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dysh

dysh is a Python spectral line data reduction and analysis program for singledish data with specific emphasis on data from the Green Bank Telescope (GBT). It is currently under development in collaboration between the Green Bank Observatory and the Laboratory for Millimeter-Wave Astronomy (LMA) at University of Maryland (UMD). It is intended to be a replacement to the GBT current data reduction package GBTIDL.

Installation

Note: if you are on the GBO network, dysh will already be installed; you do not need to do anything further! Other uses cases are outlined below.

Global Installation

Example use case: you want to quickly install and use dysh on a non-GBO computer

Via uv

This will install a persistent global version of dysh via uv:

# Install dysh
$ uv tool install dysh[all]
# Launch dysh notebook
$ dysh-lab

Via pipx

You can also use pipx. After installing pipx, dysh can be installed via:

# Install dysh
$ pipx install dysh[nb]
# Launch dysh notebook
$ dysh-lab

Local Installation via pip

Example use case: you want to use dysh with a specific set of dependencies, or in conjunction with an existing project

Stable Version

dysh is most easily installed with pip, which will take care of any dependencies. The packaged code is hosted at the Python Packaging Index.

$ pip install dysh[all]

Beta Version

Beta versions will also be published to PyPI, and can be installed via:

$ pip install dysh[all] --pre

Development Version

Development versions can be installed from GitHub branches via:

$ pip install "dysh[all] @ git+https://github.com/GreenBankObservatory/dysh"

For more options, see the pip VCS Support documentation.

Reporting Issues

If you find a bug or something you think is in error, please report it on the GitHub issue tracker. (You must have a GitHub account to submit an issue)


Development

See the For Developers documentation for more detailed instructions on setting up a development environment.

Clone the Repo

$ git clone git@github.com:GreenBankObservatory/dysh.git

Set Up Dysh Environment

Via uv

The recommended development workflow is to use uv. After installing uv all you need to do is:

$ uv sync

You also have access to "dysh shell" and "dysh lab":

$ uv run dysh
$ uv run dysh-lab

Or you can source the uv virtual environment just like any other:

$ source .venv/bin/activate

Via Hatch

Another workflow is to use hatch. After installing hatch, this will look something like:

$ hatch shell

Without Hatch

If you do not want to use Hatch, it is possible to develop using a "classic" workflow. From the root of the dysh repo:

$ # Create your virtual environment
$ python -m venv /path/to/venv
$ # Activate your virtual environment
$ source /path/to/venv/bin/activate
$ # Install dysh and its development dependencies
$ pip install -e .[all]

Testing

We use pytest for unit and integration testing. From the top-level dysh directory, run:

$ pytest

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