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.

See docs/contributing.rst.

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 run the test runner image:

$ docker-compose run --rm testrunner

Now you are in a bash shell. You can now run tests as you would do in your local environment:

$ tox -e '{py35,py36}-redis{210}'

We also provide a shell script to execute commands in the provided container.

For example to run the tests for redis-py 2.10 on Python 3.5 and 3.6:

$ ./scripts/ddtest tox -e '{py35,py36}-redis{210}'

If you want to run a list of tox environment (as CircleCI does) based on a pattern, you can use the following command:

$ scripts/ddtest scripts/run-tox-scenario '^futures_contrib-'

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