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structlog

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structlog makes logging in Python faster, less painful, and more powerful by adding structure to your log entries.

It's up to you whether you want structlog to 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 logging module.

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.".

Easier Logging

You can stop writing prose and start thinking in terms of an event that happens in the context of key/value pairs:

>>> from structlog import get_logger
>>> log = get_logger()
>>> log.info("key_value_logging", out_of_the_box=True, effort=0)
2020-11-18 09:17.09 [info     ] key_value_logging              effort=0 out_of_the_box=True

Each log entry is a meaningful dictionary instead of an opaque string now!

Data Binding

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:

>>> log = log.bind(user="anonymous", some_key=23)
>>> log = log.bind(user="hynek", another_key=42)
>>> log.info("user.logged_in", happy=True)
2020-11-18 09:18.28 [info     ] user.logged_in                 another_key=42 happy=True some_key=23 user=hynek

Powerful Pipelines

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:

def timestamper(logger, log_method, event_dict):
    """Add a timestamp to each log entry."""
    event_dict["timestamp"] = time.time()
    return event_dict

There are plenty of processors for most common tasks coming with structlog:

Formatting

structlog is completely flexible about how the resulting log entry is emitted. Since each log entry is a dictionary, it can be formatted to any format:

  • A colorful key/value format for local development,
  • JSON for easy parsing,
  • or some standard format you have parsers for like nginx or Apache httpd.

Internally, formatters are processors whose return value (usually a string) is passed into loggers that are responsible for the output of your message. structlog comes with multiple useful formatters out-of-the-box.

Output

structlog is also very flexible with the final output of your log entries:

  • A built-in lightweight printer like in the examples above. Easy to use and fast.
  • Use the standard library's or Twisted's logging modules for compatibility. In this case structlog works like a wrapper that formats a string and passes them off into existing systems that won't ever know that structlog even exists. Or the other way round: structlog comes with a logging formatter that allows for processing third party log records.
  • Don't format it to a string at all! structlog passes 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.

Getting Help

Please use the structlog tag on StackOverflow to get help.

Answering questions of your fellow developers is also a great way to help the project!

Project Information

structlog is 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 our wiki.

structlog targets 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.

structlog for Enterprise

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. Learn more.