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Selectors — Scrapy 2.5.1 documentation

When you’re scraping web pages, the most common task you need to perform is
to extract data from the HTML source. There are several libraries available to
achieve this, such as:
BeautifulSoup is a very popular web scraping library among Python
programmers which constructs a Python object based on the structure of the
HTML code and also deals with bad markup reasonably well, but it has one
drawback: it’s slow.
lxml is an XML parsing library (which also parses HTML) with a pythonic
API based on ElementTree. (lxml is not part of the Python
standard library. )
Scrapy comes with its own mechanism for extracting data. They’re called
selectors because they “select” certain parts of the HTML document specified
either by XPath or CSS expressions.
XPath is a language for selecting nodes in XML documents, which can also be
used with HTML. CSS is a language for applying styles to HTML documents. It
defines selectors to associate those styles with specific HTML elements.
Note
Scrapy Selectors is a thin wrapper around parsel library; the purpose of
this wrapper is to provide better integration with Scrapy Response objects.
parsel is a stand-alone web scraping library which can be used without
Scrapy. It uses lxml library under the hood, and implements an
easy API on top of lxml API. It means Scrapy selectors are very similar
in speed and parsing accuracy to lxml.
Using selectors¶
Constructing selectors¶
Response objects expose a Selector instance
on. selector attribute:
>>> (‘//span/text()’)()
‘good’
Querying responses using XPath and CSS is so common that responses include two
more shortcuts: () and ():
>>> (‘span::text’)()
Scrapy selectors are instances of Selector class
constructed by passing either TextResponse object or
markup as a string (in text argument).
Usually there is no need to construct Scrapy selectors manually:
response object is available in Spider callbacks, so in most cases
it is more convenient to use () and ()
shortcuts. By using lector or one of these shortcuts
you can also ensure the response body is parsed only once.
But if required, it is possible to use Selector directly.
Constructing from text:
>>> from lector import Selector
>>> body = ‘good
>>> Selector(text=body)(‘//span/text()’)()
Constructing from response – HtmlResponse is one of
TextResponse subclasses:
>>> from import HtmlResponse
>>> response = HtmlResponse(url=”, body=body)
>>> Selector(response=response)(‘//span/text()’)()
Selector automatically chooses the best parsing rules
(XML vs HTML) based on input type.
To explain how to use the selectors we’ll use the Scrapy shell (which
provides interactive testing) and an example page located in the Scrapy
documentation server:
For the sake of completeness, here’s its full HTML code:



Example website

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First, let’s open the shell:
scrapy shell
Then, after the shell loads, you’ll have the response available as response
shell variable, and its attached selector in lector attribute.
Since we’re dealing with HTML, the selector will automatically use an HTML parser.
So, by looking at the HTML code of that
page, let’s construct an XPath for selecting the text inside the title tag:
>>> (‘//title/text()’)
[]
To actually extract the textual data, you must call the selector ()
or () methods, as follows:
>>> (‘//title/text()’)()
[‘Example website’]
‘Example website’
() always returns a single result; if there are several matches,
content of a first match is returned; if there are no matches, None
is returned. () returns a list with all results.
Notice that CSS selectors can select text or attribute nodes using CSS3
pseudo-elements:
>>> (‘title::text’)()
As you can see, () and () methods return a
SelectorList instance, which is a list of new
selectors. This API can be used for quickly selecting nested data:
>>> (‘img’)(‘@src’)()
[”,
”,
”]
If you want to extract only the first matched element, you can call the
selector () (or its alias. extract_first() commonly used in
previous Scrapy versions):
>>> (‘//div[@id=”images”]/a/text()’)()
‘Name: My image 1 ‘
It returns None if no element was found:
>>> (‘//div[@id=”not-exists”]/text()’)() is None
True
A default return value can be provided as an argument, to be used instead
of None:
>>> (‘//div[@id=”not-exists”]/text()’)(default=’not-found’)
‘not-found’
Instead of using e. g. ‘@src’ XPath it is possible to query for attributes
using property of a Selector:
>>> [[‘src’] for img in (‘img’)]
As a shortcut, is also available on SelectorList directly;
it returns attributes for the first matching element:
>>> (‘img’)[‘src’]

This is most useful when only a single result is expected, e. when selecting
by id, or selecting unique elements on a web page:
>>> (‘base’)[‘href’]
Now we’re going to get the base URL and some image links:
>>> (‘//base/@href’)()
>>> (‘base::attr(href)’)()
>>> (‘//a[contains(@href, “image”)]/@href’)()
>>> (‘a[href*=image]::attr(href)’)()
>>> (‘//a[contains(@href, “image”)]/img/@src’)()
>>> (‘a[href*=image] img::attr(src)’)()
Extensions to CSS Selectors¶
Per W3C standards, CSS selectors do not support selecting text nodes
or attribute values.
But selecting these is so essential in a web scraping context
that Scrapy (parsel) implements a couple of non-standard pseudo-elements:
to select text nodes, use::text
to select attribute values, use::attr(name) where name is the
name of the attribute that you want the value of
Warning
These pseudo-elements are Scrapy-/Parsel-specific.
They will most probably not work with other libraries like
lxml or PyQuery.
Examples:
title::text selects children text nodes of a descendant element:<br /> *::text selects all descendant text nodes of the current selector context:<br /> >>> (‘#images *::text’)()<br /> [‘\n ‘,<br /> ‘Name: My image 1 ‘,<br /> ‘\n ‘,<br /> ‘Name: My image 2 ‘,<br /> ‘Name: My image 3 ‘,<br /> ‘Name: My image 4 ‘,<br /> ‘Name: My image 5 ‘,<br /> ‘\n ‘]<br /> foo::text returns no results if foo element exists, but contains<br /> no text (i. e. text is empty):<br /> >>> (‘img::text’)()<br /> []<br /> This means (‘foo::text’)() could return None even if an element<br /> exists. Use default=” if you always want a string:<br /> >>> (‘img::text’)(default=”)<br /> a::attr(href) selects the href attribute value of descendant links:<br /> >>> (‘a::attr(href)’)()<br /> See also: Selecting element attributes.<br /> You cannot chain these pseudo-elements. But in practice it would not<br /> make much sense: text nodes do not have attributes, and attribute values<br /> are string values already and do not have children nodes.<br /> Nesting selectors¶<br /> The selection methods (() or ()) return a list of selectors<br /> of the same type, so you can call the selection methods for those selectors<br /> too. Here’s an example:<br /> >>> links = (‘//a[contains(@href, “image”)]’)<br /> >>> ()<br /> [‘<a href="">Name: My image 1 <br /><img src=""></a>‘,<br /> ‘<a href="">Name: My image 2 <br /><img src=""></a>‘,<br /> ‘<a href="">Name: My image 3 <br /><img src=""></a>‘,<br /> ‘<a href="">Name: My image 4 <br /><img src=""></a>‘,<br /> ‘<a href="">Name: My image 5 <br /><img src=""></a>‘]<br /> >>> for index, link in enumerate(links):… href_xpath = (‘@href’)()… img_xpath = (‘img/@src’)()… print(f’Link number {index} points to url {href_xpath! r} and image {img_xpath! r}’)<br /> Link number 0 points to url ” and image ”<br /> Link number 1 points to url ” and image ”<br /> Link number 2 points to url ” and image ”<br /> Link number 3 points to url ” and image ”<br /> Link number 4 points to url ” and image ”<br /> Selecting element attributes¶<br /> There are several ways to get a value of an attribute. First, one can use<br /> XPath syntax:<br /> >>> (“//a/@href”)()<br /> [”, ”, ”, ”, ”]<br /> XPath syntax has a few advantages: it is a standard XPath feature, and<br /> @attributes can be used in other parts of an XPath expression – e. g.<br /> it is possible to filter by attribute value.<br /> Scrapy also provides an extension to CSS selectors (::attr(… ))<br /> which allows to get attribute values:<br /> In addition to that, there is a property of Selector.<br /> You can use it if you prefer to lookup attributes in Python<br /> code, without using XPaths or CSS extensions:<br /> >>> [[‘href’] for a in (‘a’)]<br /> This property is also available on SelectorList; it returns a dictionary<br /> with attributes of a first matching element. It is convenient to use when<br /> a selector is expected to give a single result (e. when selecting by element<br /> ID, or when selecting an unique element on a page):<br /> >>> (‘base’)<br /> {‘href’: ”}<br /> property of an empty SelectorList is empty:<br /> >>> (‘foo’)<br /> {}<br /> Using selectors with regular expressions¶<br /> Selector also has a () method for extracting<br /> data using regular expressions. However, unlike using () or<br /> () methods, () returns a list of strings. So you<br /> can’t construct nested () calls.<br /> Here’s an example used to extract image names from the HTML code above:<br /> >>> (‘//a[contains(@href, “image”)]/text()’)(r’Name:\s*(. *)’)<br /> [‘My image 1’,<br /> ‘My image 2’,<br /> ‘My image 3’,<br /> ‘My image 4’,<br /> ‘My image 5’]<br /> There’s an additional helper reciprocating () (and its<br /> alias. extract_first()) for (), named. re_first().