isort src/python

src/python/aqueduct_executor/migrators/artifact_migration_000016/execute.py

@@ -3,6 +3,7 @@
 
 import cloudpickle as pickle
 from aqueduct.utils.type_inference import infer_artifact_type
+
 from aqueduct_executor.migrators.artifact_migration_000016.spec import MigrationSpec
 from aqueduct_executor.operators.utils.enums import ArtifactType, SerializationType
 from aqueduct_executor.operators.utils.storage.parse import parse_storage

src/python/aqueduct_executor/migrators/artifact_migration_000016/spec.py

@@ -1,8 +1,9 @@
 import json
 
-from aqueduct_executor.operators.utils.storage import config
 from pydantic import BaseModel, parse_obj_as
 
+from aqueduct_executor.operators.utils.storage import config
+
 
 class MigrationSpec(BaseModel):
     artifact_type: str

src/python/aqueduct_executor/migrators/backfill_python_type_000022/serialize.py

@@ -10,9 +10,10 @@
 
 import cloudpickle as pickle
 import pandas as pd
-from aqueduct_executor.operators.utils.enums import ArtifactType, SerializationType
 from PIL import Image
 
+from aqueduct_executor.operators.utils.enums import ArtifactType, SerializationType
+
 _DEFAULT_ENCODING = "utf8"
 
 # The temporary file name that a Tensorflow keras model will be dumped into before we read/write it from storage.

src/python/aqueduct_executor/migrators/backfill_python_type_000022/spec.py

@@ -1,8 +1,9 @@
 import json
 
-from aqueduct_executor.operators.utils.storage import config
 from pydantic import BaseModel, parse_obj_as
 
+from aqueduct_executor.operators.utils.storage import config
+
 
 class MigrationSpec(BaseModel):
     serialization_type: str

src/python/aqueduct_executor/migrators/parameter_val_type_inference_000019/execute.py

@@ -2,6 +2,7 @@
 import json
 
 from aqueduct.utils.type_inference import infer_artifact_type
+
 from aqueduct_executor.migrators.parameter_val_type_inference_000019 import serialize
 from aqueduct_executor.operators.utils.enums import SerializationType
 

src/python/aqueduct_executor/migrators/parameter_val_type_inference_000019/serialize.py

@@ -5,9 +5,10 @@
 
 import cloudpickle as pickle
 import pandas as pd
-from aqueduct_executor.operators.utils.enums import ArtifactType, SerializationType
 from PIL import Image
 
+from aqueduct_executor.operators.utils.enums import ArtifactType, SerializationType
+
 _DEFAULT_ENCODING = "utf8"
 _DEFAULT_IMAGE_FORMAT = "jpeg"
 

src/python/aqueduct_executor/migrators/parameter_val_type_inference_000019/spec.py

@@ -1,8 +1,9 @@
 import json
 
-from aqueduct_executor.operators.utils.storage import config
 from pydantic import BaseModel, parse_obj_as
 
+from aqueduct_executor.operators.utils.storage import config
+
 
 class MigrationSpec(BaseModel):
     param_val: str

src/python/aqueduct_executor/operators/airflow/execute.py

@@ -3,6 +3,8 @@
 import traceback
 from typing import Dict, List, Tuple, Union
 
+from jinja2 import Environment, FileSystemLoader
+
 from aqueduct_executor.operators.airflow import spec
 from aqueduct_executor.operators.connectors.data import spec as conn_spec
 from aqueduct_executor.operators.function_executor import spec as func_spec
@@ -11,7 +13,6 @@
 from aqueduct_executor.operators.utils import utils
 from aqueduct_executor.operators.utils.execution import ExecutionState, Logs
 from aqueduct_executor.operators.utils.storage import parse
-from jinja2 import Environment, FileSystemLoader
 
 TaskSpec = Union[
     conn_spec.ExtractSpec,

src/python/aqueduct_executor/operators/airflow/spec.py

@@ -2,12 +2,13 @@
 import uuid
 from typing import Dict, List, Literal, Union
 
+from pydantic import BaseModel, parse_obj_as
+
 from aqueduct_executor.operators.connectors.data import spec as conn_spec
 from aqueduct_executor.operators.function_executor import spec as func_spec
 from aqueduct_executor.operators.param_executor import spec as param_spec
 from aqueduct_executor.operators.utils import enums
 from aqueduct_executor.operators.utils.storage import config
-from pydantic import BaseModel, parse_obj_as
 
