# pygmo2 **Repository Path**: mirrors_esa/pygmo2 ## Basic Information - **Project Name**: pygmo2 - **Description**: A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model. - **Primary Language**: Unknown - **License**: MPL-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2023-02-24 - **Last Updated**: 2026-06-28 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README pygmo ===== [![Python CI](https://img.shields.io/github/actions/workflow/status/esa/pygmo2/ci-python.yml?branch=master&style=for-the-badge&label=Python%20CI)](https://github.com/esa/pygmo2/actions/workflows/ci-python.yml) [![Manylinux CI](https://img.shields.io/github/actions/workflow/status/esa/pygmo2/ci-manylinux.yml?branch=master&style=for-the-badge&label=Manylinux%20CI)](https://github.com/esa/pygmo2/actions/workflows/ci-manylinux.yml) [![Anaconda-Server Badge](https://img.shields.io/conda/vn/conda-forge/pygmo.svg?style=for-the-badge)](https://anaconda.org/conda-forge/pygmo) [![PyPI](https://img.shields.io/pypi/v/pygmo.svg?style=for-the-badge)](https://pypi.python.org/pypi/pygmo) [![DOI](https://joss.theoj.org/papers/10.21105/joss.02338/status.svg)](https://doi.org/10.21105/joss.02338) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1045337.svg)](https://doi.org/10.5281/zenodo.1045336) pygmo is a scientific Python library for massively parallel optimization. It is built around the idea of providing a unified interface to optimization algorithms and to optimization problems and to make their deployment in massively parallel environments easy. If you are using pygmo as part of your research, teaching, or other activities, we would be grateful if you could star the repository and/or cite our work. For citation purposes, you can use the following BibTex entry, which refers to the [pygmo paper](https://doi.org/10.21105/joss.02338) in the Journal of Open Source Software: ```bibtex @article{Biscani2020, doi = {10.21105/joss.02338}, url = {https://doi.org/10.21105/joss.02338}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {53}, pages = {2338}, author = {Francesco Biscani and Dario Izzo}, title = {A parallel global multiobjective framework for optimization: pagmo}, journal = {Journal of Open Source Software} } ``` The DOI of the latest version of the software is available at [this link](https://doi.org/10.5281/zenodo.1045336). The full documentation can be found [here](https://esa.github.io/pygmo2/). Installation ------------ The recommended installation route is via conda-forge: ```bash conda install -c conda-forge pygmo ``` You can also install from PyPI: ```bash pip install pygmo ``` At the moment, PyPI wheels are provided for Linux `x86_64` and Linux `aarch64` only. For other platforms, please use conda-forge or build from source.