<br /> Use it to extract just the first matching string:<br /> >>> (‘//a[contains(@href, “image”)]/text()’). re_first(r’Name:\s*(. *)’)<br /> ‘My image 1’<br /> extract() and extract_first()¶<br /> If you’re a long-time Scrapy user, you’re probably familiar<br /> with. extract() and. extract_first() selector methods. Many blog posts<br /> and tutorials are using them as well. These methods are still supported<br /> by Scrapy, there are no plans to deprecate them.<br /> However, Scrapy usage docs are now written using () and<br /> () methods. We feel that these new methods result in a more concise<br /> and readable code.<br /> The following examples show how these methods map to each other.<br /> () is the same as SelectorList. extract_first():<br /> >>> (‘a::attr(href)’). extract_first()<br /> () is the same as SelectorList. extract():<br /> >>> (‘a::attr(href)’). extract()<br /> () is the same as Selector. extract():<br /> >>> (‘a::attr(href)’)[0]()<br /> >>> (‘a::attr(href)’)[0]. extract()<br /> For consistency, there is also (), which returns a list:<br /> [”]<br /> So, the main difference is that output of () and () methods<br /> is more predictable: () always returns a single result, ()<br /> always returns a list of all extracted results. With. extract() method<br /> it was not always obvious if a result is a list or not; to get a single<br /> result either. extract() or. extract_first() should be called.<br /> Working with XPaths¶<br /> Here are some tips which may help you to use XPath with Scrapy selectors<br /> effectively. If you are not much familiar with XPath yet,<br /> you may want to take a look first at this XPath tutorial.<br /> Working with relative XPaths¶<br /> Keep in mind that if you are nesting selectors and use an XPath that starts<br /> with /, that XPath will be absolute to the document and not relative to the<br /> Selector you’re calling it from.<br /> For example, suppose you want to extract all </p> <p> elements inside </p> <div> elements. First, you would get all </p> <div> elements:<br /> >>> divs = (‘//div’)<br /> At first, you may be tempted to use the following approach, which is wrong, as<br /> it actually extracts all </p> <p> elements from the document, not only those<br /> inside </p> <div> elements:<br /> >>> for p in (‘//p’): # this is wrong – gets all </p> <p> from the whole document… print(())<br /> This is the proper way to do it (note the dot prefixing the. //p XPath):<br /> >>> for p in (‘. //p’): # extracts all </p> <p> inside… print(())<br /> Another common case would be to extract all direct </p> <p> children:<br /> >>> for p in (‘p’):… print(())<br /> For more details about relative XPaths see the Location Paths section in the<br /> XPath specification.<br /> When querying by class, consider using CSS¶<br /> Because an element can contain multiple CSS classes, the XPath way to select elements<br /> by class is the rather verbose:<br /> *[contains(concat(‘ ‘, normalize-space(@class), ‘ ‘), ‘ someclass ‘)]<br /> If you use @class=’someclass’ you may end up missing elements that have<br /> other classes, and if you just use contains(@class, ‘someclass’) to make up<br /> for that you may end up with more elements that you want, if they have a different<br /> class name that shares the string someclass.<br /> As it turns out, Scrapy selectors allow you to chain selectors, so most of the time<br /> you can just select by class using CSS and then switch to XPath when needed:<br /> >>> from scrapy import Selector<br /> >>> sel = Selector(text=’</p> <div class="hero shout"><time datetime="2014-07-23 19:00">Special date</time></div> <p>‘)<br /> >>> (”)(‘. /time/@datetime’)()<br /> [‘2014-07-23 19:00’]<br /> This is cleaner than using the verbose XPath trick shown above. Just remember<br /> to use the. in the XPath expressions that will follow.<br /> Beware of the difference between //node[1] and (//node)[1]¶<br /> //node[1] selects all the nodes occurring first under their respective parents.<br /> (//node)[1] selects all the nodes in the document, and then gets only the first of them.<br /> Example:<br /> >>> sel = Selector(text=”””…. : </p> <ul class="list">…. : </p> <li>1</li> <p>…. : </p> <li>2</li> <p>…. : </p> <li>3</li> <p>…. : </ul> <p>…. : </p> <li>4</li> <p>…. : </p> <li>5</li> <p>…. : </p> <li>6</li> <p>…. : </ul> <p>“””)<br /> >>> xp = lambda x: (x)()<br /> This gets all first </p> <li> elements under whatever it is its parent:<br /> >>> xp(“//li[1]”)<br /> [‘</p> <li>1</li> <p>‘, ‘</p> <li>4</li> <p>‘]<br /> And this gets the first </p> <li> element in the whole document:<br /> >>> xp(“(//li)[1]”)<br /> [‘</p> <li>1</li> <p>‘]<br /> This gets all first </p> <li> elements under an <ul> parent:<br /> >>> xp(“//ul/li[1]”)<br /> And this gets the first </p> <li> element under an <ul> parent in the whole document:<br /> >>> xp(“(//ul/li)[1]”)<br /> Using text nodes in a condition¶<br /> When you need to use the text content as argument to an XPath string function,<br /> avoid using. //text() and use just. instead.<br /> This is because the expression. //text() yields a collection of text elements – a node-set.<br /> And when a node-set is converted to a string, which happens when it is passed as argument to<br /> a string function like contains() or starts-with(), it results in the text for the first element only.<br /> >>> sel = Selector(text=’<a href="#">Click here to go to the <strong>Next Page</strong></a>‘)<br /> Converting a node-set to string:<br /> >>> (‘//a//text()’)() # take a peek at the node-set<br /> [‘Click here to go to the ‘, ‘Next Page’]<br /> >>> (“string(//a[1]//text())”)() # convert it to string<br /> [‘Click here to go to the ‘]<br /> A node converted to a string, however, puts together the text of itself plus of all its descendants:<br /> >>> (“//a[1]”)() # select the first node<br /> [‘<a href="#">Click here to go to the <strong>Next Page</strong></a>‘]<br /> >>> (“string(//a[1])”)() # convert it to string<br /> [‘Click here to go to the Next Page’]<br /> So, using the. //text() node-set won’t select anything in this case:<br /> >>> (“//a[contains(. //text(), ‘Next Page’)]”)()<br /> But using the. to mean the node, works:<br /> >>> (“//a[contains(., ‘Next Page’)]”)()<br /> Variables in XPath expressions¶<br /> XPath allows you to reference variables in your XPath expressions, using<br /> the $somevariable syntax. This is somewhat similar to parameterized<br /> queries or prepared statements in the SQL world where you replace<br /> some arguments in your queries with placeholders like?,<br /> which are then substituted with values passed with the query.<br /> Here’s an example to match an element based on its “id” attribute value,<br /> without hard-coding it (that was shown previously):<br /> >>> # `$val` used in the expression, a `val` argument needs to be passed<br /> >>> (‘//div[@id=$val]/a/text()’, val=’images’)()<br /> Here’s another example, to find the “id” attribute of a </p> <div> tag containing<br /> five <a> children (here we pass the value 5 as an integer):<br /> >>> (‘//div[count(a)=$cnt]/@id’, cnt=5)()<br /> ‘images’<br /> All variable references must have a binding value when calling ()<br /> (otherwise you’ll get a ValueError: XPath error: exception).<br /> This is done by passing as many named arguments as necessary.<br /> parsel, the library powering Scrapy selectors, has more details and examples<br /> on XPath variables.<br /> Removing namespaces¶<br /> When dealing with scraping projects, it is often quite convenient to get rid of<br /> namespaces altogether and just work with element names, to write more<br /> simple/convenient XPaths. You can use the<br /> move_namespaces() method for that.<br /> Let’s show an example that illustrates this with the Python Insider blog atom feed.<br /> First, we open the shell with the url we want to scrape:<br /> $ scrapy shell<br /> This is how the file starts:<br /> <? xml version="1. 0" encoding="UTF-8"? ><br /> <? xml-stylesheet... <feed xmlns_blogger=" xmlns_georss=" xmlns_gd=" xmlns_thr=" xmlns_feedburner=">…<br /> You can see several namespace declarations including a default<br /> “ and another one using the “gd:” prefix for<br /> “.<br /> Once in the shell we can try selecting all <link> objects and see that it<br /> doesn’t work (because the Atom XML namespace is obfuscating those nodes):<br /> >>> (“//link”)<br /> But once we call the move_namespaces() method, all<br /> nodes can be accessed directly by their names:<br /> >>> move_namespaces()<br /> [<Selector xpath='//link' data='<link rel="alternate" type="text/html" h'>,<br /> <Selector xpath='//link' data='<link rel="next" type="application/atom+'>,…<br /> If you wonder why the namespace removal procedure isn’t always called by default<br /> instead of having to call it manually, this is because of two reasons, which, in order<br /> of relevance, are:<br /> Removing namespaces requires to iterate and modify all nodes in the<br /> document, which is a reasonably expensive operation to perform by default<br /> for all documents crawled by Scrapy<br /> There could be some cases where using namespaces is actually required, in<br /> case some element names clash between namespaces. These cases are very rare<br /> though.<br /> Using EXSLT extensions¶<br /> Being built atop lxml, Scrapy selectors support some EXSLT extensions<br /> and come with these pre-registered namespaces to use in XPath expressions:<br /> prefix<br /> namespace<br /> usage<br /> re<br /> regular expressions<br /> set<br /> set manipulation<br /> Regular expressions¶<br /> The test() function, for example, can prove quite useful when XPath’s<br /> starts-with() or contains() are not sufficient.