Metadata-Version: 2.1
Name: flytekit
Version: 0.12.2
Summary: Flyte SDK for Python
Home-page: https://github.com/lyft/flytekit
Maintainer: Lyft
Maintainer-email: flyte-eng@lyft.com
License: apache2
Description: # Flytekit
        
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        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` or `all-spark2.4` or `all-spark3` directives which will install all the plugins and a specific Spark version.
         Please note that `all` currently defaults to Spark 2.4.x. In a future release (starting 0.15.x), `all` will be switched to use Spark 3.x.
        
        
        ```bash
        pip install "flytekit[all]"
        ```
        
        ## Development
        
        ### Recipes
        
        ```
        $ make
        Available recipes:
          setup        Install requirements
          fmt          Format code with black and isort
          lint         Run linters
          test         Run tests
          requirements Compile requirements
        ```
        
        ### Setup (Do Once)
        
        ```bash
        virtualenv ~/.virtualenvs/flytekit
        source ~/.virtualenvs/flytekit/bin/activate
        make setup
        ```
        
        ### Formatting
        
        We use [black](https://github.com/psf/black) and [isort](https://github.com/timothycrosley/isort) to autoformat code. Run the following command to execute the formatters:
        
        ```bash
        source ~/.virtualenvs/flytekit/bin/activate
        make fmt
        ```
        
        ### Testing
        
        #### Unit Testing
        
        ```bash
        source ~/.virtualenvs/flytekit/bin/activate
        make test
        ```
        
        ### Updating requirements
        
        Update requirements in [`setup.py`](setup.py), or update requirements for development in [`dev-requirements.in`](dev-requirements.in). Then, validate, pin and freeze all requirements by running:
        
        ```bash
        source ~/.virtualenvs/flytekit/bin/activate
        make requirements
        ```
        
        This will re-create the [`requirements.txt`](requirements.txt) and [`dev-requirements.txt`](dev-requirements.txt) files which will be used for testing. You will have also have to re-run `make setup` to update your local environment with the updated requirements.
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=2.7
Description-Content-Type: text/markdown
Provides-Extra: spark
Provides-Extra: spark3
Provides-Extra: sidecar
Provides-Extra: schema
Provides-Extra: hive_sensor
Provides-Extra: pytorch
Provides-Extra: all-spark2.4
Provides-Extra: all-spark3
Provides-Extra: all
