Skip to content

conda-pypi

conda-pypi is a conda plugin that installs PyPI packages into a conda environment by converting their sdists or wheels into the .conda format at install time. The conda solver tracks every package the plugin installs, which closes the long-standing gap where pip-installed packages were invisible to conda and the two views of the environment would drift apart. As of conda 26.5.3, the conda-pypi channel integrates with the standard conda install command, enabling a single solve across conda-forge and PyPI packages without a separate pip step.

Warning

conda-pypi is in public beta (June 2026). The plugin is suitable for experimentation and non-critical workloads, but the Conda team does not yet recommend it for production environments.

Why conda-pypi Exists

Mixing conda and pip in a single environment is a recurring source of broken installs. Conda’s dependency solver only sees packages it installed; pip’s only sees packages it installed. When the two install overlapping dependencies, conda can overwrite pip-installed files, pip can leave conda’s metadata stale, and conda update afterward can produce an environment that no longer matches either tool’s record of it. The conventional workaround is the pip-last pattern: install everything available on conda channels first, run pip install for whatever is left, and never run a conda command in that environment again. The pattern works but is fragile and undocumented in the environment itself.

conda-pypi replaces the pattern with a single tool that records PyPI installs the same way conda records its own. Every PyPI package becomes a .conda artifact with its metadata indexed in the environment, so the solver sees it on subsequent operations. The plugin also installs an EXTERNALLY-MANAGED marker (the PEP 668 mechanism that Debian uses to protect the system Python) so accidental pip install invocations are refused with a message pointing at conda pypi install instead.

Installation

conda-pypi requires conda 26.5.3 or newer and the rattler solver. On a recent Miniforge, one command pulls in both:

conda install -n base "conda>=26.5.3"

The upgrade transaction pulls conda-pypi and conda-rattler-solver in as dependencies. After the upgrade, configure the rattler solver and the conda-pypi channel:

conda config --set solver rattler
conda config --append channels conda-pypi

conda --version should report 26.5.3 or newer when the upgrade completes. No shell restart is required.

The conda-pypi Channel

The conda-pypi channel hosted by Anaconda publishes metadata for approximately 600,000 pure Python wheels pre-validated against conda packaging conventions. The wheel files themselves are still fetched from pypi.org at install time. The channel is free for all use and is not subject to the Anaconda commercial-license terms that apply to the default channel.

Appending the channel globally (the conda config --append channels conda-pypi step in Installation) enables the native conda install integration. This is the recommended configuration as of conda 26.5.3.

Usage

Native conda install

With the conda-pypi channel appended to the global config (see Installation), the standard conda install command resolves conda-forge and PyPI packages together:

conda install scipy requests

scipy resolves from conda-forge; requests, if not available on any conda channel, resolves from PyPI and is converted to a .conda artifact before being installed. Packages from both sources are tracked in conda-meta on equal footing.

Multi-platform lockfiles work the same way:

conda list --explicit --from-history > environment.lock

Pass --platform linux-64, --platform osx-arm64, etc. to generate platform-specific lockfiles.

Subcommands

conda pypi install

Installs PyPI packages into the active or named environment using a hybrid resolution strategy. Explicitly requested packages always come from PyPI and are converted to .conda format on the fly. Dependencies follow a conda-first preference: if a dependency exists on a configured conda channel, conda installs that build; otherwise the dependency is also pulled from PyPI and converted.

Use this subcommand when you need flags specific to PyPI installs (editable installs, custom index URLs) that the standard conda install command does not expose.

Common flags:

  • -n, --name ENV (parent flag on conda pypi) targets a named environment without activating it.
  • -p, --prefix PATH targets an environment by full path.
  • -i, --index-url URL adds a PyPI index URL; can be repeated for multiple indexes.
  • --ignore-channels forces every package, including dependencies, to be resolved from PyPI rather than the configured conda channels.
  • -e, --editable PATH installs a local project in editable mode by building a .conda artifact from the source tree and linking it into the environment.
  • -d, --dry-run (parent flag on conda pypi) reports the resolved install plan without writing files. Invoked as conda pypi -d install <pkg>.

