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 <div class="section" id="module-logging.config">
<h1>15.8. <a class="reference internal" href="#module-logging.config" title="logging.config: Configuration of the logging module."><tt class="xref py py-mod docutils literal">logging.config</tt></a> &#8212; Logging configuration<a class="headerlink" href="#module-logging.config" title="Permalink to this headline">¶</a></h1>
<div class="sidebar">
Important
This page contains only reference information. For tutorials,
please see
<ul class="last simple">
<li><a class="reference internal" href="../howto/logging.html#logging-basic-tutorial">Basic Tutorial</a></li>
<li><a class="reference internal" href="../howto/logging.html#logging-advanced-tutorial">Advanced Tutorial</a></li>
<li><a class="reference internal" href="../howto/logging-cookbook.html#logging-cookbook">Logging Cookbook</a></li>
</ul>
</div>
This section describes the API for configuring the logging module.
<div class="section" id="configuration-functions">
<h2>15.8.1. Configuration functions<a class="headerlink" href="#configuration-functions" title="Permalink to this headline">¶</a></h2>
The following functions configure the logging module. They are located in the
<a class="reference internal" href="#module-logging.config" title="logging.config: Configuration of the logging module."><tt class="xref py py-mod docutils literal">logging.config</tt></a> module. Their use is optional &#8212; you can configure the
logging module using these functions or by making calls to the main API (defined
in <a class="reference internal" href="logging.html#module-logging" title="logging: Flexible event logging system for applications."><tt class="xref py py-mod docutils literal">logging</tt></a> itself) and defining handlers which are declared either in
<a class="reference internal" href="logging.html#module-logging" title="logging: Flexible event logging system for applications."><tt class="xref py py-mod docutils literal">logging</tt></a> or <a class="reference internal" href="logging.handlers.html#module-logging.handlers" title="logging.handlers: Handlers for the logging module."><tt class="xref py py-mod docutils literal">logging.handlers</tt></a>.
<dl class="function">
<dt id="logging.config.dictConfig">
<tt class="descclassname">logging.config.</tt><tt class="descname">dictConfig</tt><big>(</big>config<big>)</big><a class="headerlink" href="#logging.config.dictConfig" title="Permalink to this definition">¶</a></dt>
<dd><blockquote>
<div>Takes the logging configuration from a dictionary. The contents of
this dictionary are described in <a class="reference internal" href="#logging-config-dictschema">Configuration dictionary schema</a>
below.
If an error is encountered during configuration, this function will
raise a <a class="reference internal" href="exceptions.html#exceptions.ValueError" title="exceptions.ValueError"><tt class="xref py py-exc docutils literal">ValueError</tt></a>, <a class="reference internal" href="exceptions.html#exceptions.TypeError" title="exceptions.TypeError"><tt class="xref py py-exc docutils literal">TypeError</tt></a>, <a class="reference internal" href="exceptions.html#exceptions.AttributeError" title="exceptions.AttributeError"><tt class="xref py py-exc docutils literal">AttributeError</tt></a>
or <a class="reference internal" href="exceptions.html#exceptions.ImportError" title="exceptions.ImportError"><tt class="xref py py-exc docutils literal">ImportError</tt></a> with a suitably descriptive message. The
following is a (possibly incomplete) list of conditions which will
raise an error:
<ul class="simple">
<li>A <tt class="docutils literal">level</tt> which is not a string or which is a string not
corresponding to an actual logging level.</li>
<li>A <tt class="docutils literal">propagate</tt> value which is not a boolean.</li>
<li>An id which does not have a corresponding destination.</li>
<li>A non-existent handler id found during an incremental call.</li>
<li>An invalid logger name.</li>
<li>Inability to resolve to an internal or external object.</li>
</ul>
Parsing is performed by the <tt class="xref py py-class docutils literal">DictConfigurator</tt> class, whose
constructor is passed the dictionary used for configuration, and
has a <tt class="xref py py-meth docutils literal">configure()</tt> method. The <a class="reference internal" href="#module-logging.config" title="logging.config: Configuration of the logging module."><tt class="xref py py-mod docutils literal">logging.config</tt></a> module
has a callable attribute <tt class="xref py py-attr docutils literal">dictConfigClass</tt>
which is initially set to <tt class="xref py py-class docutils literal">DictConfigurator</tt>.
You can replace the value of <tt class="xref py py-attr docutils literal">dictConfigClass</tt> with a
suitable implementation of your own.
<a class="reference internal" href="#logging.config.dictConfig" title="logging.config.dictConfig"><tt class="xref py py-func docutils literal">dictConfig()</tt></a> calls <tt class="xref py py-attr docutils literal">dictConfigClass</tt> passing
the specified dictionary, and then calls the <tt class="xref py py-meth docutils literal">configure()</tt> method on
the returned object to put the configuration into effect:
<div class="highlight-python"><div class="highlight"><pre>def dictConfig(config):
 dictConfigClass(config).configure()
</pre></div>
</div>
For example, a subclass of <tt class="xref py py-class docutils literal">DictConfigurator</tt> could call
<tt class="docutils literal">DictConfigurator.__init__()</tt> in its own <a class="reference internal" href="../reference/datamodel.html#object.__init__" title="object.__init__"><tt class="xref py py-meth docutils literal">__init__()</tt></a>, then
set up custom prefixes which would be usable in the subsequent
<tt class="xref py py-meth docutils literal">configure()</tt> call. <tt class="xref py py-attr docutils literal">dictConfigClass</tt> would be bound to
this new subclass, and then <a class="reference internal" href="#logging.config.dictConfig" title="logging.config.dictConfig"><tt class="xref py py-func docutils literal">dictConfig()</tt></a> could be called exactly as
in the default, uncustomized state.
</div></blockquote>

