Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

1.4.0 Release Organization #159

Closed
wdm0006 opened this issue Dec 25, 2018 · 17 comments
Closed

1.4.0 Release Organization #159

wdm0006 opened this issue Dec 25, 2018 · 17 comments
Assignees
Labels
Milestone

Comments

@wdm0006
Copy link
Collaborator

wdm0006 commented Dec 25, 2018

Hey all, been away from the project for a bit, but I'm going back through all of the issues and PRs worked on recently (looks like a bunch of good progress!). Special thanks to @janmotl for all of the work as primary maintainer over the past months.

Our last release was 1.3.0 on October 14th. Since then ya'll have:

  • Sped up the TargetEncoder and LeaveOneOutEncoder w/ vectorization (significantly)
  • Added support for Categorical types in many encoders
  • Implemented get_feature_names in remaining transformers
  • Improved testing coverage and quality
  • Solved edge cases in repeated column names for some transformers
  • Added support for transforming pandas Series as well as DataFrames and numpy Arrays
  • Fixed inverse transform for many encoders
  • Lots of smaller performance enhancements and code cleanups

Which I think is a quite full set of features to constitute a release. I will be opening a separate issue to discuss how we as a community can improve our release cycle, but for now will be going through open issues and tagging anything that should be included before the v1.4.0 release. Any input on what should or shouldn't be completed prior to release is welcome.

Thank you all for the work and support this year, and Happy Holidays.

@wdm0006 wdm0006 added this to the v1.4.0 milestone Dec 25, 2018
@wdm0006 wdm0006 self-assigned this Dec 25, 2018
@wdm0006
Copy link
Collaborator Author

wdm0006 commented Dec 25, 2018

So currently I have 3 bugs and one WIP PR that may be good to get resolved before a v1.4.0 release, but need to dig into them a bit further.

Bugs:

WIP PR:

@janmotl
Copy link
Collaborator

janmotl commented Jan 5, 2019

It has to be noted that v1.4.0 also introduces braking changes: arguments impute_missing and handle_unknown are now called handle_missing and handle_unknown. And their possible values have changed.

@wdm0006
Copy link
Collaborator Author

wdm0006 commented Jan 6, 2019

Hm good point, probably should be a major release then.

@amueller
Copy link
Member

amueller commented Feb 5, 2019

have you run check_estimator on these or is that not possible right now?

@janmotl
Copy link
Collaborator

janmotl commented Feb 6, 2019

It would be nice to pass 'check_estimator'.

@gammadistribution
Copy link

Hey @janmotl, do you happen to know when the new version would be released?

If there are remaining tasks, I can help to close them if desired.

@janmotl
Copy link
Collaborator

janmotl commented Feb 11, 2019

@JohnnyC08 , don't you know how to deal with "errors" like:

======================================================================
ERROR: test_inverse_transform_BothFieldsAreReturnNanWithNan_ExpectValueError (category_encoders.tests.test_basen.TestBaseNEncoder)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/travis/build/scikit-learn-contrib/categorical-encoding/category_encoders/tests/test_basen.py", line 116, in test_inverse_transform_BothFieldsAreReturnNanWithNan_ExpectValueError
    enc.inverse_transform(result)
  File "/home/travis/build/scikit-learn-contrib/categorical-encoding/category_encoders/basen.py", line 287, in inverse_transform
    "the unknown category nan when encode %s" % (col,))
UserWarning: inverse_transform is not supported because transform impute the unknown category nan when encode city

as reported at: https://travis-ci.org/scikit-learn-contrib/categorical-encoding/jobs/491609594 ?

@JohnnyC08
Copy link
Contributor

@janmotl I will pull the latest master and see if I can reproduce locally

@janmotl
Copy link
Collaborator

janmotl commented Feb 12, 2019

Beside the failing Travis CI (I didn't manage to reproduce the error with nosetest on my local computer), the code should be ready for release 2.0.0.

@wdm0006
Copy link
Collaborator Author

wdm0006 commented Apr 17, 2019

@janmotl sorry for the delay, I'll take a look at a 2.0.0 release here shortly.

@wdm0006
Copy link
Collaborator Author

wdm0006 commented Apr 17, 2019

@janmotl actually, to avoid delays like this in the future, it'd probably make sense to add you as a collaborator on PyPI.org right? If you send me your PyPI username I can add you to the project there.

@janmotl
Copy link
Collaborator

janmotl commented Apr 17, 2019

Good. My PyPI username: janmotl

@wdm0006
Copy link
Collaborator Author

wdm0006 commented Apr 17, 2019

@janmotl should be a maintainer there now, please check and let me know.

@janmotl
Copy link
Collaborator

janmotl commented Apr 18, 2019

Thank you, @wdm0006. I am now a maintainer. Do we have a procedure how to make a release?

@wdm0006
Copy link
Collaborator Author

wdm0006 commented Apr 25, 2019

@janmotl not very formally, I usually just up the version in setup.py, run update_docs.sh and use twine to publish to pypi. Would you like to give that a shot and I can help out with any issues that crop up.

@janmotl
Copy link
Collaborator

janmotl commented Apr 28, 2019

Done. Could you check it?

@wdm0006
Copy link
Collaborator Author

wdm0006 commented May 2, 2019

Looks good!

@wdm0006 wdm0006 closed this as completed May 2, 2019
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

No branches or pull requests

5 participants