def test_halfnull_halfequal_notrespected1(self):
data = pd.DataFrame()
c1 = [chr(1) for _ in range(50)]
c2 = [2 for _ in range(50)]
c3 = [2 / 0.6 for _ in range(50)]
c1.extend(["" for _ in range(50)])
c2.extend([0 for _ in range(50)])
c3.extend([0. for _ in range(40)])
c3.extend([10. for _ in range(10)])
data["c1"] = c1
data["c2"] = c2
data["c3"] = c3
df = self.spark.createDataFrame(data)
df = df.withColumn("c1", replace_empty_with_null(df["c1"]))
df = df.withColumn("c2", replace_0_with_null(df["c2"]))
r = constraint([0, 1], [2], df=df)[0]
self.assertEqual(r, 50.0)
condition1 = {"column": "c2", "operator": "lt", "value": 3}
condition2 = {"column": "c2", "operator": "gt", "value": 0}
conditions = [condition1, condition2]
r = constraint([0, 1], [2], conditions, df)[0]
self.assertEqual(r, 100.0)
r = constraint([0, 2], [1], conditions, df)[0]
self.assertEqual(r, 100.0)
def test_allnull(self):
data = pd.DataFrame()
data["c1"] = [" " for _ in range(100)]
data["c2"] = [1 for _ in range(100)]
data["c3"] = [1 for _ in range(100)]
df = self.spark.createDataFrame(data)
df = df.withColumn("c1", replace_every_string_with_null(df["c1"]))
df = df.withColumn("c2", replace_every_int_with_null(df["c2"]))
r = constraint([0, 1], [2], df=df)[0]
self.assertEqual(r, 100.0)
def test_empty(self):
data = pd.DataFrame()
data["c1"] = []
data["c2"] = []
schema = [StructField("c1", IntegerType(), True), StructField("c2", StringType(), True)]
df = self.spark.createDataFrame(data, StructType(schema))
condition1 = {"column": "c1", "operator": "lt", "value": 1000}
condition2 = {"column": "c1", "operator": "gt", "value": 0}
conditions = [condition1, condition2]
r = constraint([0], [1], conditions, df)[0]
self.assertEqual(r, 100.)
def test_allnull_with_conditions(self):
data = pd.DataFrame()
data["c1"] = [" " for _ in range(100)]
data["c2"] = [1 for _ in range(100)]
data["c3"] = [1 for _ in range(100)]
df = self.spark.createDataFrame(data)
df = df.withColumn("c1", replace_every_string_with_null(df["c1"]))
df = df.withColumn("c2", replace_every_int_with_null(df["c2"]))
condition1 = {"column": "c1", "operator": "lt", "value": 1000}
condition2 = {"column": "c1", "operator": "gt", "value": 0}
conditions = [condition1, condition2]
r = constraint([0, 1], [2], conditions, df)[0]
self.assertEqual(r, 100.0)
def test_halfnull_halfequal_notrespected3(self):
data = pd.DataFrame()
c1 = ["", "2", "2", "3", "3", "3", ""]
c2 = [0, 2, 2, 3, 3, 0, 3]
c3 = [24., 4, 4, 4, 2, 24, 2]
data["c1"] = c1
data["c2"] = c2
data["c3"] = c3
df = self.spark.createDataFrame(data)
df = df.withColumn("c1", replace_empty_with_null(df["c1"]))
df = df.withColumn("c2", replace_0_with_null(df["c2"]))
df = df.withColumn("c3", replace_0dot_with_null(df["c3"]))
r = constraint([0, 1], [2], df=df)[0]
self.assertEqual(r, (5 / 7.) * 100)
condition1 = {"column": "c2", "operator": "lt", "value": 3}
conditions = [condition1]
r = constraint([0, 1], [2], conditions, df)[0]
self.assertEqual(r, 100.)
condition1 = {"column": "c2", "operator": "eq", "value": 3}
conditions = [condition1]
r = constraint([0, 1], [2], conditions, df)[0]
self.assertEqual(r, (1 / 3.) * 100)
condition1 = {"column": "c2", "operator": "eq", "value": 3}
condition2 = {"column": "c1", "operator": "eq", "value": "3"}
conditions = [condition1, condition2]
r = constraint([0, 1], [2], conditions, df)[0]
self.assertEqual(r, 0.)
condition1 = {"column": "c3", "operator": "gt", "value": 20}
condition2 = {"column": "c2", "operator": "lt", "value": 3}
condition3 = {"column": "c1", "operator": "eq", "value": "3"}
conditions = [condition1, condition2, condition3]
r = constraint([0, 1], [2], conditions, df)[0]
self.assertEqual(r, 100.)
r = constraint([0], [1, 2], df=df)[0]
self.assertEqual(r, (2 / 7.) * 100)
#!/usr/bin/python3
from pyspark.sql import SparkSession
from haychecker.dhc.metrics import constraint
spark = SparkSession.builder.appName("constraint_example").getOrCreate()
df = spark.read.format("csv").option(
"header", "true").load("examples/resources/employees.csv")
df.show()
r1 = constraint(["title"], ["salary"], df=df)[0]
print("Constraint title/salary: {}".format(r1))
task1 = constraint(["city"], ["region"])
task2 = constraint(["region"], ["city"])
task3 = task1.add(task2)
result = task3.run(df)
r1 = result[0]["scores"][0]
r2 = result[1]["scores"][0]
print("Constraint city/region: {}, сonstraint region/city: {}".format(r1, r2))
