Skip to content

Latest commit

 

History

History
105 lines (69 loc) · 5.71 KB

CONTRIBUTING.md

File metadata and controls

105 lines (69 loc) · 5.71 KB

Contributing Guidelines

Thank you for your interest in contributing to our project. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check existing open, or recently closed, issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. You are working against the latest source on the main branch.
  2. You check existing open, and recently merged, pull requests to make sure someone else hasn't addressed the problem already.
  3. You open an issue to discuss any significant work - we would hate for your time to be wasted.

Pull Down the Code

  1. If you do not already have one, create a GitHub account by following the prompts at Join Github.
  2. Create a fork of this repository on GitHub. You should end up with a fork at https://github.com/<username>/studio-lab-examples.
    1. Follow the instructions at Fork a Repo to fork a GitHub repository.
  3. Clone your fork of the repository: git clone https://github.com/<username>/studio-lab-examples where <username> is your github username.

Create the Example

Here are some general guidelines to follow when writing example notebooks:

  • Do not require user input to run the notebook.
    • 👍 bucket = session.default_bucket()
    • 👎 bucket = <YOUR_BUCKET_NAME_HERE>
  • Do not require user secret to run the notebook.
    • 👍 Please execute aws configure and input your secrets by opening the Terminal from the menu.
    • 👎 aws_access_key_id = < paste your access key here, run this cell, then delete the cell >
  • Lint your code and notebooks. (See the section on running the linters for guidance.)
  • Use present tense.
    • 👍 "The estimator fits a model."
    • 👎 "The estimator will fit a model."
  • When referring to an AWS product, use its full name in the first invocation. (This applies only to prose; use what makes sense when it comes to writing code, etc.)
    • 👍 "Amazon S3"
    • 👎 "s3"
  • Provide links to other ReadTheDocs pages, AWS documentation, etc. when helpful. Try to not duplicate documentation when you can reference it instead.

Run the Linter

Apply Python code formatting to Jupyter notebook files using black-nb.

  1. Install black-nb using pip install black-nb
  2. Run the following black-nb command on each of your ipynb notebook files and verify that the linter passes: black-nb -l 100 {path}/{notebook-name}.ipynb
  3. Some notebook features such as % bash commands or %% cell magic cause black-nb to fail. As long as you run the above command to format as much as possible, that is sufficient, even if the check fails

Test Your Notebook End-to-End

Please ensure that your notebook runs end-to-end by Restart & Run All.

Commit Your Change

Use imperative style and keep things concise but informative. See How to Write a Git Commit Message for guidance.

Send a Pull Request

GitHub provides additional document on Creating a Pull Request.

Please remember to:

  • Send us a pull request, answering any default questions in the pull request interface.

Merge a Pull Request (Done by maintainer)

We merge your pull request by squash merge to put commits together.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As our projects, by default, use the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any 'help wanted' issues is a great place to start.

Code of Conduct

This project has adopted the Amazon Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Security issue notifications

If you discover a potential security issue in this project we ask that you notify AWS/Amazon Security via our vulnerability reporting page. Please do not create a public github issue.

Licensing

See the LICENSE file for our project's licensing. We will ask you to confirm the licensing of your contribution.