Using Pixi with pyproject.toml based Python packages - Reproducible reuse by default: Use of Pixi for software in (Py)HEP

Example project being used

The example project being shown is taken from the September 2023 talk Distributing your Science: Turning analyses into scientific tools by Matthew Feickert. The example project has the following directory tree structure

$ tree .
.
├── CMakeLists.txt
├── LICENSE
├── pyproject.toml
├── README.md
├── src
│   ├── basic_math.cpp
│   └── rosen_cpp
│       ├── example.py
│       └── __init__.py
└── tests
    └── test_example.py

4 directories, 8 files

You can clone the talk repository to get access to those files, or get them from this tutorial’s source repository.

Checkout the Scientific Python org’s Scientific Python Library Development Guide for more!

Initializing a Pixi project¶

If you initialize a Pixi project in the same directory as a pyproject.toml, it will prompt you to create the Pixi workspace as a [tool.pixi] subtable in the pyproject.toml

pixi init

A 'pyproject.toml' file already exists. Do you want to extend it with the '[tool.pixi]' configuration? yes
✔ Added package 'rosen-cpp' as an editable dependency.

pyproject.toml

[build-system]
requires = [
  "scikit-build-core>=0.5.0",
  "pybind11>=2.10.0",
  ]
build-backend = "scikit_build_core.build"


[project]
name = "rosen-cpp"
dynamic = ["version"]
description = "Example package for demonstration"
...
requires-python = ">=3.10"

dependencies = [
    "scipy>=1.14.0",
    "numpy",  # compatible versions controlled through scipy
]

...

[tool.pixi.workspace]
channels = ["conda-forge"]
platforms = ["linux-64"]

[tool.pixi.pypi-dependencies]
rosen-cpp = { path = ".", editable = true }

[tool.pixi.tasks]

Which at pixi install time, will:

Automatically add python as a dependency
Install the Python project.dependencies from PyPI
Install the project as a local Python project (as an editable project by default) using the tools that exist already on the system

editable install are for non-compiled extension projects

We can remove the editable install as rosen-cpp has compiled extensions, and so won’t benefit from editable installs.

[tool.pixi.pypi-dependencies]
rosen-cpp = { path = "." }

Extending as a normal Pixi project¶

Beyond that nothing is special about the Pixi workspace, so we can add additional platforms

pixi workspace platform add linux-64 osx-arm64

✔ Added linux-64
✔ Added osx-arm64

pyproject.toml

...

[tool.pixi.workspace]
channels = ["conda-forge"]
platforms = ["linux-64", "osx-arm64"]

[tool.pixi.pypi-dependencies]
rosen-cpp = { path = "." }

[tool.pixi.tasks]

or add build tools for the build process to pick up

pixi add cxx-compiler

✔ Added cxx-compiler >=1.11.0,<2

pyproject.toml

...

[tool.pixi.workspace]
channels = ["conda-forge"]
platforms = ["linux-64", "osx-arm64"]

[tool.pixi.pypi-dependencies]
rosen-cpp = { path = "." }

[tool.pixi.tasks]

[tool.pixi.dependencies]
cxx-compiler = ">=1.11.0,<2"

Using conda packages over Python packages for local builds¶

Our Python dependencies are currently being installed as Python packages from PyPI (which is fine)

