Python库 | flytekit-0.11.3.tar.gz

# Flytekit [](https://pypi.python.org/pypi/flytekit/) [](https://pypi.python.org/pypi/flytekit/) [](https://pypi.python.org/pypi/flytekit/) [](https://pypi.python.org/pypi/flytekit/) [](https://pypi.python.org/pypi/flytekit/)  Python Library for easily authoring, testing, deploying, and interacting with Flyte tasks, workflows, and launch plans. To understand more about flyte refer to, - [Flyte homepage](https://flyte.org) - [Flyte master repository](https://github.com/lyft/flyte) ## Installation Flytekit is designed for minimal footprint, and thus some features must be installed as extras. ### Base Installation This is the lightest-weight SDK install. This installation includes everything you need to interact with Flyte. Modules include: 1. The full Flyte IDL and an additional model layer for easier extension of the data model. 2. gRPC client for communicating with the platform. 3. Implementations for authoring and extending all Flyte entities (including tasks, workflows, and launch plans). Tools include: 1. flyte-cli (Command-Line Interface for Interacting with the Flyte Platform) 2. pyflyte (Command-Line tool for easing the registration of Flyte entities) ```bash pip install flytekit ``` ### Plugin Installation #### Spark If `@spark_task` is to be used, one should install the `spark` plugin. ```bash pip install "flytekit[spark]" for Spark 2.4.x pip install "flytekit[spark3]" for Spark 3.x ``` #### Schema If `Types.Schema()` is to be used for computations involving large dataframes, one should install the `schema` extension. ```bash pip install "flytekit[schema]" ``` #### Sidecar If `@sidecar_task` is to be used, one should install the `sidecar` plugin. ```bash pip install "flytekit[sidecar]" ``` ### Pytorch If `@pytorch_task` is to be used, one should install the `pytorch` plugin. ```bash pip install "flytekit[pytorch]" ``` ### Full Installation To install all or multiple available plugins, one can specify them individually: ```bash pip install "flytekit[sidecar,spark,schema]" ``` Or install them with the `all` directive. `all` defaults to Spark 2.4.x currently. ```bash pip install "flytekit[all]" ``` ## Testing Flytekit is Python 2.7+ compatible, so when feasible, it is recommended to test with both Python 2 and 3. ### Unit Testing #### Setup (Do Once) ```bash virtualenv ~/.virtualenvs/flytekit source ~/.virtualenvs/flytekit/bin/activate python -m pip install -r requirements.txt python -m pip install -U ".[all]" ``` #### Execute ```bash source ~/.virtualenvs/flytekit/bin/activate python -m pytest tests/flytekit/unit shellcheck **/*.sh ```