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.
- Fork this repository.
- Make a new folder in
recipesfor your package. Look at the example recipe and our 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 create 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.
There are two ways to get started:
a. If it is a python package you can generate a skeleton as a starting point with
conda skeleton pypi your_package_name. You do not have to use skeleton, and the
recipes produced by skeleton will need to be edited.
b. Look at one of these examples in this repository and modify it as necessary.
Your final recipe should have no comments and follow the order in the example.
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 md5 hash from your package's page on PyPI; look for the md5 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 you have a package which links against numpy you need to build and run against the same version of numpy.
Putting numpy x.x in the build and run requirements ensure that a separate package will be built for each
version of numpy that conda-forge builds against.
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.
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.
8. When or why do I need to use python setup.py install --single-version-externally-managed --record record.txt?
These options should be added to setup.py if your project uses setuptools. The goal is to prevent setuptools from creating an egg-info directory because they do not interact well with conda.
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 eventual maintenance PRs from conda-forge's bots;
- keep the package updated by bumping the version whenever there is a new release;
- answer eventual question about the package on the feedstock issue tracker.