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conda-export

An alternative to conda env export that helps create portable environment specifications with minimum number of packages.

Conda-export creates environment specifications which contain only top-level (non-transient) dependencies. It tries to minimize specific version information and total number of packages, so that the resulting spec maximizes upgradability. At the same time, it respects specific package versions that were used while creating the environment. If, at some point, you installed a package with explicit version (e. g. conda install pytorch=1.9.0), conda-export will include this specific version in the resulting spec file.

Installation

It makes sense to install conda-export into base environment and call it from there, since it would be weird to install conda into your actual working env.

conda install conda-export -n base -c conda-forge

Usage

conda-export -n [env name] -f [optional output file]

If -f is not specified, dumps the spec to the console.

How it works

This is the exact algorithm that is used to export environment specifications:

  1. conda-leaves ← make a dependency graph of all conda packages and select top-level ones. Exclude packages that were installed with pip.
  2. versioned_hist ← execute conda env export --from-history to get only those packages that were explicitly installed by user with conda create or conda install. Filter packages to leave only those with explicit version specified.
  3. conda_pip ← execute conda env export and get packages that were installed with pip and not conda.
  4. pip_leaves ← execute pip list --not-required to get top-level packages from pip's perspective.
  5. Compile the final list as follows:
    • conda dependencies: conda_leaves.union(versioned_hist)
    • pip dependencies: conda_pip.intersection(pip_leaves)

What about exactly reproducible environments?

conda-export is not suited for creating reproducible environments. Please use conda-lock with environment specs generated from conda-export in order to create multi-platform lock files that contain exact package versions.

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  • Python 100.0%