Single Event Data Frame Processor: Backend to handle photoelectron resolved datastreams
Project description
Backend to handle photoelectron resolved datastreams.
Installation
Pip (for users)
- Create a new virtual environment using either venv, pyenv, conda, etc. See below for an example.
python -m venv .sed-venv
- Activate your environment:
source .sed-venv/bin/activate
- Install
sed
, distributed assed-processor
on PyPI:
pip install sed-processor
-
This should install all the requirements to run
sed
in your environment. -
If you intend to work with Jupyter notebooks, it is helpful to install a Jupyter kernel for your environment. This can be done, once your environment is activated, by typing:
python -m ipykernel install --user --name=sed_kernel
For Contributors
To contribute to the development of sed
, you can follow these steps:
- Clone the repository:
git clone https://github.com/OpenCOMPES/sed.git
cd sed
- Install the repository in editable mode:
pip install -e .
Now you have the development version of sed
installed in your local environment. Feel free to make changes and submit pull requests.
Poetry (for maintainers)
-
Prerequisites:
- Poetry: https://python-poetry.org/docs/
-
Create a virtual environment by typing:
poetry shell
-
A new shell will be spawned with the new environment activated.
-
Install the dependencies from the
pyproject.toml
by typing:
poetry install --with dev, docs
-
If you wish to use the virtual environment created by Poetry to work in a Jupyter notebook, you first need to install the optional notebook dependencies and then create a Jupyter kernel for that.
- Install the optional dependencies
ipykernel
andjupyter
:
poetry install -E notebook
- Make sure to run the command below within your virtual environment (
poetry run
ensures this) by typing:
poetry run ipython kernel install --user --name=sed_poetry
- The new kernel will now be available in your Jupyter kernels list.
- Install the optional dependencies
Project details
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