Logging¶
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.
警告
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:
The
pservecommand calls thepyramid.paster.setup_logging()function, passing the.inifile.setup_loggingis a thin wrapper which calls the Python standard library'slogging.config.fileConfig().logging.config.fileConfig()reads the logging configuration from the.inifile 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:
29###
30# logging configuration
31# https://docs.pylonsproject.org/projects/pyramid/en/latest/narr/logging.html
32###
33
34[loggers]
35keys = root, myproject
36
37[handlers]
38keys = console
39
40[formatters]
41keys = generic
42
43[logger_root]
44level = INFO
45handlers = console
46
47[logger_myproject]
48level = DEBUG
49handlers =
50qualname = myproject
51
52[handler_console]
53class = StreamHandler
54args = (sys.stderr,)
55level = NOTSET
56formatter = generic
57
58[formatter_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
rootis created that logs messages at a level above or equal to theINFOlevel to stderr, with the following format:2007-08-17 15:04:08,704 INFO [packagename] Loading resource, id: 86
a logger named
myprojectis configured that logs messages sent at a level above or equal toDEBUGto 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:
[logger_root]
#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__)
3
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:
[logger_sqlalchemy.pool]
level = DEBUG
handlers =
qualname = sqlalchemy.pool
then add it to the list of loggers:
[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
[loggers]
keys = root, myproject
[logger_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):
[handler_filelog]
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:
[handlers]
keys = console, myproject, filelog
and finally utilized by a logger.
[logger_root]
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:
[app:main]
use = egg:myproject
To this:
[app:mypyramidapp]
use = egg:myproject
[filter:translogger]
use = egg:Paste#translogger
setup_console_handler = False
[pipeline:main]
pipeline = translogger
mypyramidapp
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
注釈
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] 192.168.1.111 - - [11/Aug/2011:20:09:33 -0700] "GET /hello
HTTP/1.1" 404 - "-"
"Mozilla/5.0 (Macintosh; U; Intel macOS; en-US; rv:1.8.1.6) Gecko/20070725
Firefox/2.0.0.6"
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
[loggers]
keys = root, myproject, wsgi
[handlers]
keys = console, accesslog
[logger_wsgi]
level = INFO
handlers = accesslog
qualname = wsgi
propagate = 0
[handler_accesslog]
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:
[formatters]
keys = generic, accesslog
[formatter_accesslog]
format = %(message)s
Finally alter the existing configuration to wire this new accesslog
formatter into the FileHandler:
[handler_accesslog]
class = FileHandler
args = ('%(here)s/access.log','a')
level = INFO
formatter = accesslog