<br /> Example selecting links in list item with a “class” attribute ending with a digit:<br /> >>> doc = “””… </p> <div>… </p> <ul>… </p> <li class="item-0"><a href="">first item</a></li> <p>… </p> <li class="item-1"><a href="">second item</a></li> <p>… </p> <li class="item-inactive"><a href="">third item</a></li> <p>… </p> <li class="item-1"><a href="">fourth item</a></li> <p>… </p> <li class="item-0"><a href="">fifth item</a></li> <p>… </ul> <p>… </p></div> <p>… “””<br /> >>> sel = Selector(text=doc, type=”html”)<br /> >>> (‘//li//@href’)()<br /> >>> (‘//li[re:test(@class, “item-\d$”)]//@href’)()<br /> [”, ”, ”, ”]<br /> C library libxslt doesn’t natively support EXSLT regular<br /> expressions so lxml’s implementation uses hooks to Python’s re module.<br /> Thus, using regexp functions in your XPath expressions may add a small<br /> performance penalty.<br /> Set operations¶<br /> These can be handy for excluding parts of a document tree before<br /> extracting text elements for example.<br /> Example extracting microdata (sample content taken from)<br /> with groups of itemscopes and corresponding itemprops:<br /> >>> doc = “””… </p> <div itemscope itemtype=">… <span itemprop="name">Kenmore White 17″ Microwave</span>… <img src="" alt='Kenmore 17" Microwave' />… </p> <div itemprop="aggregateRating"... itemscope itemtype=">… Rated <span itemprop="ratingValue">3. 5</span>/5… based on <span itemprop="reviewCount">11</span> customer reviews… </div> <p>…… </p> <div itemprop="offers" itemscope itemtype=">… <span itemprop="price">$55. 00</span>… <link itemprop="availability" href=" />In stock… Product description:… <span itemprop="description">0. 7 cubic feet countertop microwave…. Has six preset cooking categories and convenience features like… Add-A-Minute and Child Lock. </span>…… Customer reviews:…… </p> <div itemprop="review" itemscope itemtype=">… <span itemprop="name">Not a happy camper</span> -… by <span itemprop="author">Ellie</span>,… <meta itemprop="datePublished" content="2011-04-01">April 1, 2011… </p> <div itemprop="reviewRating" itemscope itemtype=">… <meta itemprop="worstRating" content = "1">… <span itemprop="ratingValue">1</span>/… <span itemprop="bestRating">5</span>stars… <span itemprop="description">The lamp burned out and now I have to replace… it. </span>… <span itemprop="name">Value purchase</span> -… by <span itemprop="author">Lucas</span>,… <meta itemprop="datePublished" content="2011-03-25">March 25, 2011… <meta itemprop="worstRating" content = "1"/>… <span itemprop="ratingValue">4</span>/… <span itemprop="description">Great microwave for the price. It is small and… fits in my apartment. </div> <p>……… “””<br /> >>> for scope in (‘//div[@itemscope]’):… print(“current scope:”, (‘@itemtype’)())… props = (”’… set:difference(. /descendant::*/@itemprop,…. //*[@itemscope]/*/@itemprop)”’)… print(f” properties: {()}”)… print(“”)<br /> current scope: [”]<br /> properties: [‘name’, ‘aggregateRating’, ‘offers’, ‘description’, ‘review’, ‘review’]<br /> properties: [‘ratingValue’, ‘reviewCount’]<br /> properties: [‘price’, ‘availability’]<br /> properties: [‘name’, ‘author’, ‘datePublished’, ‘reviewRating’, ‘description’]<br /> properties: [‘worstRating’, ‘ratingValue’, ‘bestRating’]<br /> Here we first iterate over itemscope elements, and for each one,<br /> we look for all itemprops elements and exclude those that are themselves<br /> inside another itemscope.<br /> Other XPath extensions¶<br /> Scrapy selectors also provide a sorely missed XPath extension function<br /> has-class that returns True for nodes that have all of the specified<br /> HTML classes.<br /> For the following HTML:</p> <p class="foo bar-baz">First</p> <p class="foo">Second</p> <p class="bar">Third</p> <p>Fourth</p> <p>You can use it like this:<br /> >>> (‘//p[has-class(“foo”)]’)<br /> [<Selector xpath='//p[has-class("foo")]' data=' <p class="foo bar-baz">First</p> <p>‘>,<br /> <Selector xpath='//p[has-class("foo")]' data=' <p class="foo">Second</p> <p>‘>]<br /> >>> (‘//p[has-class(“foo”, “bar-baz”)]’)<br /> [<Selector xpath='//p[has-class("foo", "bar-baz")]' data=' <p class="foo bar-baz">First</p> <p>‘>]<br /> >>> (‘//p[has-class(“foo”, “bar”)]’)<br /> So XPath //p[has-class(“foo”, “bar-baz”)] is roughly equivalent to CSS<br /> Please note, that it is slower in most of the cases,<br /> because it’s a pure-Python function that’s invoked for every node in question<br /> whereas the CSS lookup is translated into XPath and thus runs more efficiently,<br /> so performance-wise its uses are limited to situations that are not easily<br /> described with CSS selectors.<br /> Parsel also simplifies adding your own XPath extensions.<br /> t_xpathfunc(fname, func)[source]¶<br /> Register a custom extension function to use in XPath expressions.<br /> The function func registered under fname identifier will be called<br /> for every matching node, being passed a context parameter as well as<br /> any parameters passed from the corresponding XPath expression.<br /> If func is None, the extension function will be removed.<br /> See more in lxml documentation.<br /> Built-in Selectors reference¶<br /> Selector objects¶<br /> class lector(*args, **kwargs)[source]¶<br /> An instance of Selector is a wrapper over response to select<br /> certain parts of its content.<br /> response is an HtmlResponse or an<br /> XmlResponse object that will be used for selecting<br /> and extracting data.<br /> text is a unicode string or utf-8 encoded text for cases when a<br /> response isn’t available. Using text and response together is<br /> undefined behavior.<br /> type defines the selector type, it can be “html”, “xml”<br /> or None (default).<br /> If type is None, the selector automatically chooses the best type<br /> based on response type (see below), or defaults to “html” in case it<br /> is used together with text.<br /> If type is None and a response is passed, the selector type is<br /> inferred from the response type as follows:<br /> “html” for HtmlResponse type<br /> “xml” for XmlResponse type<br /> “html” for anything else<br /> Otherwise, if type is set, the selector type will be forced and no<br /> detection will occur.<br /> xpath(query, namespaces=None, **kwargs)[source]¶<br /> Find nodes matching the xpath query and return the result as a<br /> SelectorList instance with all elements flattened. List<br /> elements implement Selector interface too.<br /> query is a string containing the XPATH query to apply.<br /> namespaces is an optional prefix: namespace-uri mapping (dict)<br /> for additional prefixes to those registered with register_namespace(prefix, uri).<br /> Contrary to register_namespace(), these prefixes are not<br /> saved for future calls.<br /> Any additional named arguments can be used to pass values for XPath<br /> variables in the XPath expression, e. :<br /> (‘//a[href=$url]’, url=”)<br /> For convenience, this method can be called as ()<br /> css(query)[source]¶<br /> Apply the given CSS selector and return a SelectorList instance.<br /> query is a string containing the CSS selector to apply.<br /> In the background, CSS queries are translated into XPath queries using<br /> cssselect library and run () method.<br /> get()[source]¶<br /> Serialize and return the matched nodes in a single unicode string.<br /> Percent encoded content is unquoted.<br /> See also: extract() and extract_first()<br /> attrib¶<br /> Return the attributes dictionary for underlying element.<br /> re(regex, replace_entities=True)[source]¶<br /> Apply the given regex and return a list of unicode strings with the<br /> matches.<br /> regex can be either a compiled regular expression or a string which<br /> will be compiled to a regular expression using mpile(regex).<br /> By default, character entity references are replaced by their<br /> corresponding character (except for & and <).<br /> Passing replace_entities as False switches off these<br /> replacements.<br /> re_first(regex, default=None, replace_entities=True)[source]¶<br /> Apply the given regex and return the first unicode string which<br /> matches. If there is no match, return the default value (None if<br /> the argument is not provided).<br /> register_namespace(prefix, uri)[source]¶<br /> Register the given namespace to be used in this Selector.<br /> Without registering namespaces you can’t select or extract data from<br /> non-standard namespaces. See Selector examples on XML response.<br /> remove_namespaces()[source]¶<br /> Remove all namespaces, allowing to traverse the document using<br /> namespace-less xpaths. See Removing namespaces.<br /> __bool__()[source]¶<br /> Return True if there is any real content selected or False<br /> otherwise. In other words, the boolean value of a Selector is<br /> given by the contents it selects.<br /> getall()[source]¶<br /> Serialize and return the matched node in a 1-element list of unicode strings.<br /> This method is added to Selector for consistency; it is more useful<br /> with SelectorList. See also: extract() and extract_first()<br /> SelectorList objects¶<br /> class lectorList(iterable=(), /)[source]¶<br /> The SelectorList class is a subclass of the builtin list<br /> class, which provides a few additional methods.<br /> xpath(xpath, namespaces=None, **kwargs)[source]¶<br /> Call the () method for each element in this list and return<br /> their results flattened as another SelectorList.<br /> query is the same argument as the one in ()<br /> Call the () method for each element is this list and return<br /> their results flattened, as a list of unicode strings.<br /> get(default=None)[source]¶<br /> Return the result of () for the first element in this list.<br /> If the list is empty, return the default value.