Pyramid allows you to make use of the Python standard library logging module. This chapter describes how to configure logging and how to send log messages to loggers that you've configured.


This chapter assumes you've used our cookiecutter to create a project which contains development.ini and production.ini files which help configure logging. The Pyramid cookiecutter provided by the Pylons Project does this. If you're not using our cookiecutter, or if you've used a third-party cookiecutter which does not create these files, the configuration information in this chapter may not be applicable.

Logging Configuration

A Pyramid project created from our cookiecutter is configured to allow you to send messages to Python standard library logging package loggers from within your application. In particular, the PasteDeploy development.ini and production.ini files created when you use our cookiecutter include a basic configuration for the Python logging package. These .ini file sections are passed to the logging module's config file configuration engine.

PasteDeploy .ini files use the Python standard library ConfigParser format. This is the same format used as the Python logging module's Configuration file format. The application-related and logging-related sections in the configuration file can coexist peacefully. The logging-related sections in the file configure logging when you run pserve.

If the configuration .ini file, specified when invoking pserve, contains a [loggers] section then on startup the following process takes place:

  1. The pserve command calls the pyramid.paster.setup_logging() function, passing the .ini file.

  2. setup_logging is a thin wrapper which calls the Python standard library's logging.config.fileConfig().

  3. logging.config.fileConfig() reads the logging configuration from the .ini file and configures logging.

Default logging configuration is provided in both the default development.ini and the production.ini files. If you use our cookiecutter to generate a Pyramid project with the name of the package as hello_world, then the logging configuration in the development.ini file is as follows:

30# logging configuration
31# https://docs.pylonsproject.org/projects/pyramid/en/latest/narr/logging.html
35keys = root, myproject
38keys = console
41keys = generic
44level = INFO
45handlers = console
48level = DEBUG
49handlers =
50qualname = myproject
53class = StreamHandler
54args = (sys.stderr,)
55level = NOTSET
56formatter = generic
59format = %(asctime)s %(levelname)-5.5s [%(name)s:%(lineno)s][%(threadName)s] %(message)s

The production.ini file uses the WARN level in its logger configuration instead of DEBUG, but it is otherwise identical.

In this logging configuration:

  • a logger named root is created that logs messages at a level above or equal to the INFO level to stderr, with the following format:

    2007-08-17 15:04:08,704 INFO [packagename] Loading resource, id: 86
  • a logger named myproject is configured that logs messages sent at a level above or equal to DEBUG to stderr in the same format as the root logger.

The root logger will be used by all applications in the Pyramid process that ask for a logger (via logging.getLogger) that has a name which begins with anything except your project's package name (e.g., myproject). The logger with the same name as your package name is reserved for your own usage in your Pyramid application. Its existence means that you can log to a known logging location from any Pyramid application generated via our cookiecutter.

Pyramid and many other libraries (such as Beaker, SQLAlchemy, Paste) log a number of messages to the root logger for debugging purposes. Switching the root logger level to DEBUG reveals them:

#level = INFO
level = DEBUG
handlers = console

Some configurations of the Pyramid cookiecutter configure additional loggers for additional subsystems they use (such as SQLAlchemy). Take a look at the production.ini and development.ini files rendered when you create a project from our cookiecutter.

Sending Logging Messages

Python's special __name__ variable refers to the current module's fully qualified name. From any module in a package named myproject, the __name__ builtin variable will always be something like myproject, or myproject.subpackage or myproject.package.subpackage if your project is named myproject. Sending a message to this logger will send it to the myproject logger.

To log messages to the package-specific logger configured in your .ini file, simply create a logger object using the __name__ builtin and call methods on it.

1import logging
2log = logging.getLogger(__name__)
4def myview(request):
5    content_type = 'text/plain'
6    content = 'Hello World!'
7    log.debug('Returning: %s (content-type: %s)', content, content_type)
8    request.response.content_type = content_type
9    return request.response

This will result in the following printed to the console, on stderr:

16:20:20,440 DEBUG [myproject.views] Returning: Hello World!
                   (content-type: text/plain)

Filtering log messages

Often there's too much log output to sift through, such as when switching the root logger's level to DEBUG.

