[ANN] Austin -- CPython frame stack sampler v2.0.0 is now available
I am delighted to announce the release 2.0.0 of Austin. If you haven't
heard of Austin before, it is an open source frame stack sampler for
CPython, distributed under the GPLv3 license. It can be used to obtain
statistical profiling data out of a running Python application without a
single line of instrumentation. This means that you can start profiling a
Python application straightaway, even while it's running on a production
environment, with minimal impact on performance.
The simplest way of using Austin is by piping its output to FlameGraph
for a quick and detailed representation of the collected samples. The
latest release introduces a memory profiling mode which allows you to
profile memory usage.
Austin is a pure C application that has no other dependencies other than
the C standard library. Its source code is hosted on GitHub at
The README contains installation and usage details, as well as some
examples of Austin in action. Details on how to contribute to Austin's
development can be found at the bottom of the page.
Austin can be installed easily on the following platforms and from the
- Snap Store
- Debian repositories
Austin is also simple to compile from sources as it only depends on the
standard C library, if you don't have access to the above listed sources.
Besides support for Python 3.9, this new release of Austin brings a
considerable performance enhancement that allows it to sample up to 8
times faster than previous versions. But please do read on until the end
to find out about some new tools that take advantage of all the key
features of Austin.
Due to increasing popularity, the sample Python applications that were
included in the main repository have been moved to dedicated projects on
GitHub. The TUI can now be found at
They can both be installed easily from PyPI, but in order to use them the
Austin binary needs to be on the PATH environment variable. These
projects now rely on the austin-python Python package that provides a
Python wrapper around Austin. If you are considering making your own
profiling tool based on Austin, this package can spare you from writing
boilerplate code, so it's worth having a look at it at
Finally, I am happy to announce the release of pytest-austin, a plugin
for pytest that allows you to set up performance regression testing by
simply decorating your existing pytest test suite. The plugin launches
Austin to profile your test runs, meaning that no further instrumentation
is required. For more details, check out the project on GitHub