<br /> corresponding character (except for & and <.<br /> Call the () method for the first element in this list and<br /> return the result in an unicode string. If the list is empty or the<br /> regex doesn’t match anything, return the default value (None if<br /> Return the attributes dictionary for the first element.<br /> If the list is empty, return an empty dict.<br /> Examples¶<br /> Selector examples on HTML response¶<br /> Here are some Selector examples to illustrate several concepts.<br /> In all cases, we assume there is already a Selector instantiated with<br /> a HtmlResponse object like this:<br /> sel = Selector(html_response)<br /> Select all </p> <h1> elements from an HTML response body, returning a list of<br /> Selector objects (i. a SelectorList object):<br /> Extract the text of all </p> <h1> elements from an HTML response body,<br /> returning a list of strings:<br /> (“//h1”)() # this includes the h1 tag<br /> (“//h1/text()”)() # this excludes the h1 tag<br /> Iterate over all </p> <p> tags and print their class attribute:<br /> for node in (“//p”):<br /> print([‘class’])<br /> Selector examples on XML response¶<br /> Here are some examples to illustrate concepts for Selector objects<br /> instantiated with an XmlResponse object:<br /> sel = Selector(xml_response)<br /> Select all <product> elements from an XML response body, returning a list<br /> of Selector objects (i. a SelectorList object):<br /> Extract all prices from a Google Base XML feed which requires registering<br /> a namespace:<br /> gister_namespace(“g”, “)<br /> (“//g:price”)()<br /> <img src="https://bilderupload.net/wp-content/uploads/2021/12/images-17.jpeg" alt="Scrapy Tutorial — Scrapy 2.5.1 documentation" title="Scrapy Tutorial — Scrapy 2.5.1 documentation" /></p> <h2>Scrapy Tutorial — Scrapy 2.5.1 documentation</h2> <p>In this tutorial, we’ll assume that Scrapy is already installed on your system.<br /> If that’s not the case, see Installation guide.<br /> We are going to scrape, a website<br /> that lists quotes from famous authors.<br /> This tutorial will walk you through these tasks:<br /> Creating a new Scrapy project<br /> Writing a spider to crawl a site and extract data<br /> Exporting the scraped data using the command line<br /> Changing spider to recursively follow links<br /> Using spider arguments<br /> Scrapy is written in Python. If you’re new to the language you might want to<br /> start by getting an idea of what the language is like, to get the most out of<br /> Scrapy.<br /> If you’re already familiar with other languages, and want to learn Python quickly, the Python Tutorial is a good resource.<br /> If you’re new to programming and want to start with Python, the following books<br /> may be useful to you:<br /> Automate the Boring Stuff With Python<br /> How To Think Like a Computer Scientist<br /> Learn Python 3 The Hard Way<br /> You can also take a look at this list of Python resources for non-programmers,<br /> as well as the suggested resources in the learnpython-subreddit.<br /> Creating a project¶<br /> Before you start scraping, you will have to set up a new Scrapy project. Enter a<br /> directory where you’d like to store your code and run:<br /> scrapy startproject tutorial<br /> This will create a tutorial directory with the following contents:<br /> tutorial/<br /> # deploy configuration file<br /> tutorial/ # project’s Python module, you’ll import your code from here<br /> # project items definition file<br /> # project middlewares file<br /> # project pipelines file<br /> # project settings file<br /> spiders/ # a directory where you’ll later put your spiders<br /> Our first Spider¶<br /> Spiders are classes that you define and that Scrapy uses to scrape information<br /> from a website (or a group of websites). They must subclass<br /> Spider and define the initial requests to make,<br /> optionally how to follow links in the pages, and how to parse the downloaded<br /> page content to extract data.<br /> This is the code for our first Spider. Save it in a file named<br /> under the tutorial/spiders directory in your project:<br /> import scrapy<br /> class QuotesSpider():<br /> name = “quotes”<br /> def start_requests(self):<br /> urls = [<br /> ”,<br /> ”, ]<br /> for url in urls:<br /> yield quest(url=url, )<br /> def parse(self, response):<br /> page = (“/”)[-2]<br /> filename = f’quotes-{page}’<br /> with open(filename, ‘wb’) as f:<br /> ()<br /> (f’Saved file {filename}’)<br /> As you can see, our Spider subclasses<br /> and defines some attributes and methods:<br /> name: identifies the Spider. It must be<br /> unique within a project, that is, you can’t set the same name for different<br /> Spiders.<br /> start_requests(): must return an iterable of<br /> Requests (you can return a list of requests or write a generator function)<br /> which the Spider will begin to crawl from. Subsequent requests will be<br /> generated successively from these initial requests.<br /> parse(): a method that will be called to handle<br /> the response downloaded for each of the requests made. The response parameter<br /> is an instance of TextResponse that holds<br /> the page content and has further helpful methods to handle it.<br /> The parse() method usually parses the response, extracting<br /> the scraped data as dicts and also finding new URLs to<br /> follow and creating new requests (Request) from them.<br /> How to run our spider¶<br /> To put our spider to work, go to the project’s top level directory and run:<br /> This command runs the spider with name quotes that we’ve just added, that<br /> will send some requests for the domain. You will get an output<br /> similar to this:… (omitted for brevity)<br /> 2016-12-16 21:24:05 [] INFO: Spider opened<br /> 2016-12-16 21:24:05 [scrapy. extensions. logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)<br /> 2016-12-16 21:24:05 [] DEBUG: Telnet console listening on 127. 0. 1:6023<br /> 2016-12-16 21:24:05 [] DEBUG: Crawled (404) <GET > (referer: None)<br /> 2016-12-16 21:24:05 [] DEBUG: Crawled (200) <GET > (referer: None)<br /> 2016-12-16 21:24:05 [quotes] DEBUG: Saved file<br /> 2016-12-16 21:24:05 [] INFO: Closing spider (finished)…<br /> Now, check the files in the current directory. You should notice that two new<br /> files have been created: and, with the content<br /> for the respective URLs, as our parse method instructs.<br /> Note<br /> If you are wondering why we haven’t parsed the HTML yet, hold<br /> on, we will cover that soon.<br /> What just happened under the hood? ¶<br /> Scrapy schedules the quest objects<br /> returned by the start_requests method of the Spider. Upon receiving a<br /> response for each one, it instantiates Response objects<br /> and calls the callback method associated with the request (in this case, the<br /> parse method) passing the response as argument.<br /> A shortcut to the start_requests method¶<br /> Instead of implementing a start_requests() method<br /> that generates quest objects from URLs,<br /> you can just define a start_urls class attribute<br /> with a list of URLs. This list will then be used by the default implementation<br /> of start_requests() to create the initial requests<br /> for your spider:<br /> start_urls = [<br /> The parse() method will be called to handle each<br /> of the requests for those URLs, even though we haven’t explicitly told Scrapy<br /> to do so. This happens because parse() is Scrapy’s<br /> default callback method, which is called for requests without an explicitly<br /> assigned callback.<br /> Storing the scraped data¶<br /> The simplest way to store the scraped data is by using Feed exports, with the following command:<br /> scrapy crawl quotes -O<br /> That will generate a file containing all scraped items,<br /> serialized in JSON.<br /> The -O command-line switch overwrites any existing file; use -o instead<br /> to append new content to any existing file. However, appending to a JSON file<br /> makes the file contents invalid JSON. When appending to a file, consider<br /> using a different serialization format, such as JSON Lines:<br /> scrapy crawl quotes -o<br /> The JSON Lines format is useful because it’s stream-like, you can easily<br /> append new records to it. It doesn’t have the same problem of JSON when you run<br /> twice. Also, as each record is a separate line, you can process big files<br /> without having to fit everything in memory, there are tools like JQ to help<br /> doing that at the command-line.<br /> In small projects (like the one in this tutorial), that should be enough.<br /> However, if you want to perform more complex things with the scraped items, you<br /> can write an Item Pipeline. A placeholder file<br /> for Item Pipelines has been set up for you when the project is created, in<br /> tutorial/ Though you don’t need to implement any item<br /> pipelines if you just want to store the scraped items.<br /> Following links¶<br /> Let’s say, instead of just scraping the stuff from the first two pages<br /> from, you want quotes from all the pages in the website.<br /> Now that you know how to extract data from pages, let’s see how to follow links<br /> from them.