For example, you're diagnosing database connection issues in your application and only want to see SQLAlchemy's DEBUG messages in relation to database connection pooling. You can leave the root logger's level at the less verbose INFO level and set that particular SQLAlchemy logger to DEBUG on its own, apart from the root logger:

level = DEBUG
handlers =
qualname = sqlalchemy.pool

then add it to the list of loggers:

keys = root, myproject, sqlalchemy.pool

No handlers need to be configured for this logger as by default non-root loggers will propagate their log records up to their parent logger's handlers. The root logger is the top level parent of all loggers.

This technique is used in the default development.ini. The root logger's level is set to INFO, whereas the application's log level is set to DEBUG:

# Begin logging configuration

keys = root, myproject

level = DEBUG
handlers =
qualname = myproject

All of the child loggers of the myproject logger will inherit the DEBUG level unless they're explicitly set differently. Meaning the myproject.views, myproject.models, and all your app's modules' loggers by default have an effective level of DEBUG too.

For more advanced filtering, the logging module provides a logging.Filter object; however it cannot be used directly from the configuration file.

Advanced Configuration

To capture log output to a separate file, use logging.FileHandler (or logging.handlers.RotatingFileHandler):

class = FileHandler
args = ('%(here)s/myproject.log','a')
level = INFO
formatter = generic

Before it's recognized, it needs to be added to the list of handlers:

keys = console, myproject, filelog

and finally utilized by a logger.

level = INFO
handlers = console, filelog

These final three lines of configuration direct all of the root logger's output to the myproject.log as well as the console.

Logging Exceptions

To log or email exceptions generated by your Pyramid application, use the pyramid_exclog package. Details about its configuration are in its documentation.

Request Logging with Paste's TransLogger

The WSGI design is modular. Waitress logs error conditions, debugging output, etc., but not web traffic. For web traffic logging, Paste provides the TransLogger middleware. TransLogger produces logs in the Apache Combined Log Format. But TransLogger does not write to files; the Python logging system must be configured to do this. The Python logging.FileHandler logging handler can be used alongside TransLogger to create an access.log file similar to Apache's.

Like any standard middleware with a Paste entry point, TransLogger can be configured to wrap your application using .ini file syntax. First rename your Pyramid .ini file's [app:main] section to [app:mypyramidapp], then add a [filter:translogger] section, then use a [pipeline:main] section file to form a WSGI pipeline with both the translogger and your application in it. For instance, change from this:

use = egg:myproject

To this:

use = egg:myproject

use = egg:Paste#translogger
setup_console_handler = False

pipeline = translogger

Using PasteDeploy this way to form and serve a pipeline is equivalent to wrapping your app in a TransLogger instance via the bottom of the main function of your project's __init__ file:

# ...
app = config.make_wsgi_app()
from paste.translogger import TransLogger
app = TransLogger(app, setup_console_handler=False)
return app


TransLogger will automatically setup a logging handler to the console when called with no arguments, so it "just works" in environments that don't configure logging. Since our logging handlers are configured, we disable the automation via setup_console_handler = False.

With the filter in place, TransLogger's logger (named the wsgi logger) will propagate its log messages to the parent logger (the root logger), sending its output to the console when we request a page:

00:50:53,694 INFO [myproject.views] Returning: Hello World!
                  (content-type: text/plain)
00:50:53,695 INFO [wsgi] - - [11/Aug/2011:20:09:33 -0700] "GET /hello
HTTP/1.1" 404 - "-"
"Mozilla/5.0 (Macintosh; U; Intel macOS; en-US; rv: Gecko/20070725

To direct TransLogger to an access.log FileHandler, we need the following to add a FileHandler (named accesslog) to the list of handlers, and ensure that the wsgi logger is configured and uses this handler accordingly:

# Begin logging configuration

keys = root, myproject, wsgi

keys = console, accesslog

level = INFO
handlers = accesslog
qualname = wsgi
propagate = 0

class = FileHandler
args = ('%(here)s/access.log','a')
level = INFO
formatter = generic

As mentioned above, non-root loggers by default propagate their log records to the root logger's handlers (currently the console handler). Setting propagate to 0 (False) here disables this; so the wsgi logger directs its records only to the accesslog handler.

Finally, there's no need to use the generic formatter with TransLogger as TransLogger itself provides all the information we need. We'll use a formatter that passes through the log messages as is. Add a new formatter called accesslog by including the following in your configuration file:

keys = generic, accesslog

format = %(message)s

Finally alter the existing configuration to wire this new accesslog formatter into the FileHandler:

class = FileHandler
args = ('%(here)s/access.log','a')
level = INFO
formatter = accesslog