AnalysisBasedConstraint[MaxState, Double, Double](maximum, assertion,
       hint = hint)
 
@@ -562,11 +637,16 @@ object Constraint {
 
     val mean = Mean(column, where)
 
+    fromAnalyzer(mean, assertion, hint)
+  }
+
+  def fromAnalyzer(mean: Mean, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[MeanState, Double, Double](mean, assertion,
       hint = hint)
 
     new NamedConstraint(constraint, s"MeanConstraint($mean)")
   }
+
   /**
     * Runs sum analysis on the given column and executes the assertion
     *
@@ -583,13 +663,16 @@ object Constraint {
 
     val sum = Sum(column, where)
 
+    fromAnalyzer(sum, assertion, hint)
+  }
+
+  def fromAnalyzer(sum: Sum, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[SumState, Double, Double](sum, assertion,
       hint = hint)
 
     new NamedConstraint(constraint, s"SumConstraint($sum)")
   }
 
-
   /**
     * Runs standard deviation analysis on the given column and executes the assertion
     *
@@ -606,6 +689,14 @@ object Constraint {
 
     val standardDeviation = StandardDeviation(column, where)
 
+    fromAnalyzer(standardDeviation, assertion, hint)
+  }
+
+  def fromAnalyzer(
+      standardDeviation: StandardDeviation,
+      assertion: Double => Boolean,
+      hint: Option[String])
+    : Constraint = {
     val constraint = AnalysisBasedConstraint[StandardDeviationState, Double, Double](
       standardDeviation, assertion, hint = hint)
 
@@ -628,6 +719,14 @@ object Constraint {
 
     val approxCountDistinct = ApproxCountDistinct(column, where)
 
+    fromAnalyzer(approxCountDistinct, assertion, hint)
+  }
+
+  def fromAnalyzer(
+      approxCountDistinct: ApproxCountDistinct,
+      assertion: Double => Boolean,
+      hint: Option[String])
+    : Constraint = {
     val constraint = AnalysisBasedConstraint[ApproxCountDistinctState, Double, Double](
       approxCountDistinct, assertion, hint = hint)
 
@@ -652,6 +751,10 @@ object Constraint {
 
     val correlation = Correlation(columnA, columnB, where)
 
+    fromAnalyzer(correlation, assertion, hint)
+  }
+
+  def fromAnalyzer(correlation: Correlation, assertion: Double => Boolean, hint: Option[String]): Constraint = {
     val constraint = AnalysisBasedConstraint[CorrelationState, Double, Double](
       correlation, assertion, hint = hint)
 
@@ -711,7 +814,11 @@ object Constraint {
 
     val kllSketch = KLLSketch(column, kllParameters = kllParameters)
 
-    val constraint = AnalysisBasedConstraint[KLLState, BucketDistribution, BucketDistribution] (
+    fromAnalyzer(kllSketch, assertion, hint)
+  }
+
+  def fromAnalyzer(kllSketch: KLLSketch, assertion: BucketDistribution => Boolean, hint: Option[String]): Constraint = {
+    val constraint = AnalysisBasedConstraint[KLLState, BucketDistribution, BucketDistribution](
       kllSketch, assertion, hint = hint)
 
     new NamedConstraint(constraint, s"kllSketchConstraint($kllSketch)")

src/test/scala/com/amazon/deequ/constraints/AnalysisBasedConstraintTest.scala

@@ -17,8 +17,13 @@
 package com.amazon.deequ.constraints
 
 import com.amazon.deequ.SparkContextSpec
+import com.amazon.deequ.VerificationSuite
 import com.amazon.deequ.analyzers._
 import com.amazon.deequ.analyzers.runners.MetricCalculationException
+import com.amazon.deequ.checks.Check
+import com.amazon.deequ.checks.CheckLevel
+import com.amazon.deequ.checks.CheckResult
+import com.amazon.deequ.checks.CheckStatus
 import com.amazon.deequ.constraints.ConstraintUtils.calculate
 import com.amazon.deequ.metrics.{DoubleMetric, Entity, Metric}
 import com.amazon.deequ.utils.FixtureSupport
@@ -74,6 +79,24 @@ class AnalysisBasedConstraintTest extends WordSpec with Matchers with SparkConte
 
   "Analysis based constraint" should {
 
+    "can convert an analyzer to a Check" in
+      withSparkSession { sparkSession =>
+        val completeness = Completeness("att1")
+        val constraint1 = Constraint.fromAnalyzer(completeness, d => d > 1)
+        val size: Size = Size()
+        val sizeAssertion: (Long => Boolean) = d => d > 0
+        val constraint2 = Constraint.fromAnalyzer(size, sizeAssertion, None)
+
+        val check1 = Check.fromConstraint(constraint1, s"Completeness att1")
+        val check2 = Check.fromConstraint(constraint2, "Size")
+
+        val df = getDfMissing(sparkSession)
+
+        val result = new VerificationSuite().onData(df).addCheck(check1).run()
+
+        assert(result.status == CheckStatus.Error)
+      }
+
     "assert correctly on values if analysis is successful" in
       withSparkSession { sparkSession =>
         val df = getDfMissing(sparkSession)