4:登录知乎后爬取首页问题

【转载】：http://www.jianshu.com/p/b7f41df6202d#pay-modal，作者：Andrew-Liu。

上篇文章十分完备的谢了模拟登录，cookies以及headers的使用。

不过要补充的是：

1：其第二步分析From data时请注意清除cookies后查看，否者会多出部分不同。（PS:rememberme:y--->remember_me:true).

2:关于此部分：

 rules = (
        Rule(SgmlLinkExtractor(allow = ('/question/d+#.*?', )), callback = 'parse_page', follow = True),
        Rule(SgmlLinkExtractor(allow = ('/question/d+', )), callback = 'parse_page', follow = True),
    )

为Link extractor部分，文档见此（已经不推荐使用SgmlLinkExtractor）

3:注意继承的来自CrawlSpider类，文档说明如下：

CrawlSpider

class scrapy.spiders.CrawlSpider

This is the most commonly used spider for crawling regular websites, as it provides a convenient mechanism for following links by defining a set of rules. It may not be the best suited for your particular web sites or project, but it’s generic enough for several cases, so you can start from it and override it as needed for more custom functionality, or just implement your own spider.

Apart from the attributes inherited from Spider (that you must specify), this class supports a new attribute:

rules

Which is a list of one (or more) Rule objects. Each Rule defines a certain behaviour for crawling the site. Rules objects are described below. If multiple rules match the same link, the first one will be used, according to the order they’re defined in this attribute.

This spider also exposes an overrideable method:

parse_start_url(response)

This method is called for the start_urls responses. It allows to parse the initial responses and must return either an Item object, a Request object, or an iterable containing any of them.

Crawling rules

class scrapy.spiders.Rule(link_extractor, callback=None, cb_kwargs=None, follow=None, process_links=None,process_request=None)

link_extractor is a Link Extractor object which defines how links will be extracted from each crawled page.

callback is a callable or a string (in which case a method from the spider object with that name will be used) to be called for each link extracted with the specified link_extractor. This callback receives a response as its first argument and must return a list containing Item and/or Request objects (or any subclass of them).

Warning

When writing crawl spider rules, avoid using parse as callback, since the CrawlSpider uses theparse method itself to implement its logic. So if you override the parse method, the crawl spider will no longer work.

cb_kwargs is a dict containing the keyword arguments to be passed to the callback function.

follow is a boolean which specifies if links should be followed from each response extracted with this rule. If callback is None follow defaults to True, otherwise it defaults to False.

process_links is a callable, or a string (in which case a method from the spider object with that name will be used) which will be called for each list of links extracted from each response using the specified link_extractor. This is mainly used for filtering purposes.

process_request is a callable, or a string (in which case a method from the spider object with that name will be used) which will be called with every request extracted by this rule, and must return a request or None (to filter out the request).

CrawlSpider example

Let’s now take a look at an example CrawlSpider with rules:

import scrapy
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor

class MySpider(CrawlSpider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = ['http://www.example.com']

    rules = (
        # Extract links matching 'category.php' (but not matching 'subsection.php')
        # and follow links from them (since no callback means follow=True by default).
        Rule(LinkExtractor(allow=('category.php', ), deny=('subsection.php', ))),

        # Extract links matching 'item.php' and parse them with the spider's method parse_item
        Rule(LinkExtractor(allow=('item.php', )), callback='parse_item'),
    )

    def parse_item(self, response):
        self.logger.info('Hi, this is an item page! %s', response.url)
        item = scrapy.Item()
        item['id'] = response.xpath('//td[@id="item_id"]/text()').re(r'ID: (d+)')
        item['name'] = response.xpath('//td[@id="item_name"]/text()').extract()
        item['description'] = response.xpath('//td[@id="item_description"]/text()').extract()
        return item

This spider would start crawling example.com’s home page, collecting category links, and item links, parsing the latter with the parse_item method. For each item response, some data will be extracted from the HTML using XPath, and an Item will be filled with it.