The extensions framework provide a mechanism for inserting your own custom functionality into Scrapy.
Extensions are just regular classes that are instantiated at Scrapy startup, when extensions are initialized.
Extensions use the Scrapy settings to manage their settings, just like any other Scrapy code.
It is customary for extensions to prefix their settings with their own name, to avoid collision with existing (and future) extensions. For example, an hypothetic extension to handle Google Sitemaps would use settings like GOOGLESITEMAP_ENABLED, GOOGLESITEMAP_DEPTH, and so on.
Extensions are loaded and activated at startup by instantiating a single instance of the extension class. Therefore, all the extension initialization code must be performed in the class constructor (__init__ method).
To make an extension available, add it to the EXTENSIONS setting in your Scrapy settings. In EXTENSIONS, each extension is represented by a string: the full Python path to the extension’s class name. For example:
EXTENSIONS = {
'scrapy.contrib.corestats.CoreStats': 500,
'scrapy.management.web.WebConsole': 500,
'scrapy.management.telnet.TelnetConsole': 500,
'scrapy.contrib.webconsole.enginestatus.EngineStatus': 500,
'scrapy.contrib.webconsole.stats.StatsDump': 500,
}
As you can see, the EXTENSIONS setting is a dict where the keys are the extension paths, and their values are the orders, which define the extension loading order. Extensions orders are not as important as middleware orders though, and they are typically irrelevant, ie. it doesn’t matter in which order the extensions are loaded because they don’t depend on each other [1].
However this feature can be exploited if you need to add an extension which depends on other extension already loaded.
[1] This is is why the EXTENSIONS_BASE setting in Scrapy (which contains all built-in extensions enabled by default) defines all the extensions with the same order (500).
Not all available extensions will be enabled. Some of them usually depend on a particular setting. For example, the HTTP Cache extension is available by default but disabled unless the HTTPCACHE_DIR setting is set. Both enabled and disabled extension can be accessed through the Extension manager.
Even though it’s not usually needed, you can access extension objects through the Extension manager which is populated when extensions are loaded. For example, to access the WebConsole extension:
from scrapy.extension import extensions
webconsole_extension = extensions.enabled['WebConsole']
See also
Extension manager, for the complete Extension manager reference.
Writing your own extension is easy. Each extension is a single Python class which doesn’t need to implement any particular method.
All extension initialization code must be performed in the class constructor (__init__ method). If that method raises the NotConfigured exception, the extension will be disabled. Otherwise, the extension will be enabled.
Let’s take a look at the following example extension which just logs a message everytime a domain/spider is opened and closed:
from scrapy.xlib.pydispatch import dispatcher
from scrapy.core import signals
class SpiderOpenCloseLogging(object):
def __init__(self):
dispatcher.connect(self.spider_opened, signal=signals.spider_opened)
dispatcher.connect(self.spider_closed, signal=signals.spider_closed)
def spider_opened(self, spider):
log.msg("opened spider %s" % spider.domain_name)
def spider_closed(self, spider):
log.msg("closed spider %s" % spider.domain_name)
The Extension Manager is responsible for loading and keeping track of installed extensions and it’s configured through the EXTENSIONS setting which contains a dictionary of all available extensions and their order similar to how you configure the downloader middlewares.
The extension manager is a singleton object, which is instantiated at module loading time and can be accessed like this:
from scrapy.extension import extensions
A dict with the enabled extensions. The keys are the extension class names, and the values are the extension objects. Example:
>>> from scrapy.extension import extensions
>>> extensions.load()
>>> print extensions.enabled
{'CoreStats': <scrapy.contrib.corestats.CoreStats object at 0x9e272ac>,
'WebConsoke': <scrapy.management.telnet.TelnetConsole instance at 0xa05670c>,
...
A dict with the disabled extensions. The keys are the extension class names, and the values are the extension class paths (because objects are never instantiated for disabled extensions). Example:
>>> from scrapy.extension import extensions
>>> extensions.load()
>>> print extensions.disabled
{'MemoryDebugger': 'scrapy.contrib.webconsole.stats.MemoryDebugger',
'MyExtension': 'myproject.extensions.MyExtension',
...
Enable the collection of core statistics, provided the stats collection are enabled (see Stats Collection).
Provides an extensible web server for managing a Scrapy process. It’s enabled by the WEBCONSOLE_ENABLED setting. The server will listen in the port specified in WEBCONSOLE_PORT, and will log to the file specified in WEBCONSOLE_LOGFILE.
The web server is designed to be extended by other extensions which can add their own management web interfaces.
See also Web Console for information on how to write your own web console extension, and Available Web console extensions for a list of available built-in (web console) extensions.
Provides a telnet console for getting into a Python interpreter inside the currently running Scrapy process, which can be very useful for debugging.
The telnet console must be enabled by the TELNETCONSOLE_ENABLED setting, and the server will listen in the port specified in WEBCONSOLE_PORT.
Note
This extension does not work in Windows.
Allows monitoring the memory used by a Scrapy process and:
1, send a notification email when it exceeds a certain value 2. terminate the Scrapy process when it exceeds a certain value
The notification emails can be triggered when a certain warning value is reached (MEMUSAGE_WARNING_MB) and when the maximum value is reached (MEMUSAGE_LIMIT_MB) which will also cause the Scrapy process to be terminated.
This extension is enabled by the MEMUSAGE_ENABLED setting and can be configured with the following settings:
A memory debugger which collects some info about objects uncollected by the garbage collector and libxml2 memory leaks. To enable this extension turn on the MEMDEBUG_ENABLED setting. The report will be printed to standard output. If the MEMDEBUG_NOTIFY setting contains a list of emails the report will also be sent to those addresses.
Closes a spider automatically when some conditions are met, using a specific closing reason for each condition.
The conditions for closing a spider can be configured through the following settings. Other conditions will be supported in the future.
Default: 0
An integer which specifies a number of seconds. If the spider remains open for more than that number of second, it will be automatically closed with the reason closespider_timeout. If zero (or non set) spiders won’t be closed by timeout.
Default: 0
An integer which specifies a number of items. If the spider scrapes more than that amount if items and those items are passed by the item pipeline, the spider will be closed with the reason closespider_itempassed. If zero (or non set) spiders won’t be closed by number of passed items.
This simple extension can be used to send a notification email every time a domain has finished scraping, including the Scrapy stats collected. The email will be sent to all recipients specified in the STATSMAILER_RCPTS setting.
Dumps the stack trace of a runnning Scrapy process when a SIGUSR2 signal is received. After the stack trace is dumped, the Scrapy process continues running normally.
The stack trace is sent to standard output.
This extension only works on POSIX-compliant platforms (ie. not Windows).
Invokes a Python debugger inside a running Scrapy process when a SIGUSR2 signal is received. After the debugger is exited, the Scrapy process continues running normally.
For more info see Debugging in Python.
This extension only works on POSIX-compliant platforms (ie. not Windows).