Contribute to CumulusCI#
Contributions are welcome, and they are greatly appreciated!
Types of Contributions#
You can contribute in many ways:
Report bugs at https://github.com/SFDO-Tooling/CumulusCI/issues.
When reporting a bug, please include:
Your operating system name and version.
Any details about your local setup that might be helpful in troubleshooting.
Detailed steps to reproduce the bug.
Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whomever wants to implement it.
Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whomever wants to implement it.
CumulusCI could always use more documentation, whether as part of the official CumulusCI docs, in docstrings, or even on the web in blog posts, articles, and such.
Install for Development#
Ready to contribute? Here’s how to set up CumulusCI for local development.
Fork the CumulusCI repo on GitHub.
Clone your fork to your local workspace.
Create a fresh Python 3 virtual environment and activate it (to keep this isolated from other Python software on your machine). Here is one way:
$ python3 -m venv cci_venv $ source cci_venv/bin/activate
Install the development requirements:
$ make dev-install
$ pre-commit install --install-hooks
After making changes, run the tests and make sure they all pass:
Your new code should also have meaningful tests. One way to double check that your tests cover everything is to ensure that your new code has test code coverage:
$ make coverage
Push your changes to GitHub and submit a Pull Request. The base branch should be a new feature branch that we create to receive the changes (contact us to create the branch). This allows us to test the changes using our build system before merging to main.
We enable typeguard with pytest so if you add type declarations to your code, those declarations will be treated as runtime assertions in your Python tests.
Pull Request Guidelines#
Before you submit a pull request, check that it meets these guidelines:
Documentation is updated to reflect all changes.
New classes, functions, etc have docstrings.
New code has comments.
Code style and file structure is similar to the rest of the project.
You have run the
If you are a new contributor, don’t forget to add yourself to the
AUTHORS.rstfile in your pull request (either GitHub username, or first/last name).
You have labeled your pull request:
critical-changesfor breaking changes,
enhancementfor new features,
bugfor when fixing a bug or closing an issue, or
ignore-for-releasefor internal changes.
Org-reliant Automated Tests#
Some tests are marked
@pytest.mark.vcr() which means that they can
either call into a real (configured) Salesforce org or use a cached YAML
file of the request/response.
By default using pytest will use the cached YAML. If you want to work against a real scratch org, you do so like this:
$ pytest --org qa <other arguments and options, such as filename or -k testname>
Where “orgname” is a configured org name like “qa”, “dev”, etc.
To regenerate the VCR file, you can run this command:
$ pytest --replace-vcrs --org qa
This will configure an org named “qa” and regenerate them.
That will run all VCR-backed tests against the org, including all of the slow integration tests.
Running Integration Tests#
Some tests generate so much data that we do not want to store the VCR
cassettes in our repo. You can mark tests like that with
@pytest.mark.large_vcr(). When they are executed, their cassettes will
go in a .gitignore’d folder called
Do not commit the files (
large_cassettes/\*.yml) to the repository.
Some tests generate even more network traffic data and it isn’t
practical to use VCR at all. Still, we’d like to run them when we run
all of the other org-reliant tests with –org. Mark them with
@pytest.mark.needs_org() and they will run with the VCR tests.
Some tests are so slow that you only want to run them on an opt-in
basis. Mark these tests with
@pytest.mark.slow() and run them with
pytest --run-slow-tests or
pytest --run-slow-tests --orgname <orgname>.
Writing Integration Tests#
All features should have integration tests which work against real orgs or APIs.
Our test suite makes extensive use of pytest fixtures; the ones below should be used in your tests where appropriate. Search the repo to see examples where they are used in context, or to see their definitions:
gh_api - get a fake github API
with temp_db():… - create a temporary SQLite Database
delete_data_from_org(“Account,Contacts”) - delete named sobjects from an org
run_code_without_recording(func) - run a function ONLY when the integration tests are being used against real orgs and DO NOT record the network traffic in a VCR cassette
sf - a handle to a simple-salesforce client tied to the current org
mock_http_response(status) - make a mock HTTP Response with a particular status
runtime - Get the CumulusCI runtime for the current working directory
project_config - Get the project config for the current working directory
org_config - Get the project config for the current working directory
createtask - Get a task _factory which can be used to construct task instances.
global_describe - Get a function that will generate the JSON that Salesforce would generate if you do a GET on the /sobjects endpoint
Decorators for tests:
pytest.mark.slow(): a slow test that should only be executed when requested with –run-slow-tests
pytest.mark.large_vcr(): a network-based test that generates VCR cassettes too large for version control. Use –org to generate them locally.
pytest.mark.needs_org(): a test that needs an org (or at least access to the network) but should not attempt to store VCR cassettes. Most tests that need network access do so because they need to talk to an org, but you can also use this decorator to give access to the network to talk to github or any other API.
pytest.mark.org_shape(‘qa’, ‘qa_org’): - switch the current org to an org created with org template “qa” after running flow “qa_org”. As with all tests, clean up any changes you make, because this org may be reused by other tests.
A complete list is available with:
$ pytest –markers
Tests should be executable in any order. You can run this command a few times to verify if they are:
It will output something like this:
Using –random-order-bucket=module Using –random-order-seed=986925
Using those two parameters on the command line, you can replicate a particular run later.
In extremely rare cases where it’s not possible to make tests independent, you can enforce an order