Use pip only when you cannot find packages on conda
If you can't find a package on conda (see Prioritize conda to install packages), then
pip can serve as a viable alternative for adding packages to your environment.
name: some_env_name channels: - conda-forge dependencies: - python=3.8 - pandas - scipy - numpy - ... - pip: - some_pip_package==2.1
Some things to note here.
pip section uses the same syntax for setting versions as
requirements.txt. It uses
== rather than
conda uses. This is because its contents are dumped to a temporary text file that gets parsed by
Secondly, keep monitoring for when the package shows up on
conda-forge, as that will help you retain the advantages of installing packages by a single package manager.
Prioritize conda to install packages
As a matter of practical advice, I usually prefer conda-installed packages over pip-installed packages. Here are the reasons why.
Firstly, Conda packages have their versions and dependencies tracked properly, and so the conda dependency solver (or its drop-in replacement mamba) can be used to pick out the right set of packages.
Secondly, on occasion one might need to use packages that come from multiple languages. There have been projects I worked on that used Python calling out to R packages. Conda was designed to handle mutliple programming languages in the same environment, and will help you pull down packages used in multiple languages, and all of their dependencies.
Thirdly, as the suite of packages that become available in conda-forge increases, and as the conda-forge developers increase the amount of tooling to automatically mirror language-specific packages on conda-forge, it becomes progressively easier to rely primarily on the conda package manager. This idea relates to the notion of specifying single sources of truth for categories of stuff.
To do so, you specify your environment using
environment.yml files. These are used by the
conda package manager to download the desired packages, their dependencies, and their appropriate versions onto your machine.
When you want to search for a package, before you assume it's available on PyPI, search for it on Anaconda.org. You can do this by either running:
conda search package_name
or by going to the Anaconda.org website and search for the package that you're interested in.
Also, be sure you check the GitHub repository under the "Installation" instructions for anything that suggests that you could install the package from
Once you've found it, add the package to your
environment.yml file under the
If you can't find a conda-installable version of the package, then consider using pip. (see: Use pip only when you cannot find packages on conda)