Getting Started

Installation

structlog can be easily installed using:

$ pip install structlog

If you’d like colorful output in development (you know you do!), install using:

$ pip install structlog colorama

Your First Log Entry

A lot of effort went into making structlog accessible without reading pages of documentation. And indeed, the simplest possible usage looks like this:

>>> import structlog
>>> log = structlog.get_logger()
>>> log.msg("greeted", whom="world", more_than_a_string=[1, 2, 3])  
2016-09-17 10:13.45 greeted                        more_than_a_string=[1, 2, 3] whom='world'

Here, structlog takes full advantage of its hopefully useful default settings:

  • Output is sent to standard out instead of exploding into the user’s face or doing nothing.

  • All keywords are formatted using structlog.dev.ConsoleRenderer. That in turn uses repr() to serialize all values to strings. Thus, it’s easy to add support for logging of your own objects*.

  • If you have colorama installed, it’s rendered in nice colors.

It should be noted that even in most complex logging setups the example would still look just like that thanks to Configuration. Using the defaults, as above, is equivalent to:

import structlog
structlog.configure(
    processors=[
        structlog.processors.StackInfoRenderer(),
        structlog.processors.format_exc_info,
        structlog.processors.TimeStamper(),
        structlog.dev.ConsoleRenderer()
    ],
    wrapper_class=structlog.BoundLogger,
    context_class=dict,  # or OrderedDict if the runtime's dict is unordered (e.g. Python <3.6)
    logger_factory=structlog.PrintLoggerFactory(),
    cache_logger_on_first_use=False
)
log = structlog.get_logger()

Note

For brevity and to enable doctests, all further examples in structlog’s documentation use the more simplistic structlog.processors.KeyValueRenderer() without timestamps.

There you go, structured logging! However, this alone wouldn’t warrant its own package. After all, there’s even a recipe on structured logging for the standard library. So let’s go a step further.

Building a Context

Imagine a hypothetical web application that wants to log out all relevant data with just the API from above:

from structlog import get_logger


log = get_logger()


def view(request):
    user_agent = request.get("HTTP_USER_AGENT", "UNKNOWN")
    peer_ip = request.client_addr
    if something:
        log.msg("something", user_agent=user_agent, peer_ip=peer_ip)
        return "something"
    elif something_else:
        log.msg("something_else", user_agent=user_agent, peer_ip=peer_ip)
        return "something_else"
    else:
        log.msg("else", user_agent=user_agent, peer_ip=peer_ip)
        return "else"

The calls themselves are nice and straight to the point, however you’re repeating yourself all over the place. At this point, you’ll be tempted to write a closure like

def log_closure(event):
   log.msg(event, user_agent=user_agent, peer_ip=peer_ip)

inside of the view. Problem solved? Not quite. What if the parameters are introduced step by step? Do you really want to have a logging closure in each of your views?

Let’s have a look at a better approach:

from structlog import get_logger


logger = get_logger()


def view(request):
    log = logger.bind(
        user_agent=request.get("HTTP_USER_AGENT", "UNKNOWN"),
        peer_ip=request.client_addr,
    )
    foo = request.get("foo")
    if foo:
        log = log.bind(foo=foo)
    if something:
        log.msg("something")
        return "something"
    elif something_else:
        log.msg("something_else")
        return "something_else"
    else:
        log.msg("else")
        return "else"

Suddenly your logger becomes your closure!

For structlog, a log entry is just a dictionary called event dict[ionary]:

  • You can pre-build a part of the dictionary step by step. These pre-saved values are called the context.

  • As soon as an event happens – which is a dictionary too – it is merged together with the context to an event dict and logged out.

  • If you don’t like the concept of pre-building a context: just don’t! Convenient key-value-based logging is great to have on its own.

  • To keep as much order of the keys as possible, an collections.OrderedDict is used for the context by default for Pythons that do not have ordered dictionaries by default (notably all versions of CPython before 3.6).

  • The recommended way of binding values is the one in these examples: creating new loggers with a new context. If you’re okay with giving up immutable local state for convenience, you can also use thread/greenlet local storage for the context.

Manipulating Log Entries in Flight

Now that your log events are dictionaries, it’s also much easier to manipulate them than if it were plain strings.

To facilitate that, structlog has the concept of processor chains. A processor is a callable like a function that receives the event dictionary along with two other arguments and returns a new event dictionary that may or may not differ from the one it got passed. The next processor in the chain receives that returned dictionary instead of the original one.

Let’s assume you wanted to add a timestamp to every event dict. The processor would look like this:

>>> import datetime
>>> def timestamper(_, __, event_dict):
...     event_dict["time"] = datetime.datetime.now().isoformat()
...     return event_dict

Plain Python, plain dictionaries. Now you have to tell structlog about your processor by configuring it:

>>> structlog.configure(processors=[timestamper, structlog.processors.KeyValueRenderer()])
>>> structlog.get_logger().msg("hi")  
event='hi' time='2018-01-21T09:37:36.976816'

Rendering

Finally you want to have control over the actual format of your log entries.

As you may have noticed in the previous section, renderers are just processors too. It’s also important to note, that they do not necessarily have to render your event dictionary to a string. It depends on the logger that is wrapped by structlog what kind of input it should get.

However, in most cases it’s gonna be strings.

So assuming you want to follow best practices and render your event dictionary to JSON that is picked up by a log aggregation system like ELK or Graylog, structlog comes with batteries included – you just have to tell it to use its JSONRenderer:

>>> structlog.configure(processors=[structlog.processors.JSONRenderer()])
>>> structlog.get_logger().msg("hi")
{"event": "hi"}

structlog and Standard Library’s logging

structlog’s primary application isn’t printing though. Instead, it’s intended to wrap your existing loggers and add structure and incremental context building to them. For that, structlog is completely agnostic of your underlying logger – you can use it with any logger you like.

The most prominent example of such an ‘existing logger’ is without doubt the logging module in the standard library. To make this common case as simple as possible, structlog comes with some tools to help you:

>>> import logging
>>> logging.basicConfig()
>>> from structlog.stdlib import LoggerFactory
>>> structlog.configure(logger_factory=LoggerFactory())  
>>> log = structlog.get_logger()
>>> log.warning("it works!", difficulty="easy")  
WARNING:structlog...:difficulty='easy' event='it works!'

In other words, you tell structlog that you would like to use the standard library logger factory and keep calling get_logger() like before.

Since structlog is mainly used together with standard library’s logging, there’s more goodness to make it as fast and convenient as possible.

Liked what you saw?

Now you’re all set for the rest of the user’s guide and can start reading about bound loggers – the heart of structlog. If you want to see more code, make sure to check out the Examples!

*

In production, you’re more likely to use JSONRenderer that can also be customized using a __structlog__ method so you don’t have to change your repr methods to something they weren’t originally intended for.