Processors¶

The true power of structlog lies in its combinable log processors. A log processor is a regular callable, i.e. a function or an instance of a class with a __call__() method.

Chains¶

The processor chain is a list of processors. Each processors receives three positional arguments:

logger: Your wrapped logger object. For example logging.Logger.
method_name: The name of the wrapped method. If you called log.warn('foo'), it will be "warn".
event_dict: Current context together with the current event. If the context was {'a': 42} and the event is "foo", the initial event_dict will be {'a':42, 'event': 'foo'}.

The return value of each processor is passed on to the next one as event_dict until finally the return value of the last processor gets passed into the wrapped logging method.

Examples¶

If you set up your logger like:

from structlog import PrintLogger, wrap_logger
wrapped_logger = PrintLogger()
logger = wrap_logger(wrapped_logger, processors=[f1, f2, f3, f4])
log = logger.new(x=42)

and call log.msg('some_event', y=23), it results in the following call chain:

wrapped_logger.msg(
   f4(wrapped_logger, 'msg',
      f3(wrapped_logger, 'msg',
         f2(wrapped_logger, 'msg',
            f1(wrapped_logger, 'msg', {'event': 'some_event', 'x': 42, 'y': 23})
         )
      )
   )
)

In this case, f4 has to make sure it returns something wrapped_logger.msg can handle (see Adapting and Rendering).

The simplest modification a processor can make is adding new values to the event_dict. Parsing human-readable timestamps is tedious, not so UNIX timestamps – let’s add one to each log entry!

import calendar
import time


def timestamper(logger, log_method, event_dict):
    event_dict['timestamp'] = calendar.timegm(time.gmtime())
    return event_dict

Easy, isn’t it? Please note, that structlog comes with such an processor built in: TimeStamper.

Filtering¶

If a processor raises structlog.DropEvent, the event is silently dropped.

Therefore, the following processor drops every entry:

from structlog import DropEvent


def dropper(logger, method_name, event_dict):
    raise DropEvent

But we can do better than that!

How about dropping only log entries that are marked as coming from a certain peer (e.g. monitoring)?

from structlog import DropEvent


class ConditionalDropper(object):
    def __init__(self, peer_to_ignore):
        self._peer_to_ignore = peer_to_ignore

    def __call__(self, logger, method_name, event_dict):
        """
        >>> cd = ConditionalDropper('127.0.0.1')
        >>> cd(None, None, {'event': 'foo', 'peer': '10.0.0.1'})
        {'peer': '10.0.0.1', 'event': 'foo'}
        >>> cd(None, None, {'event': 'foo', 'peer': '127.0.0.1'})
        Traceback (most recent call last):
        ...
        DropEvent
        """
        if event_dict.get('peer') == self._peer_to_ignore:
            raise DropEvent
        else:
            return event_dict

Adapting and Rendering¶

An important role is played by the last processor because its duty is to adapt the event_dict into something the underlying logging method understands. With that, it’s also the only processor that needs to know anything about the underlying system.

For that, it can either return a string that is passed as the first (and only) positional argument to the underlying logger or a tuple of (args, kwargs) that are passed as log_method(*args, **kwargs). Therefore return 'hello world' is a shortcut for return (('hello world',), {}) (the example in Chains assumes this shortcut has been taken).

This should give you enough power to use structlog with any logging system while writing agnostic processors that operate on dictionaries.

Examples¶

The probably most useful formatter for string based loggers is JSONRenderer. Advanced log aggregation and analysis tools like logstash offer features like telling them “this is JSON, deal with it” instead of fiddling with regular expressions.

More examples can be found in the examples chapter. For a list of shipped processors, check out the API documentation.