This repo is a holding area for recipes destined for a conda-forge feedstock repo. To find out more about conda-forge, see https://github.com/conda-forge/conda-smithy.
Failures with the above job are often caused by API rate limits from the various services used by conda-forge. This can result in empty feedstock repositories and will resolve itself automatically. If the issue persists, support can be found on Zulip.
- Fork this repository.
- Make a new folder in
recipesfor your package. Look at the example recipe, our documentation and the FAQ for help. - Open a pull request. Building of your package will be tested on Windows, Mac and Linux.
- When your pull request is merged a new repository, called a feedstock, will be created in the github conda-forge organization, and build/upload of your package will automatically be triggered. Once complete, the package is available on conda-forge.
pixi is a project based environment and task runner optimized for conda. Several of
the local workflows and their dependencies described below are captured in
pixi.toml. Install pixi via the documented approaches,
or via conda/mamba/micromamba:
$CONDA_EXE install -c conda-forge pixiSee the available tasks with pixi task list.
The script build-locally.py will guide you through the local debugging process. This script
will then launch the platform-specific scripts, which support some key environment variables in
macOS and Windows:
MINIFORGE_HOME: Where the build tools will be installed. Defaults to~/Miniforge3.CONDA_BLD_PATH: Where the build artifacts will be kept. Defaults to~/Miniforge3/conda-bldon macOS andC:\bldon Windows.
On Linux, everything runs in a Docker container. The staged-recipes directory is mounted as a volume. The resulting artifacts will be available under build_artifacts in the repository directory.
build-locally.py can be run with any recent Python, or via a pixi task:
pixi run build-linux: will launch a Docker container, provision all the necessary tools and build your recipe for Linux.pixi run build-osx: will provision a conda environment with the necessary tools to build your recipe for macOS. This involves fetching and caching the necessary Apple SDKs.pixi run build-win: will provision a conda environment with the necessary tools to build your recipe for Windows.
These tasks will pass any extra arguments to build-locally.py, including --help. The resulting
artifacts will be available under build_artifacts.
grayskull can generate recipes from Python packages on PyPI or R packages on CRAN. The user should review the recipe generated, especially the license and dependencies.
Use one of:
- manually
- install
grayskull:conda install -c conda-forge grayskull - generate recipe:
cd recipes && grayskull pypi PACKAGE_NAME_ON_PYPI_HERE [PACKAGE_NAME_ON_PYPI_HERE...]cd recipes && grayskull cran PACKAGE_NAME_ON_CRAN_HERE [PACKAGE_NAME_ON_CRAN_HERE...]
- install
- with
pixi:- generate recipe
pixi run pypi PACKAGE_NAME_ON_PYPI_HERE [PACKAGE_NAME_ON_PYPI_HERE...] - generate recipe
pixi run cran PACKAGE_NAME_ON_CRAN_HERE [PACKAGE_NAME_ON_CRAN_HERE...]
- generate recipe
The conda-smithy package provides
helpful linters that can save CI resources by catching known issues up-front.
Use one of:
- manually
- install
conda-smithy:conda install -c conda-forge conda-smithy - lint recipes:
conda-smithy recipe-lint --conda-forge recipes/*
- install
- with
pixi:- lint recipes:
pixi run lint
- lint recipes:
NOTE
conda-smithyis frequently updated with current best practices. Ensure using the latest with:
$CONDA_EXE upgrade conda-smithypixi upgrade --feature conda-smithy
Look at one of these examples in this repository and modify it as necessary.
Follow the order of the sections in the example recipe. If you make a copy of example recipe, please remove the example's explainer comments from your recipe. Add your own comments to the recipe and build scripts to explain unusual build behavior or recipe options.
If there are details you are not sure about please open a pull request. The conda-forge team will be happy to answer your questions.
If your package is on PyPI, you can get the sha256 hash from your package's page on PyPI; look for the SHA256 link next to the download link for your package.
You can also generate a hash from the command line on Linux (and Mac if you install the necessary tools below). If you go this route, the sha256 hash is preferable to the md5 hash.
