Structured Logging for Python
.. raw:: html
structlogmakes logging in Python faster, less painful, and more powerful by adding structure to your log entries.
It's up to you whether you want
structlogto take care about the output of your log entries or whether you prefer to forward them to an existing logging system like the standard library's
Once you feel inspired to try it out, check out our friendly
Getting Started tutorial_ that also contains detailed installation instructions!
If you prefer videos over reading, check out this DjangoCon Europe 2019 talk by
Markus Holtermann: "
Logging Rethought 2: The Actions of Frank Taylor Jr.".
You can stop writing prose and start thinking in terms of an event that happens in the context of key/value pairs:
.. code-block:: pycon
from structlog import getlogger log = getlogger() log.info("keyvaluelogging", outofthebox=True, effort=0) 2020-11-18 09:17.09 [info ] keyvaluelogging effort=0 outofthebox=True
Each log entry is a meaningful dictionary instead of an opaque string now!
Since log entries are dictionaries, you can start binding and re-binding key/value pairs to your loggers to ensure they are present in every following logging call:
.. code-block:: pycon
log = log.bind(user="anonymous", somekey=23) log = log.bind(user="hynek", anotherkey=42) log.info("user.loggedin", happy=True) 2020-11-18 09:18.28 [info ] user.loggedin anotherkey=42 happy=True somekey=23 user=hynek
Each log entry goes through a
processor pipeline_ that is just a chain of functions that receive a dictionary and return a new dictionary that gets fed into the next function. That allows for simple but powerful data manipulation:
.. code-block:: python
def timestamper(logger, logmethod, eventdict): """Add a timestamp to each log entry.""" eventdict["timestamp"] = time.time() return eventdict
plenty of processors_ for most common tasks coming with
call stack information_ ("How did this log entry happen?"),
exceptions_ ("What happened‽").
structlogis completely flexible about how the resulting log entry is emitted. Since each log entry is a dictionary, it can be formatted to any format:
JSON_ for easy parsing,
Internally, formatters are processors whose return value (usually a string) is passed into loggers that are responsible for the output of your message.
structlogcomes with multiple useful formatters out-of-the-box.
structlogis also very flexible with the final output of your log entries:
structlogworks like a wrapper that formats a string and passes them off into existing systems that won't ever know that
structlogeven exists. Or the other way round:
structlogcomes with a
loggingformatter that allows for processing third party log records.
structlogpasses you a dictionary and you can do with it whatever you want. Reported uses cases are sending them out via network or saving them in a database.
Please use the
StackOverflow_ to get help.
Answering questions of your fellow developers is also a great way to help the project!
structlogis dual-licensed under
Apache License, version 2_ and
MIT, available from
PyPI, the source code can be found on
GitHub_, the documentation at https://www.structlog.org/.
We collect useful third party extension in
structlogtargets Python 3.6 and newer, and PyPy3.
If you need support for older Python versions, the last release with support for Python 2.7 and 3.5 was
20.1.0_. The package meta data should ensure that you get the correct version.
Available as part of the Tidelift Subscription.
The maintainers of structlog and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source packages you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact packages you use.