Scrapy provides a built-in mechanism for extracting data (called selectors) but you can easily use BeautifulSoup (or lxml) instead, if you feel more comfortable working with them. After all, they’re just parsing libraries which can be imported and used from any Python code.
Scrapy runs in Python 2.5, 2.6 and 2.7. But it’s recommended you use Python 2.6 or above, since the Python 2.5 standard library has a few bugs in their URL handling libraries. Some of these Python 2.5 bugs not only affect Scrapy but any user code, such as spiders.
No, and there are no plans to port Scrapy to Python 3.0 yet. At the moment, Scrapy works with Python 2.5, 2.6 and 2.7.
Probably, but we don’t like that word. We think Django is a great open source project and an example to follow, so we’ve used it as an inspiration for Scrapy.
We believe that, if something is already done well, there’s no need to reinvent it. This concept, besides being one of the foundations for open source and free software, not only applies to software but also to documentation, procedures, policies, etc. So, instead of going through each problem ourselves, we choose to copy ideas from those projects that have already solved them properly, and focus on the real problems we need to solve.
We’d be proud if Scrapy serves as an inspiration for other projects. Feel free to steal from us!
Yes. Support for HTTP proxies is provided (since Scrapy 0.8) through the HTTP Proxy downloader middleware. See HttpProxyMiddleware.
By default, Scrapy uses a LIFO queue for storing pending requests, which basically means that it crawls in DFO order. This order is more convenient in most cases. If you do want to crawl in true BFO order, you can do it by setting the following settings:
DEPTH_PRIORITY = 1 SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue' SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'
Also, Python has a builtin memory leak issue which is described in Leaks without leaks.
See previous question.
Yes. You can use the runspider command. For example, if you have a spider written in a my_spider.py file you can run it with:
scrapy runspider my_spider.py
See runspider command for more info.
Those messages (logged with DEBUG level) don’t necessarily mean there is a problem, so you may not need to fix them.
Those message are thrown by the Offsite Spider Middleware, which is a spider middleware (enabled by default) whose purpose is to filter out requests to domains outside the ones covered by the spider.
For more info see: OffsiteMiddleware.
Some signals support returning deferreds from their handlers, others don’t. See the Built-in signals reference to know which ones.
999 is a custom reponse status code used by Yahoo sites to throttle requests. Try slowing down the crawling speed by using a download delay of 2 (or higher) in your spider:
class MySpider(CrawlSpider): name = 'myspider' DOWNLOAD_DELAY = 2 # [ ... rest of the spider code ... ]
Or by setting a global download delay in your project with the DOWNLOAD_DELAY setting.
Yes, but you can also use the Scrapy shell which allows you too quickly analyze (and even modify) the response being processed by your spider, which is, quite often, more useful than plain old pdb.set_trace().
For more info see Invoking the shell from spiders to inspect responses.
To dump into a JSON file:
scrapy crawl myspider -o items.json -t json
To dump into a CSV file:
scrapy crawl myspider -o items.csv -t csv
To dump into a XML file:
scrapy crawl myspider -o items.xml -t xml
For more information see Feed exports
Parsing big feeds with XPath selectors can be problematic since they need to build the DOM of the entire feed in memory, and this can be quite slow and consume a lot of memory.
In order to avoid parsing all the entire feed at once in memory, you can use the functions xmliter and csviter from scrapy.utils.iterators module. In fact, this is what the feed spiders (see Spiders) use under the cover.
Some websites implement certain measures to prevent bots from crawling them, with varying degrees of sophistication. Getting around those measures can be difficult and tricky, and may sometimes require special infrastructure.
Here are some tips to keep in mind when dealing with these kind of sites:
If you are still unable to prevent your bot getting banned, consider contacting commercial support.