New in version 2.7.
</dd></dl>

<dl class="function">
<dt id="logging.config.fileConfig">
<tt class="descclassname">logging.config.</tt><tt class="descname">fileConfig</tt><big>(</big>fname, defaults=None, disable_existing_loggers=True<big>)</big><a class="headerlink" href="#logging.config.fileConfig" title="Permalink to this definition">¶</a></dt>
<dd>Reads the logging configuration from a <tt class="xref py py-mod docutils literal">configparser</tt>-format file
named fname. This function can be called several times from an
application, allowing an end user to select from various pre-canned
configurations (if the developer provides a mechanism to present the choices
and load the chosen configuration).
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li>defaults &#8211; Defaults to be passed to the ConfigParser can be specified
in this argument.</li>
<li>disable_existing_loggers &#8211; If specified as <tt class="docutils literal">False</tt>, loggers which
exist when this call is made are left
alone. The default is <tt class="docutils literal">True</tt> because this
enables old behaviour in a backward-
compatible way. This behaviour is to
disable any existing loggers unless they or
their ancestors are explicitly named in the
logging configuration.</li>
</ul>
</td>
</tr>
</tbody>
</table>

Changed in version 2.6: The <tt class="docutils literal">disable_existing_loggers</tt> keyword argument was added. Previously,
existing loggers were always disabled.
</dd></dl>

<dl class="function">
<dt id="logging.config.listen">
<tt class="descclassname">logging.config.</tt><tt class="descname">listen</tt><big>(</big>port=DEFAULT_LOGGING_CONFIG_PORT<big>)</big><a class="headerlink" href="#logging.config.listen" title="Permalink to this definition">¶</a></dt>
<dd>Starts up a socket server on the specified port, and listens for new
configurations. If no port is specified, the module&#8217;s default
<tt class="xref py py-const docutils literal">DEFAULT_LOGGING_CONFIG_PORT</tt> is used. Logging configurations will be
sent as a file suitable for processing by <a class="reference internal" href="#logging.config.fileConfig" title="logging.config.fileConfig"><tt class="xref py py-func docutils literal">fileConfig()</tt></a>. Returns a
<tt class="xref py py-class docutils literal">Thread</tt> instance on which you can call <tt class="xref py py-meth docutils literal">start()</tt> to start the
server, and which you can <tt class="xref py py-meth docutils literal">join()</tt> when appropriate. To stop the server,
call <a class="reference internal" href="#logging.config.stopListening" title="logging.config.stopListening"><tt class="xref py py-func docutils literal">stopListening()</tt></a>.
To send a configuration to the socket, read in the configuration file and
send it to the socket as a string of bytes preceded by a four-byte length
string packed in binary using <tt class="docutils literal">struct.pack('&gt;L', n)</tt>.
<div class="admonition note">
Note
Because portions of the configuration are passed through
<a class="reference internal" href="functions.html#eval" title="eval"><tt class="xref py py-func docutils literal">eval()</tt></a>, use of this function may open its users to a security risk.
While the function only binds to a socket on <tt class="docutils literal">localhost</tt>, and so does
not accept connections from remote machines, there are scenarios where
untrusted code could be run under the account of the process which calls
<a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a>. Specifically, if the process calling <a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a> runs
on a multi-user machine where users cannot trust each other, then a
malicious user could arrange to run essentially arbitrary code in a
victim user&#8217;s process, simply by connecting to the victim&#8217;s
<a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a> socket and sending a configuration which runs whatever
code the attacker wants to have executed in the victim&#8217;s process. This is
especially easy to do if the default port is used, but not hard even if a
different port is used).
</div>
</dd></dl>

<dl class="function">
<dt id="logging.config.stopListening">
<tt class="descclassname">logging.config.</tt><tt class="descname">stopListening</tt><big>(</big><big>)</big><a class="headerlink" href="#logging.config.stopListening" title="Permalink to this definition">¶</a></dt>
<dd>Stops the listening server which was created with a call to <a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a>.
This is typically called before calling <tt class="xref py py-meth docutils literal">join()</tt> on the return value from
<a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a>.
</dd></dl>

