Mailman 3 January 2023 - Pandas-dev

pandas new infrastructure (OVH donation)
by Marc Garcia Sept. 21, 2024

Sept. 21, 2024

Hi all, pandas has received a donation from OVHcloud <https://www.ovhcloud.com/> to support the project infrastructure, with OVHcloud public cloud credits (an initial amount of 10,000 EUR for a period of one year). OVH is open to sponsor longer term and also other projects of the ecosystem (or NumFOCUS as a whole), but we started with this to have feedback at a smaller scale first. The credits will be used initially for: - Hosting of the pandas website - Running the pandas benchmarks - Speeding up the project CI I detail next what I have in mind to set up for each. If anyone is interested in getting involved, or has ideas, comments... please let me know. I'll publish updates here as there is progress on this. Website: I'm planning to experiment on splitting the website in two (it'll be transparent for users). The website and the stable docs which receive most of the traffic can probably be stored in Cloudflare pages. We're already using Cloudflare as a CDN, so instead of using it as a cache, we can publish the documents there. The rest of the docs (old versions and the dev version) can be hosted in bucket storage of the OVHcloud. Response times may be a bit slower, but our website is bigger than the Cloudflare quota, and having old docs rarely accessed in a CDN seems unnecessary anyway. - Benchmarks: OVHcloud instances have guaranteed hardware, and we'll be checking if this is enough for the results of the benchmarks to be consistent over runs, or if there is too much variability and we need dedicated hardware. If consistency is good enough that would be great, since our benchmarks mostly use one core, and using dedicated hardware is likely to be a decent waste of resources, since most servers will likely have 16 cores or more. We'll discuss with OVH if dedicated hardware is needed, as at the moment their public cloud doesn't offer it (there is an alpha for providing dedicated instances, but we need to check with them). - Faster CI: Our GitHub runners are small, and most builds take around one hour or more to finish. We should be able to use bigger OVH instances for our existing CI pretty easily, via their OpenStack API and CIrun.

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Is it time for a bi-weekly pandas call?
by Marco Gorelli May 13, 2024

May 13, 2024

Currently, there's a monthly pandas call, which has been in place for several years. Seeing as there's now more people working on pandas as part of their jobs, might it be time to increase the frequency? E.g. to meet every 2 weeks, instead of once a month?

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EA Naming Conventions
by Brock Mendel Feb. 8, 2023

Feb. 8, 2023

For historical reasons we've built up an EA namespace without much internal logic in terms of what is public/private. While this isn't _that_ big of a deal, it'd be nice to make this more coherent. I see two useful options: 1) Use the traditional "an underscore means this should only be called from within self". Very few methods on the base class satisfy that characteristic, including the constructor _from_sequence. One benefit of moving to this is it would make "official" that we shouldn't be using _values_for_foo from outside EA methods. 2) Use underscores to signal to 3rd party authors whether or not there exists a working (not necessarily performant) implementation on the base class. In this scenario authors would _have_ to implement private methods, while implementing public methods would be optional. Thoughts?

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ANN: pandas v1.5.3
by Marc Garcia Jan. 20, 2023

Jan. 20, 2023

We are pleased to announce the release of pandas v1.5.3. This is a patch release in the 1.5.x series and includes some regression fixes and bug fixes. We recommend that all users in the 1.5.x series upgrade to this version. See the release notes <https://pandas.pydata.org/docs/whatsnew/v1.5.3.html> for a list of all the changes. The release can be installed from PyPI python -m pip install --upgrade pandas==1.5.3 Or from conda-forge mamba install -c conda-forge pandas==1.5.3 Please report any issues with the release on the pandas issue tracker <https://github.com/pandas-dev/pandas/issues/new/choose>. Thanks to all the contributors <https://pandas.pydata.org/docs/whatsnew/v1.5.3.html#contributors> who made this release possible.

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