Mach configures a built-in logging facility so commands can easily log data.

What sets the logging facility apart from most loggers you’ve seen is that it encourages structured logging. Instead of conventional logging where simple strings are logged, the internal logging mechanism logs all events with the following pieces of information:

  • A string action

  • A dict of log message fields

  • A formatting string

Essentially, instead of assembling a human-readable string at logging-time, you create an object holding all the pieces of data that will constitute your logged event. For each unique type of logged event, you assign an action name.

Depending on how logging is configured, your logged event could get written a couple of different ways.

JSON Logging

Where machines are the intended target of the logging data, a JSON logger is configured. The JSON logger assembles an array consisting of the following elements:

  • Decimal wall clock time in seconds since UNIX epoch

  • String action of message

  • Object with structured message data

The JSON-serialized array is written to a configured file handle. Consumers of this logging stream can just perform a readline() then feed that into a JSON deserializer to reconstruct the original logged message. They can key off the action element to determine how to process individual events. There is no need to invent a parser. Convenient, isn’t it?

Logging for Humans

Where humans are the intended consumer of a log message, the structured log message are converted to more human-friendly form. This is done by utilizing the formatting string provided at log time. The logger simply calls the format method of the formatting string, passing the dict containing the message’s fields.

When mach is used in a terminal that supports it, the logging facility also supports terminal features such as colorization. This is done automatically in the logging layer - there is no need to control this at logging time.

In addition, messages intended for humans typically prepends every line with the time passed since the application started.

Logging HOWTO

Structured logging piggybacks on top of Python’s built-in logging infrastructure provided by the logging package. We accomplish this by taking advantage of logging.Logger.log()’s extra argument. To this argument, we pass a dict with the fields action and params. These are the string action and dict of message fields, respectively. The formatting string is passed as the msg argument, like normal.

If you were logging to a logger directly, you would do something like:

logger.log(logging.INFO, 'My name is {name}',
    extra={'action': 'my_name', 'params': {'name': 'Gregory'}})

The JSON logging would produce something like:

[1339985554.306338, "my_name", {"name": "Gregory"}]

Human logging would produce something like:

0.52 My name is Gregory

Since there is a lot of complexity using logger.log directly, it is recommended to go through a wrapping layer that hides part of the complexity for you. The easiest way to do this is by utilizing the LoggingMixin:

import logging
from mach.mixin.logging import LoggingMixin

class MyClass(LoggingMixin):
    def foo(self):
         self.log(logging.INFO, 'foo_start', {'bar': True},
             'Foo performed. Bar: {bar}')