EKO is a Python module to solve the DGLAP equations in N-space in terms of Evolution Kernel Operators in x-space.
Installation
EKO is available via
The documentation is available here:
ekore
We also provide a convenient access to the core elements of EKO: the anomalous dimensions $\gamma$ and operator matrix elements/transition matrix elements $\mathbf A$. These are collected from various references (see our documentation) and provide the current state of the art in one single place.
Python
In Python you can access these elements through the ekore module installed together with the main Python library - see our documentation.
This module is scheduled for removal once we move the ekore content to Rust (see below).
Rust
In Rust you can access these elements through the ekore crate
C
In C you can access these elements through the ekore_capi crate
For installation instructions and usage see the documentation:
Python (via Rust)
In Python you can access these elements through the ekore-rs module :
$ pip install ekore-rs
Citation policy
When using our code please cite
Contributing
- Your feedback is welcome! If you want to report a (possible) bug or want to ask for a new feature, please raise an issue:
- If you need help, for installation, usage, or anything related, feel free to open a new discussion in the "Support" section
- Please follow our Code of Conduct and read the Contribution Guidelines
Development installation
If you want to install from source you can run
git clone git@github.com:N3PDF/eko.git
cd eko
poetry install
To setup poetry, and other tools, see Contribution
Guidelines.
Building the documentation
- The documentation is available here:
- To build the documentation from source install graphviz and run in addition to the installation commands
poe docs
Tests and benchmarks
- To run unit test you can do
poe tests
- Benchmarks of specific part of the code, such as the strong coupling or msbar masses running, are available doing
poe bench
- The complete list of benchmarks with external codes is available through
ekomark: documentation
Metadata
Release files for eko 0.15.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| eko-0.15.7.tar.gz | 267.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| eko-0.15.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 587.5 kB
Release files / eko-0.15.7.tar.gz
| Download URL | eko-0.15.7.tar.gz |
|---|---|
| Size | 267.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / eko-0.15.7-py3-none-any.whl
| Download URL | eko-0.15.7-py3-none-any.whl |
|---|---|
| Size | 319.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 16, 2026.
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