How to install

You can either install straditize through a package manager such as conda or pip or install it from source.

Installation using conda

We highly recommend to use conda for installing straditize. Here you can install it via manually via the chilipp channel

After having downloaded and installed anaconda, open a terminal (or the Anaconda Prompt on windows) and install straditize from the conda-forge channel. You can choose: We recommend to install straditize into its own environment via:

$ conda create -n straditize -c conda-forge straditize

and then activate this environment via:

$ conda activate straditize

In that way you do not mess up your base environment. Nevertheless you can also install it into an existing environment via:

$ conda install -c conda-forge straditize

In the same terminal, now type straditize to start the software.


The latest master branch on github is always available under the master label on the chilipp channel. Just type:

$ conda install -c chilipp/label/master straditize

to install the latest version from the master branch. Note that you then have to add the conda-forge channel to your default channels via:

$ conda config --add channels conda-forge

Installation using pip

If you do not want to use conda for managing your python packages and already have python3 installed on your computer, you can also use the python package manager pip. To be on the safe side, make sure you have the Dependencies installed. If so, open a terminal and install it via:

$ pip install straditize

To open the software, type straditize in the same terminal.

Installation from source

To install it from source, make sure you have the Dependencies installed. Download (or clone) the github repository, e.g. via:

git clone

and install it via:

pip install .  # or python install, but pip is recommended

from your terminal. To open the software, type straditize in the same terminal.


Required dependencies

straditize has been tested for python>=3.6. Furthermore the package is built upon multiple other packages, mainly

  • psyplot-gui>1.2.0: The graphical user interface for psyplot

  • PyQt5: Pythons Qt bindings that are required by psyplot-gui (note that PyQt4 is not supported!)

  • numpy, scipy and pandas: for the data management and compuations

  • matplotlib>=2.0: The python visualiation package

  • pillow: for reading and writing images

  • scikit-image: For image recognition features

  • openpyxl: For exports to Excel files

  • netCDF4: A library for saving and storing netCDF files.

Optional dependencies

We furthermore recommend to use

Running the tests

We use pytest to run our tests. So you can either run clone out the github repository and run:

$ python test

or install pytest by yourself and run

$ py.test

Alternatively you can build the recipe in the conda-recipe directory via

$ conda build conda-recipe

which will also run the test suite.


Running the entire test suite in one single process (such as python test) might be quite memory consumptive because it involves the creation and closing of many PyQt widgets and unfortunately some memory is leaked from one test to another. Therefore we recommend to split the tests into multiple processes, e.g.:

# run the test suite but ignore some modules
python test -a '--ignore=tests/widgets/ --ignore=tests/widgets/ --ignore=tests/widgets/ --ignore=tests/widgets/'
# run the tests for the previously ignored modules
python test -a 'tests/widgets/
python test -a 'tests/widgets/'
python test -a 'tests/widgets/'

or equivalently with py.test instead of python test -a. Note that conda build conda-recipe already splits the session into multiple processes.

Nevertheless, you should expect about ~180 tests to be ran and a total memory usage of about 3 to 4GB RAM.

Building the docs

The online documentation is accessible as PDF, HTML and Epub under or Thanks to the free services by, the online documentation is build automatically after each commit to the github repository.

To build the docs locally on your machine, check out the github repository and install the requirements in 'docs/environment.yml' and the sphinx_rtd_theme package. The easiest way to do this is via anaconda by typing:

$ conda env create -f docs/environment.yml
$ conda activate straditize_docs
$ conda install sphinx_rtd_theme

Then build the docs via:

$ cd docs
$ make html  # or `make pdf` for a PDF version compiled with Latex

Updating straditize

Updating the software depends on how you installed it on your system.

Updating via conda

If you installed straditize via conda (see Installation using conda), you can update it via:

$ conda update -c chilipp straditize

Updating via pip

If you installed it via pip (see Installation using pip), you can update it via:

$ pip install -U straditize

Updating from source files

If you installed it via python install from the source repository (see Installation from source), just run that command again after having checked out the latest version from github.


The uninstallation depends on the system you used to install straditize. Either you did it via conda (see Uninstallation via conda), via pip or from the source files (see Uninstallation via pip).

Anyway, if you may want to remove the psyplot configuration files. If you did not specify anything else (see psyplot.config.rcsetup.psyplot_fname()), the configuration files for psyplot are located in the user home directory. Under linux and OSX, this is $HOME/.config/psyplot. On other platforms it is in the .psyplot directory in the user home.

Uninstallation via conda

If you installed straditize via conda, simply run:

conda uninstall straditize

Uninstallation via pip

Uninstalling via pip simply goes via:

pip uninstall straditize

Note, however, that you should use conda if you also installed it via conda.