Sometimes, for big sites, it's desirable to pause crawls and be able to resume them later.
Scrapy supports this functionality out of the box by providing the following facilities:
- a scheduler that persists scheduled requests on disk
- a duplicates filter that persists visited requests on disk
- an extension that keeps some spider state (key/value pairs) persistent between batches
To enable persistence support you just need to define a job directory through
the JOBDIR
setting. This directory will be for storing all required data to
keep the state of a single job (ie. a spider run). It's important to note that
this directory must not be shared by different spiders, or even different
jobs/runs of the same spider, as it's meant to be used for storing the state of
a single job.
To start a spider with persistence supported enabled, run it like this:
scrapy crawl somespider -s JOBDIR=crawls/somespider-1
Then, you can stop the spider safely at any time (by pressing Ctrl-C or sending a signal), and resume it later by issuing the same command:
scrapy crawl somespider -s JOBDIR=crawls/somespider-1
Sometimes you'll want to keep some persistent spider state between pause/resume
batches. You can use the spider.state
attribute for that, which should be a
dict. There's a built-in extension that takes care of serializing, storing and
loading that attribute from the job directory, when the spider starts and
stops.
Here's an example of a callback that uses the spider state (other spider code is omitted for brevity):
def parse_item(self, response): # parse item here self.state['items_count'] = self.state.get('items_count', 0) + 1
There are a few things to keep in mind if you want to be able to use the Scrapy persistence support:
Cookies may expire. So, if you don't resume your spider quickly the requests scheduled may no longer work. This won't be an issue if you spider doesn't rely on cookies.
Requests must be serializable by the pickle module, in order for persistence to work, so you should make sure that your requests are serializable.
The most common issue here is to use lambda
functions on request callbacks that
can't be persisted.
So, for example, this won't work:
def some_callback(self, response): somearg = 'test' return scrapy.Request('http://www.example.com', callback=lambda r: self.other_callback(r, somearg)) def other_callback(self, response, somearg): print "the argument passed is:", somearg
But this will:
def some_callback(self, response): somearg = 'test' return scrapy.Request('http://www.example.com', callback=self.other_callback, meta={'somearg': somearg}) def other_callback(self, response): somearg = response.meta['somearg'] print "the argument passed is:", somearg