Pixi is built on top of both the conda and PyPI ecosystems.
**Conda** is a cross-platform, cross-language package ecosystem that allows users to install packages and manage environments.
It is widely used in the data science and machine learning community, but it is also used in other fields.
Its power comes from the fact that it always installs binary packages, meaning that it doesn’t need to compile anything.
This makes the ecosystem very fast and easy to use.
**PyPI** is the Python Package Index, which is the main package index for Python packages.
It is a much larger ecosystem than conda, especially because the barrier to entry for uploading packages is lower.
This means that there are a lot of packages available, but it also means that the quality of the packages is not always as high as in the conda ecosystem.
Pixi can install packages from **both** **ecosystems**, but it uses a **conda-first approach**.
The simplified process is as follows:
1. Resolve the conda dependencies.
2. Map the conda packages to PyPI packages.
3. Resolve the remaining PyPI dependencies.
## Tool Comparison
Here is a non-exhaustive comparison of the features of conda and PyPI ecosystems.
| Feature | Conda | PyPI |
| ------- | ----- | ---- |
| Package format | Binary | Source & Binary (wheel) |
| Package managers | [`conda`](https://github.com/conda/conda), [`mamba`](https://github.com/mamba-org/mamba), [`micromamba`](https://github.com/mamba-org/mamba), [`pixi`](https://github.com/prefix-dev/pixi) | [`pip`](https://github.com/pypa/pip), [`poetry`](https://github.com/python-poetry/poetry), [`uv`](https://github.com/astral-sh/uv), [`pdm`](https://github.com/pdm-project/pdm), [`hatch`](https://github.com/pypa/hatch), [`rye`](https://github.com/astral-sh/rye), [`pixi`](https://github.com/prefix-dev/pixi) |
| Environment management | [`conda`](https://github.com/conda/conda), [`mamba`](https://github.com/mamba-org/mamba), [`micromamba`](https://github.com/mamba-org/mamba), [`pixi`](https://github.com/prefix-dev/pixi) | [`venv`](https://docs.python.org/3/library/venv.html), [`virtualenv`](https://virtualenv.pypa.io/en/latest/), [`pipenv`](https://pipenv.pypa.io/en/latest/), [`pyenv`](https://github.com/pyenv/pyenv), [`uv`](https://github.com/astral-sh/uv), [`poetry`](https://github.com/python-poetry/poetry), [`pixi`](https://github.com/prefix-dev/pixi) |
| Package building | [`conda-build`](https://github.com/conda/conda-build), [`pixi`](https://github.com/prefix-dev/pixi) | [`setuptools`](https://github.com/pypa/setuptools), [`poetry`](https://github.com/python-poetry/poetry), [`flit`](https://github.com/pypa/flit), [`hatch`](https://github.com/pypa/hatch), [`uv`](https://github.com/astral-sh/uv), [`rye`](https://github.com/astral-sh/rye) |
| Package index | [`conda-forge`](https://prefix.dev/channels/conda-forge), [`bioconda`](https://prefix.dev/channels/bioconda), and more | [pypi.org](https://pypi.org) |
## `uv` by Astral
Pixi uses the [`uv`](https://github.com/astral-sh/uv) library to handle PyPI packages.
Pixi doesn't install `uv` (the tool) itself: because both tools are built in Rust, it is used as a library.
We're extremely grateful to the [Astral](https://astral.sh) team for their work on `uv`, which is a great library that allows us to handle PyPI packages in a much better way than before.
Initially, next to `pixi` we were building a library called `rip` which had the same goals as `uv`, but we decided to switch to `uv` because it quickly became a more mature library, and it has a lot of features that we need.
- [Initial blog post about announcing `rip`](https://prefix.dev/blog/pypi_support_in_pixi)
- [Blog post to announce the switch to `uv`](https://prefix.dev/blog/uv_in_pixi)
## Solvers
Because Pixi supports both ecosystems, it currently needs two different solvers to handle the dependencies.
- The [`resolvo`](https://github.com/prefix-dev/resolvo) library is used to solve the conda dependencies. Implemented in [`rattler`](https://github.com/conda/rattler).
- The [`PubGrub`](https://github.com/pubgrub-rs/pubgrub) library is used to solve the PyPI dependencies. Implemented in [`uv`](https://github.com/astral-sh/uv).
!!! Note
The holy grail of Pixi is to have a single solver that can handle both ecosystems.
Because resolvo is written to support both ecosystems, it is possible to use it for PyPI packages as well, but this is not yet implemented.
Because PyPI packages need a base environment to install into, we need to use the conda-first approach, which means that we first solve the conda dependencies, then the PyPI dependencies.