</div>
<div class="section" id="configuration-dictionary-schema">
<h2>15.8.2. Configuration dictionary schema<a class="headerlink" href="#configuration-dictionary-schema" title="Permalink to this headline">¶</a></h2>
Describing a logging configuration requires listing the various
objects to create and the connections between them; for example, you
may create a handler named &#8216;console&#8217; and then say that the logger
named &#8216;startup&#8217; will send its messages to the &#8216;console&#8217; handler.
These objects aren&#8217;t limited to those provided by the <a class="reference internal" href="logging.html#module-logging" title="logging: Flexible event logging system for applications."><tt class="xref py py-mod docutils literal">logging</tt></a>
module because you might write your own formatter or handler class.
The parameters to these classes may also need to include external
objects such as <tt class="docutils literal">sys.stderr</tt>. The syntax for describing these
objects and connections is defined in <a class="reference internal" href="#logging-config-dict-connections">Object connections</a>
below.
<div class="section" id="dictionary-schema-details">
<h3>15.8.2.1. Dictionary Schema Details<a class="headerlink" href="#dictionary-schema-details" title="Permalink to this headline">¶</a></h3>
The dictionary passed to <a class="reference internal" href="#logging.config.dictConfig" title="logging.config.dictConfig"><tt class="xref py py-func docutils literal">dictConfig()</tt></a> must contain the following
keys:
<ul class="simple">
<li>version - to be set to an integer value representing the schema
version. The only valid value at present is 1, but having this key
allows the schema to evolve while still preserving backwards
compatibility.</li>
</ul>
All other keys are optional, but if present they will be interpreted
as described below. In all cases below where a &#8216;configuring dict&#8217; is
mentioned, it will be checked for the special <tt class="docutils literal">'()'</tt> key to see if a
custom instantiation is required. If so, the mechanism described in
<a class="reference internal" href="#logging-config-dict-userdef">User-defined objects</a> below is used to create an instance;
otherwise, the context is used to determine what to instantiate.
<ul>
<li>formatters - the corresponding value will be a dict in which each
key is a formatter id and each value is a dict describing how to
configure the corresponding Formatter instance.
The configuring dict is searched for keys <tt class="docutils literal">format</tt> and <tt class="docutils literal">datefmt</tt>
(with defaults of <tt class="docutils literal">None</tt>) and these are used to construct a
<a class="reference internal" href="logging.html#logging.Formatter" title="logging.Formatter"><tt class="xref py py-class docutils literal">logging.Formatter</tt></a> instance.
</li>
<li>filters - the corresponding value will be a dict in which each key
is a filter id and each value is a dict describing how to configure
the corresponding Filter instance.
The configuring dict is searched for the key <tt class="docutils literal">name</tt> (defaulting to the
empty string) and this is used to construct a <a class="reference internal" href="logging.html#logging.Filter" title="logging.Filter"><tt class="xref py py-class docutils literal">logging.Filter</tt></a>
instance.
</li>
<li>handlers - the corresponding value will be a dict in which each
key is a handler id and each value is a dict describing how to
configure the corresponding Handler instance.
The configuring dict is searched for the following keys:
<ul class="simple">
<li><tt class="docutils literal">class</tt> (mandatory). This is the fully qualified name of the
handler class.</li>
<li><tt class="docutils literal">level</tt> (optional). The level of the handler.</li>
<li><tt class="docutils literal">formatter</tt> (optional). The id of the formatter for this
handler.</li>
<li><tt class="docutils literal">filters</tt> (optional). A list of ids of the filters for this
handler.</li>
</ul>
All other keys are passed through as keyword arguments to the
handler&#8217;s constructor. For example, given the snippet:
<div class="highlight-python"><pre>handlers:
 console:
 class : logging.StreamHandler
 formatter: brief
 level : INFO
 filters: [allow_foo]
 stream : ext://sys.stdout
 file:
 class : logging.handlers.RotatingFileHandler
 formatter: precise
 filename: logconfig.log
 maxBytes: 1024
 backupCount: 3</pre>
</div>
the handler with id <tt class="docutils literal">console</tt> is instantiated as a
<a class="reference internal" href="logging.handlers.html#logging.StreamHandler" title="logging.StreamHandler"><tt class="xref py py-class docutils literal">logging.StreamHandler</tt></a>, using <tt class="docutils literal">sys.stdout</tt> as the underlying
stream. The handler with id <tt class="docutils literal">file</tt> is instantiated as a
<a class="reference internal" href="logging.handlers.html#logging.handlers.RotatingFileHandler" title="logging.handlers.RotatingFileHandler"><tt class="xref py py-class docutils literal">logging.handlers.RotatingFileHandler</tt></a> with the keyword arguments
<tt class="docutils literal">filename='logconfig.log', maxBytes=1024, backupCount=3</tt>.
</li>
<li>loggers - the corresponding value will be a dict in which each key
is a logger name and each value is a dict describing how to
configure the corresponding Logger instance.
The configuring dict is searched for the following keys:
<ul class="simple">
<li><tt class="docutils literal">level</tt> (optional). The level of the logger.</li>
<li><tt class="docutils literal">propagate</tt> (optional). The propagation setting of the logger.</li>
<li><tt class="docutils literal">filters</tt> (optional). A list of ids of the filters for this
logger.</li>
<li><tt class="docutils literal">handlers</tt> (optional). A list of ids of the handlers for this
logger.</li>
</ul>
The specified loggers will be configured according to the level,
propagation, filters and handlers specified.
</li>
<li>root - this will be the configuration for the root logger.
Processing of the configuration will be as for any logger, except
that the <tt class="docutils literal">propagate</tt> setting will not be applicable.
</li>
<li>incremental - whether the configuration is to be interpreted as
incremental to the existing configuration. This value defaults to
<tt class="docutils literal">False</tt>, which means that the specified configuration replaces the
existing configuration with the same semantics as used by the
existing <a class="reference internal" href="#logging.config.fileConfig" title="logging.config.fileConfig"><tt class="xref py py-func docutils literal">fileConfig()</tt></a> API.
If the specified value is <tt class="docutils literal">True</tt>, the configuration is processed
as described in the section on <a class="reference internal" href="#logging-config-dict-incremental">Incremental Configuration</a>.
</li>
<li>disable_existing_loggers - whether any existing loggers are to be
disabled. This setting mirrors the parameter of the same name in
<a class="reference internal" href="#logging.config.fileConfig" title="logging.config.fileConfig"><tt class="xref py py-func docutils literal">fileConfig()</tt></a>. If absent, this parameter defaults to <tt class="docutils literal">True</tt>.
This value is ignored if incremental is <tt class="docutils literal">True</tt>.
</li>
</ul>
</div>
<div class="section" id="incremental-configuration">
<h3>15.8.2.2. Incremental Configuration<a class="headerlink" href="#incremental-configuration" title="Permalink to this headline">¶</a></h3>
It is difficult to provide complete flexibility for incremental
configuration. For example, because objects such as filters
and formatters are anonymous, once a configuration is set up, it is
not possible to refer to such anonymous objects when augmenting a
configuration.
Furthermore, there is not a compelling case for arbitrarily altering
the object graph of loggers, handlers, filters, formatters at
run-time, once a configuration is set up; the verbosity of loggers and
handlers can be controlled just by setting levels (and, in the case of
loggers, propagation flags). Changing the object graph arbitrarily in
a safe way is problematic in a multi-threaded environment; while not
impossible, the benefits are not worth the complexity it adds to the
implementation.
Thus, when the <tt class="docutils literal">incremental</tt> key of a configuration dict is present
and is <tt class="docutils literal">True</tt>, the system will completely ignore any <tt class="docutils literal">formatters</tt> and
<tt class="docutils literal">filters</tt> entries, and process only the <tt class="docutils literal">level</tt>
settings in the <tt class="docutils literal">handlers</tt> entries, and the <tt class="docutils literal">level</tt> and
<tt class="docutils literal">propagate</tt> settings in the <tt class="docutils literal">loggers</tt> and <tt class="docutils literal">root</tt> entries.
Using a value in the configuration dict lets configurations to be sent
over the wire as pickled dicts to a socket listener. Thus, the logging
verbosity of a long-running application can be altered over time with
no need to stop and restart the application.
</div>
<div class="section" id="object-connections">
<h3>15.8.2.3. Object connections<a class="headerlink" href="#object-connections" title="Permalink to this headline">¶</a></h3>
The schema describes a set of logging objects - loggers,
handlers, formatters, filters - which are connected to each other in
an object graph. Thus, the schema needs to represent connections
between the objects. For example, say that, once configured, a
particular logger has attached to it a particular handler. For the
purposes of this discussion, we can say that the logger represents the
source, and the handler the destination, of a connection between the
two. Of course in the configured objects this is represented by the
logger holding a reference to the handler. In the configuration dict,
this is done by giving each destination object an id which identifies
