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Install and upgrade

Requirements

This package requires Python 3.10 or later (see :ref:`Python support`). It is continuously tested on Linux, and most parts should also work on other operating systems (MacOS, Windows).

I cannot use my system's Python distribution, what now?

Several Python distributions can co-exist on a single system. If you don't have access to a recent Python version via your system's package manager (this might be the case for old operating systems), it is recommended to install the latest version of the Anaconda Python 3 distribution.

Also, there is the possibility to use multiple virtual environments via:

python3 -m virtualenv ENV_NAME
source ENV_NAME/bin/activate

where ENV_NAME denotes an individual environment name, if you do not want to mess up the system environment.

Install from PIP

The package can be installed from the Python Package Index PyPI via pip:

pip3 install pypesto

Install from GIT

If you want the bleeding edge version, install directly from github:

pip3 install git+https://github.com/icb-dcm/pypesto.git

If you need to have access to the source code, you can download it via:

git clone https://github.com/icb-dcm/pypesto.git

and then install from the local repository via:

cd pypesto
pip3 install .

Upgrade

If you want to upgrade from an existing previous version, replace install by ìnstall --upgrade in the above commands.

Install optional packages and external dependencies

  • pyPESTO includes multiple convenience methods to simplify parameter estimation for models generated using the toolbox AMICI. To use AMICI, install it via pip:

    pip3 install amici

    or, in case of problems, follow the full instructions from the AMICI documentation.

  • This package inherently supports optimization using the dlib toolbox. To use it, install dlib via:

    pip3 install dlib

  • All external dependencies can be installed through this shell script.

Python support

We adopt the NEP 29 - Recommend Python and NumPy version support as a community policy standard. That means, we adopt a time window based policy for support of Python (and NumPy) versions.