pygmo
=====

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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/).

Security note
-------------

pygmo relies on Python's `pickle` module (and, by default, on
[cloudpickle](https://github.com/cloudpipe/cloudpickle)) to (de)serialise user-defined problems,
algorithms, islands, etc., including within `population`, `archipelago`, `problem`, `algorithm`,
`bfe`, `island`, `r_policy`, `s_policy` and `topology` objects. As with the standard `pickle`
module, **deserialising (unpickling) data is equivalent to arbitrary code execution**. Never
unpickle, load archipelago/island checkpoints, or otherwise deserialise pygmo objects coming from
an untrusted or unauthenticated source.

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.