sed-processor 0.1.10a4

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

Backend to handle photoelectron resolved datastreams.

Table of Contents

Installation

• For Users (pip)
• For Contributors (pip)
• For Maintainers (poetry)

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

2. 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

3. 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

• Poetry: Poetry Installation

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.