Package names are translated between PyPI and conda conventions using the Grayskull name-mapping tables.

conda pypi convert

Builds a local Python project, sdist, or wheel into a .conda artifact without installing it. Useful for preparing offline installs, building internal mirrors, or inspecting how the plugin would translate a package before committing to an install.

The positional argument is a path on the local filesystem, not a PyPI package name. Convert a remote package by downloading the wheel first (for example with pip download) and pointing conda pypi convert at the local file.

Common flags:

  • --output-folder DIR writes the converted artifacts to a directory rather than the conda package cache.
  • -e, --editable builds the project as an editable package.
  • -t, --test-dir DIR injects a test-files directory into the converted conda package.
  • --name-mapping FILE points at a JSON file containing a custom PyPI-to-conda name mapping.

Environment Protection

When conda-pypi is installed into an environment, the plugin places an EXTERNALLY-MANAGED file in the environment’s standard library location. Subsequent pip install calls against that environment fail with the PEP 668 rejection message, which conda-pypi customizes to direct users to conda pypi install instead. See How to fix the externally-managed-environment error for the underlying mechanism.

The warning can be disabled per environment with conda config --set plugins.conda_pypi_pip_warning false, though doing so reintroduces the failure mode the plugin is designed to prevent.

Limits

  • Pure Python wheels only. Packages with platform-specific compiled extensions are not supported. Compiled scientific stacks (NumPy, SciPy, PyTorch, CuPy) must come from conda-forge or another conda channel.
  • PEP 508 dependency markers are partially handled. The extra == "..." form is split into per-extra dependency tables in the converted .conda artifact. Other environment markers (python_version, sys_platform, os_name) are dropped during conversion, which can produce a thinner dependency graph than the wheel itself would install via pip.
  • The wheel-channels feature is experimental. A draft Conda Enhancement Proposal defines how a channel can expose wheels directly in its repodata under a v3.whl section. The conda-pypi plugin implements this path, but the specification is still under discussion and the on-disk format is not guaranteed to remain stable.
  • Security inherits PyPI’s model. The channel only republishes metadata; the wheel files themselves come from pypi.org without independent vetting. Supply-chain controls that apply to PyPI (trusted publishing, attestations, package signing) also apply here. Conda-forge’s screened feedstock process does not.

Related Approaches

  • pixi resolves conda-forge and PyPI packages together in a single lockfile, using uv internally for the PyPI side. The model is integrated from the start rather than bolted onto conda after the fact; pixi is the alternative to evaluate when both PyPI and compiled-wheel interop matter and a project-local workflow is acceptable. See uv vs pixi vs conda for scientific Python.
  • The pip-last convention is the long-standing workaround that conda-pypi replaces. Install every available dependency via conda first, run pip install once for the remainder, and avoid further conda operations in the environment. It still works and is appropriate for teams that cannot adopt beta tooling, but it leaves no record in the environment that pip was used.

Pros

  • Standard conda install resolves conda-forge and PyPI packages in one operation; no pip step, no separate tool.
  • The conda solver tracks PyPI packages on the same footing as conda packages, eliminating the silent-drift failure mode of mixed environments.
  • Hybrid resolution prefers conda-channel builds for dependencies, which keeps compiled libraries on a tested build path even when the requested package is PyPI-only.
  • EXTERNALLY-MANAGED enforcement prevents accidental pip install from corrupting environments after the fact.
  • Editable installs work the same way as pip install -e, supporting standard development workflows.
  • The conda-pypi channel covers approximately 600,000 pure Python wheels and is free for all use without Anaconda commercial-license obligations.

Cons

  • Beta software; not recommended for production by its maintainers.
  • Pure Python wheels only; compiled extensions require conda-forge or another conda channel.
  • Requires conda 26.5.3 plus the rattler solver, which is newer than many existing installations.
  • PEP 508 environment markers other than extra == are dropped during conversion.
  • The wheel-channels feature depends on a CEP still under discussion.

Learn More

Handbook pages

Official documentation

Last updated on