<br /> First thing is to extract the link to the page we want to follow. Examining<br /> our page, we can see there is a link to the next page with the following<br /> markup:</p> <ul class="pager"> <li class="next"> <a href="/page/2/">Next <span aria-hidden="true">→</span></a> </li> </ul> <p>We can try extracting it in the shell:<br /> >>> (‘ a’)()<br /> ‘<a href="/page/2/">Next <span aria-hidden="true">→</span></a>‘<br /> This gets the anchor element, but we want the attribute href. For that,<br /> Scrapy supports a CSS extension that lets you select the attribute contents,<br /> like this:<br /> >>> (‘ a::attr(href)’)()<br /> ‘/page/2/’<br /> There is also an attrib property available<br /> (see Selecting element attributes for more):<br /> >>> (‘ a’)[‘href’]<br /> Let’s see now our spider modified to recursively follow the link to the next<br /> page, extracting data from it:<br /> for quote in (”):<br /> yield {<br /> ‘text’: (”)(),<br /> ‘author’: (”)(),<br /> ‘tags’: (‘ ‘)(), }<br /> next_page = (‘ a::attr(href)’)()<br /> if next_page is not None:<br /> next_page = response. urljoin(next_page)<br /> yield quest(next_page, )<br /> Now, after extracting the data, the parse() method looks for the link to<br /> the next page, builds a full absolute URL using the<br /> urljoin() method (since the links can be<br /> relative) and yields a new request to the next page, registering itself as<br /> callback to handle the data extraction for the next page and to keep the<br /> crawling going through all the pages.<br /> What you see here is Scrapy’s mechanism of following links: when you yield<br /> a Request in a callback method, Scrapy will schedule that request to be sent<br /> and register a callback method to be executed when that request finishes.<br /> Using this, you can build complex crawlers that follow links according to rules<br /> you define, and extract different kinds of data depending on the page it’s<br /> visiting.<br /> In our example, it creates a sort of loop, following all the links to the next page<br /> until it doesn’t find one – handy for crawling blogs, forums and other sites with<br /> pagination.<br /> A shortcut for creating Requests¶<br /> As a shortcut for creating Request objects you can use<br /> ‘author’: (‘span small::text’)(),<br /> yield (next_page, )<br /> Unlike quest, supports relative URLs directly – no<br /> need to call urljoin. Note that just returns a Request<br /> instance; you still have to yield this Request.<br /> You can also pass a selector to instead of a string;<br /> this selector should extract necessary attributes:<br /> for href in (‘ a::attr(href)’):<br /> yield (href, )<br /> For <a> elements there is a shortcut: uses their href<br /> attribute automatically. So the code can be shortened further:<br /> for a in (‘ a’):<br /> yield (a, )<br /> To create multiple requests from an iterable, you can use<br /> llow_all instead:<br /> anchors = (‘ a’)<br /> yield from llow_all(anchors, )<br /> or, shortening it further:<br /> yield from llow_all(css=’ a’, )<br /> More examples and patterns¶<br /> Here is another spider that illustrates callbacks and following links,<br /> this time for scraping author information:<br /> class AuthorSpider():<br /> name = ‘author’<br /> start_urls = [”]<br /> author_page_links = (‘ + a’)<br /> yield from llow_all(author_page_links, rse_author)<br /> pagination_links = (‘ a’)<br /> yield from llow_all(pagination_links, )<br /> def parse_author(self, response):<br /> def extract_with_css(query):<br /> return (query)(default=”)()<br /> ‘name’: extract_with_css(”),<br /> ‘birthdate’: extract_with_css(”),<br /> ‘bio’: extract_with_css(”), }<br /> This spider will start from the main page, it will follow all the links to the<br /> authors pages calling the parse_author callback for each of them, and also<br /> the pagination links with the parse callback as we saw before.<br /> Here we’re passing callbacks to<br /> llow_all as positional<br /> arguments to make the code shorter; it also works for<br /> Request.<br /> The parse_author callback defines a helper function to extract and cleanup the<br /> data from a CSS query and yields the Python dict with the author data.<br /> Another interesting thing this spider demonstrates is that, even if there are<br /> many quotes from the same author, we don’t need to worry about visiting the<br /> same author page multiple times. By default, Scrapy filters out duplicated<br /> requests to URLs already visited, avoiding the problem of hitting servers too<br /> much because of a programming mistake. This can be configured by the setting<br /> DUPEFILTER_CLASS.<br /> Hopefully by now you have a good understanding of how to use the mechanism<br /> of following links and callbacks with Scrapy.<br /> As yet another example spider that leverages the mechanism of following links,<br /> check out the CrawlSpider class for a generic<br /> spider that implements a small rules engine that you can use to write your<br /> crawlers on top of it.<br /> Also, a common pattern is to build an item with data from more than one page,<br /> using a trick to pass additional data to the callbacks.<br /> Using spider arguments¶<br /> You can provide command line arguments to your spiders by using the -a<br /> option when running them:<br /> scrapy crawl quotes -O -a tag=humor<br /> These arguments are passed to the Spider’s __init__ method and become<br /> spider attributes by default.<br /> In this example, the value provided for the tag argument will be available<br /> via You can use this to make your spider fetch only quotes<br /> with a specific tag, building the URL based on the argument:<br /> url = ”<br /> tag = getattr(self, ‘tag’, None)<br /> if tag is not None:<br /> url = url + ‘tag/’ + tag<br /> yield quest(url, )<br /> ‘author’: (”)(), }<br /> If you pass the tag=humor argument to this spider, you’ll notice that it<br /> will only visit URLs from the humor tag, such as<br /> You can learn more about handling spider arguments here.<br /> Next steps¶<br /> This tutorial covered only the basics of Scrapy, but there’s a lot of other<br /> features not mentioned here. Check the What else? section in<br /> Scrapy at a glance chapter for a quick overview of the most important ones.<br /> You can continue from the section Basic concepts to know more about the<br /> command-line tool, spiders, selectors and other things the tutorial hasn’t covered like<br /> modeling the scraped data. If you prefer to play with an example project, check<br /> the Examples section.<br /> <img src="https://bilderupload.net/wp-content/uploads/2021/12/images-18.jpeg" alt="Requests and Responses — Scrapy 2.5.1 documentation" title="Requests and Responses — Scrapy 2.5.1 documentation" /></p> <h2>Requests and Responses — Scrapy 2.5.1 documentation</h2> <p>Scrapy uses Request and Response objects for crawling web<br /> sites.<br /> Typically, Request objects are generated in the spiders and pass<br /> across the system until they reach the Downloader, which executes the request<br /> and returns a Response object which travels back to the spider that<br /> issued the request.<br /> Both Request and Response classes have subclasses which add<br /> functionality not required in the base classes. These are described<br /> below in Request subclasses and<br /> Response subclasses.<br /> Request objects¶<br /> class (*args, **kwargs)[source]¶<br /> A Request object represents an HTTP request, which is usually<br /> generated in the Spider and executed by the Downloader, and thus generating<br /> a Response.<br /> Parameters<br /> url (str) – the URL of this request<br /> If the URL is invalid, a ValueError exception is raised.<br /> callback () – the function that will be called with the response of this<br /> request (once it’s downloaded) as its first parameter. For more information<br /> see Passing additional data to callback functions below.<br /> If a Request doesn’t specify a callback, the spider’s<br /> parse() method will be used.<br /> Note that if exceptions are raised during processing, errback is called instead.<br /> method (str) – the HTTP method of this request. Defaults to ‘GET’.<br /> meta (dict) – the initial values for the attribute. If<br /> given, the dict passed in this parameter will be shallow copied.<br /> body (bytes or str) – the request body. If a string is passed, then it’s encoded as<br /> bytes using the encoding passed (which defaults to utf-8). If<br /> body is not given, an empty bytes object is stored. Regardless of the<br /> type of this argument, the final value stored will be a bytes object<br /> (never a string or None).<br /> headers (dict) – the headers of this request. The dict values can be strings<br /> (for single valued headers) or lists (for multi-valued headers). If<br /> None is passed as value, the HTTP header will not be sent at all.<br /> Caution<br /> Cookies set via the Cookie header are not considered by the<br /> CookiesMiddleware. If you need to set cookies for a request, use the<br /> okies parameter. This is a known<br /> current limitation that is being worked on.<br /> cookies (dict or list) – the request cookies. These can be sent in two forms.<br /> Using a dict:<br /> request_with_cookies = Request(url=”,<br /> cookies={‘currency’: ‘USD’, ‘country’: ‘UY’})<br /> Using a list of dicts:<br /> cookies=[{‘name’: ‘currency’,<br /> ‘value’: ‘USD’,<br /> ‘domain’: ”,<br /> ‘path’: ‘/currency’}])<br /> The latter form allows for customizing the domain and path<br /> attributes of the cookie. This is only useful if the cookies are saved<br /> for later requests.<br /> When some site returns cookies (in a response) those are stored in the<br /> cookies for that domain and will be sent again in future requests.<br /> That’s the typical behaviour of any regular web browser.