it unambiguously, and then using the id in the source object&#8217;s
configuration to indicate that a connection exists between the source
and the destination object with that id.
So, for example, consider the following YAML snippet:
<div class="highlight-python"><pre>formatters:
 brief:
 # configuration for formatter with id 'brief' goes here
 precise:
 # configuration for formatter with id 'precise' goes here
handlers:
 h1: #This is an id
 # configuration of handler with id 'h1' goes here
 formatter: brief
 h2: #This is another id
 # configuration of handler with id 'h2' goes here
 formatter: precise
loggers:
 foo.bar.baz:
 # other configuration for logger 'foo.bar.baz'
 handlers: [h1, h2]</pre>
</div>
(Note: YAML used here because it&#8217;s a little more readable than the
equivalent Python source form for the dictionary.)
The ids for loggers are the logger names which would be used
programmatically to obtain a reference to those loggers, e.g.
<tt class="docutils literal">foo.bar.baz</tt>. The ids for Formatters and Filters can be any string
value (such as <tt class="docutils literal">brief</tt>, <tt class="docutils literal">precise</tt> above) and they are transient,
in that they are only meaningful for processing the configuration
dictionary and used to determine connections between objects, and are
not persisted anywhere when the configuration call is complete.
The above snippet indicates that logger named <tt class="docutils literal">foo.bar.baz</tt> should
have two handlers attached to it, which are described by the handler
ids <tt class="docutils literal">h1</tt> and <tt class="docutils literal">h2</tt>. The formatter for <tt class="docutils literal">h1</tt> is that described by id
<tt class="docutils literal">brief</tt>, and the formatter for <tt class="docutils literal">h2</tt> is that described by id
<tt class="docutils literal">precise</tt>.
</div>
<div class="section" id="user-defined-objects">
<h3>15.8.2.4. User-defined objects<a class="headerlink" href="#user-defined-objects" title="Permalink to this headline">¶</a></h3>
The schema supports user-defined objects for handlers, filters and
formatters. (Loggers do not need to have different types for
different instances, so there is no support in this configuration
schema for user-defined logger classes.)
Objects to be configured are described by dictionaries
which detail their configuration. In some places, the logging system
will be able to infer from the context how an object is to be
instantiated, but when a user-defined object is to be instantiated,
the system will not know how to do this. In order to provide complete
flexibility for user-defined object instantiation, the user needs
to provide a &#8216;factory&#8217; - a callable which is called with a
configuration dictionary and which returns the instantiated object.
This is signalled by an absolute import path to the factory being
made available under the special key <tt class="docutils literal">'()'</tt>. Here&#8217;s a concrete
example:
<div class="highlight-python"><pre>formatters:
 brief:
 format: '%(message)s'
 default:
 format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
 datefmt: '%Y-%m-%d %H:%M:%S'
 custom:
 (): my.package.customFormatterFactory
 bar: baz
 spam: 99.9
 answer: 42</pre>
</div>
The above YAML snippet defines three formatters. The first, with id
<tt class="docutils literal">brief</tt>, is a standard <a class="reference internal" href="logging.html#logging.Formatter" title="logging.Formatter"><tt class="xref py py-class docutils literal">logging.Formatter</tt></a> instance with the
specified format string. The second, with id <tt class="docutils literal">default</tt>, has a
longer format and also defines the time format explicitly, and will
result in a <a class="reference internal" href="logging.html#logging.Formatter" title="logging.Formatter"><tt class="xref py py-class docutils literal">logging.Formatter</tt></a> initialized with those two format
strings. Shown in Python source form, the <tt class="docutils literal">brief</tt> and <tt class="docutils literal">default</tt>
formatters have configuration sub-dictionaries:
<div class="highlight-python"><div class="highlight"><pre>{
 &#39;format&#39; : &#39;%(message)s&#39;
}
</pre></div>
</div>
and:
<div class="highlight-python"><div class="highlight"><pre>{
 &#39;format&#39; : &#39;%(asctime)s %(levelname)-8s %(name)-15s %(message)s&#39;,
 &#39;datefmt&#39; : &#39;%Y-%m-%d %H:%M:%S&#39;
}
</pre></div>
</div>
respectively, and as these dictionaries do not contain the special key
<tt class="docutils literal">'()'</tt>, the instantiation is inferred from the context: as a result,
standard <a class="reference internal" href="logging.html#logging.Formatter" title="logging.Formatter"><tt class="xref py py-class docutils literal">logging.Formatter</tt></a> instances are created. The
configuration sub-dictionary for the third formatter, with id
<tt class="docutils literal">custom</tt>, is:
<div class="highlight-python"><div class="highlight"><pre>{
 &#39;()&#39; : &#39;my.package.customFormatterFactory&#39;,
 &#39;bar&#39; : &#39;baz&#39;,
 &#39;spam&#39; : 99.9,
 &#39;answer&#39; : 42
}
</pre></div>
</div>
and this contains the special key <tt class="docutils literal">'()'</tt>, which means that
user-defined instantiation is wanted. In this case, the specified
factory callable will be used. If it is an actual callable it will be
used directly - otherwise, if you specify a string (as in the example)
the actual callable will be located using normal import mechanisms.
The callable will be called with the remaining items in the
configuration sub-dictionary as keyword arguments. In the above
example, the formatter with id <tt class="docutils literal">custom</tt> will be assumed to be
returned by the call:
<div class="highlight-python"><div class="highlight"><pre>my.package.customFormatterFactory(bar=&#39;baz&#39;, spam=99.9, answer=42)
</pre></div>
</div>
The key <tt class="docutils literal">'()'</tt> has been used as the special key because it is not a
valid keyword parameter name, and so will not clash with the names of
the keyword arguments used in the call. The <tt class="docutils literal">'()'</tt> also serves as a
mnemonic that the corresponding value is a callable.
</div>
<div class="section" id="access-to-external-objects">
<h3>15.8.2.5. Access to external objects<a class="headerlink" href="#access-to-external-objects" title="Permalink to this headline">¶</a></h3>
There are times where a configuration needs to refer to objects
external to the configuration, for example <tt class="docutils literal">sys.stderr</tt>. If the
configuration dict is constructed using Python code, this is
straightforward, but a problem arises when the configuration is
provided via a text file (e.g. JSON, YAML). In a text file, there is
no standard way to distinguish <tt class="docutils literal">sys.stderr</tt> from the literal string
<tt class="docutils literal">'sys.stderr'</tt>. To facilitate this distinction, the configuration
system looks for certain special prefixes in string values and
treat them specially. For example, if the literal string
<tt class="docutils literal">'ext://sys.stderr'</tt> is provided as a value in the configuration,
then the <tt class="docutils literal">ext://</tt> will be stripped off and the remainder of the
value processed using normal import mechanisms.
The handling of such prefixes is done in a way analogous to protocol
handling: there is a generic mechanism to look for prefixes which
match the regular expression <tt class="docutils literal">^(?P&lt;prefix&gt;[a-z]+)://(?P&lt;suffix&gt;.*)$</tt>
whereby, if the <tt class="docutils literal">prefix</tt> is recognised, the <tt class="docutils literal">suffix</tt> is processed
in a prefix-dependent manner and the result of the processing replaces
the string value. If the prefix is not recognised, then the string
value will be left as-is.
</div>
<div class="section" id="access-to-internal-objects">
<h3>15.8.2.6. Access to internal objects<a class="headerlink" href="#access-to-internal-objects" title="Permalink to this headline">¶</a></h3>
As well as external objects, there is sometimes also a need to refer
to objects in the configuration. This will be done implicitly by the
configuration system for things that it knows about. For example, the
string value <tt class="docutils literal">'DEBUG'</tt> for a <tt class="docutils literal">level</tt> in a logger or handler will
automatically be converted to the value <tt class="docutils literal">logging.DEBUG</tt>, and the
<tt class="docutils literal">handlers</tt>, <tt class="docutils literal">filters</tt> and <tt class="docutils literal">formatter</tt> entries will take an
object id and resolve to the appropriate destination object.
However, a more generic mechanism is needed for user-defined
objects which are not known to the <a class="reference internal" href="logging.html#module-logging" title="logging: Flexible event logging system for applications."><tt class="xref py py-mod docutils literal">logging</tt></a> module. For
example, consider <a class="reference internal" href="logging.handlers.html#logging.handlers.MemoryHandler" title="logging.handlers.MemoryHandler"><tt class="xref py py-class docutils literal">logging.handlers.MemoryHandler</tt></a>, which takes
a <tt class="docutils literal">target</tt> argument which is another handler to delegate to. Since
the system already knows about this class, then in the configuration,
the given <tt class="docutils literal">target</tt> just needs to be the object id of the relevant
target handler, and the system will resolve to the handler from the
id. If, however, a user defines a <tt class="docutils literal">my.package.MyHandler</tt> which has
an <tt class="docutils literal">alternate</tt> handler, the configuration system would not know that
the <tt class="docutils literal">alternate</tt> referred to a handler. To cater for this, a generic
resolution system allows the user to specify:
<div class="highlight-python"><pre>handlers:
 file:
 # configuration of file handler goes here

