Performance testing and profiling
=================================

Load testing
------------

The venueless source tree includes a small load testing tool that opens up many websocket connections to a venueless
server, sends messages and measures response times. To use it, open up the folder and install the dependencies::

    $ cd load-test
    $ npm install

Then, you can use it like this::

    $ npm start ws://localhost:8375/ws/world/sample/

To modify the load testing parameters, you can adjust the following command line options:

``--clients``
    The number of clients to simulate that connect to the websocket.

``--rampup``
    The wait time in milliseconds between the creation of two new clients.

``--msgs``
    The total number of chat messages per second to emulate (once all clients are connected).

Note that the regular development webserver started by our docker compose setup is a single-threaded, non-optimized
setup. To run a more production-like setting, you can run the following commands::

    $ docker-compose stop server
    $ docker-compose run -p 8375:8375 \
        --entrypoint "gunicorn -k uvicorn.workers.UvicornWorker --bind 0.0.0.0:8375 -w 12 venueless.asgi:application" \
        server

Replace ``12`` with two times the number of CPU cores you have.
Note: With these settings, the server will not automatically reload when you change the code.

Profiling
---------

To find out which part of the server code is eating your CPU, you can start a profiled server. To do so with our standard
setup, execute the following commands::

    $ docker-compose stop server
    $ docker-compose run -p 8375:8375 \
        --entrypoint "python manage.py runserver_profiled 0.0.0.0:8375" \
        server

Then, apply your load, e.g. run the load testing tool from above or use venueless manually. Once you hit Ctrl+C, the
console will show a list of all called functions and the time the CPU spent on them. The output is generated by
`yappi`_, so please read there documentation for in-depth guidance what it means.

You can also trigger statistical output without stopping the server by running the following command in a separate
shell::

    $ docker-compose kill -s SIGUSR1 server

Note: With these settings, the server will not automatically reload when you change the code.

.. _yappi: https://github.com/sumerc/yappi