cftime

Time-handling functionality from netcdf4-python


Keywords
cf-conventions, netcdf, netcdftime, time
Licenses
MIT/GPL-3.0
Install
conda install -c anaconda cftime

Documentation

cftime

Time-handling functionality from netcdf4-python

Linux Build Status Windows Build Status PyPI package Coverage Status Tag Status Release Status Commits Status

News

For details on the latest updates, see the Changelog.

3/16/2020: version 1.1.1 released. Fix bug in microsecond formatting, ensure identical num2date results if input is an array of times, or a single scalar (issue #143).

2/12/2020: version 1.1.0 released. cftime.datetime instances are returned by default from num2date (instead of returning python datetime instances where possible (issue #136)). num2pydate convenience function added (always returns python datetime instances, issue #134). Fix for fraction seconds in reference date string (issue #140). Added daysinmonth attribute (issue #137).

10/25/2019: version 1.0.4.2 released (fix for issue #126).

10/21/2019: version 1.0.4 released.

12/05/2018: version 1.0.3.4 released (just to fix a problem with the source tarball on pypi).

12/05/2018: version 1.0.3.1 released. Bugfix release (fixed issue with installation when cython not installed, regression on 32-bit platforms, workaround for pandas compatibility).

12/01/2018: version 1.0.3 released. Test coverage with coveralls.io, improved round-tripping accuracy for non-real world calendars (like 360_day).

10/27/2018: version 1.0.2 released. Improved accuracy (from approximately 1000 microseconds to 10 microseconds on x86 platforms). Refactored calendar calculations now allow for negative reference years. num2date function now more than an order of magnitude faster. months since units now allowed, but only for 360_day calendar.

08/15/2018: version 1.0.1 released.

11/8/2016: cftime was split out of the netcdf4-python package.

Quick Start

  • Clone GitHub repository (git clone https://github.com/Unidata/cftime.git), or get source tarball from PyPI. Links to Windows and OS X precompiled binary packages are also available on PyPI.

  • Make sure numpy and Cython are installed and you have Python 2.7 or newer.

  • Run python setup.py build, then python setup.py install (with sudo if necessary).

  • To run all the tests, execute py.test.

Documentation

See the online docs for more details.