Synopsis • Installation • Usage • Compatibility • Documentation • Contribute
The austin-python package is a Python wrapper around the Austin binary that
provides convenience classes to quickly develop your statistical profiling
tools. Whether your code is thread-based or asynchronous, austin-python has
you covered. This is, for instance, how you would turn Austin into a Python
application:
import asyncio
import sys
from austin.aio import AsyncAustin
from austin.format.collapsed_stack import AustinEventCollapsedStackFormatter
FORMATTER = AustinEventCollapsedStackFormatter()
class CollapsedStackAsyncAustin(AsyncAustin):
async def on_sample(self, sample):
print(FORMATTER.format(sample))
async def on_metadata(self, metadata):
print(FORMATTER.format(metadata))
if sys.platform == "win32":
asyncio.set_event_loop(asyncio.ProactorEventLoop())
async def main():
austin = CollapsedStackAsyncAustin()
await austin.start(["-i", "10ms", "python", "myscript.py"])
await austin.wait()
asyncio.run(main())The austin-python package is at the heart of the Austin
TUI and the Austin
Web Python applications. Go check them
out if you are looking for full-fledged usage examples.
Included with the package come two applications for the conversion of Austin collected output, which is in the form of collapsed stacks, to either the Speedscope JSON format or the Google pprof format. Note, however, that the Speedscope web application supports Austin native format directly.
This package can be installed from PyPI with
pip install --user austin-python --upgradePlease note that austin-python requires the Austin binary. The default
lookup locations are, in order,
- current working directory;
- the
AUSTINPATHenvironment variable which gives the path to the folder that contains the Austin binary; - the
.austinrcTOML configuration file in the user's home folder, e.g.~/.austinrcon Linux (see below for a sample.austinrcfile); - the
PATHenvironment variable.
A sample .austinrc file would look like so
binary = "/path/to/austin"A simple example of an echo application was shown above. Other examples using,
e.g., threads, can be found in the official documentation. You can also browse
through the code of the Austin TUI
and the Austin Web Python
applications to see how they leverage austin-python.
As it was mentioned before, this package also comes with two scripts for format
conversion, namely austin2speedscope and austin2pprof. They both take two
mandatory arguments, that is, the input and output file. For example, to convert
the Austin profile data file myscript.aprof to the Google pprof data file
myscript.pprof, you can run
austin2pprof myscript.aprof myscript.pprofThe package also provide the austin-compress utility to compress the Austin
raw samples by aggregation.
The latest austin-python package is tested on Linux, macOS and Windows with
Python 3.9-3.14.
The official documentation is hosted on readthedocs.io at austin-python.readthedocs.io.
If you want to help with the development, then have a look at the open issues and have a look at the contributing guidelines before you open a pull request.
You can also contribute to the development by either becoming a Patron on Patreon, by buying me a coffee on BMC or by chipping in a few pennies on PayPal.Me.