<br /> To create a request that does not send stored cookies and does not<br /> store received cookies, set the dont_merge_cookies key to True<br /> in<br /> Example of a request that sends manually-defined cookies and ignores<br /> cookie storage:<br /> Request(<br /> url=”,<br /> cookies={‘currency’: ‘USD’, ‘country’: ‘UY’},<br /> meta={‘dont_merge_cookies’: True}, )<br /> For more info see CookiesMiddleware.<br /> encoding (str) – the encoding of this request (defaults to ‘utf-8’).<br /> This encoding will be used to percent-encode the URL and to convert the<br /> body to bytes (if given as a string).<br /> priority (int) – the priority of this request (defaults to 0).<br /> The priority is used by the scheduler to define the order used to process<br /> requests. Requests with a higher priority value will execute earlier.<br /> Negative values are allowed in order to indicate relatively low-priority.<br /> dont_filter (bool) – indicates that this request should not be filtered by<br /> the scheduler. This is used when you want to perform an identical<br /> request multiple times, to ignore the duplicates filter. Use it with<br /> care, or you will get into crawling loops. Default to False.<br /> errback () – a function that will be called if any exception was<br /> raised while processing the request. This includes pages that failed<br /> with 404 HTTP errors and such. It receives a<br /> Failure as first parameter.<br /> For more information,<br /> see Using errbacks to catch exceptions in request processing below.<br /> Changed in version 2. 0: The callback parameter is no longer required when the errback<br /> parameter is specified.<br /> flags (list) – Flags sent to the request, can be used for logging or similar purposes.<br /> cb_kwargs (dict) – A dict with arbitrary data that will be passed as keyword arguments to the Request’s callback.<br /> url¶<br /> A string containing the URL of this request. Keep in mind that this<br /> attribute contains the escaped URL, so it can differ from the URL passed in<br /> the __init__ method.<br /> This attribute is read-only. To change the URL of a Request use<br /> replace().<br /> method¶<br /> A string representing the HTTP method in the request. This is guaranteed to<br /> be uppercase. Example: “GET”, “POST”, “PUT”, etc<br /> A dictionary-like object which contains the request headers.<br /> body¶<br /> The request body as bytes.<br /> This attribute is read-only. To change the body of a Request use<br /> meta¶<br /> A dict that contains arbitrary metadata for this request. This dict is<br /> empty for new Requests, and is usually populated by different Scrapy<br /> components (extensions, middlewares, etc). So the data contained in this<br /> dict depends on the extensions you have enabled.<br /> See special keys for a list of special meta keys<br /> recognized by Scrapy.<br /> This dict is shallow copied when the request is<br /> cloned using the copy() or replace() methods, and can also be<br /> accessed, in your spider, from the attribute.<br /> cb_kwargs¶<br /> A dictionary that contains arbitrary metadata for this request. Its contents<br /> will be passed to the Request’s callback as keyword arguments. It is empty<br /> for new Requests, which means by default callbacks only get a Response<br /> object as argument.<br /> accessed, in your spider, from the response. cb_kwargs attribute.<br /> In case of a failure to process the request, this dict can be accessed as<br /> quest. cb_kwargs in the request’s errback. For more information,<br /> see Accessing additional data in errback functions.<br /> copy()[source]¶<br /> Return a new Request which is a copy of this Request. See also:<br /> Passing additional data to callback functions.<br /> replace([url, method, headers, body, cookies, meta, flags, encoding, priority, dont_filter, callback, errback, cb_kwargs])[source]¶<br /> Return a Request object with the same members, except for those members<br /> given new values by whichever keyword arguments are specified. The<br /> Request. cb_kwargs and attributes are shallow<br /> copied by default (unless new values are given as arguments). See also<br /> classmethod from_curl(curl_command, ignore_unknown_options=True, **kwargs)[source]¶<br /> Create a Request object from a string containing a cURL command. It populates the HTTP method, the<br /> URL, the headers, the cookies and the body. It accepts the same<br /> arguments as the Request class, taking preference and<br /> overriding the values of the same arguments contained in the cURL<br /> command.<br /> Unrecognized options are ignored by default. To raise an error when<br /> finding unknown options call this method by passing<br /> ignore_unknown_options=False.<br /> To translate a cURL command into a Scrapy request,<br /> you may use curl2scrapy.<br /> Passing additional data to callback functions¶<br /> The callback of a request is a function that will be called when the response<br /> of that request is downloaded. The callback function will be called with the<br /> downloaded Response object as its first argument.<br /> Example:<br /> def parse_page1(self, response):<br /> return quest(“,<br /> rse_page2)<br /> def parse_page2(self, response):<br /> # this would log (“Visited%s”, )<br /> In some cases you may be interested in passing arguments to those callback<br /> functions so you can receive the arguments later, in the second callback.<br /> The following example shows how to achieve this by using the<br /> Request. cb_kwargs attribute:<br /> def parse(self, response):<br /> request = quest(”,<br /> rse_page2,<br /> cb_kwargs=dict())<br /> request. cb_kwargs[‘foo’] = ‘bar’ # add more arguments for the callback<br /> yield request<br /> def parse_page2(self, response, main_url, foo):<br /> yield dict(<br /> main_url=main_url,,<br /> foo=foo, )<br /> Request. cb_kwargs was introduced in version 1. 7.<br /> Prior to that, using was recommended for passing<br /> information around callbacks. After 1. 7, Request. cb_kwargs<br /> became the preferred way for handling user information, leaving<br /> for communication with components like middlewares and extensions.<br /> Using errbacks to catch exceptions in request processing¶<br /> The errback of a request is a function that will be called when an exception<br /> is raise while processing it.<br /> It receives a Failure as first parameter and can<br /> be used to track connection establishment timeouts, DNS errors etc.<br /> Here’s an example spider logging all errors and catching some specific<br /> errors if needed:<br /> import scrapy<br /> from tperror import HttpError<br /> from import DNSLookupError<br /> from import TimeoutError, TCPTimedOutError<br /> class ErrbackSpider():<br /> name = “errback_example”<br /> start_urls = [<br /> “, # HTTP 200 expected<br /> “, # Not found error<br /> “, # server issue<br /> “, # non-responding host, timeout expected<br /> “, # DNS error expected]<br /> def start_requests(self):<br /> for u in art_urls:<br /> yield quest(u, rse_bin,<br /> rback_bin,<br /> dont_filter=True)<br /> def parse_bin(self, response):<br /> (‘Got successful response from {}'())<br /> # do something useful here…<br /> def errback_bin(self, failure):<br /> # log all failures<br /> (repr(failure))<br /> # in case you want to do something special for some errors,<br /> # you may need the failure’s type:<br /> if (HttpError):<br /> # these exceptions come from HttpError spider middleware<br /> # you can get the non-200 response<br /> response =<br /> (‘HttpError on%s’, )<br /> elif (DNSLookupError):<br /> # this is the original request<br /> request = quest<br /> (‘DNSLookupError on%s’, )<br /> elif (TimeoutError, TCPTimedOutError):<br /> (‘TimeoutError on%s’, )<br /> Accessing additional data in errback functions¶<br /> In case of a failure to process the request, you may be interested in<br /> accessing arguments to the callback functions so you can process further<br /> based on the arguments in the errback. The following example shows how to<br /> achieve this by using quest. cb_kwargs:<br /> rback_page2,<br /> def parse_page2(self, response, main_url):<br /> pass<br /> def errback_page2(self, failure):<br /> quest. cb_kwargs[‘main_url’], )<br /> special keys¶<br /> The attribute can contain any arbitrary data, but there<br /> are some special keys recognized by Scrapy and its built-in extensions.<br /> Those are:<br /> bindaddress<br /> cookiejar<br /> dont_cache<br /> dont_merge_cookies<br /> dont_obey_robotstxt<br /> dont_redirect<br /> dont_retry<br /> download_fail_on_dataloss<br /> download_latency<br /> download_maxsize<br /> download_timeout<br /> ftp_password (See FTP_PASSWORD for more info)<br /> ftp_user (See FTP_USER for more info)<br /> handle_tatus_all<br /> handle_tatus_list<br /> max_retry_times<br /> proxy<br /> redirect_reasons<br /> redirect_urls<br /> referrer_policy<br /> bindaddress¶<br /> The IP of the outgoing IP address to use for the performing the request.<br /> download_timeout¶<br /> The amount of time (in secs) that the downloader will wait before timing out.<br /> See also: DOWNLOAD_TIMEOUT.<br /> download_latency¶<br /> The amount of time spent to fetch the response, since the request has been<br /> started, i. e. HTTP message sent over the network. This meta key only becomes<br /> available when the response has been downloaded. While most other meta keys are<br /> used to control Scrapy behavior, this one is supposed to be read-only.<br /> download_fail_on_dataloss¶<br /> Whether or not to fail on broken responses. See:<br /> DOWNLOAD_FAIL_ON_DATALOSS.<br /> max_retry_times¶<br /> The meta key is used set retry times per request. When initialized, the<br /> max_retry_times meta key takes higher precedence over the<br /> RETRY_TIMES setting.