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Version 7.17.3 -> conda-forge #1980

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brsolomon-deloitte opened this issue May 10, 2022 · 4 comments
Closed

Version 7.17.3 -> conda-forge #1980

brsolomon-deloitte opened this issue May 10, 2022 · 4 comments

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@brsolomon-deloitte
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Could a maintainer please upload release 7.17.3 for conda/mamba? Thank you!

Looking for: ['bokeh==2.3.3', 'boto3==1.20.54', "cudatoolkit[version='>=11.2']", 'elasticsearch-dsl==7.4.0', 'elasticsearch==7.17.3', 'matplotlib-base==3.5.1', 'nltk==3.6.7', 'imbalanced-learn==0.9.0', 'pandas==1.4.2', 'pyod==0.9.9', 'pyspark==3.2.1', 'scikit-learn==1.0.2', 'seaborn==0.11.2', 'statsmodels==0.13.2', 'tensorflow-gpu==2.7.0']


Pinned packages:
  - python 3.9.*
  - python 3.9.12


Encountered problems while solving:
  - nothing provides requested elasticsearch 7.17.3
@sethmlarson
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Hmm, is there a way we can manually trigger an upload? This one didn't get automatically opened.

@brsolomon-deloitte
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brsolomon-deloitte commented Jun 1, 2022

Hmm, is there a way we can manually trigger an upload? This one didn't get automatically opened.

I'm not sure :( but it looks like 7.17.0 is the latest 7.17.x version even though the 8.x versions are being picked up. It would be really nice to be able to keep the elasticsearch python client patch version in line with the elasticsearch version. I'm admittedly quite confused reading https://conda-forge.org/docs/maintainer/updating_pkgs.html#pushing-to-regro-cf-autotick-bot-branch, though, because as you alluded to,

When a new version of a package is released on PyPI/CRAN/.., we have a bot that automatically creates version updates for the feedstock

Though the 7.17.x versions are indeed available on PyPY.

@brsolomon-deloitte
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Hello @sethmlarson , bump on this one!

Currently no 7.17.x release past 7.17.0 are present on conda-forge.

It would be great to be able to keep the client in line with the server version.

Screen Shot 2022-09-26 at 9 53 43 AM

@sethmlarson
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I've moved this issue to conda-forge/elasticsearch-feedstock#73 as there's nothing to change on this repository. Hopefully the Conda team has a ready-made solution to our problem. 🤞

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