pixi list

Package                   Version    Build               Size       Kind   Source
_libgcc_mutex             0.1        conda_forge         2.5 KiB    conda  https://conda.anaconda.org/conda-forge/
_openmp_mutex             4.5        2_gnu               23.1 KiB   conda  https://conda.anaconda.org/conda-forge/
binutils                  2.44       h4852527_4          34.2 KiB   conda  https://conda.anaconda.org/conda-forge/
binutils_impl_linux-64    2.44       h9d8b0ac_4          3.5 MiB    conda  https://conda.anaconda.org/conda-forge/
binutils_linux-64         2.44       h4852527_4          35.2 KiB   conda  https://conda.anaconda.org/conda-forge/
bzip2                     1.0.8      hda65f42_8          254.2 KiB  conda  https://conda.anaconda.org/conda-forge/
c-compiler                1.11.0     h4d9bdce_0          6.5 KiB    conda  https://conda.anaconda.org/conda-forge/
ca-certificates           2025.10.5  hbd8a1cb_0          152.3 KiB  conda  https://conda.anaconda.org/conda-forge/
conda-gcc-specs           14.3.0     hb991d5c_7          32.5 KiB   conda  https://conda.anaconda.org/conda-forge/
cxx-compiler              1.11.0     hfcd1e18_0          6.5 KiB    conda  https://conda.anaconda.org/conda-forge/
gcc                       14.3.0     h76bdaa0_7          30.3 KiB   conda  https://conda.anaconda.org/conda-forge/
gcc_impl_linux-64         14.3.0     hd9e9e21_7          66.7 MiB   conda  https://conda.anaconda.org/conda-forge/
gcc_linux-64              14.3.0     h298d278_12         27.3 KiB   conda  https://conda.anaconda.org/conda-forge/
gxx                       14.3.0     he448592_7          29.7 KiB   conda  https://conda.anaconda.org/conda-forge/
gxx_impl_linux-64         14.3.0     he663afc_7          14.5 MiB   conda  https://conda.anaconda.org/conda-forge/
gxx_linux-64              14.3.0     h95f728e_12         26.4 KiB   conda  https://conda.anaconda.org/conda-forge/
kernel-headers_linux-64   4.18.0     he073ed8_8          1.2 MiB    conda  https://conda.anaconda.org/conda-forge/
ld_impl_linux-64          2.44       h1aa0949_4          725.1 KiB  conda  https://conda.anaconda.org/conda-forge/
libexpat                  2.7.1      hecca717_0          73.1 KiB   conda  https://conda.anaconda.org/conda-forge/
libffi                    3.5.2      h9ec8514_0          56.5 KiB   conda  https://conda.anaconda.org/conda-forge/
libgcc                    15.2.0     h767d61c_7          803.3 KiB  conda  https://conda.anaconda.org/conda-forge/
libgcc-devel_linux-64     14.3.0     h85bb3a7_107        2.6 MiB    conda  https://conda.anaconda.org/conda-forge/
libgomp                   15.2.0     h767d61c_7          437.4 KiB  conda  https://conda.anaconda.org/conda-forge/
liblzma                   5.8.1      hb9d3cd8_2          110.2 KiB  conda  https://conda.anaconda.org/conda-forge/
libmpdec                  4.0.0      hb9d3cd8_0          89 KiB     conda  https://conda.anaconda.org/conda-forge/
libsanitizer              14.3.0     hd08acf3_7          4.9 MiB    conda  https://conda.anaconda.org/conda-forge/
libsqlite                 3.50.4     h0c1763c_0          910.7 KiB  conda  https://conda.anaconda.org/conda-forge/
libstdcxx                 15.2.0     h8f9b012_7          3.7 MiB    conda  https://conda.anaconda.org/conda-forge/
libstdcxx-devel_linux-64  14.3.0     h85bb3a7_107        12.6 MiB   conda  https://conda.anaconda.org/conda-forge/
libuuid                   2.41.2     he9a06e4_0          36.3 KiB   conda  https://conda.anaconda.org/conda-forge/
libzlib                   1.3.1      hb9d3cd8_2          59.5 KiB   conda  https://conda.anaconda.org/conda-forge/
ncurses                   6.5        h2d0b736_3          870.7 KiB  conda  https://conda.anaconda.org/conda-forge/
numpy                     2.3.4                          55.2 MiB   pypi   numpy-2.3.4-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
openssl                   3.5.4      h26f9b46_0          3 MiB      conda  https://conda.anaconda.org/conda-forge/
python                    3.14.0     h32b2ec7_102_cp314  35 MiB     conda  https://conda.anaconda.org/conda-forge/
python_abi                3.14       8_cp314             6.8 KiB    conda  https://conda.anaconda.org/conda-forge/
readline                  8.2        h8c095d6_2          275.9 KiB  conda  https://conda.anaconda.org/conda-forge/
rosen_cpp                 0.1.dev12                                 pypi
scipy                     1.16.2                         112.9 MiB  pypi   scipy-1.16.2-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
sysroot_linux-64          2.28       h4ee821c_8          23.1 MiB   conda  https://conda.anaconda.org/conda-forge/
tk                        8.6.13     noxft_hd72426e_102  3.1 MiB    conda  https://conda.anaconda.org/conda-forge/
tzdata                    2025b      h78e105d_0          120.1 KiB  conda  https://conda.anaconda.org/conda-forge/
zstd                      1.5.7      hb8e6e7a_2          554.3 KiB  conda  https://conda.anaconda.org/conda-forge/

though if we want to harmonize and use as much of Pixi’s abilities as possible, we can additionally add our Python package dependencies to our Pixi dependency table

pixi add 'scipy >=1.14.0'

✔ Added scipy >=1.14.0

pyproject.toml

...

