Flyte SDK for Python
Project description
# Flytekit
Library for easily authoring, testing, deploying, and interacting with Flyte tasks, workflows, and launch plans.
## 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 `
### Spark Plugin Installation
If @spark_task is to be used, one should install the spark plugin.
`bash pip install flytekit[spark] `
### Schema Plugin Installation
If Types.Schema() is to be used for computations involving large dataframes, one should install the schema extension.
`bash pip install flytekit[schema] `
### Sidecar Plugin Installation
If @sidecar_task is to be used, one should install the sidecar plugin.
`bash pip install flytekit[sidecar] `
### 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.
`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 `
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