Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

conda-forge packages

Open
#33 2 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
anaconda, python
Domain
build-system

Research direction

Read the conda-forge adding_pkgs documentation first, then inspect DSS_Python's current packaging and the decoupled DSS C-API build setup. Run the basic DSS_Python tests mentioned in the issue; done means a working conda-forge recipe and passing package tests, with support considerations addressed for the listed platforms.

Written by the indexing model from the issue text.

Description

⚙️ backend 📦 packaging

Moving my comment below into a new ticket now that conda packages are available at https://anaconda.org/dss-extensions/dss_python


It's a good idea to revisit this later, providing a conda-forge recipe. Conda-forge dropped 32-bit packages a while ago, but providing DSS_Python and OpenDSSDirect.py on conda-forge is valuable. The 32-bit packages would still be available on PyPI (they're useful especially for testing).

For me, conda itself has been kind of a letdown the past few years. I imagined the commercial interest doesn't align well with it. The Anaconda.org repositories frequently have issues, reported both for DSS_Python (most people download it from PyPI anyway) and NILMTK (the recommended install method is conda due to the dependencies).

Conda-build, specifically, is really bad on Windows. Even if I can build normal/wheel packages easily on Windows, conda-build craps itself on the minimum unexpected thing that Anaconda didn't expect. There are many unresolved tickets with no useful feedback, some for multiple years.

Some third-party projects like Mamba (replaces the conda installation tool) and Boa (replaces conda-build) might help things.

To alleviate things and save my time, I'll investigate conda-forge tooling and settings since it should reduce the maintenance of conda-packages here. If successful, might be worth to officially submit the packages to the conda-forge repository. Conda-forge also supports ARM64 and (limited) PyPy, which the official conda repos don't.

Docs: https://conda-forge.org/docs/maintainer/adding_pkgs.html

Since we decoupled DSS C-API builds from DSS_Python a while ago, shouldn't be too hard. Before submitting the new packages to conda-forge, it's better to provide some basic tests in DSS_Python too.

About PyPy:


EDIT: there is now (Feb 2024) whl2conda; not sure it that's acceptable for conda-forge, but it's an option if we want to distribute conda packages again

Dominant language
Python
Stars
78
Forks
8
PR merge metrics
No merged PRs in 30d

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from dss-extensions/DSS-Python

All issues in dss-extensions/DSS-Python

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.