[tool.pixi.workspace]
channels = ["conda-forge"]
platforms = ["linux-64", "osx-arm64"]

[tool.pixi.pypi-dependencies]
rosen-cpp = { path = "." }

[tool.pixi.tasks]

[tool.pixi.dependencies]
cxx-compiler = ">=1.11.0,<2"
scipy = ">=1.14.0"

pixi list

Package                   Version    Build                 Size       Kind   Source
_libgcc_mutex             0.1        conda_forge           2.5 KiB    conda  https://conda.anaconda.org/conda-forge/
_openmp_mutex             4.5        2_gnu                 23.1 KiB   conda  https://conda.anaconda.org/conda-forge/
binutils                  2.44       h4852527_4            34.2 KiB   conda  https://conda.anaconda.org/conda-forge/
binutils_impl_linux-64    2.44       h9d8b0ac_4            3.5 MiB    conda  https://conda.anaconda.org/conda-forge/
binutils_linux-64         2.44       h4852527_4            35.2 KiB   conda  https://conda.anaconda.org/conda-forge/
bzip2                     1.0.8      hda65f42_8            254.2 KiB  conda  https://conda.anaconda.org/conda-forge/
c-compiler                1.11.0     h4d9bdce_0            6.5 KiB    conda  https://conda.anaconda.org/conda-forge/
ca-certificates           2025.10.5  hbd8a1cb_0            152.3 KiB  conda  https://conda.anaconda.org/conda-forge/
conda-gcc-specs           14.3.0     hb991d5c_7            32.5 KiB   conda  https://conda.anaconda.org/conda-forge/
cxx-compiler              1.11.0     hfcd1e18_0            6.5 KiB    conda  https://conda.anaconda.org/conda-forge/
gcc                       14.3.0     h76bdaa0_7            30.3 KiB   conda  https://conda.anaconda.org/conda-forge/
gcc_impl_linux-64         14.3.0     hd9e9e21_7            66.7 MiB   conda  https://conda.anaconda.org/conda-forge/
gcc_linux-64              14.3.0     h298d278_12           27.3 KiB   conda  https://conda.anaconda.org/conda-forge/
gxx                       14.3.0     he448592_7            29.7 KiB   conda  https://conda.anaconda.org/conda-forge/
gxx_impl_linux-64         14.3.0     he663afc_7            14.5 MiB   conda  https://conda.anaconda.org/conda-forge/
gxx_linux-64              14.3.0     h95f728e_12           26.4 KiB   conda  https://conda.anaconda.org/conda-forge/
kernel-headers_linux-64   4.18.0     he073ed8_8            1.2 MiB    conda  https://conda.anaconda.org/conda-forge/
ld_impl_linux-64          2.44       h1aa0949_4            725.1 KiB  conda  https://conda.anaconda.org/conda-forge/
libblas                   3.9.0      37_h4a7cf45_openblas  17.1 KiB   conda  https://conda.anaconda.org/conda-forge/
libcblas                  3.9.0      37_h0358290_openblas  17.1 KiB   conda  https://conda.anaconda.org/conda-forge/
libexpat                  2.7.1      hecca717_0            73.1 KiB   conda  https://conda.anaconda.org/conda-forge/
libffi                    3.5.2      h9ec8514_0            56.5 KiB   conda  https://conda.anaconda.org/conda-forge/
libgcc                    15.2.0     h767d61c_7            803.3 KiB  conda  https://conda.anaconda.org/conda-forge/
libgcc-devel_linux-64     14.3.0     h85bb3a7_107          2.6 MiB    conda  https://conda.anaconda.org/conda-forge/
libgfortran               15.2.0     h69a702a_7            28.6 KiB   conda  https://conda.anaconda.org/conda-forge/
libgfortran5              15.2.0     hcd61629_7            1.5 MiB    conda  https://conda.anaconda.org/conda-forge/
libgomp                   15.2.0     h767d61c_7            437.4 KiB  conda  https://conda.anaconda.org/conda-forge/
liblapack                 3.9.0      37_h47877c9_openblas  17.1 KiB   conda  https://conda.anaconda.org/conda-forge/
liblzma                   5.8.1      hb9d3cd8_2            110.2 KiB  conda  https://conda.anaconda.org/conda-forge/
libmpdec                  4.0.0      hb9d3cd8_0            89 KiB     conda  https://conda.anaconda.org/conda-forge/
libopenblas               0.3.30     pthreads_h94d23a6_2   5.7 MiB    conda  https://conda.anaconda.org/conda-forge/
libsanitizer              14.3.0     hd08acf3_7            4.9 MiB    conda  https://conda.anaconda.org/conda-forge/
libsqlite                 3.50.4     h0c1763c_0            910.7 KiB  conda  https://conda.anaconda.org/conda-forge/
libstdcxx                 15.2.0     h8f9b012_7            3.7 MiB    conda  https://conda.anaconda.org/conda-forge/
libstdcxx-devel_linux-64  14.3.0     h85bb3a7_107          12.6 MiB   conda  https://conda.anaconda.org/conda-forge/
libuuid                   2.41.2     he9a06e4_0            36.3 KiB   conda  https://conda.anaconda.org/conda-forge/
libzlib                   1.3.1      hb9d3cd8_2            59.5 KiB   conda  https://conda.anaconda.org/conda-forge/
ncurses                   6.5        h2d0b736_3            870.7 KiB  conda  https://conda.anaconda.org/conda-forge/
numpy                     2.3.4      py314h2b28147_0       8.5 MiB    conda  https://conda.anaconda.org/conda-forge/
openssl                   3.5.4      h26f9b46_0            3 MiB      conda  https://conda.anaconda.org/conda-forge/
python                    3.14.0     h32b2ec7_102_cp314    35 MiB     conda  https://conda.anaconda.org/conda-forge/
python_abi                3.14       8_cp314               6.8 KiB    conda  https://conda.anaconda.org/conda-forge/
readline                  8.2        h8c095d6_2            275.9 KiB  conda  https://conda.anaconda.org/conda-forge/
rosen_cpp                 0.1.dev12                                   pypi
scipy                     1.16.2     py314he7377e1_0       16.5 MiB   conda  https://conda.anaconda.org/conda-forge/
sysroot_linux-64          2.28       h4ee821c_8            23.1 MiB   conda  https://conda.anaconda.org/conda-forge/
tk                        8.6.13     noxft_hd72426e_102    3.1 MiB    conda  https://conda.anaconda.org/conda-forge/
tzdata                    2025b      h78e105d_0            120.1 KiB  conda  https://conda.anaconda.org/conda-forge/
zstd                      1.5.7      hb8e6e7a_2            554.3 KiB  conda  https://conda.anaconda.org/conda-forge/