custom:
 (): my.package.MyHandler
 alternate: cfg://handlers.file</pre>
</div>
The literal string <tt class="docutils literal">'cfg://handlers.file'</tt> will be resolved in an
analogous way to strings with the <tt class="docutils literal">ext://</tt> prefix, but looking
in the configuration itself rather than the import namespace. The
mechanism allows access by dot or by index, in a similar way to
that provided by <tt class="docutils literal">str.format</tt>. Thus, given the following snippet:
<div class="highlight-python"><pre>handlers:
 email:
 class: logging.handlers.SMTPHandler
 mailhost: localhost
 fromaddr: my_app@domain.tld
 toaddrs:
 - support_team@domain.tld
 - dev_team@domain.tld
 subject: Houston, we have a problem.</pre>
</div>
in the configuration, the string <tt class="docutils literal">'cfg://handlers'</tt> would resolve to
the dict with key <tt class="docutils literal">handlers</tt>, the string <tt class="docutils literal">'cfg://handlers.email</tt>
would resolve to the dict with key <tt class="docutils literal">email</tt> in the <tt class="docutils literal">handlers</tt> dict,
and so on. The string <tt class="docutils literal">'cfg://handlers.email.toaddrs[1]</tt> would
resolve to <tt class="docutils literal">'dev_team.domain.tld'</tt> and the string
<tt class="docutils literal">'cfg://handlers.email.toaddrs[0]'</tt> would resolve to the value
<tt class="docutils literal">'support_team&#64;domain.tld'</tt>. The <tt class="docutils literal">subject</tt> value could be accessed
using either <tt class="docutils literal">'cfg://handlers.email.subject'</tt> or, equivalently,
<tt class="docutils literal">'cfg://handlers.email[subject]'</tt>. The latter form only needs to be
used if the key contains spaces or non-alphanumeric characters. If an
index value consists only of decimal digits, access will be attempted
using the corresponding integer value, falling back to the string
value if needed.
Given a string <tt class="docutils literal">cfg://handlers.myhandler.mykey.123</tt>, this will
resolve to <tt class="docutils literal">config_dict['handlers']['myhandler']['mykey']['123']</tt>.
If the string is specified as <tt class="docutils literal">cfg://handlers.myhandler.mykey[123]</tt>,
the system will attempt to retrieve the value from
<tt class="docutils literal">config_dict['handlers']['myhandler']['mykey'][123]</tt>, and fall back
to <tt class="docutils literal">config_dict['handlers']['myhandler']['mykey']['123']</tt> if that
fails.
</div>
<div class="section" id="import-resolution-and-custom-importers">
<h3>15.8.2.7. Import resolution and custom importers<a class="headerlink" href="#import-resolution-and-custom-importers" title="Permalink to this headline">¶</a></h3>
Import resolution, by default, uses the builtin <a class="reference internal" href="functions.html#__import__" title="__import__"><tt class="xref py py-func docutils literal">__import__()</tt></a> function
to do its importing. You may want to replace this with your own importing
mechanism: if so, you can replace the <tt class="xref py py-attr docutils literal">importer</tt> attribute of the
<tt class="xref py py-class docutils literal">DictConfigurator</tt> or its superclass, the
<tt class="xref py py-class docutils literal">BaseConfigurator</tt> class. However, you need to be
careful because of the way functions are accessed from classes via
descriptors. If you are using a Python callable to do your imports, and you
want to define it at class level rather than instance level, you need to wrap
it with <a class="reference internal" href="functions.html#staticmethod" title="staticmethod"><tt class="xref py py-func docutils literal">staticmethod()</tt></a>. For example:
<div class="highlight-python"><div class="highlight"><pre>from importlib import import_module
from logging.config import BaseConfigurator

