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Single Event Data Frame Processor: Backend to handle photoelectron resolved datastreams

Project description

Documentation Status Ruff Coverage Status

Backend to handle photoelectron resolved datastreams.

Table of Contents

Installation

Installation

For Users (pip)

Prerequisites

  • Python 3.8+
  • pip

Steps

  • Create a new virtual environment using either venv, pyenv, conda, etc. See below for an example.
python -m venv .sed-venv
  • Activate your environment:
# On macOS/Linux
source .sed-venv/bin/activate

# On Windows
.sed-venv\Scripts\activate
  • Install sed, distributed as sed-processor on PyPI:
pip install sed-processor[all]
  • 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
  • If you do not use Jupyter Notebook or Jupyter Lab, you can skip the installing those dependencies
pip install sed-processor

For Contributors (pip)

Prerequisites

  • Git
  • Python 3.8+
  • pip

Steps

  1. Clone the repository:
git clone https://github.com/OpenCOMPES/sed.git
cd sed
  1. Create and activate a virtual environment:
# Create a virtual environment
python -m venv .sed-dev

# Activate the virtual environment
# On macOS/Linux
source .sed-dev/bin/activate

# On Windows
.sed-dev\Scripts\activate
  1. Install the repository in editable mode with all dependencies:
pip install -e .[all]

Now you have the development version of sed installed in your local environment. Feel free to make changes and submit pull requests.

For Maintainers (poetry)

Prerequisites

Steps

  • 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:
    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.

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