Hi, thanks for your interest in the project! We welcome pull requests from developers of all skill levels.
Jens H. Nielsen ([email protected]), William H.P Nielsen ([email protected]), Dominik Vogel ([email protected]), and Sohail Chatoor ([email protected]) are the current maintainers of QCoDeS (aka core developers), along with a group of talented and smart volunteers. Please don't hesitate to reach out if you have any questions, or just need a little help getting started.
Join us on Slack, where informal discussion is more than welcome. (For now email one of us to be invited)
Contents
We use github's issues. Search for existing and closed issues. If your problem or idea is not yet addressed, please open a new issue
The github GUI will show you a template both for bugs and features. Delete the wrong part and try to follow the template. Writing a good issue helps you in the first place. Bug reports must be accompanied by a reproducible example.
Have an idea about future directions to go with Qcodes? Visions of
data-utopia that would take more than a few weeks to add or might change
some core ideas in the package? We can use issues for this too. We will pick the
long-term
or discussion
labels.
If somebody is assigned to an issue it means that somebody is working on it.
Figured out a new way to use QCoDeS? Found a package that makes your life better and easier? Got realtime analysis working after struggling with it for days? Write it on Slack so we can keep github more organized.
- Clone and register the package for development as described in the README
- Run tests
- Ready to hack
We don't want to reinvent the wheel, and thus use py.test. It's easy to install:
pip install coverage pytest-cov pytest
Then to test and view the coverage:
- ::
- py.test --cov=qcodes --cov-report xml --cov-config=.coveragerc
You can also run single tests with:
# python -m unittest module # python -m unittest module.class # python -m unittest module.class.function python -m unittest qcodes.tests.test_metadata # or python -m unittest qcodes.tests.test_metadata.TestMetadatable.test_snapshot
If the tests pass, you should be ready to start developing!
To tests actual instruments, first instantiate them in an interactive
python session, then run qcodes.test_instruments()
:
import qcodes
sig_gen = qcodes.instrument_drivers.agilent.E8527D.Agilent_E8527D('source', address='...')
qcodes.test_instruments() # optional verbosity = 1 (default) or 2
The output of this command should include lines like:
***** found one Agilent_E8527D, testing *****
for each class of instrument you have defined. Note that if you instantiate several instruments of the same class, only the last one will be tested unless you write the test to explicitly test more than this.
Coverage testing is generally meaningless for instrument drivers, as
calls to add_parameter
and add_function
do not add any code
other than the call itself, which is covered immediately on
instantiation rather than on calling these parameters/functions. So it
is up to the driver author to ensure that all functionality the
instrument supports is covered by tests. Also, it's mentioned below but
bears repeating: if you fix a bug, write a test that would have failed
before your fix, so we can be sure the bug does not reappear later!
- Fork the repo into your github account
- Make a branch within this repo
- branch naming matters:
- always select a prefix:
- feature/bar (if you add the feature bar)
- hotfix/bar (if you fix the bug bar)
- foo/bar (if you foo the bar)
- never use your username If you can't figure out a name for your branch, re-think about what you would be doing. It's always a good exercise to model the problem before you try to solve it. Also, ping on slack. We <3 you in the first place.
- always select a prefix:
A useful git repo starts with great commits. This is not optional, and it may seem daunting at first but you'll soon get the hang of it and will find out that it helps with developing good software. Nobody will get shot/tortured if the guidelines are not followed but you'll have to fix your commits.
Each commit message consists of a header, a body and a footer. The header has a special format that includes a type and a subject:
<type>: <subject> <BLANK LINE> <body> <BLANK LINE> <footer>
Limit the subject line to 50 characters. This is mandatory, github will truncate otherwise making the commit hard to read. No line may exceed 100 characters. This makes it easier to read the message on GitHub as well as in various git tools.
Type
Must be one of the following:
- feat: A new feature
- fix: A bug fix
- docs: Documentation only changes
- style: Changes that do not affect the meaning of the code (white-space, formatting, missing semi-colons, etc)
- refactor: A code change that neither fixes a bug nor adds a feature
- perf: A code change that improves performance
- test: Adding missing tests
- chore: Changes to the build process or auxiliary tools and libraries such as documentation generation
Subject
The subject contains succinct description of the change:
- use the imperative, present tense: "change" not "changed" nor "changes"
- capitalize first letter
- no dot (.) at the end
Body
Just as in the subject, use the imperative, present tense: "change" not "changed" nor "changes"The body should include the motivation for the change and contrast this with previous behavior.
Footer
The footer should contain any information about Breaking Changes and is also the place to reference GitHub issues that this commit Closes.
You are allowed to skip both body and footer only and only if your header is indeed enough to understandable 10 years after.
A good commit is really important (for you writing it in the first place). If you need a loving guide all the time you commit, see here. Do not push! Unless you are sure about your commits. If you have a typo in your commit message, do not push. If you added more files/changes that the commit says, do not push. In general everything is fixable if you don't push. The reason is that on your local machine you can always re-write history and make everything look nice, once pushed is just harder to go back. If in doubt, ask and help will be given. Nobody was born familiar with git, and everybody makes mistakes.