BaseConfigurator.importer = staticmethod(import_module)
</pre></div>
</div>
You don&#8217;t need to wrap with <a class="reference internal" href="functions.html#staticmethod" title="staticmethod"><tt class="xref py py-func docutils literal">staticmethod()</tt></a> if you&#8217;re setting the import
callable on a configurator instance.
</div>
</div>
<div class="section" id="configuration-file-format">
<h2>15.8.3. Configuration file format<a class="headerlink" href="#configuration-file-format" title="Permalink to this headline">¶</a></h2>
The configuration file format understood by <a class="reference internal" href="#logging.config.fileConfig" title="logging.config.fileConfig"><tt class="xref py py-func docutils literal">fileConfig()</tt></a> is based on
<tt class="xref py py-mod docutils literal">configparser</tt> functionality. The file must contain sections called
<tt class="docutils literal">[loggers]</tt>, <tt class="docutils literal">[handlers]</tt> and <tt class="docutils literal">[formatters]</tt> which identify by name the
entities of each type which are defined in the file. For each such entity, there
is a separate section which identifies how that entity is configured. Thus, for
a logger named <tt class="docutils literal">log01</tt> in the <tt class="docutils literal">[loggers]</tt> section, the relevant
configuration details are held in a section <tt class="docutils literal">[logger_log01]</tt>. Similarly, a
handler called <tt class="docutils literal">hand01</tt> in the <tt class="docutils literal">[handlers]</tt> section will have its
configuration held in a section called <tt class="docutils literal">[handler_hand01]</tt>, while a formatter
called <tt class="docutils literal">form01</tt> in the <tt class="docutils literal">[formatters]</tt> section will have its configuration
specified in a section called <tt class="docutils literal">[formatter_form01]</tt>. The root logger
configuration must be specified in a section called <tt class="docutils literal">[logger_root]</tt>.
Examples of these sections in the file are given below.
<div class="highlight-python"><div class="highlight"><pre>[loggers]
keys=root,log02,log03,log04,log05,log06,log07

