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Numerical Utilities for Finite Element Analysis

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Nutils is a Free and Open Source Python programming library for Finite Element Method computations, developed by Evalf Computing and distributed under the permissive MIT license. Key features are a readable, math centric syntax, an object oriented design, strict separation of topology and geometry, and high level function manipulations with support for automatic differentiation.

Nutils provides the tools required to construct a typical simulation workflow in just a few lines of Python code, while at the same time leaving full flexibility to build novel workflows or interact with third party tools. With native support for Isogeometric Analysis (IGA), the Finite Cell method (FCM), multi-physics, mixed methods, and hierarchical refinement, Nutils is at the forefront of numerical discretization science. Efficient under-the-hood vectorization and built-in parallellisation provide for an effortless transition from academic research projects to full scale, real world applications.


Nutils is platform independent and is known to work on Linux, Windows and macOS.

A working installation of Python 3.5 or higher is required. Many different installers exist and there are no known issues with any of them. When in doubt about which to use, a safe option is to go with the official installer.

With Python installed, the recommended way to install the latest stable version of Nutils is through pip (included in the standard installer):

python3 -m pip install --user nutils

By default and without explicitly specifying the source of the given packages, pip installs packages from the Python Package Index. To install the latest development version of Nutils, pass a zip of branch master of the official repository to pip:

python3 -m pip install --user

To view which version of Nutils is currently installed, run:

python3 -m pip show nutils

Nutils can be installed in a Windows machine using WSL environment. If you want to assemble matrices in parallel using nutils on a Windows machine, then WSL is the way to go. Instructions to setup WSL are available here. After setting up WSL, nutils can be installed using the above instructions.

First steps

To confirm Nutils and its dependencies are installed correctly, try to run the Laplace example or any of the other examples included in this repostitory. Make sure to use the same version of an example as the version of Nutils that is currently installed.

When running an example from a terminal or editor with Python console, log messages should appear in the terminal or console. Simulateneously, a html file log.html and any produced figures are written to public_html/<script_name>/yyyy/mm/dd/hh-mm-ss in the home directory. In case a webserver is running and configured for user directories this automatically makes simulations remotely accessible. For convenience, public_html/log.html always redirects to the most recent simulation.


Docker container images with the latest and recent stable versions of Nutils preinstalled are available from The container images includes all examples in this repository. To run an example, add the name of the example and any additional arguments to the command line. For example, you can run example laplace using the latest version of Nutils with

docker run --rm -it laplace

HTML log files are generated in the /log directory of the container. If you want to store the log files in /path/to/log on the host, add -v /path/to/log:/log to the command line before the name of the image. Extending the previous example:

docker run --rm -it -v /path/to/log:/log laplace

To run a Python script in this container, bind mount the directory containing the script, including all files necessary to run the script, to /app in the container and add the relative path to the script and any arguments to the command line. For example, you can run /path/to/script/ with Docker using

docker run --rm -it -v /path/to/script:/app:ro

Next steps and support

For the numerical background of all examples as well as line by line documentation see the overview of examples. Documentation of individual functions can be found in the API reference.

Most simulations will have components in common with the example scripts, so a mix-and-match approach is a good way to start building your own script. For questions that are not answered by the API reference there is the nutils-users support channel at Note that you will need to create an account at any Matrix server in order to join this channel.

If you are using Nutils in academic research, please consider citing Nutils.

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