The Python special interest group (SIG) meets regularly. See the OpenTelemetry community repo for information on this and other language SIGs.
See the public meeting notes for a summary description of past meetings. To request edit access, join the meeting or get in touch on Slack.
See to the community membership document on how to become a Member, Approver and Maintainer.
If you are looking for someone to help you find a starting point and be a resource for your first contribution, join our Slack and find a buddy!
- Join Slack and join our chat room.
- Post in the room with an introduction to yourself, what area you are interested in (check issues marked "Help Wanted"), and say you are looking for a buddy. We will match you with someone who has experience in that area.
Your OpenTelemetry buddy is your resource to talk to directly on all aspects of contributing to OpenTelemetry: providing context, reviewing PRs, and helping those get merged. Buddies will not be available 24/7, but is committed to responding during their normal contribution hours.
To quickly get up and running, you can use the scripts/eachdist.py
tool that
ships with this project. First create a virtualenv and activate it.
Then run python scripts/eachdist.py develop
to install all required packages
as well as the project's packages themselves (in --editable
mode).
You can then run scripts/eachdist.py test
to test everything or
scripts/eachdist.py lint
to lint everything (fixing anything that is auto-fixable).
Additionally, this project uses tox
to automate some aspects
of development, including testing against multiple Python versions.
You can run:
tox
to run all existing tox commands, including unit tests for all packages under multiple Python versionstox -e py37-test-flask
to e.g. run the Flask tests under a specific Python versiontox -e lint
to run lint checks on all code
See
tox.ini
for more detail on available tox commands.
Performance progression of benchmarks for packages distributed by OpenTelemetry Python can be viewed as a graph of throughput vs commit history. From the linked page, you can download a JSON file with the performance results.
Running the tox
tests also runs the performance tests if any are available. Benchmarking tests are done with pytest-benchmark
and they output a table with results to the console.
To write benchmarks, simply use the pytest benchmark fixture like the following:
def test_simple_start_span(benchmark):
def benchmark_start_as_current_span(span_name, attribute_num):
span = tracer.start_span(
span_name,
attributes={"count": attribute_num},
)
span.end()
benchmark(benchmark_start_as_current_span, "benchmarkedSpan", 42)
Make sure the test file is under the tests/performance/benchmarks/
folder of
the package it is benchmarking and further has a path that corresponds to the
file in the package it is testing. Make sure that the file name begins with
test_benchmark_
. (e.g. propagator/opentelemetry-propagator-aws-xray/tests/performance/benchmarks/trace/propagation/test_benchmark_aws_xray_propagator.py
)
Everyone is welcome to contribute code to opentelemetry-python-contrib
via GitHub
pull requests (PRs).
To create a new PR, fork the project in GitHub and clone the upstream repo:
$ git clone https://github.com/open-telemetry/opentelemetry-python-contrib.git
Add your fork as an origin:
$ git remote add fork https://github.com/YOUR_GITHUB_USERNAME/opentelemetry-python-contrib.git
Run tests:
# make sure you have all supported versions of Python installed
$ pip install tox # only first time.
$ tox # execute in the root of the repository
Check out a new branch, make modifications and push the branch to your fork:
$ git checkout -b feature
# edit files
$ git commit
$ git push fork feature
Open a pull request against the main opentelemetry-python-contrib
repo.
- If the PR is not ready for review, please put
[WIP]
in the title, tag it aswork-in-progress
, or mark it asdraft
. - Make sure CLA is signed and CI is clear.
A PR is considered to be ready to merge when:
- It has received two approvals from Approvers / Maintainers (at different companies).
- Major feedbacks are resolved.
- It has been open for review for at least one working day. This gives people reasonable time to review.
- Trivial change (typo, cosmetic, doc, etc.) doesn't have to wait for one day.
- Urgent fix can take exception as long as it has been actively communicated.
- A changelog entry is added to the corresponding changelog for the code base, if there is any impact on behavior. e.g. doc entries are not required, but small bug entries are.
Any Approver / Maintainer can merge the PR once it is ready to merge.
As with other OpenTelemetry clients, opentelemetry-python follows the opentelemetry-specification.
It's especially valuable to read through the library guidelines.
OpenTelemetry is an evolving specification, one where the desires and use cases are clear, but the method to satisfy those uses cases are not.
As such, contributions should provide functionality and behavior that conforms to the specification, but the interface and structure is flexible.
It is preferable to have contributions follow the idioms of the language rather than conform to specific API names or argument patterns in the spec.
For a deeper discussion, see: open-telemetry/opentelemetry-specification#165
- Go to your Contrib repo directory.
git clone [email protected]:open-telemetry/opentelemetry-python-contrib.git && cd opentelemetry-python-contrib
. - Make sure you have
tox
installed.pip install tox
. - Run
tox
without any arguments to run tests for all the packages. Read more about tox.
Some of the tox targets install packages from the OpenTelemetry Python Core Repository via pip. The version of the packages installed defaults to the main branch in that repository when tox is run locally. It is possible to install packages tagged with a specific git commit hash by setting an environment variable before running tox as per the following example:
CORE_REPO_SHA=c49ad57bfe35cfc69bfa863d74058ca9bec55fc3 tox
The continuation integration overrides that environment variable with as per the configuration here.
- docstrings should adhere to the Google Python Style Guide as specified with the napolean extension extension in Sphinx.
Below is a checklist of things to be mindful of when implementing a new instrumentation or working on a specific instrumentation. It is one of our goals as a community to keep the implementation specific details of instrumentations as similar across the board as possible for ease of testing and feature parity. It is also good to abstract as much common functionality as possible.
- Follow semantic conventions
- The instrumentation should follow the semantic conventions defined here
- Extends from BaseInstrumentor
- Supports auto-instrumentation
- Add an entry point (ex. https://github.com/open-telemetry/opentelemetry-python-contrib/blob/main/instrumentation/opentelemetry-instrumentation-requests/setup.cfg#L56)
- Run
python scripts/setup.py
followed bypython scripts/generate_instrumentation_bootstrap.py
after adding a new instrumentation package.
- Functionality that is common amongst other instrumentation and can be abstracted here
- Request/response hooks for http instrumentations
suppress_instrumentation
functionality- Suppress propagation functionality
- open-telemetry#344 for more context
exclude_urls
functionalityurl_filter
functonalityis_recording()
optimization on non-sampled spans- Appropriate error handling
OpenTelemetry is an open source community, and as such, greatly encourages contributions from anyone interested in the project. With that being said, there is a certain level of expectation from contributors even after a pull request is merged, specifically pertaining to instrumentations. The OpenTelemetry Python community expects contributors to maintain a level of support and interest in the instrumentations they contribute. This is to ensure that the instrumentation does not become stale and still functions the way the original contributor intended. Some instrumentations also pertain to libraries that the current memebers of the community are not so familiar with, so it is necessary to rely on the expertise of the original contributing parties.