 OperatorSpec = Union[
     conn_spec.ExtractSpec, conn_spec.LoadSpec, func_spec.FunctionSpec, param_spec.ParamSpec

src/python/aqueduct_executor/operators/connectors/data/athena.py

@@ -2,6 +2,7 @@
 
 import awswrangler as wr
 import pandas as pd
+
 from aqueduct_executor.operators.connectors.data import connector, extract, load
 from aqueduct_executor.operators.connectors.data.config import AthenaConfig
 from aqueduct_executor.operators.connectors.data.utils import construct_boto_session

src/python/aqueduct_executor/operators/connectors/data/bigquery.py

@@ -2,12 +2,13 @@
 from typing import Any, Dict, List, Optional
 
 import pandas as pd
+from google.cloud import bigquery
+from google.oauth2 import service_account
+
 from aqueduct_executor.operators.connectors.data import common, config, connector, extract, load
 from aqueduct_executor.operators.utils.enums import ArtifactType
 from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
 from aqueduct_executor.operators.utils.utils import delete_object
-from google.cloud import bigquery
-from google.oauth2 import service_account
 
 
 class BigQueryConnector(connector.DataConnector):

src/python/aqueduct_executor/operators/connectors/data/config.py

@@ -1,9 +1,10 @@
 from enum import Enum
 from typing import Optional, Union
 
+from pydantic import Field
+
 from aqueduct_executor.operators.connectors.data import models
 from aqueduct_executor.operators.utils.enums import MetaEnum
-from pydantic import Field
 
 """Duplicated at `aqueduct/integrations/connect_config.py` for now, please keep them in sync."""
 

src/python/aqueduct_executor/operators/connectors/data/extract.py

@@ -4,9 +4,10 @@
 from typing import Any, Dict, List, Optional, Union
 
 from aqueduct.resources.parameters import BUILT_IN_EXPANSIONS, TAG_PATTERN
+from pydantic import parse_obj_as
+
 from aqueduct_executor.operators.connectors.data import common, models
 from aqueduct_executor.operators.utils.enums import ArtifactType
-from pydantic import parse_obj_as
 
 # The TAG for 'previous table' when the user specifies a chained query.
 PREV_TABLE_TAG = "$"

src/python/aqueduct_executor/operators/connectors/data/gcs.py

@@ -1,12 +1,13 @@
 import json
 from typing import Any, List
 
+from google.cloud import storage
+from google.oauth2 import service_account
+
 from aqueduct_executor.operators.connectors.data import connector
 from aqueduct_executor.operators.connectors.data.config import GCSConfig
 from aqueduct_executor.operators.utils.enums import ArtifactType
 from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
-from google.cloud import storage
-from google.oauth2 import service_account
 
 _CREDENTIALS_ENV_VAR = "GCS_CREDENTIALS"
 

src/python/aqueduct_executor/operators/connectors/data/load.py

@@ -1,8 +1,9 @@
 from typing import Optional, Union
 
-from aqueduct_executor.operators.connectors.data import common, models
 from pydantic import validator
 
+from aqueduct_executor.operators.connectors.data import common, models
+
 
 class RelationalParams(models.BaseParams):
     table: str

src/python/aqueduct_executor/operators/connectors/data/models.py

@@ -1,4 +1,5 @@
 from typing import Optional
+
 from pydantic import BaseModel, Extra
 
 
@@ -18,6 +19,7 @@ class BaseConfig(BaseModel):
     BaseConfig defines the Pydantic Config shared by all connector Config's, e.g.
     postgres.Config, mysql.Config, etc.
     """
+
     exec_state: Optional[str]
 
     class Config:

src/python/aqueduct_executor/operators/connectors/data/mongodb.py

@@ -1,14 +1,15 @@
 from typing import Any, List, Optional
 
 import pandas as pd
+from pymongo import MongoClient
+from pymongo.client_session import ClientSession
+from pymongo.database import Database
+
 from aqueduct_executor.operators.connectors.data import common, connector, extract, load
 from aqueduct_executor.operators.connectors.data.config import MongoDBConfig
 from aqueduct_executor.operators.utils.enums import ArtifactType
 from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
 from aqueduct_executor.operators.utils.utils import delete_object
-from pymongo import MongoClient
-from pymongo.client_session import ClientSession
-from pymongo.database import Database
 
 
 class MongoDBConnector(connector.DataConnector):

src/python/aqueduct_executor/operators/connectors/data/mysql.py

@@ -1,6 +1,7 @@
-from aqueduct_executor.operators.connectors.data import config, relational, utils
 from sqlalchemy import create_engine, engine
 
