Skip to main content

Batch generation from Xarray objects

Project description

github actions build status code coverage docs pypi conda-forge license

Xbatcher is a small library for iterating Xarray DataArrays and Datasets in batches. The goal is to make it easy to feed Xarray objects to machine learning libraries such as PyTorch or TensorFlow. View the docs for more info.

Installation

Xbatcher can be installed from PyPI as:

python -m pip install xbatcher

Or via Conda as:

conda install -c conda-forge xbatcher

Or from source as:

python -m pip install git+https://github.com/xarray-contrib/xbatcher.git

Documentation

Documentation is hosted on ReadTheDocs: https://xbatcher.readthedocs.org

License

Apache License 2.0, see LICENSE file.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

xbatcher-0.3.0.tar.gz (45.2 kB view details)

Uploaded Source

Built Distribution

xbatcher-0.3.0-py3-none-any.whl (22.2 kB view details)

Uploaded Python 3

File details

Details for the file xbatcher-0.3.0.tar.gz.

File metadata

  • Download URL: xbatcher-0.3.0.tar.gz
  • Upload date:
  • Size: 45.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for xbatcher-0.3.0.tar.gz
Algorithm Hash digest
SHA256 f382830d2214643c199e1763c0fc96b472eeb3a50d6878191476bf343439c005
MD5 e79581ba4fe1ba9950e6bdd7984fe718
BLAKE2b-256 b9bae2fa0ebff6d7debded2788db2508288cbc8756a7bf364a125e4bc77b0b64

See more details on using hashes here.

File details

Details for the file xbatcher-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: xbatcher-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 22.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for xbatcher-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 7c3a2ad0850349eefb0d4573361db825d04c2f90c13e537f5b01b6c9882d16fd
MD5 1092200b96323bf804ac86b5573ccf38
BLAKE2b-256 00283d5d3c5f35742ca35382da872fe6d394402ecb80339018f789aca4a20594

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page