- Write your new feature or fix. Be sure it doesn't break any existing tests, and please write tests that cover your feature as well, or if you are fixing a bug, write a test that would have failed before your fix. Our goal is 100% test coverage, and although we are not there, we should always strive to increase our coverage with each new feature. Please be aware also that 100% test coverage does NOT necessarily mean 100% logic coverage. If (as is often the case in Python) a single line of code can behave differently for different inputs, coverage in itself will not ensure that this is tested.
- Write the docs, following the other documentation files (.rst) in the repo.
NOTE(giulioungaretti): maybe running test locally should be simplified, and then unit testing should be run on pull-request, using CI. Maybe simplify to a one command that says: if there's enough cover, and all good or fail and where it fails.
- We should have a few high-level "integration" tests, but simple unit tests (that just depend on code in one module) are more valuable for several reasons:
- If complex tests fail it's more difficult to tell why
- When features change it is likely that more tests will need to change
- Unit tests can cover many scenarios much faster than integration tests.
- If you're having difficulty making unit tests, first consider whether your code could be restructured to make it less dependent on other modules. Often, however, extra techniques are needed to break down a complex test into simpler ones. @alexcjohnson or @giulioungaretti are happy to help with this. Two ideas that are useful here:
- Patching, one of the most useful parts of the unittest.mock library. This lets you specify exactly how other functions/objects should behave when they're called by the code you are testing.
- Supporting files / data: Lets say you have a test of data acquisition and analysis. You can break that up into an acquisition test and an analysis by saving the intermediate state, namely the data file, in the test directory. Use it to compare to the output of the acquisition test, and as the input for the analysis test.
- We have not yet settled on a framework for testing real hardware. Stay tuned, or post any ideas you have as issues!
NOTE(giulioungaretti): is this enough ?
- Try to make your code self-documenting. Python is generally quite amenable to that, but some things that can help are:
- Use clearly-named variables
- Only use "one-liners" like list comprehensions if they really fit on one line.
- Comments should be for describing why you are doing something. If you feel you need a comment to explain what you are doing, the code could probably be rewritten more clearly.
- If you do need a multiline statement, use implicit continuation (inside parentheses or brackets) and implicit string literal concatenation rather than backslash continuation
- Format non-trivial comments using your GitHub nick and one of these
prefixes:
- TODO( theBrain ): Take over the world!
- NOTE( pinky ): Well, that's a good idea.
- Docstrings are required for classes, attributes, methods, and functions (if public i.e no leading underscore). Because docstrings (and comments) are not code, pay special attention to them when modifying code: an incorrect comment or docstring is worse than none at all! Docstrings should utilize the google style in order to make them read well, regardless of whether they are viewed through help() or on Read the Docs. See the falcon framework for best practices examples.
- Use PEP8 style. Not only is this style good for readability in an absolute sense, but consistent styling helps us all read each other's code.
- There is a command-line tool (
pip install pep8
) you can run after writing code to validate its style. - A lot of editors have plugins that will check this for you automatically as you type. Sublime Text for example has sublimelinter-pep8 and the even more powerful sublimelinter-flake8. For Emacs, the elpy package is strongly recommended (https://github.com/jorgenschaefer/elpy).
- BUT: do not change someone else's code to make it pep8-compliant unless that code is fully tested.
- BUT: remove all trailing spaces.
- BUT: do not mix tabs and indentation for any reason.
- JavaScript: The Airbnb style guide is quite good. If we start writing a lot more JavaScript we can go into more detail.
- Push your branch back to github and make a pull request (PR). If you visit the repo home page soon after pushing to a branch, github will automatically ask you if you want to make a PR and help you with it.
- Naming matters; try to come up with a nice header:
- fix(dataformatter): Decouple foo from bar
- feature: Add logviewer
- The template will help you write nice pull requests <3 !
- Try to keep PRs small and focused on a single task. Frequent small PRs are much easier to review, and easier for others to work around, than large ones that touch the whole code base.
- tag AT LEAST ONE person in the description of the PR (a tag is
@username
) who you would like to have look at your work. Of course everyone is welcome and encouraged to chime in. - It's OK (in fact encouraged) to open a pull request when you still
have some work to do. Just make a checklist
(
- [ ] take over the world
) to let others know what more to expect in the near future. - There are a number of emoji that have specific meanings within our github conversations. The most important one is 💃 which means "approved" - typically one of the core contributors should give the dancer. Ideally this person was also tagged when you opened the PR.
- Delete your branch once you have merged (using the helpful button
provided by github after the merge) to keep the repository clean.
Then on your own computer, after you merge and pull the merged master
down, you can call
git branch --merged
to list branches that can be safely deleted, thengit branch -d <branch-name>
to delete it.