Skip to content

ty-zhao/Qcodes

 
 

Repository files navigation

QCoDeS PyPi DOCS PyPI python versions DOI

Build Status Github Build Status Github Docs Codacy Badge

QCoDeS is a Python-based data acquisition framework developed by the Copenhagen / Delft / Sydney / Microsoft quantum computing consortium. While it has been developed to serve the needs of nanoelectronic device experiments, it is not inherently limited to such experiments, and can be used anywhere a system with many degrees of freedom is controllable by computer. To learn more about QCoDeS, browse our homepage .

To get a feeling of QCoDeS read 15 minutes to QCoDeS, and/or browse the Jupyter notebooks in docs/examples .

QCoDeS is compatible with Python 3.7+. It is primarily intended for use from Jupyter notebooks, but can be used from traditional terminal-based shells and in stand-alone scripts as well. The features in qcodes.utils.magic are exclusively for Jupyter notebooks.

Install

In general, refer to here for installation.

Docs

Read it here . Documentation is updated and deployed on every successful build in master.

We use sphinx for documentations, makefiles are provided both for Windows, and *nix, so that you can build the documentation locally.

Make sure that you have the extra dependencies required to install the docs

pip install -r docs_requirements.txt

Go to the directory docs and

make html

This generate a webpage, index.html, in docs/_build/html with the rendered html.

Code of Conduct

QCoDeS strictly adheres to the Microsoft Open Source Code of Conduct

Contributing

The QCoDeS instrument drivers developed by the members of the QCoDeS community but not supported by the QCoDeS developers are contained in

https://github.com/QCoDeS/Qcodes_contrib_drivers

See Contributing for general information about bug/issue reports, contributing code, style, and testing.

License

See License.

About

Modular data acquisition framework

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%