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Contributing to Abstraction Layer in Measurement Plug-In for Python

Contributions to Abstraction Layer in Measurement Plug-In for Python are welcome from all!

Abstraction Layer in Measurement Plug-In for Python is managed via git, with the canonical upstream repository hosted on GitHub.

Abstraction Layer in Measurement Plug-In for Python follows a pull-request model for development. If you wish to contribute, you will need to create a GitHub account, fork this project, push a branch with your changes to your project, and then submit a pull request.

Please remember to sign off your commits (e.g., by using git commit -s if you are using the command line client). This amends your git commit message with a line of the form Signed-off-by: Name Lastname <name.lastmail@emailaddress.com>. Please include all authors of any given commit into the commit message with a Signed-off-by line. This indicates that you have read and signed the Developer Certificate of Origin (see below) and are able to legally submit your code to this repository.

See GitHub's official documentation for more details.

Getting Started

Prerequisites

Clone Repo

Clone the repo, this will pull the workflow documentation to create the Abstraction Layer in Measurement Plug-In for Python measurements and related examples.

git clone https://github.com/NI-Measurement-Plug-Ins/abstraction-layer-python.git

HAL and FAL Implementation workflow

Adding dependencies

Add dependency package for the example measurement plug-in using the poetry add command.

poetry add <name_of_dependency>:<version>

Lint Code

To check the code and update it for formatting errors

poetry run ni-python-styleguide fix

Developer Certificate of Origin (DCO)

Developer's Certificate of Origin 1.1

By making a contribution to this project, I certify that:

(a) The contribution was created in whole or in part by me and I have the right to submit it under the open source license indicated in the file; or

(b) The contribution is based upon previous work that, to the best of my knowledge, is covered under an appropriate open source license and I have the right under that license to submit that work with modifications, whether created in whole or in part by me, under the same open source license (unless I am permitted to submit under a different license), as indicated in the file; or

(c) The contribution was provided directly to me by some other person who certified (a), (b) or (c) and I have not modified it.

(d) I understand and agree that this project and the contribution are public and that a record of the contribution (including all personal information I submit with it, including my sign-off) is maintained indefinitely and may be redistributed consistent with this project or the open source license(s) involved.

(taken from developercertificate.org)

See LICENSE for details about how Abstraction Layer in Measurement Plug-In for Python is licensed.