ddtrace is Datadog's tracing library for Python. It is used to trace requests
as they flow across web servers, databases and microservices so that developers
have great visibility into bottlenecks and troublesome requests.
For a basic product overview, installation and quick start, check out our setup documentation.
For more advanced usage and configuration, check out our API documentation.
For descriptions of terminology used in APM, take a look at the official documentation.
The tracer library uses formatting/linting tools including black, flake8, and mypy.
While these are run in each CI pipeline for pull requests, they are automated to run
when you call git commit as pre-commit hooks to catch any formatting errors before
you commit. To initialize the pre-commit hook script to run in your development
branch, run the following command:
$ hooks/autohook.sh install
The test suite requires many backing services such as PostgreSQL, MySQL, Redis
and more. We use docker and docker-compose to run the services in our CI
and for development. To run the test matrix, please install docker and
docker-compose using the instructions provided by your platform. Then
launch them through:
$ docker-compose up -d
Once your docker-compose environment is running, you can use the shell script to execute tests within a Docker image. You can start the container with a bash shell:
$ scripts/ddtest
You can now run tests as you would do in your local environment. We use tox as well as riot, a new tool that we developed for addressing our specific needs with an ever growing matrix of tests. You can list the tests managed by each:
$ tox -l
$ riot list
You can run multiple tests by using regular expressions:
$ scripts/run-tox-scenario '^futures_contrib-'
$ riot run psycopg
We use CircleCI 2.0 for our continuous integration.
The CI tests are configured through config.yml.
The CI tests can be run locally using the circleci CLI. More information about
the CLI can be found at https://circleci.com/docs/2.0/local-cli/.
After installing the circleci CLI, you can run jobs by name. For example:
$ circleci build --job django