Installing with Conda#

Anaconda and Miniconda are Python distributions that include the conda package manager, which can be used to install Cantera.

Installing Cantera using Conda can provide the Cantera Python module and MATLAB toolbox, as well as libraries for linking to applications written in C++, C, or Fortran 90. There are some exceptions to the availability of each interface depending on the operating system and Conda channel used.

Both the Anaconda and Miniconda distributions are available for Linux, macOS (Intel and ARM/Apple Silicon), and Windows. On Windows, users should install a 64-bit version of Anaconda or Miniconda, since the Cantera Conda packages are only available for 64-bit installations.

Both Anaconda and Miniconda include the conda package manager; the difference is that Anaconda includes a large number of Python packages that are widely used in scientific applications, while Miniconda is a minimal distribution that only includes Python and Conda, although all of the packages available in Anaconda can be installed in Miniconda. For more details on how to use conda, see the conda documentation.

Conda can install a large set of packages by default and it is possible to install packages such as Cantera that are maintained independently. These additional channels from which packages may be obtained are specified by adding the --channel option in the install or create commands.

For instructions on upgrading an existing conda-based installation of Cantera, see Upgrading from an earlier Cantera version.

Python interface#

Cantera’s Python interface is available from two channels:

The cantera channel. This channel should be used if you installed Python from the default channel in conda. This channel also has pre-release versions of Cantera for testing. Cantera packages are available in this channel for the following platforms:
- Windows (64-bit Intel)
- Linux (64-bit Intel)
- macOS (64-bit Intel and 64-bit ARM (Apple Silicon))
The conda-forge channel. This channel should be used if you installed Python from the conda-forge channel or if your OS/processor combination is not supported by the cantera channel. Cantera packages are available in this channel for the following platforms:
- Windows (64-bit Intel)
- Linux (64-bit Intel, 64-bit ARM, and 64-bit PPCLE)
- macOS (64-bit Intel and 64-bit ARM (Apple Silicon))

Option 1: Create a new environment for Cantera#

The following instructions will create a conda environment where you can use Cantera from Python. For this example, the environment is named ct-env. From the command line (or the Anaconda Prompt on Windows), run:

conda create --name ct-env --channel cantera cantera ipython matplotlib jupyter

This will create an environment named ct-env with Cantera, IPython, Matplotlib, and all their dependencies installed. In this case, we want to install Cantera from the cantera channel, so we add --channel cantera and to tell Conda to look at the cantera channel in addition to the default channels.

If you want to use the conda-forge channel, replace --channel cantera with --channel conda-forge.

To use the scripts and modules installed in the ct-env environment, including Jupyter, you must activate it it by running:

conda activate ct-env

Option 2: Create a new environment using an environment file#

This option is similar to Option 1 but includes a few other packages that you may find helpful as you’re working with Cantera. Copy and paste the contents of the file shown below into a file called environment.yaml. Then, save the the file somewhere and remember that location.

name: ct-env
channels:
- cantera  # or use cantera/label/dev for alpha/beta packages
- defaults
dependencies:
- python  # Cantera supports Python 3.8 and up
- cantera
- ipython  # optional (needed for nicer interactive command line)
- jupyter  # optional (needed for Jupyter Notebook)
- matplotlib  # optional (needed for plots)
- python-graphviz  # optional (needed for reaction path diagrams)
- pandas  # optional (needed for pandas interface)

From the command line (or the Anaconda Prompt on Windows), change directory into the folder where you saved environment.yaml:

cd folder/where/you/saved

and then run:

conda env create -f environment.yaml

This will create an environment called ct-env. Once you’ve done that, you need to activate the environment before using any scripts or modules that you just installed:

conda activate ct-env

Option 3: Install the development version of Cantera#

To install a recent development snapshot (that is, an alpha or beta version) of Cantera, use the cantera/label/dev channel. Assuming you have an environment named ct-dev, you can type:

conda activate ct-dev
conda install --channel cantera/label/dev cantera

If you later want to revert back to the stable version in that environment, first remove and then reinstall Cantera:

conda activate ct-dev
conda remove cantera
conda install --channel cantera cantera

Alternatively, you can remove the ct-dev environment and follow Options 1 or 2 above to create a new environment.