<br /> Stopping the download of a Response¶<br /> Raising a StopDownload exception from a handler for the<br /> bytes_received or headers_received<br /> signals will stop the download of a given response. See the following example:<br /> class StopSpider():<br /> name = “stop”<br /> start_urls = [“]<br /> @classmethod<br /> def from_crawler(cls, crawler):<br /> spider = super(). from_crawler(crawler)<br /> nnect(spider. on_bytes_received, tes_received)<br /> return spider<br /> # ‘last_chars’ show that the full response was not downloaded<br /> yield {“len”: len(), “last_chars”: [-40:]}<br /> def on_bytes_received(self, data, request, spider):<br /> raise opDownload(fail=False)<br /> which produces the following output:<br /> 2020-05-19 17:26:12 [] INFO: Spider opened<br /> 2020-05-19 17:26:12 [scrapy. extensions. logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)<br /> 2020-05-19 17:26:13 [] DEBUG: Download stopped for <GET > from signal handler StopSpider. on_bytes_received<br /> 2020-05-19 17:26:13 [] DEBUG: Crawled (200) <GET > (referer: None) [‘download_stopped’]<br /> 2020-05-19 17:26:13 [] DEBUG: Scraped from <200 ><br /> {‘len’: 279, ‘last_chars’: ‘dth, initial-scale=1. 0″>\n \n <title>Scr’}<br /> 2020-05-19 17:26:13 [] INFO: Closing spider (finished)<br /> By default, resulting responses are handled by their corresponding errbacks. To<br /> call their callback instead, like in this example, pass fail=False to the<br /> StopDownload exception.<br /> Request subclasses¶<br /> Here is the list of built-in Request subclasses. You can also subclass<br /> it to implement your own custom functionality.<br /> FormRequest objects¶<br /> The FormRequest class extends the base Request with functionality for<br /> dealing with HTML forms. It uses forms to pre-populate form<br /> fields with form data from Response objects.<br /> class (url[, formdata,… ])[source]¶<br /> The FormRequest class adds a new keyword parameter to the __init__ method. The<br /> remaining arguments are the same as for the Request class and are<br /> not documented here.<br /> formdata (dict or) – is a dictionary (or iterable of (key, value) tuples)<br /> containing HTML Form data which will be url-encoded and assigned to the<br /> body of the request.<br /> The FormRequest objects support the following class method in<br /> addition to the standard Request methods:<br /> classmethod from_response(response[, formname=None, formid=None, formnumber=0, formdata=None, formxpath=None, formcss=None, clickdata=None, dont_click=False,… ])[source]¶<br /> Returns a new FormRequest object with its form field values<br /> pre-populated with those found in the HTML </p> <form> element contained<br /> in the given response. For an example see<br /> Using om_response() to simulate a user login.<br /> The policy is to automatically simulate a click, by default, on any form<br /> control that looks clickable, like a <input type="submit">. Even<br /> though this is quite convenient, and often the desired behaviour,<br /> sometimes it can cause problems which could be hard to debug. For<br /> example, when working with forms that are filled and/or submitted using<br /> javascript, the default from_response() behaviour may not be the<br /> most appropriate. To disable this behaviour you can set the<br /> dont_click argument to True. Also, if you want to change the<br /> control clicked (instead of disabling it) you can also use the<br /> clickdata argument.<br /> Using this method with select elements which have leading<br /> or trailing whitespace in the option values will not work due to a<br /> bug in lxml, which should be fixed in lxml 3. 8 and above.<br /> response (Response object) – the response containing a HTML form which will be used<br /> to pre-populate the form fields<br /> formname (str) – if given, the form with name attribute set to this value will be used.<br /> formid (str) – if given, the form with id attribute set to this value will be used.<br /> formxpath (str) – if given, the first form that matches the xpath will be used.<br /> formcss (str) – if given, the first form that matches the css selector will be used.<br /> formnumber (int) – the number of form to use, when the response contains<br /> multiple forms. The first one (and also the default) is 0.<br /> formdata (dict) – fields to override in the form data. If a field was<br /> already present in the response </p> <form> element, its value is<br /> overridden by the one passed in this parameter. If a value passed in<br /> this parameter is None, the field will not be included in the<br /> request, even if it was present in the response </p> <form> element.<br /> clickdata (dict) – attributes to lookup the control clicked. If it’s not<br /> given, the form data will be submitted simulating a click on the<br /> first clickable element. In addition to html attributes, the control<br /> can be identified by its zero-based index relative to other<br /> submittable inputs inside the form, via the nr attribute.<br /> dont_click (bool) – If True, the form data will be submitted without<br /> clicking in any element.<br /> The other parameters of this class method are passed directly to the<br /> FormRequest __init__ method.<br /> Request usage examples¶<br /> Using FormRequest to send data via HTTP POST¶<br /> If you want to simulate a HTML Form POST in your spider and send a couple of<br /> key-value fields, you can return a FormRequest object (from your<br /> spider) like this:<br /> return [FormRequest(url=”,<br /> formdata={‘name’: ‘John Doe’, ‘age’: ’27’},<br /> ter_post)]<br /> Using om_response() to simulate a user login¶<br /> It is usual for web sites to provide pre-populated form fields through <input type="hidden"> elements, such as session related data or authentication<br /> tokens (for login pages). When scraping, you’ll want these fields to be<br /> automatically pre-populated and only override a couple of them, such as the<br /> user name and password. You can use the om_response()<br /> method for this job. Here’s an example spider which uses it:<br /> def authentication_failed(response):<br /> # TODO: Check the contents of the response and return True if it failed<br /> # or False if it succeeded.<br /> class LoginSpider():<br /> name = ”<br /> start_urls = [”]<br /> return om_response(<br /> response,<br /> formdata={‘username’: ‘john’, ‘password’: ‘secret’},<br /> ter_login)<br /> def after_login(self, response):<br /> if authentication_failed(response):<br /> (“Login failed”)<br /> return<br /> # continue scraping with authenticated session…<br /> JsonRequest¶<br /> The JsonRequest class extends the base Request class with functionality for<br /> dealing with JSON requests.<br /> class (url[,… data, dumps_kwargs])[source]¶<br /> The JsonRequest class adds two new keyword parameters to the __init__ method. The<br /> Using the JsonRequest will set the Content-Type header to application/json<br /> and Accept header to application/json, text/javascript, */*; q=0. 01<br /> data (object) – is any JSON serializable object that needs to be JSON encoded and assigned to body.<br /> if argument is provided this parameter will be ignored.<br /> if argument is not provided and data argument is provided will be<br /> set to ‘POST’ automatically.<br /> dumps_kwargs (dict) – Parameters that will be passed to underlying () method which is used to serialize<br /> data into JSON format.<br /> JsonRequest usage example¶<br /> Sending a JSON POST request with a JSON payload:<br /> data = {<br /> ‘name1’: ‘value1’,<br /> ‘name2’: ‘value2’, }<br /> yield JsonRequest(url=”, data=data)<br /> Response objects¶<br /> A Response object represents an HTTP response, which is usually<br /> downloaded (by the Downloader) and fed to the Spiders for processing.<br /> url (str) – the URL of this response<br /> status (int) – the HTTP status of the response. Defaults to 200.<br /> headers (dict) – the headers of this response. The dict values can be strings<br /> (for single valued headers) or lists (for multi-valued headers).<br /> body (bytes) – the response body. To access the decoded text as a string, use<br /> from an encoding-aware<br /> Response subclass,<br /> such as TextResponse.<br /> flags (list) – is a list containing the initial values for the<br /> attribute. If given, the list will be shallow<br /> copied.<br /> request () – the initial value of the quest attribute.<br /> This represents the Request that generated this response.<br /> certificate () – an object representing the server’s SSL certificate.<br /> ip_address (ipaddress. IPv4Address or ipaddress. IPv6Address) – The IP address of the server from which the Response originated.<br /> protocol (str) – The protocol that was used to download the response.<br /> For instance: “HTTP/1. 0”, “HTTP/1. 1”, “h2”<br /> New in version 2. 0. 0: The certificate parameter.<br /> New in version 2. 1. 0: The ip_address parameter.<br /> New in version 2. 5. 0: The protocol parameter.<br /> A string containing the URL of the response.<br /> This attribute is read-only. To change the URL of a Response use<br /> status¶<br /> An integer representing the HTTP status of the response. Example: 200,<br /> 404.<br /> A dictionary-like object which contains the response headers. Values can<br /> be accessed using get() to return the first header value with the<br /> specified name or getlist() to return all header values with the<br /> specified name. For example, this call will give you all cookies in the<br /> headers:<br /> tlist(‘Set-Cookie’)<br /> The response body as bytes.