New option --use-source-timestamp

[mwouts]

Fixes #784

[mwouts]

Hi @DancingQuanta, @Midnighter, would you like to give a try at this PR that introduces a new --use-source-timestamp argument? Does it improve your experience of using jupytext together with make?

NB: to install the version locally, use

pip install git+https://github.com/mwouts/jupytext.git@use_source_timestamp

See https://jupytext.readthedocs.io/en/latest/developing.html for more details. Thanks!

[codecov]

Codecov Report

Merging #790 (2b2abc7) into master (1d63611) will increase coverage by 0.01%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #790      +/-   ##
==========================================
+ Coverage   99.11%   99.13%   +0.01%     
==========================================
  Files         106      106              
  Lines       10100    10138      +38     
==========================================
+ Hits        10011    10050      +39     
+ Misses         89       88       -1     

Impacted Files	Coverage Δ
jupytext/cli.py	96.17% <100.00%> (+0.08%)	⬆️
tests/test_cli.py	100.00% <100.00%> (ø)
jupytext/paired_paths.py	98.49% <0.00%> (+0.75%)	⬆️

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[Midnighter]

Thank you for the quick response @mwouts.

I've tried this branch and the --use-source-timestamp works as advertised for me.

I also tried it without that flag, jupytext --to ipynb notebook.py, with the py:percent and ipynb files not being in sync and it doesn't update the timestamp of the .py file any longer while generating the .ipynb with the current time. This is what I needed for my workflow. Thanks a lot again.

[mwouts]

Thank you @Midnighter for your feedback! Glad it works as expected 😄 I'll fix (I mean... ignore) the sub-micro second timestamp issue on mac os (https://github.com/mwouts/jupytext/pull/790/checks?check_run_id=2702174937) and merge this

dest_timestamp = test_ipynb.stat().mtime
>       assert src_timestamp == dest_timestamp
E       assert 1622323297.7878923 == 1622323297.787892

[Midnighter]

Since you use pytest, you could use pytest.approx here.

[mwouts]

Oh that's right... I like very much pytest.approx indeed! But here maybe the micro-second truncation is a bit more specific than a numerical uncertainty? Anyway thanks for commenting!

[Midnighter]

Fair point!