Upgrading from an earlier Cantera version#

If you already have Cantera installed in a conda environment (named, for example, ct-dev), you can upgrade it to the latest version available by running the commands:

conda activate ct-dev
conda update --channel cantera cantera

This assumes you are using Python from the default conda channel. If you installed Python and Cantera from the conda-forge channel, you should specify the option --channel conda-forge.

MATLAB interface#

Cantera’s MATLAB interface can be installed from the cantera channel. In this example, the command will create a new conda environment named ct-env. From the command line (or the Anaconda Prompt on Windows), run:

conda create --name ct-env --channel cantera cantera cantera-matlab

This will create an environment named ct-env with Cantera’s Python and MATLAB interfaces. Even if you plan to use Cantera via MATLAB, the Python interface is required to convert input files. In this case, Cantera must be installed from the cantera channel, so we add --channel cantera and to tell Conda to look at the cantera channel in addition to the default channels.

To install the a development version of Cantera, specify cantera/label/dev as the channel.

Upgrading from an earlier Cantera version#

If you already have the Cantera MATLAB interface installed in a conda environment (named, for example, ct-env), you can upgrade it to the latest version available by running the commands:

conda activate ct-env
conda update --channel cantera cantera cantera-matlab

Development (C++ & Fortran 90) Interface#

The Cantera development interface provides header files and libraries needed to compile your own C++, C, or Fortran applications that link to Cantera. It also provides several sample programs and build scripts that you can adapt for your own applications.

In the following example, Cantera’s development interface is installed from the cantera/label/dev channel. From the command line (or the Anaconda Prompt on Windows), create a new conda environment named ct-dev using:

conda create --name ct-dev --channel cantera/label/dev libcantera-devel

This will create an environment named ct-dev with Cantera’s development interface. In this case, the addition of --channel cantera/label/dev ensures that the package is pulled from the most recent available Cantera version. Note that label/dev refers to the experimental development channel of Cantera, and not the development interface.

C++ header and libraries are installed within the ct-dev environment folder, which itself depends on the type of conda installation, and is abbreviated as path/to/conda/envs below. Within the ct-dev folder, locations follow conda recommendations for a given operating system.

Linux and macOS Systems#

Installation folders are:

library files               path/to/conda/envs/ct-dev/lib
pkg-config                  path/to/conda/envs/ct-dev/lib/pkgconfig
C++ headers                 path/to/conda/envs/ct-dev/include
Fortran module files        path/to/conda/envs/ct-dev/include/cantera
samples                     path/to/conda/envs/ct-dev/share/cantera/samples
data files                  path/to/conda/envs/ct-dev/share/cantera/data

In addition to libcantera-devel, installation of additional packages is recommended:

$ conda activate ct-dev
$ conda install cmake scons pkg-config

C++ programs can be compiled according to instructions outlined in the C++ Guide. Sample folders for C, C++ and Fortran include preconfigured instruction files to facilitate compilation using the build tools SCons and CMake, for example:

$ cd /path/to/conda/envs/ct-dev/share/cantera/samples/cxx/demo
$ scons  # uses SConstruct; or
$ cmake . && cmake --build .  # uses CMakeLists.txt

In addition, individual C++ Cantera sample programs can also be compiled using the pkg-config build system:

$ g++ demo.cpp -o demo $(pkg-config --cflags --libs cantera)

In all cases, the build process yields the executable demo, which is run as:

$ ./demo

Windows Systems#

Installation folders are:

library files               path\to\conda\envs\ct-dev\Library\lib
C++ headers                 path\to\conda\envs\ct-dev\Library\include
samples                     path\to\conda\envs\ct-dev\share\cantera\samples
data files                  path\to\conda\envs\ct-dev\share\cantera\data

C++ programs can be compiled according to instructions outlined in the C++ Guide. Sample folders for C and C++ programs include preconfigured instruction files to facilitate compilation using the build tools SCons and CMake, for example:

$ cd path\to\conda\envs\ct-dev\share\cantera\samples\cxx\demo
$ scons  # uses SConstruct; or
$ cmake . && cmake --build . --config Release  # uses CMakeLists.txt

Fortran 90 support is not provided for Windows.

Upgrading from an earlier Cantera version#

If you already have the Cantera development interface installed in a conda environment (named, for example, ct-dev), you can upgrade it to the latest version available by running the commands:

conda activate ct-dev
conda update --channel cantera/label/dev libcantera-devel