<br /> If you want the body as a string, use (only<br /> available in TextResponse and subclasses).<br /> This attribute is read-only. To change the body of a Response use<br /> request¶<br /> The Request object that generated this response. This attribute is<br /> assigned in the Scrapy engine, after the response and the request have passed<br /> through all Downloader Middlewares.<br /> In particular, this means that:<br /> HTTP redirections will cause the original request (to the URL before<br /> redirection) to be assigned to the redirected response (with the final<br /> URL after redirection).<br /> doesn’t always equal<br /> This attribute is only available in the spider code, and in the<br /> Spider Middlewares, but not in<br /> Downloader Middlewares (although you have the Request available there by<br /> other means) and handlers of the response_downloaded signal.<br /> A shortcut to the attribute of the<br /> quest object (i. ).<br /> Unlike the quest attribute, the<br /> attribute is propagated along redirects and retries, so you will get<br /> the original sent from your spider.<br /> See also<br /> attribute<br /> New in version 2. 0.<br /> A shortcut to the Request. cb_kwargs attribute of the<br /> quest object (i. quest. cb_kwargs).<br /> Response. cb_kwargs attribute is propagated along redirects and<br /> retries, so you will get the original Request. cb_kwargs sent<br /> from your spider.<br /> Request. cb_kwargs attribute<br /> flags¶<br /> A list that contains flags for this response. Flags are labels used for<br /> tagging Responses. For example: ‘cached’, ‘redirected’, etc. And<br /> they’re shown on the string representation of the Response (__str__<br /> method) which is used by the engine for logging.<br /> certificate¶<br /> New in version 2. 0.<br /> A object representing<br /> the server’s SSL certificate.<br /> Only populated for responses, None otherwise.<br /> ip_address¶<br /> New in version 2. 0.<br /> The IP address of the server from which the Response originated.<br /> This attribute is currently only populated by the HTTP 1. 1 download<br /> handler, i. for (s) responses. For other handlers,<br /> ip_address is always None.<br /> protocol¶<br /> New in version 2. 0.<br /> The protocol that was used to download the response.<br /> For instance: “HTTP/1. 1”<br /> This attribute is currently only populated by the HTTP download<br /> handlers, i. For other handlers,<br /> protocol is always None.<br /> Returns a new Response which is a copy of this Response.<br /> replace([url, status, headers, body, request, flags, cls])[source]¶<br /> Returns a Response object with the same members, except for those members<br /> attribute is copied by default.<br /> urljoin(url)[source]¶<br /> Constructs an absolute url by combining the Response’s url with<br /> a possible relative url.<br /> This is a wrapper over urljoin(), it’s merely an alias for<br /> making this call:<br /> (, url)<br /> follow(url, callback=None, method=’GET’, headers=None, body=None, cookies=None, meta=None, encoding=’utf-8′, priority=0, dont_filter=False, errback=None, cb_kwargs=None, flags=None) → [source]¶<br /> Return a Request instance to follow a link url.<br /> It accepts the same arguments as Request. __init__ method,<br /> but url can be a relative URL or a object,<br /> not only an absolute URL.<br /> TextResponse provides a follow()<br /> method which supports selectors in addition to absolute/relative URLs<br /> and Link objects.<br /> New in version 2. 0: The flags parameter.<br /> follow_all(urls, callback=None, method=’GET’, headers=None, body=None, cookies=None, meta=None, encoding=’utf-8′, priority=0, dont_filter=False, errback=None, cb_kwargs=None, flags=None) → Generator[, None, None][source]¶<br /> Return an iterable of Request instances to follow all links<br /> in urls. It accepts the same arguments as Request. __init__ method,<br /> but elements of urls can be relative URLs or Link objects,<br /> not only absolute URLs.<br /> TextResponse provides a follow_all()<br /> Response subclasses¶<br /> Here is the list of available built-in Response subclasses. You can also<br /> subclass the Response class to implement your own functionality.<br /> TextResponse objects¶<br /> class (url[, encoding[,… ]])[source]¶<br /> TextResponse objects adds encoding capabilities to the base<br /> Response class, which is meant to be used only for binary data,<br /> such as images, sounds or any media file.<br /> TextResponse objects support a new __init__ method argument, in<br /> addition to the base Response objects. The remaining functionality<br /> is the same as for the Response class and is not documented here.<br /> encoding (str) – is a string which contains the encoding to use for this<br /> response. If you create a TextResponse object with a string as<br /> body, it will be converted to bytes encoded using this encoding. If<br /> encoding is None (default), the encoding will be looked up in the<br /> response headers and body instead.<br /> TextResponse objects support the following attributes in addition<br /> to the standard Response ones:<br /> text¶<br /> Response body, as a string.<br /> The same as (response. encoding), but the<br /> result is cached after the first call, so you can access<br /> multiple times without extra overhead.<br /> Note<br /> str() is not a correct way to convert the response<br /> body into a string:<br /> >>> str(b’body’)<br /> “b’body'”<br /> encoding¶<br /> A string with the encoding of this response. The encoding is resolved by<br /> trying the following mechanisms, in order:<br /> the encoding passed in the __init__ method encoding argument<br /> the encoding declared in the Content-Type HTTP header. If this<br /> encoding is not valid (i. unknown), it is ignored and the next<br /> resolution mechanism is tried.<br /> the encoding declared in the response body. The TextResponse class<br /> doesn’t provide any special functionality for this. However, the<br /> HtmlResponse and XmlResponse classes do.<br /> the encoding inferred by looking at the response body. This is the more<br /> fragile method but also the last one tried.<br /> selector¶<br /> A Selector instance using the response as<br /> target. The selector is lazily instantiated on first access.<br /> TextResponse objects support the following methods in addition to<br /> the standard Response ones:<br /> xpath(query)[source]¶<br /> A shortcut to (query):<br /> css(query)[source]¶<br /> follow(url, callback=None, method=’GET’, headers=None, body=None, cookies=None, meta=None, encoding=None, priority=0, dont_filter=False, errback=None, cb_kwargs=None, flags=None) → [source]¶<br /> but url can be not only an absolute URL, but also<br /> a relative URL<br /> a Link object, e. g. the result of<br /> Link Extractors<br /> a Selector object for a <link> or <a> element, e. g.<br /> (‘_link’)[0]<br /> an attribute Selector (not SelectorList), e. g.<br /> (‘a::attr(href)’)[0] or<br /> (‘//img/@src’)[0]<br /> See A shortcut for creating Requests for usage examples.<br /> follow_all(urls=None, callback=None, method=’GET’, headers=None, body=None, cookies=None, meta=None, encoding=None, priority=0, dont_filter=False, errback=None, cb_kwargs=None, flags=None, css=None, xpath=None) → Generator[, None, None][source]¶<br /> A generator that produces Request instances to follow all<br /> links in urls. It accepts the same arguments as the Request’s<br /> __init__ method, except that each urls element does not need to be<br /> an absolute URL, it can be any of the following:<br /> In addition, css and xpath arguments are accepted to perform the link extraction<br /> within the follow_all method (only one of urls, css and xpath is accepted).<br /> Note that when passing a SelectorList as argument for the urls parameter or<br /> using the css or xpath parameters, this method will not produce requests for<br /> selectors from which links cannot be obtained (for instance, anchor tags without an<br /> href attribute)<br /> json()[source]¶<br /> New in version 2. 2.<br /> Deserialize a JSON document to a Python object.<br /> Returns a Python object from deserialized JSON document.<br /> The result is cached after the first call.<br /> HtmlResponse objects¶<br /> class (url[,… ])[source]¶<br /> The HtmlResponse class is a subclass of TextResponse<br /> which adds encoding auto-discovering support by looking into the HTML meta<br /> -equiv attribute. See TextResponse. encoding.<br /> XmlResponse objects¶<br /> The XmlResponse class is a subclass of TextResponse which<br /> adds encoding auto-discovering support by looking into the XML declaration<br /> line. encoding.</p> <h2>Frequently Asked Questions about scrapy html</h2> <h3>How do you make a Scrapy in HTML?</h3> <p>Short answer:Scrapy/Parsel selectors’ . re() and . re_first() methods replace HTML entities (except &lt; , &amp; )instead, use . extract() or . extract_first() to get raw HTML (or raw JavaScript instructions) and use Python’s re module on extracted string.Jan 20, 2016</p> <h3>Why would you choose to use Scrapy to parse HTML?</h3> <p>Scrapy is a Python framework for creating web scraping applications. It provides a programming interface to crawl the web by identifying new links, and extracts structured data from the downloaded content.Dec 4, 2017</p> <h3>Is Scrapy better than Beautifulsoup?</h3> <p>Performance. Due to the built-in support for generating feed exports in multiple formats, as well as selecting and extracting data from various sources, the performance of Scrapy can be said to be faster than Beautiful Soup. 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