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  • dazza-codes · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
485922055 https://github.com/pydata/xarray/issues/2888#issuecomment-485922055 https://api.github.com/repos/pydata/xarray/issues/2888 MDEyOklzc3VlQ29tbWVudDQ4NTkyMjA1NQ== dazza-codes 240623 2019-04-23T18:31:02Z 2019-04-23T18:31:02Z NONE

WRT points: - right, it's not tracked and that's the motivation for this issue - just because it's not widely done is not a reason to ignore it and does not justify not doing it - IMO it is not widely done because many science projects are lapse in managing version dependencies using SEM-VER best practices, leaving it to the consumers, who are often clueless about these matters, to wonder why their project crashes with one or more dependencies that they don't understand nor care to dive into at any depth - many science projects avoid the whole problem by lagging with 0.x releases, failing to commit to stable, reliable APIs with at least 1.x releases - by adopting better SEM-VER practices, across the board, it should provide more confidence to arrive at 1.x releases. But this is not my battle to wage, I'm just the messenger for thousands of consumers who have no idea what versions are compatible or not.

 
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   Optional extras to manage dependencies 432058005
485868641 https://github.com/pydata/xarray/issues/2888#issuecomment-485868641 https://api.github.com/repos/pydata/xarray/issues/2888 MDEyOklzc3VlQ29tbWVudDQ4NTg2ODY0MQ== dazza-codes 240623 2019-04-23T16:04:41Z 2019-04-23T16:18:40Z NONE

Since xarray is operating as a meta-package with various wrappers, it is the only place that can apply version compatibility on it's dependencies. If there are optional dependencies, the python package extras are the process to manage them (not a README). The SEM-VER standards allow specification of more than one version for any dependency (so long as it complies with SEM-VER standards).

Essentially, this is a request for more sophistication in the setup.py file - https://github.com/pydata/xarray/blob/master/setup.py

Consider, for example, how Apache Airflow does it: - https://github.com/apache/airflow/blob/master/setup.py - https://github.com/apache/airflow/blob/master/setup.py#L353

 
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   Optional extras to manage dependencies 432058005

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