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Getting Started

Weather forecast oriented Python library to process xarray Datasets.

Features

  • Grid to points interpolations routines

  • Temporal interpolation routines

  • Spatial and temporal aggregation routines

  • Ensemble and spatial statistics

  • Configurable data model (dimension, coordinate and variable names) to support many data conventions

  • And much more

Development Setup with Poetry

Building the Project

$ cd grid-process
$ poetry install

Run Tests

$ poetry run pytest

Run Quality Tools

$ poetry run pylint grid_process
$ poetry run mypy grid_process
$ poetry run ruff format

Generate Documentation

$ poetry run sphinx-build doc doc/_build

Then open the index.html file generated in grid-process/doc/_build/.

Build wheels

$ poetry build

Using the Library

To install grid-process in your project, run this command in your terminal:

$ poetry add grid-process

You can then use the library in your project through

import grid_process

Migrating from gridefix-process

  • Package and import name: gridefix-process / gridefix_process became grid-process / grid_process.

  • Environment variable prefix: GRIDEFIX_PROCESS__ became GRID_PROCESS__ (e.g. GRID_PROCESS__data_model__validtime).

  • Versioning restarts at 1.0.0; the last internal release was gridefix-process 6.0.1.

Release the Project

The project follows the GitOps concept: releases are triggered whenever a Git TAG is created.

The TAG must follow the semantic version format and PEP 440 , otherwise the release task will fail.

Follow these steps to create a new release:

  • Adapt CHANGELOG.rst with release information

  • Adapt doc/_static/switcher_config.json adding the new documentation URL for the release

  • Create a new Release in the Github project

Metadata

Release files for grid-process 1.0.0

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