Pixi first runs the conda (`rattler`) solver, which will resolve the conda dependencies.
Then it maps the conda packages to PyPI packages, using [`parselmouth`](https://github.com/prefix-dev/parselmouth).
Then it runs the PyPI (`uv`) solver, which will resolve the remaining PyPI dependencies.
The consequence is that Pixi will install the conda package (and not the PyPI package) if both are available and specified as dependencies.
Here is an example of how this works in practice:
```toml title="pixi.toml"
[dependencies]
python = ">=3.8"
numpy = ">=1.21.0"
[pypi-dependencies]
numpy = ">=1.21.0"
```
Which results in the following output:
```output
➜ pixi list -x
Package Version Build Size Kind Source
numpy 2.3.0 py313h41a2e72_0 6.2 MiB conda https://conda.anaconda.org/conda-forge/
python 3.13.5 hf3f3da0_102_cp313 12.3 MiB conda https://conda.anaconda.org/conda-forge/
```
In this example, Pixi will first resolve the conda dependencies and install the `numpy` and `python` conda packages.
Then it will map the `numpy` conda package to the `numpy` PyPI package and resolve any PyPI dependencies.
Since there are no remaining PyPI dependencies (as `numpy` was already installed as a conda package), no PyPI packages will be installed.
Another example is when you have a PyPI package dependency that is not specified as a conda package dependency:
```toml title="pixi.toml"
[dependencies]
python = ">=3.8"
[pypi-dependencies]
numpy = ">=1.21.0"
```
Which results in the following output:
```output
> pixi list --explicit
Package Version Build Size Kind Source
numpy 2.3.1 43.8 MiB pypi numpy-2.3.1-cp313-cp313-macosx_11_0_arm64.whl
python 3.13.5 hf3f3da0_102_cp313 12.3 MiB conda https://conda.anaconda.org/conda-forge/
```
In this example, Pixi will first resolve the conda dependencies and install the `python` conda package.
Then, since `numpy` is not specified as a conda dependency, Pixi will resolve the PyPI dependencies and install the `numpy` PyPI package.
To override or change the mapping of conda packages to PyPI packages, you can use the [`conda-pypi-map`](../reference/pixi_manifest.md#conda-pypi-map-optional) field in the `pixi.toml` file.
### Pinned package conflicts
When trying to install conda and PyPI dependencies,
such as with the following `pixi.toml` manifest:
```toml title="pixi.toml"
[dependencies]
typing_extensions = "*"
[pypi-dependencies]
typing_extensions = "==4.14"
```
you might encounter the following error message:
```
Error: × failed to solve the pypi requirements of environment 'default' for platform 'osx-arm64'
├─▶ failed to resolve pypi dependencies
╰─▶ Because you require typing-extensions==4.14 and typing-extensions==4.15.0, we can conclude that your requirements are unsatisfiable.
help: The following PyPI packages have been pinned by the conda solve, and this version may be causing a conflict:
typing-extensions==4.15.0
```
This is due to the (current) two-stage solve.
First, the conda dependencies are resolved.
As any version (`*`) of `typing_extensions` is valid,
it resolves to the latest available (`4.15.0` in this case).
Then, the PyPI dependencies are resolved (`typing_extensions == 4.14`),
with the constraints of the already resolved conda dependencies (`typing_extensions == 4.15.0`).
These two dependencies are incompatible and the solve fails.
While this might be a trivial case,
it is less obvious when the packages are not explicit dependencies:
```toml title="pixi.toml"
[dependencies]
some-conda-package = "*" # depends on any typing-extensions
[pypi-dependencies]
some-pypi-package = "==0.1.0" # depends on typing-extensions<4.14
```
which produces the following solve error:
```
Error: × failed to solve the pypi requirements of environment 'default' for platform 'osx-arm64'
├─▶ failed to resolve pypi dependencies
╰─▶ Because some-pypi-dependency==0.1.0 depends on typing-extensions<4.15 and typing-extensions==4.15.0, we can conclude that some-pypi-dependency==0.1.0
cannot be used.
And because only some-pypi-dependency==0.1.0 is available and you require some-pypi-dependency, we can conclude that your requirements are unsatisfiable.
help: The following PyPI packages have been pinned by the conda solve, and this version may be causing a conflict:
typing-extensions==4.15.0
```
A solution in this case would be to add to the conda dependencies `typing-extensions < 4.15`,
that is, the same constraint imposed by the PyPI package(s):
```toml title="pixi.toml"
[dependencies]
some-conda-package = "*" # depends on any typing-extensions
typing_extensions = "<4.15"
[pypi-dependencies]
some-pypi-package = "==0.1.0" # depends on typing-extensions<4.14
```
