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import pytest
from chispa import assert_df_equality
from datetime import datetime, date
from pyspark.sql.types import StructType, StructField, StringType, NullType, TimestampType, ArrayType, DateType, Row
from lib import DataLoader, Transformations
from lib.ConfigLoader import get_config
from lib.DataLoader import get_party_schema
from lib.Utils import get_spark_session
@pytest.fixture(scope='session')
def spark():
return get_spark_session("LOCAL")
@pytest.fixture(scope='session')
def expected_party_rows():
return [Row(load_date=date(2022, 8, 2), account_id='6982391060',
party_id='9823462810', relation_type='F-N', relation_start_date=datetime(2019, 7, 29, 6, 21, 32)),
Row(load_date=date(2022, 8, 2), account_id='6982391061', party_id='9823462811', relation_type='F-N',
relation_start_date=datetime(2018, 8, 31, 5, 27, 22)),
Row(load_date=date(2022, 8, 2), account_id='6982391062', party_id='9823462812', relation_type='F-N',
relation_start_date=datetime(2018, 8, 25, 15, 50, 29)),
Row(load_date=date(2022, 8, 2), account_id='6982391063', party_id='9823462813', relation_type='F-N',
relation_start_date=datetime(2018, 5, 11, 7, 23, 28)),
Row(load_date=date(2022, 8, 2), account_id='6982391064', party_id='9823462814', relation_type='F-N',
relation_start_date=datetime(2019, 6, 6, 14, 18, 12)),
Row(load_date=date(2022, 8, 2), account_id='6982391065', party_id='9823462815', relation_type='F-N',
relation_start_date=datetime(2019, 5, 4, 5, 12, 37)),
Row(load_date=date(2022, 8, 2), account_id='6982391066', party_id='9823462816', relation_type='F-N',
relation_start_date=datetime(2019, 5, 15, 10, 39, 29)),
Row(load_date=date(2022, 8, 2), account_id='6982391067', party_id='9823462817', relation_type='F-N',
relation_start_date=datetime(2018, 5, 16, 9, 53, 4)),
Row(load_date=date(2022, 8, 2), account_id='6982391068', party_id='9823462818', relation_type='F-N',
relation_start_date=datetime(2017, 11, 27, 1, 20, 12)),
Row(load_date=date(2022, 8, 2), account_id='6982391067', party_id='9823462820', relation_type='F-S',
relation_start_date=datetime(2017, 11, 20, 14, 18, 5)),
Row(load_date=date(2022, 8, 2), account_id='6982391067', party_id='9823462821', relation_type='F-S',
relation_start_date=datetime(2018, 7, 19, 18, 56, 57))]
@pytest.fixture(scope='session')
def parties_list():
return [
(date(2022, 8, 2), '6982391060', '9823462810', 'F-N', datetime.fromisoformat('2019-07-29 06:21:32.000+05:30')),
(date(2022, 8, 2), '6982391061', '9823462811', 'F-N', datetime.fromisoformat('2018-08-31 05:27:22.000+05:30')),
(date(2022, 8, 2), '6982391062', '9823462812', 'F-N', datetime.fromisoformat('2018-08-25 15:50:29.000+05:30')),
(date(2022, 8, 2), '6982391063', '9823462813', 'F-N', datetime.fromisoformat('2018-05-11 07:23:28.000+05:30')),
(date(2022, 8, 2), '6982391064', '9823462814', 'F-N', datetime.fromisoformat('2019-06-06 14:18:12.000+05:30')),
(date(2022, 8, 2), '6982391065', '9823462815', 'F-N', datetime.fromisoformat('2019-05-04 05:12:37.000+05:30')),
(date(2022, 8, 2), '6982391066', '9823462816', 'F-N', datetime.fromisoformat('2019-05-15 10:39:29.000+05:30')),
(date(2022, 8, 2), '6982391067', '9823462817', 'F-N', datetime.fromisoformat('2018-05-16 09:53:04.000+05:30')),
(date(2022, 8, 2), '6982391068', '9823462818', 'F-N', datetime.fromisoformat('2017-11-27 01:20:12.000+05:30')),
(date(2022, 8, 2), '6982391067', '9823462820', 'F-S', datetime.fromisoformat('2017-11-20 14:18:05.000+05:30')),
(date(2022, 8, 2), '6982391067', '9823462821', 'F-S', datetime.fromisoformat('2018-07-19 18:56:57.000+05:30'))]
@pytest.fixture(scope='session')
def expected_contract_df(spark):
schema = StructType([StructField('account_id', StringType()),
StructField('contractIdentifier',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('sourceSystemIdentifier',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('contactStartDateTime',
StructType([StructField('operation', StringType()),
StructField('newValue', TimestampType()),
StructField('oldValue', NullType())])),
StructField('contractTitle',
StructType([StructField('operation', StringType()),
StructField('newValue',
ArrayType(StructType(
[StructField('contractTitleLineType', StringType()),
StructField('contractTitleLine', StringType())]))),
StructField('oldValue', NullType())])),
StructField('taxIdentifier',
StructType([StructField('operation', StringType()),
StructField('newValue',
StructType([StructField('taxIdType', StringType()),
StructField('taxId', StringType())])),
StructField('oldValue', NullType())])),
