Markus v3.0.0 released! Better metrics API for Python projects.

What is it?

Markus is a Python library for generating metrics.

Markus makes it easier to generate metrics in your program by:

  • providing multiple backends (Datadog statsd, statsd, logging, logging roll-up, and so on) for sending metrics data to different places

  • sending metrics to multiple backends at the same time

  • providing testing helpers for easy verification of metrics generation

  • providing a decoupled architecture making it easier to write code to generate metrics without having to worry about making sure creating and configuring a metrics client has been done--similar to the Python logging module in this way

We use it at Mozilla on many projects.

v3.0.0 released!

I released v3.0.0 just now. Changes:

Features

  • Added support for Python 3.9 (#79). Thank you, Brady!

  • Changed assert_* helper methods on markus.testing.MetricsMock to print the records to stdout if the assertion fails. This can save some time debugging failing tests. (#74)

Backwards incompatible changes

  • Dropped support for Python 3.5 (#78). Thank you, Brady!

  • markus.testing.MetricsMock.get_records and markus.testing.MetricsMock.filter_records return markus.main.MetricsRecord instances now.

    This might require you to rewrite/update tests that use the MetricsMock.

Where to go for more

Changes for this release: https://markus.readthedocs.io/en/latest/history.html#february-5th-2021

Documentation and quickstart here: https://markus.readthedocs.io/en/latest/index.html

Source code and issue tracker here: https://github.com/willkg/markus/

Let me know how this helps you!

Want to comment? Send an email to willkg at bluesock dot org. Include the url for the blog entry in your comment so I have some context as to what you're talking about.