To generate the md5 hash: md5 your_sdist.tar.gz
To generate the sha256 hash: openssl sha256 your_sdist.tar.gz
You may need the openssl package, available on conda-forge:
conda install openssl -c conda-forge
Use the skip key in the build section along with a selector:
build:
skip: true # [win]A full description of selectors is in the conda docs.
If the package can otherwise be noarch you can also skip it by using virtual packages.
Note: As the package will always be built on linux, it needs to be at least available on there.
The build number is used when the source code for the package has not changed but you need to make a new build. For example, if one of the dependencies of the package was not properly specified the first time you build a package, then when you fix the dependency and rebuild the package you should increase the build number.
When the package version changes you should reset the build number to 0.
No, you do not. The main purpose of the test section is to test whether this conda package was built and installed correctly (not whether the upstream package contains bugs).
Short answer: yes. Long answer: In principle, as long as your dependencies are in at least one of your user's conda channels they will be able to install your package. In practice, that is difficult to manage, and we strive to get all dependencies built in conda-forge.
This should be the default install line for most Python packages. This is preferable to python setup.py because it handles metadata in a conda-friendlier way.
In many cases, no. Python packages almost never need it. If the build can be done with one line you can put it in the script line of the build section.
The maintainers "job" is to:
- keep the feedstock updated by merging maintenance PRs from conda-forge's bots;
- keep the package updated by bumping the version whenever there is a new release;
- answer questions about the package on the feedstock issue tracker.
When a PR of recipe(s) is ready to go, it is merged into main. This will trigger a CI build specially designed to convert the recipe(s). However, for any number of reasons the recipe(s) may not be converted right away. In the interim, the recipe(s) will remain in main until they can be converted. There is no action required on the part of recipe contributors to resolve this. Also it should have no impact on any other PRs being proposed. If these recipe(s) pending conversion do cause issues for your submission, please ping conda-forge/core for help.
Sometimes, some of the CI tools' builds fail due to no error within your recipe. If that happens, you can trigger a rebuild by re-creating the last commit and force pushing it to your branch:
# edit your last commit, giving it a new time stamp and hash
# (you can just leave the message as it is)
git commit --amend
# push to github, overwriting your branch
git push -fIf the problem was due to scripts in the staged-recipes repository, you may be asked to "rebase" once these are fixed. To do so, run:
# If you didn't add a remote for conda-forge/staged-recipes yet, also run
# these lines:
# git remote add upstream https://github.com/conda-forge/staged-recipes.git
# git fetch --all
git rebase upstream/main
git push -f12. My pull request passes all checks, but hasn't received any attention. How do I call attention to my PR? What is the customary amount of time to wait?
Thank you very much for putting in this recipe PR!
This repository is very active, so if you need help with a PR, please let the right people know. There are language-specific teams for reviewing recipes.
| Language | Name of review team |
|---|---|
| python | @conda-forge/help-python |
| python/c hybrid | @conda-forge/help-python-c |
| r | @conda-forge/help-r |
| java | @conda-forge/help-java |
| nodejs | @conda-forge/help-nodejs |
| c/c++ | @conda-forge/help-c-cpp |
| perl | @conda-forge/help-perl |
| Julia | @conda-forge/help-julia |
| ruby | @conda-forge/help-ruby |
| other | @conda-forge/staged-recipes |
Once the PR is ready for review, please mention one of the teams above in a
new comment. i.e. @conda-forge/help-some-language, ready for review!
Then, a bot will label the PR as 'review-requested'.
Due to GitHub limitations, first time contributors to conda-forge are unable
to ping conda-forge teams directly, but you can ask a bot to ping the team
using a special command in a comment on the PR to get the attention of the
staged-recipes team. You can also consider asking on our Zulip chat
if your recipe isn't reviewed promptly.
All apologies in advance if your recipe PR does not receive prompt attention. This is a high volume repository and the reviewers are volunteers. Review times vary depending on the number of reviewers on a given language team and may be days or weeks. We are always looking for more staged-recipe reviewers. If you are interested in volunteering, please contact a member of @conda-forge/core. We'd love to have your help!
There's no changelog file, but the following git command gives a good overview of the recent changes in the repository:
$ git log --merges -- ':!recipes'