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add 1% threshold in codecove yml #2434

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merged 1 commit into from May 13, 2020

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jeromedockes
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this should reduce noise of checks failing with "+- .01%" diff coverage etc.
1% is the value used by scikit-learn

this should reduce noise of checks failing with "+- .01%" diff coverage etc.
1% is the value used by scikit-learn
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codecov bot commented May 6, 2020

Codecov Report

Merging #2434 into master will increase coverage by 0.00%.
The diff coverage is n/a.

Impacted file tree graph

@@           Coverage Diff           @@
##           master    #2434   +/-   ##
=======================================
  Coverage   92.30%   92.31%           
=======================================
  Files         180      180           
  Lines       23693    23721   +28     
  Branches     2824     2828    +4     
=======================================
+ Hits        21871    21897   +26     
- Misses       1186     1187    +1     
- Partials      636      637    +1     
Impacted Files Coverage Δ
nilearn/input_data/nifti_labels_masker.py 92.07% <0.00%> (-1.54%) ⬇️
nilearn/stats/first_level_model/design_matrix.py 90.90% <0.00%> (ø)
...learn/input_data/tests/test_nifti_labels_masker.py 100.00% <0.00%> (ø)
nilearn/plotting/img_plotting.py 89.01% <0.00%> (+0.25%) ⬆️

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@bthirion bthirion left a comment

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Thx.

patch:
default:
# Be tolerant on slight code coverage diff on PRs to limit
# noisy red coverage status on github PRs.
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Is it worth also including the comment from sklearn about using the browser extension ?

# Note The coverage stats are still uploaded
# to codecov so that PR reviewers can see uncovered lines
# in the github diff if they install the codecov browser
# extension:
# https://github.com/codecov/browser-extension

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@emdupre emdupre left a comment

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Small, non-substantive question. But regardless, I think this will make a big difference to the contributor experience ! Thanks !!

@jeromedockes
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jeromedockes commented May 6, 2020 via email

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emdupre commented May 7, 2020

You're right; I think it's outdated !

I remembered using the extension at some point (I think I installed it on an older computer), but it looks like it's totally deprecated, now. Maybe worth an issue in sklearn :)

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3 participants