[handlers]
keys=hand01,hand02,hand03,hand04,hand05,hand06,hand07,hand08,hand09

[formatters]
keys=form01,form02,form03,form04,form05,form06,form07,form08,form09
</pre></div>
</div>
The root logger must specify a level and a list of handlers. An example of a
root logger section is given below.
<div class="highlight-python"><div class="highlight"><pre>[logger_root]
level=NOTSET
handlers=hand01
</pre></div>
</div>
The <tt class="docutils literal">level</tt> entry can be one of <tt class="docutils literal">DEBUG, INFO, WARNING, ERROR, CRITICAL</tt> or
<tt class="docutils literal">NOTSET</tt>. For the root logger only, <tt class="docutils literal">NOTSET</tt> means that all messages will be
logged. Level values are <a class="reference internal" href="functions.html#eval" title="eval"><tt class="xref py py-func docutils literal">eval()</tt></a>uated in the context of the <tt class="docutils literal">logging</tt>
package&#8217;s namespace.
The <tt class="docutils literal">handlers</tt> entry is a comma-separated list of handler names, which must
appear in the <tt class="docutils literal">[handlers]</tt> section. These names must appear in the
<tt class="docutils literal">[handlers]</tt> section and have corresponding sections in the configuration
file.
For loggers other than the root logger, some additional information is required.
This is illustrated by the following example.
<div class="highlight-python"><div class="highlight"><pre>[logger_parser]
level=DEBUG
handlers=hand01
propagate=1
qualname=compiler.parser
</pre></div>
</div>
The <tt class="docutils literal">level</tt> and <tt class="docutils literal">handlers</tt> entries are interpreted as for the root logger,
except that if a non-root logger&#8217;s level is specified as <tt class="docutils literal">NOTSET</tt>, the system
consults loggers higher up the hierarchy to determine the effective level of the
logger. The <tt class="docutils literal">propagate</tt> entry is set to 1 to indicate that messages must
propagate to handlers higher up the logger hierarchy from this logger, or 0 to
indicate that messages are not propagated to handlers up the hierarchy. The
<tt class="docutils literal">qualname</tt> entry is the hierarchical channel name of the logger, that is to
say the name used by the application to get the logger.
Sections which specify handler configuration are exemplified by the following.
<div class="highlight-python"><pre>[handler_hand01]
class=StreamHandler
level=NOTSET
formatter=form01
args=(sys.stdout,)</pre>
</div>
The <tt class="docutils literal">class</tt> entry indicates the handler&#8217;s class (as determined by <a class="reference internal" href="functions.html#eval" title="eval"><tt class="xref py py-func docutils literal">eval()</tt></a>
in the <tt class="docutils literal">logging</tt> package&#8217;s namespace). The <tt class="docutils literal">level</tt> is interpreted as for
loggers, and <tt class="docutils literal">NOTSET</tt> is taken to mean &#8216;log everything&#8217;.

