Getting Started#


Standard setup#

# Get the code
git clone && cd scipp
git submodule init
git submodule update

# Setup dev env
mamba env create -f docs/environments/developer.yml
conda activate scipp-dev
pre-commit install
pre-commit run --all-files

# Build, install, and run C++ tests
cmake --preset base
cmake --build --preset build
ctest --preset test

# Setup editable install and run Python tests
tox -e editable
conda develop src
python -m pytest

You should now also be able to run python -c 'import scipp as sc'.

Common tasks#

All of the below assume that the standard setup outlined above was performed.

Build the docs:

tox -e docs

# To clean and build all docs

tox -e docs-clean

Update the pip requirements via pip-compile-multi:

tox -e deps

Update the stubs with stubgen. Do this every time you changed the interface of core classes like Variable.

tox -e stubgen

Prepare a release (make sure to give the desired release instead):

tox -e prepare-release -- 23.01.0


We provide a Conda environment file with developer dependencies in our Git repository. Other build dependencies are installed automatically through Conan when running CMake. See Tooling for compilers and other required tools.

Getting the code#

Clone the git repository (either via SSH or HTTPS) from GitHub.

git clone
cd scipp

# Update Git submodules
git submodule init
git submodule update

# Create Conda environment with dependencies and development tools
mamba env create -f docs/environments/developer.yml
conda activate scipp-dev

Pre-commit Hooks#

We use pre-commit for static analysis and code formatting. Install the pre-commit hooks to avoid committing non-compliant code. In the source directory run:

pre-commit install
pre-commit run --all-files

Building Scipp#

As big parts of Scipp are written in C++, we use CMake for building. This assumes you will end up with a directory structure similar to the following. If you want something different be sure to modify paths as appropriate:

|-- /home/user/scipp (source code)
|   |-- build (build directory)
|   |-- install (Python library installation)
|   |-- ...
|-- ...

To build and install the library:

# Create build and library install directories
mkdir build
mkdir install
cd build

If you are running on Windows, you need to use a visual studio developer command prompt for the following steps. This can be opened manually from the start menu, or programmatically by calling the appropriate vcvars script, for example:

"C:\Program Files\Microsoft Visual Studio\2022\Professional\VC\Auxiliary\Build\vcvars64.bat"

If you wish to build using the Visual Studio CMake generators instead, there is a windows-msbuild CMake preset for this purpose.

To build a debug version of the library:

cmake \
  -GNinja \
  -DPython_EXECUTABLE=$(command -v python3) \

# C++ unit tests
cmake --build . --target all-tests

# Benchmarks
cmake --build . --target all-benchmarks

# Install Python library
cmake --build . --target install

Alternatively, to build a release version with all optimizations enabled:

cmake \
  -GNinja \
  -DPython_EXECUTABLE=$(command -v python3) \

cmake --build . --target all-tests
cmake --build . --target all-benchmarks
cmake --build . --target install

To use the scipp Python module:

conda develop /home/user/scipp/install

In Python:

import scipp as sc

Some developers may prefer an “editable” install, i.e., with changes to Python files in the src directly becoming visible without reinstalling. This is commonly done via pip install -e .. However, Scipp uses scikit-build, which currently does not fully support this directly. Therefore, we need to call cmake manually in this case and install into the Python source directory, or create symlinks. We have configured tox for this purpose:

cmake --preset base -DCONAN_TBB=ON
cmake --build --preset build
tox -e editable
conda develop src

Here conda develop src can also be replaced by pip install -e .. Above we used some of the cmake presets, but you may also call cmake without those for more control of the options. We can also use tox instead of the first two lines:

tox -e lib
tox -e editable
conda develop src

You can now use the editable install as usual, i.e., changes to Python files of Scipp are directly visible when importing Scipp, without the need for a new install. When making changes to the C++ side of Scipp, you will need to re-run the install target using cmake, e.g.,

cmake --build --preset build

Additional build options#

  1. -DDYNAMIC_LIB forces the shared libraries building, that also decreases link time.

  2. -DTHREADING enable or disable multi-threading. ON by default.

  3. -DPRECOMPILED_HEADERS toggle usage of precompiled headers. OFF by default.

  4. -DCPPCHECK toggle run of cppcheck during compilation. OFF by default.

  5. -DCTEST_DISCOVER_TESTS toggle discovery of individual tests for better (but much slower) integration with ctest. OFF by default.

Running the unit tests#

After editing C++ code or tests, make sure to update the build/install:

cmake --build --preset build

Alternatively, the all-tests CMake target can be used to build all tests.

There are two ways of running C++ tests. Executables for the unit tests can be found in the build directory as build/bin/scipp-XYZ-test, where XYZ is the Scipp component under test (e.g. core). These use google-test and provide full control over options, e.g., to filter tests:


Alternatively, use ctest:

ctest --preset test

If only Python code or tests have been updated, there is no need to rebuild or reinstall, provided that you use an editable install (using conda develop src as described earlier).

To run the Python tests, run (in the top-level directory):

python -m pytest tests

Building Documentation#


tox -e lib  # omit if using cmake, or install is up-to-date
tox -e docs

This will build the HTML documentation and put it in a folder named html. If you want to build all docs after cleaning html and doctrees folders, please use tox -e docs-clean.

Using Scipp as a C++ library#

Using Scipp as a C++ library is not recommended at this point as the API (and ABI) is not stable and documentation is sparse. Nonetheless, it can be used as a cmake package as follows. In your CMakeLists.txt:

# replace 23.01 with required version
find_package(scipp 23.01 REQUIRED COMPONENTS conan-config)
find_package(scipp 23.01 REQUIRED)

target_link_libraries(mytarget PUBLIC scipp::dataset)

If Scipp was install using conda, cmake should find it automatically. If you build and installed Scipp from source use, e.g.,:

cmake -DCMAKE_PREFIX_PATH=<your_scipp_install_dir>

where <your_scipp_install_dir> should point to the CMAKE_INSTALL_PREFIX that was used when building Scipp. Alternative set the Scipp_DIR or CMAKE_PREFIX_PATH (environment) variables to this path.

Generating coverage reports#

  • Run cmake with options -DCOVERAGE=On -DCMAKE_BUILD_TYPE=Debug.

  • Run cmake --build . --target coverage from your build directory.

  • Open coverage/index.html in a browser.