+from aqueduct_executor.operators.connectors.data import config, relational, utils
+
 
 class MySqlConnector(relational.RelationalConnector):
     def __init__(self, config: config.MySqlConfig):

src/python/aqueduct_executor/operators/connectors/data/postgres.py

@@ -1,6 +1,7 @@
-from aqueduct_executor.operators.connectors.data import config, relational, utils
 from sqlalchemy import create_engine, engine
 
+from aqueduct_executor.operators.connectors.data import config, relational, utils
+
 
 class PostgresConnector(relational.RelationalConnector):
     def __init__(self, config: config.PostgresConfig):

src/python/aqueduct_executor/operators/connectors/data/relational.py

@@ -1,15 +1,16 @@
 from typing import Any, Callable, Dict, List, Optional
 
 import pandas as pd
-from aqueduct_executor.operators.connectors.data import connector, extract, load
-from aqueduct_executor.operators.utils.enums import ArtifactType
-from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
-from aqueduct_executor.operators.utils.utils import delete_object
 from sqlalchemy import MetaData, engine, inspect
 from sqlalchemy.exc import SQLAlchemyError
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.types import VARCHAR
 
+from aqueduct_executor.operators.connectors.data import connector, extract, load
+from aqueduct_executor.operators.utils.enums import ArtifactType
+from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
+from aqueduct_executor.operators.utils.utils import delete_object
+
 
 def default_map_object_dtype_to_varchar(df: pd.DataFrame) -> Dict[str, VARCHAR]:
     col_to_type = {}

src/python/aqueduct_executor/operators/connectors/data/s3.py

@@ -4,6 +4,8 @@
 import numpy as np
 import pandas as pd
 from aqueduct.utils.serialization import deserialize
+from botocore.client import ClientError
+
 from aqueduct_executor.operators.connectors.data import connector, extract, load
 from aqueduct_executor.operators.connectors.data.config import S3Config
 from aqueduct_executor.operators.connectors.data.s3_serialization import (
@@ -17,7 +19,6 @@
 from aqueduct_executor.operators.utils.enums import ArtifactType
 from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
 from aqueduct_executor.operators.utils.utils import delete_object
-from botocore.client import ClientError
 
 
 class S3Connector(connector.DataConnector):

src/python/aqueduct_executor/operators/connectors/data/s3_serialization.py

@@ -7,9 +7,10 @@
 from aqueduct.constants.enums import S3SerializationType
 from aqueduct.utils.serialization import PickleableCollectionSerializationFormat
 from aqueduct.utils.type_inference import infer_artifact_type
+from PIL import Image
+
 from aqueduct_executor.operators.connectors.data.common import S3TableFormat
 from aqueduct_executor.operators.utils.enums import ArtifactType
-from PIL import Image
 
 _DEFAULT_JSON_ENCODING = "utf8"
 _DEFAULT_IMAGE_FORMAT = "jpeg"

src/python/aqueduct_executor/operators/connectors/data/snowflake.py

@@ -1,10 +1,11 @@
 from typing import Dict
 
 import pandas as pd
-from aqueduct_executor.operators.connectors.data import config, relational, utils
 from sqlalchemy import create_engine, engine
 from sqlalchemy.types import VARCHAR
 
