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Use the power of hypothesis property based testing in PySpark tests

Project description


Hypothesis for Spark Unit tests

Library for easily creating PySpark tests using Hypothesis. Create heterogenious test data with ease


pip install sparkle-hypothesis


from sparkle_hypothesis import SparkleHypothesisTestCase, save_dfs

class MyTestCase(SparkleHypothesisTestCase)
    st_groups = st.sampled_from(['Pro', 'Consumer'])

    st_customers = st.fixed_dictionaries(
        {'customer_id:long': st.integers(min_value=1, max_value=10),
        'customer_group:str': st.shared(st_groups, 'group')})

    st_groups = st.fixed_dictionaries(
        {'group_id:long': st.just(1),
         'group_name:str': st.shared(st_groups, 'group'))

    @given(st_customers, st_groups)
    def test_answer_parsing(self, customers: dict, groups:dict):
        customers_df = self.spark.table('customers')
        groups_df = self.spark.table('groups')

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