Skip to main content
Join the official 2019 Python Developers SurveyStart the survey!

Reading and Writing netCDF files according to CF conventions

Project description

https://travis-ci.org/TUW-GEO/pynetCF.svg?branch=master https://coveralls.io/repos/github/TUW-GEO/pynetCF/badge.svg?branch=master https://badge.fury.io/py/pynetcf.svg https://readthedocs.org/projects/pynetcf/badge/?version=latest

Basic python classes that map to netCDF files on disk written according to the Climate and Forecast metadata conventions

This is a first draft which has a lot of room for improvements, this is especially true for the time series based representations.

Citation

https://zenodo.org/badge/DOI/10.5281/zenodo.846767.svg

If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version.

Please select your specific version at https://doi.org/10.5281/zenodo.846767 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility.

You can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning

Installation

This package should be installable through pip:

pip install pynetcf

Contribute

We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes.

Development setup

For Development we also recommend a conda environment. You can create one including test dependencies and debugger by running conda env create -f environment.yml. This will create a new pynetcf environment which you can activate by using source activate pynetcf.

Guidelines

If you want to contribute please follow these steps:

  • Fork the pynetCF repository to your account
  • make a new feature branch from the pynetCF master branch
  • Add your feature
  • Please include tests for your contributions in one of the test directories. We use py.test so a simple function called test_my_feature is enough
  • submit a pull request to our master branch

Note

For now please see the tests for examples on how to use the classes.

Project details


Download files

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

Files for pynetcf, version 0.1.19
Filename, size File type Python version Upload date Hashes
Filename, size pynetcf-0.1.19.tar.gz (37.5 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page