v4.4.2

[carlhiggs]

This release has updated the region configuration template. This is now better documented, with more guidance, standalone (no need to edit datasets.yml), all options present but commented out if optional (and guidance provided on how to use them). There are also more informative errors now.

You can also initialise a new study region now withing Python using the ghsci module, and drop a database within Python too.

For example,

from subprocesses import ghsci
codename = 'your_study_region_codename'
# Initialise configuration file for your region
r = ghsci.Region(codename)
# Now, you need to source and download data, documenting metadata and file paths in the configuration file
# Once that is completed, you can proceed:
r.analysis()
r.generate()
# if you've analysed and generated results for other study regions, you can compare the main results
r.compare('another_previously_processed_codename')
# if for some reason you want to drop the database for your study region to start again:
r.drop()
# You will be asked if you really want to do this!  It requires entering "ghscic" to confirm
# This doesn't remove any generated files or folders - you'll have to remove those yourself, if you want to

What's Changed

• Enhancements by @carlhiggs in https://github.com/global-healthy-liveable-cities/global-indicators/pull/320

Full Changelog: global-healthy-liveable-cities/global-indicators@v4.4.1...v4.4.2

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This discussion was created from the release v4.4.2.