StructField('contractBranchCode',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('contractCountry',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())]))])
return spark.read.format("json").schema(schema).load("test_data/results/contract_df.json")
@pytest.fixture(scope='session')
def expected_final_df(spark):
schema = StructType(
[StructField('keys',
ArrayType(StructType([StructField('keyField', StringType()),
StructField('keyValue', StringType())]))),
StructField('payload',
StructType([
StructField('contractIdentifier',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('sourceSystemIdentifier',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('contactStartDateTime',
StructType([StructField('operation', StringType()),
StructField('newValue', TimestampType()),
StructField('oldValue', NullType())])),
StructField('contractTitle',
StructType([StructField('operation', StringType()),
StructField('newValue', ArrayType(
StructType([StructField('contractTitleLineType', StringType()),
StructField('contractTitleLine', StringType())]))),
StructField('oldValue', NullType())])),
StructField('taxIdentifier',
StructType([StructField('operation', StringType()),
StructField('newValue',
StructType([StructField('taxIdType', StringType()),
StructField('taxId', StringType())])),
StructField('oldValue', NullType())])),
StructField('contractBranchCode',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('contractCountry',
StructType([StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('partyRelations',
ArrayType(StructType([
StructField('partyIdentifier',
StructType([
StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('partyRelationshipType',
StructType([
StructField('operation', StringType()),
StructField('newValue', StringType()),
StructField('oldValue', NullType())])),
StructField('partyRelationStartDateTime',
StructType([
StructField('operation', StringType()),
StructField('newValue', TimestampType()),
StructField('oldValue', NullType())])),
StructField('partyAddress',
StructType([StructField('operation', StringType()),
StructField(
'newValue',
StructType(
[StructField('addressLine1', StringType()),
StructField('addressLine2', StringType()),
StructField('addressCity', StringType()),
StructField('addressPostalCode',
StringType()),
StructField('addressCountry', StringType()),
StructField('addressStartDate', DateType())
])),
StructField('oldValue', NullType())]))])))]))])
return spark.read.format("json").schema(schema).load("test_data/results/final_df.json") \
.select("keys", "payload")
def test_blank_test(spark):
print(spark.version)
assert spark.version == "3.3.0"
def test_get_config():
conf_local = get_config("LOCAL")
conf_qa = get_config("QA")
assert conf_local["kafka.topic"] == "sbdl_kafka_cloud"
assert conf_qa["hive.database"] == "sbdl_db_qa"
def test_read_accounts(spark):
accounts_df = DataLoader.read_accounts(spark, "LOCAL", False, None)
assert accounts_df.count() == 8
def test_read_parties_row(spark, expected_party_rows):
actual_party_rows = DataLoader.read_parties(spark, "LOCAL", False, None).collect()
assert expected_party_rows == actual_party_rows
def test_read_parties(spark, parties_list):
expected_df = spark.createDataFrame(parties_list)
actual_df = DataLoader.read_parties(spark, "LOCAL", False, None)
assert_df_equality(expected_df, actual_df, ignore_schema=True)
def test_read_party_schema(spark, parties_list):
expected_df = spark.createDataFrame(parties_list, get_party_schema())
actual_df = DataLoader.read_parties(spark, "LOCAL", False, None)
assert_df_equality(expected_df, actual_df)
def test_get_contract(spark, expected_contract_df):
accounts_df = DataLoader.read_accounts(spark, "LOCAL", False, None)
actual_contract_df = Transformations.get_contract(accounts_df)
assert expected_contract_df.collect() == actual_contract_df.collect()
assert_df_equality(expected_contract_df, actual_contract_df, ignore_schema=True)
def test_kafka_kv_df(spark, expected_final_df):
accounts_df = DataLoader.read_accounts(spark, "LOCAL", False, None)
contract_df = Transformations.get_contract(accounts_df)
parties_df = DataLoader.read_parties(spark, "LOCAL", False, None)
relations_df = Transformations.get_relations(parties_df)
address_df = DataLoader.read_address(spark, "LOCAL", False, None)
relation_address_df = Transformations.get_address(address_df)
party_address_df = Transformations.join_party_address(relations_df, relation_address_df)
data_df = Transformations.join_contract_party(contract_df, party_address_df)
actual_final_df = Transformations.apply_header(spark, data_df) \
.select("keys", "payload")
assert_df_equality(actual_final_df, expected_final_df, ignore_schema=True)
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