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CONTRIBUTING.md

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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

Here is a list of tags to label issues and help us triage them:

  • question: A question on the library. Consider starting a discussion instead
  • bug: An error encountered when using the library
  • feature: A completely new idea not currently covered by the library
  • enhancement: A suggestion to enhance an existing feature

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.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass.
  4. Commit to your fork using clear commit messages.
  5. Send us a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional document on forking a repository and creating a pull request.

Note: An automated Code Build is triggered with every pull request. To skip it, add the prefix [skip-ci] to your commit message.

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.

We may ask you to sign a Contributor License Agreement (CLA) for larger changes.

Environments

There are hundreds of tests that run against several AWS Services. You don't need to test everything to open a Pull Request. You can choose from three environments to test your fixes/changes, based on what makes sense for your use case.

Start at Step by step, and then choose from one of these environments:

  • Mocked test environment

    • Based on moto.
    • Does not require real AWS resources
    • Fastest approach
    • Limited to a few services (S3 tests)
  • Basic test environment

    • Requires some AWS services
    • Amazon S3, Amazon Athena, AWS Glue Catalog, AWS KMS
    • A cost is incurred
  • Full test environment

    • Requires access to numerous AWS services
    • Amazon S3, Amazon Athena, AWS Glue Catalog, AWS KMS, Amazon Redshift, Aurora PostgreSQL, Aurora MySQL, Amazon Quicksight, etc
    • Full test coverage
    • A cost is incurred

Step by step

These instructions are for Linux and Mac machines, some steps might not work for Windows.

Fork the AWS SDK for pandas repository and clone it into your development environment.

poetry is the Python dependency management system used for development. To install it use:

curl -sSL https://install.python-poetry.org | python3 -

You can then install required and dev dependencies with:

poetry install

If you are testing an optional dependency (e.g. sparql), you can add it with:

poetry install --extras "sparql" -vvv

To install all extra dependencies (only recommended for advanced usage):

poetry install --all-extras

Poetry creates a virtual environment for you. To activate it, use:

source "$(poetry env info --path )/bin/activate"

A validate.sh script is used for linting and typing (black, mypy...):

./validate.sh

Mocked test environment

Some unit tests can be mocked locally, i.e. no AWS account is required:

To run a specific test:

pytest tests/unit/test_moto.py::test_get_bucket_region_succeed

To run all mocked tests (Using 8 parallel processes):

pytest -n 8 tests/unit/test_moto.py

Basic test environment

DISCLAIMER: You will incur a cost for some of the services used in your AWS account. A basic understanding of AWS security principles is highly recommended.

OPTIONAL: Set the AWS_DEFAULT_REGION environment variable to define the AWS region where the infrastructure is deployed:

export AWS_DEFAULT_REGION=ap-northeast-1

Infrastructure is deployed with the AWS CDK. Follow this guide to install it if it's missing.

Navigate to the test_infra directory and install CDK dependencies

cd test_infra
poetry install

Then deploy the base CDK stack (i.e. minimum required infrastructure)

./scripts/deploy-stack.sh base

Return to the project root directory

cd ../

To run a specific test:

pytest tests/unit/test_athena_parquet.py::test_parquet_catalog

To run all athena tests (Using 8 parallel processes):

pytest -n 8 tests/unit/test_athena*

OPTIONAL: To remove the base test environment CloudFormation stack, use:

./test_infra/scripts/delete-stack.sh base

Full test environment

DISCLAIMER: You will incur a cost for some of the services used in your AWS account. A basic understanding of AWS security principles is highly recommended.

DISCLAIMER: This environment provisions Aurora MySQL, Aurora PostgreSQL, Redshift (single-node) clusters which may incur a significant cost while running.

OPTIONAL: Set the AWS_DEFAULT_REGION environment variable to define the AWS region where the infrastructure is deployed:

export AWS_DEFAULT_REGION=ap-northeast-1

Infrastructure is deployed with the AWS CDK. Follow this guide to install it if it's missing.

Navigate to the test_infra directory and install CDK dependencies

cd test_infra
poetry install

Deploy the base and databases CDK stacks. This step could take 15 minutes to complete.

./scripts/deploy-stack.sh base
./scripts/deploy-stack.sh databases

OPTIONAL: Deploy the opensearch CDK stack (if you need to test against the Amazon OpenSearch Service). This step could take 15 minutes to complete.

./scripts/deploy-stack.sh opensearch

Go to the EC2 -> SecurityGroups console, open the aws-sdk-pandas-* security group and configure it to accept your IP from any TCP port.

  • Alternatively run:

./scripts/security-group-databases-add-local-ip.sh

  • Check local IP was applied:

./scripts/security-group-databases-check.sh

P.S Make sure that your security group will not be open to the World! Configure your security group to only give access to your IP.

Return to the project root directory

cd ../

OPTIONAL: If you intend to run all tests, you must also ensure that Amazon QuickSight is activated and your AWS user/role is registered.

To run a specific test:

pytest tests/unit/test_mysql.py::test_read_sql_query_simple

To run all database MySQL tests (Using 8 parallel processes):

pytest -n 8 tests/unit/test_mysql.py

To run all tests for all python versions (assuming Amazon QuickSight is activated and the optional stack deployed):

./test.sh

OPTIONAL: To destroy stacks use:

./test_infra/scripts/delete-stack.sh <name>

Recommended Visual Studio Code Recommended setting

{
  "python.formatting.provider": "black",
  "python.linting.enabled": true,
  "python.linting.flake8Enabled": true,
  "python.linting.mypyEnabled": true,
  "python.linting.pylintEnabled": false
}

Common Errors

Check the file below to check the common errors and solutions ERRORS

Bumping the version

When there is a new release you can use bump-my-version for updating the version number in relevant files. You can run bump-my-version major|minor|patch in the top directory and the following steps will be executed:

  • The version number in all files which are listed in .bumpversion.toml is updated
  • A new commit with message Bump version: {current_version} → {new_version} is created
  • A new Git tag {new_version} is created