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| Original file line number | Diff line number | Diff line change |
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| from .task import SQLAlchemyConfig, SQLAlchemyTask |
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| import typing | ||
| from dataclasses import dataclass | ||
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| import pandas as pd | ||
| from sqlalchemy import create_engine | ||
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| from flytekit import current_context, kwtypes | ||
| from flytekit.core.base_sql_task import SQLTask | ||
| from flytekit.core.python_function_task import PythonInstanceTask | ||
| from flytekit.models.security import Secret | ||
| from flytekit.types.schema import FlyteSchema | ||
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| @dataclass | ||
| class SQLAlchemyConfig(object): | ||
| """ | ||
| Use this configuration to configure task. String should be standard | ||
| sqlalchemy connector format | ||
| (https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls). | ||
| Database can be found: | ||
| - within the container | ||
| - or from a publicly accessible source | ||
| Args: | ||
| uri: default sqlalchemy connector | ||
| connect_args: sqlalchemy kwarg overrides -- ex: host | ||
| secret_connect_args: flyte secrets loaded into sqlalchemy connect args | ||
| -- ex: {"password": {"name": SECRET_NAME, "group": SECRET_GROUP}} | ||
| """ | ||
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| uri: str | ||
| connect_args: typing.Optional[typing.Dict[str, typing.Any]] = None | ||
| secret_connect_args: typing.Optional[typing.Dict[str, Secret]] = None | ||
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| class SQLAlchemyTask(PythonInstanceTask[SQLAlchemyConfig], SQLTask[SQLAlchemyConfig]): | ||
| """ | ||
| Makes it possible to run client side SQLAlchemy queries that optionally return a FlyteSchema object | ||
| TODO: How should we use pre-built containers for running portable tasks like this. Should this always be a | ||
| referenced task type? | ||
| """ | ||
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| _SQLALCHEMY_TASK_TYPE = "sqlalchemy" | ||
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| def __init__( | ||
| self, | ||
| name: str, | ||
| query_template: str, | ||
| task_config: SQLAlchemyConfig, | ||
| inputs: typing.Optional[typing.Dict[str, typing.Type]] = None, | ||
| output_schema_type: typing.Optional[typing.Type[FlyteSchema]] = None, | ||
| **kwargs, | ||
| ): | ||
| output_schema = output_schema_type if output_schema_type else FlyteSchema | ||
| outputs = kwtypes(results=output_schema) | ||
| self._uri = task_config.uri | ||
| self._connect_args = task_config.connect_args or {} | ||
| self._secret_connect_args = task_config.secret_connect_args | ||
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| super().__init__( | ||
| name=name, | ||
| task_config=task_config, | ||
| task_type=self._SQLALCHEMY_TASK_TYPE, | ||
| query_template=query_template, | ||
| inputs=inputs, | ||
| outputs=outputs, | ||
| **kwargs, | ||
| ) | ||
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| @property | ||
| def output_columns(self) -> typing.Optional[typing.List[str]]: | ||
| c = self.python_interface.outputs["results"].column_names() | ||
| return c if c else None | ||
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| def execute(self, **kwargs) -> typing.Any: | ||
| if self._secret_connect_args is not None: | ||
| for key, secret in self._secret_connect_args.items(): | ||
| value = current_context().secrets.get(secret.group, secret.key) | ||
| self._connect_args[key] = value | ||
| engine = create_engine(self._uri, connect_args=self._connect_args, echo=False) | ||
| print(f"Connecting to db {self._uri}") | ||
| with engine.begin() as connection: | ||
| df = pd.read_sql_query(self.get_query(**kwargs), connection) | ||
| return df |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,34 @@ | ||
| from setuptools import setup | ||
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| PLUGIN_NAME = "sqlalchemy" | ||
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| microlib_name = f"flytekitplugins-{PLUGIN_NAME}" | ||
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| plugin_requires = ["flytekit>=0.17.0,<1.0.0", "sqlalchemy>=1.4.7"] | ||
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| __version__ = "0.0.0+develop" | ||
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| setup( | ||
| name=microlib_name, | ||
| version=__version__, | ||
| author="dolthub", | ||
| author_email="[email protected]", | ||
| description="SQLAlchemy plugin for flytekit", | ||
| namespace_packages=["flytekitplugins"], | ||
| packages=[f"flytekitplugins.{PLUGIN_NAME}"], | ||
| install_requires=plugin_requires, | ||
| license="apache2", | ||
| python_requires=">=3.7", | ||
| classifiers=[ | ||
| "Intended Audience :: Science/Research", | ||
| "Intended Audience :: Developers", | ||
| "License :: OSI Approved :: Apache Software License", | ||
| "Programming Language :: Python :: 3.7", | ||
| "Programming Language :: Python :: 3.8", | ||
| "Topic :: Scientific/Engineering", | ||
| "Topic :: Scientific/Engineering :: Artificial Intelligence", | ||
| "Topic :: Software Development", | ||
| "Topic :: Software Development :: Libraries", | ||
| "Topic :: Software Development :: Libraries :: Python Modules", | ||
| ], | ||
| ) |
Empty file.
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,31 @@ | ||
| from collections import OrderedDict | ||
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| from flytekit.common.translator import get_serializable | ||
| from flytekit.core import context_manager | ||
| from flytekit.core.context_manager import Image, ImageConfig | ||
| from plugins.tests.sqlalchemy.test_task import tk as not_tk | ||
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| def test_sql_lhs(): | ||
| assert not_tk.lhs == "tk" | ||
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| def test_sql_command(): | ||
| default_img = Image(name="default", fqn="test", tag="tag") | ||
| serialization_settings = context_manager.SerializationSettings( | ||
| project="project", | ||
| domain="domain", | ||
| version="version", | ||
| env=None, | ||
| image_config=ImageConfig(default_image=default_img, images=[default_img]), | ||
| ) | ||
| srz_t = get_serializable(OrderedDict(), serialization_settings, not_tk) | ||
| assert srz_t.container.args[-7:] == [ | ||
| "--resolver", | ||
| "flytekit.core.python_auto_container.default_task_resolver", | ||
| "--", | ||
| "task-module", | ||
| "plugins.tests.sqlalchemy.test_task", | ||
| "task-name", | ||
| "tk", | ||
| ] |
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