+from aqueduct_executor.operators.connectors.data import config, relational, utils
+
 
 class SnowflakeConnector(relational.RelationalConnector):
     def __init__(self, config: config.SnowflakeConfig):

src/python/aqueduct_executor/operators/connectors/data/spark/s3.py

@@ -6,15 +6,16 @@
 import cloudpickle as pickle
 import numpy as np
 import pandas as pd
+from botocore.client import ClientError
+from PIL import Image
+from pyspark.sql import DataFrame, SparkSession
+
 from aqueduct_executor.operators.connectors.data import common, connector, extract, load, s3
 from aqueduct_executor.operators.connectors.data.config import S3Config
 from aqueduct_executor.operators.connectors.data.utils import construct_boto_session
 from aqueduct_executor.operators.utils.enums import ArtifactType
 from aqueduct_executor.operators.utils.saved_object_delete import SavedObjectDelete
 from aqueduct_executor.operators.utils.utils import delete_object
-from botocore.client import ClientError
-from PIL import Image
-from pyspark.sql import DataFrame, SparkSession
 
 _DEFAULT_JSON_ENCODING = "utf8"
 _DEFAULT_IMAGE_FORMAT = "jpeg"

src/python/aqueduct_executor/operators/connectors/data/spark/snowflake.py

@@ -1,5 +1,8 @@
 from typing import Any
 
+from pyspark.sql import DataFrame, SparkSession
+from pyspark.sql.types import FloatType
+
 from aqueduct_executor.operators.connectors.data import (
     common,
     config,
@@ -9,8 +12,6 @@
     snowflake,
 )
 from aqueduct_executor.operators.utils.enums import ArtifactType
-from pyspark.sql import DataFrame, SparkSession
-from pyspark.sql.types import FloatType
 
 
 class SparkSnowflakeConnector(relational.RelationalConnector):

src/python/aqueduct_executor/operators/connectors/data/spec.py

@@ -8,10 +8,11 @@
 
 import json
 
+from pydantic import parse_obj_as, validator
+
 from aqueduct_executor.operators.connectors.data import common, config, extract, load, models
 from aqueduct_executor.operators.utils import enums
 from aqueduct_executor.operators.utils.storage import config as sconfig
-from pydantic import parse_obj_as, validator
 
 AQUEDUCT_DEMO_NAME = "aqueduct_demo"
 

src/python/aqueduct_executor/operators/connectors/data/sql_server.py

@@ -1,7 +1,8 @@
 import pandas as pd
+from sqlalchemy import create_engine, engine
+
 from aqueduct_executor.operators.connectors.data import config, load, relational, utils
 from aqueduct_executor.operators.utils.enums import ArtifactType
-from sqlalchemy import create_engine, engine
 
 
 class SqlServerConnector(relational.RelationalConnector):

src/python/aqueduct_executor/operators/connectors/data/sqlite.py

@@ -1,11 +1,12 @@
 import sqlite3
 
 import pandas as pd
-from aqueduct_executor.operators.connectors.data import config, load, relational
-from aqueduct_executor.operators.utils.enums import ArtifactType
 from packaging.version import parse as parse_version
 from sqlalchemy import create_engine, engine
 
+from aqueduct_executor.operators.connectors.data import config, load, relational
+from aqueduct_executor.operators.utils.enums import ArtifactType
+
 # https://www.sqlite.org/limits.html#max_variable_number
 SQLITE_MAX_VARIABLE_NUMBER = 32766
 SQLITE_MAX_VARIABLE_NUMBER_EARLIER_VERSION = 999

src/python/aqueduct_executor/operators/connectors/data/utils.py

@@ -4,6 +4,7 @@
 from typing import Union
 
 import boto3
+
 from aqueduct_executor.operators.connectors.data.config import (
     AthenaConfig,
     AWSCredentialType,

src/python/aqueduct_executor/operators/connectors/tests/test_bigquery.py

@@ -1,9 +1,10 @@
 import pytest
+from google.cloud import bigquery
+
 from aqueduct_executor.operators.connectors.data import bigquery as bq
 from aqueduct_executor.operators.connectors.data.extract import RelationalParams as ExtractParam
 from aqueduct_executor.operators.connectors.data.load import RelationalParams as LoadParam
 from aqueduct_executor.operators.connectors.tests import conf, utils
-from google.cloud import bigquery
 
 _DATASET = "testdata"
 _TABLE = "testdata.bigquery"

src/python/aqueduct_executor/operators/connectors/tests/test_mariadb.py

@@ -1,4 +1,5 @@
 import pytest
+
 from aqueduct_executor.operators.connectors.data import dataframe, maria_db
 from aqueduct_executor.operators.connectors.tests import conf, utils