Changed in version 2.6: Added support for resolving the handler’s class as a dotted module and
class name.
The <tt class="docutils literal">formatter</tt> entry indicates the key name of the formatter for this
handler. If blank, a default formatter (<tt class="docutils literal">logging._defaultFormatter</tt>) is used.
If a name is specified, it must appear in the <tt class="docutils literal">[formatters]</tt> section and have
a corresponding section in the configuration file.
The <tt class="docutils literal">args</tt> entry, when <a class="reference internal" href="functions.html#eval" title="eval"><tt class="xref py py-func docutils literal">eval()</tt></a>uated in the context of the <tt class="docutils literal">logging</tt>
package&#8217;s namespace, is the list of arguments to the constructor for the handler
class. Refer to the constructors for the relevant handlers, or to the examples
below, to see how typical entries are constructed.
<div class="highlight-python"><pre>[handler_hand02]
class=FileHandler
level=DEBUG
formatter=form02
args=('python.log', 'w')

[handler_hand03]
class=handlers.SocketHandler
level=INFO
formatter=form03
args=('localhost', handlers.DEFAULT_TCP_LOGGING_PORT)

[handler_hand04]
class=handlers.DatagramHandler
level=WARN
formatter=form04
args=('localhost', handlers.DEFAULT_UDP_LOGGING_PORT)

[handler_hand05]
class=handlers.SysLogHandler
level=ERROR
formatter=form05
args=(('localhost', handlers.SYSLOG_UDP_PORT), handlers.SysLogHandler.LOG_USER)

[handler_hand06]
class=handlers.NTEventLogHandler
level=CRITICAL
formatter=form06
args=('Python Application', '', 'Application')

[handler_hand07]
class=handlers.SMTPHandler
level=WARN
formatter=form07
args=('localhost', 'from@abc', ['user1@abc', 'user2@xyz'], 'Logger Subject')

[handler_hand08]
class=handlers.MemoryHandler
level=NOTSET
formatter=form08
target=
args=(10, ERROR)

[handler_hand09]
class=handlers.HTTPHandler
level=NOTSET
formatter=form09
args=('localhost:9022', '/log', 'GET')</pre>
</div>
Sections which specify formatter configuration are typified by the following.
<div class="highlight-python"><pre>[formatter_form01]
format=F1 %(asctime)s %(levelname)s %(message)s
datefmt=
class=logging.Formatter</pre>
</div>
The <tt class="docutils literal">format</tt> entry is the overall format string, and the <tt class="docutils literal">datefmt</tt> entry is
the <tt class="xref py py-func docutils literal">strftime()</tt>-compatible date/time format string. If empty, the
package substitutes ISO8601 format date/times, which is almost equivalent to
specifying the date format string <tt class="docutils literal">'%Y-%m-%d %H:%M:%S'</tt>. The ISO8601 format
also specifies milliseconds, which are appended to the result of using the above
format string, with a comma separator. An example time in ISO8601 format is
<tt class="docutils literal">2003-01-23 00:29:50,411</tt>.
The <tt class="docutils literal">class</tt> entry is optional. It indicates the name of the formatter&#8217;s class
(as a dotted module and class name.) This option is useful for instantiating a
<tt class="xref py py-class docutils literal">Formatter</tt> subclass. Subclasses of <tt class="xref py py-class docutils literal">Formatter</tt> can present
exception tracebacks in an expanded or condensed format.
<div class="admonition note">
Note
Due to the use of <a class="reference internal" href="functions.html#eval" title="eval"><tt class="xref py py-func docutils literal">eval()</tt></a> as described above, there are
potential security risks which result from using the <a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a> to send
and receive configurations via sockets. The risks are limited to where
multiple users with no mutual trust run code on the same machine; see the
<a class="reference internal" href="#logging.config.listen" title="logging.config.listen"><tt class="xref py py-func docutils literal">listen()</tt></a> documentation for more information.
</div>
<div class="admonition-see-also admonition seealso">
See also
<dl class="last docutils">
<dt>Module <a class="reference internal" href="logging.html#module-logging" title="logging: Flexible event logging system for applications."><tt class="xref py py-mod docutils literal">logging</tt></a></dt>
<dd>API reference for the logging module.</dd>
<dt>Module <a class="reference internal" href="logging.handlers.html#module-logging.handlers" title="logging.handlers: Handlers for the logging module."><tt class="xref py py-mod docutils literal">logging.handlers</tt></a></dt>
<dd>Useful handlers included with the logging module.</dd>
</dl>
</div>
</div>
</div>

</div>
 </div>
 </div>
 <div class="sphinxsidebar">
 <div class="sphinxsidebarwrapper">
 <h3><a href="../contents.html">Table Of Contents</a></h3>
 <ul>
<li><a class="reference internal" href="#">15.8. <tt class="docutils literal">logging.config</tt> &#8212; Logging configuration</a><ul>
<li><a class="reference internal" href="#configuration-functions">15.8.1. Configuration functions</a></li>
<li><a class="reference internal" href="#configuration-dictionary-schema">15.8.2. Configuration dictionary schema</a><ul>
<li><a class="reference internal" href="#dictionary-schema-details">15.8.2.1. Dictionary Schema Details</a></li>
<li><a class="reference internal" href="#incremental-configuration">15.8.2.2. Incremental Configuration</a></li>
<li><a class="reference internal" href="#object-connections">15.8.2.3. Object connections</a></li>
<li><a class="reference internal" href="#user-defined-objects">15.8.2.4. User-defined objects</a></li>
<li><a class="reference internal" href="#access-to-external-objects">15.8.2.5. Access to external objects</a></li>
<li><a class="reference internal" href="#access-to-internal-objects">15.8.2.6. Access to internal objects</a></li>
<li><a class="reference internal" href="#import-resolution-and-custom-importers">15.8.2.7. Import resolution and custom importers</a></li>
</ul>
</li>
<li><a class="reference internal" href="#configuration-file-format">15.8.3. Configuration file format</a></li>
</ul>
</li>
</ul>

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