Python code for the JUAMI potentiostat
The JUAMI potentiostat is a low-cost potentiostat, for classroom demonstrations and simple lab potentiostat experiments, that is built on the Arduino platform.
This project provides a Python API for controlling the potentiostat.
For more info about JUAMI: http://www.juami.org/ For more questions about the pytentiostat project: Dylan Bardgett ([email protected]), Austin Plymill ([email protected]) Simon Billinge: [email protected]
For more information about the pytentiostat library, please consult our online documentation.
If you use pytentiostat in a scientific publication, we would like you to cite this package as
Yuguang C. Li, Elizabeth L. Melenbrink, Guy J. Cordonier, Christopher Boggs, Anupama Khan, Morko Kwembur Isaac, Lameck Kabambalika Nkhonjera, David Bahati, Simon J. L. Billinge, Sossina M. Haile, Rodney A. Kreuter, Robert M. Crable, and Thomas E. Mallouk. “An easily fabricated low-cost potentiostat coupled with user-friendly software for introducing students to electrochemical reactions and electroanalytical techniques”. In: J. Chem. Educ. 95 (2018), pp. 1658-1661. DOI: 10.1021/acs.jchemed.8b00340
For the JUAMI hackathon participants, Please see installation instructions the Support and Participation section below.
The preferred method is to use Miniconda Python and install from the "conda-forge" channel of Conda packages.
To add "conda-forge" to the conda channels, run the following in a terminal.
conda config --add channels conda-forge
We want to install our packages in a suitable conda environment.
The following creates and activates a new environment named pytentiostat_env
conda create -n pytentiostat_env pytentiostat conda activate pytentiostat_env
To confirm that the installation was successful, type
python -c "import pytentiostat; print(pytentiostat.__version__)"
The output should print the latest version displayed on the badges above.
If the above does not work, you can use pip to download and install the latest release from
Python Package Index.
To install using pip into your pytentiostat_env environment, type
pip install pytentiostat
If you prefer to install from sources, after installing the dependencies, obtain the source archive from
GitHub. Once installed, cd into your pytentiostat directory
and run the following
pip install .
You may consult our online documentation for tutorials and API references.
Diffpy user group is the discussion forum for general questions and discussions about the use of pytentiostat. Please join the pytentiostat users community by joining the Google group. The pytentiostat project welcomes your expertise and enthusiasm!
If you see a bug or want to request a feature, please report it as an issue and/or submit a fix as a PR. You can also post it to the Diffpy user group.
Feel free to fork the project and contribute. To install pytentiostat in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory of the package (i.e., the top level pytentiostat/ directory):
conda create -n pytentiostat-dev python=3.12 conda install --file requirements/conda.txt pip install -e .
To ensure code quality and to prevent accidental commits into the default branch, please set up the use of our pre-commit hooks.
- Install pre-commit in your working environment by running
conda install pre-commit. - Initialize pre-commit (one time only)
pre-commit install.
Thereafter your code will be linted by black and isort and checked against flake8 before you can commit. If it fails by black or isort, just rerun and it should pass (black and isort will modify the files so should pass after they are modified). If the flake8 test fails please see the error messages and fix them manually before trying to commit again.
Improvements and fixes are always appreciated.
Before contributing, please read our Code of Conduct and Our coding standards.
For more information on pytentiostat please visit the project web-page or email Prof. Simon Billinge at [email protected].