We similarly can add other features and environments

$ pixi add --feature test pytest
✔ Added pytest
Added these only for feature: test
$ pixi workspace environment add --feature test test
✔ Added environment test
$ pixi task add --feature test test "pytest tests"
✔ Added task `test`: pytest tests
$ pixi run test
✨ Pixi task (test in test): pytest tests
====================================================== test session starts ...
platform linux -- Python 3.14.0, pytest-8.4.2, pluggy-1.6.0
rootdir: <path>/compiled_packaging
configfile: pyproject.toml
collected 2 items

tests/test_example.py ..                                  [100%]

...

======================================================== 2 passed, 1 warning in 0.60s ...

When to use Pixi vs. uv?¶

You might have noticed that these operations are defintiely slower than performing similar setup with uv

$ pixi global install uv
└── uv (already installed)
    ├─ dependencies: uv 0.9.5, python 3.14.0
    └─ exposes: uvx, uv
$ uv venv --python 3.14
Using CPython 3.14.0
Creating virtual environment at: .venv
Activate with: source .venv/bin/activate
$ . .venv/bin/activate
(compiled_packaging) $ uv pip install .
Resolved 3 packages in 858ms
      Built rosen-cpp @ file:///<path>/compiled_packaging
Prepared 3 packages in 6.81s
Installed 3 packages in 22ms
 + numpy==2.3.4
 + rosen-cpp==0.1.dev16 (from file:///<path>/compiled_packaging)
 + scipy==1.16.2
(compiled_packaging) $ uv pip install pytest
Resolved 5 packages in 118ms
Installed 5 packages in 16ms
 + iniconfig==2.3.0
 + packaging==25.0
 + pluggy==1.6.0
 + pygments==2.19.2
 + pytest==8.4.2
(compiled_packaging) $ pytest tests/
====================================================== test session starts ...
platform linux -- Python 3.14.0, pytest-8.4.2, pluggy-1.6.0
rootdir: <path>/compiled_packaging
configfile: pyproject.toml
collected 2 items

tests/test_example.py ..                                  [100%]

======================================================== 2 passed in 0.81s ...

uv is optimized for Python packages and has been excellently engineered to be as efficient as possible in this space and to unlock developer capabilities. uv is limited to only Python packages, though and does not have the ability to manage things that exist outside of a Python package index (e.g. build tools like cmake, complex or large proejcts like Boost or ROOT).

Reproducible reuse by default: Use of Pixi for software in (Py)HEP

Introduction to Pixi basics

Reproducible reuse by default: Use of Pixi for software in (Py)HEP

Using CUDA conda packages with Pixi