Scrapling/docs/overview.md at 21bf2af9ec3fef2d66bda295b903783f397dc98a

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Karim shoair ed694f0a79 First version of Scrapling full documentation

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We will start by quickly reviewing the parsing capabilities. Then, we will fetch websites with custom browsers, make requests, and parse the response.

Here's an HTML document generated by ChatGPT we will be using as an example throughout this page:

<html>
  <head>
    <title>Complex Web Page</title>
    <style>
      .hidden { display: none; }
    </style>
  </head>
  <body>
    <header>
      <nav>
        <ul>
          <li> <a href="#home">Home</a> </li>
          <li> <a href="#about">About</a> </li>
          <li> <a href="#contact">Contact</a> </li>
        </ul>
      </nav>
    </header>
    <main>
      <section id="products" schema='{"jsonable": "data"}'>
        <h2>Products</h2>
        <div class="product-list">
          <article class="product" data-id="1">
            <h3>Product 1</h3>
            <p class="description">This is product 1</p>
            <span class="price">$10.99</span>
            <div class="hidden stock">In stock: 5</div>
          </article>

          <article class="product" data-id="2">
            <h3>Product 2</h3>
            <p class="description">This is product 2</p>
            <span class="price">$20.99</span>
            <div class="hidden stock">In stock: 3</div>
          </article>

          <article class="product" data-id="3">
            <h3>Product 3</h3>
            <p class="description">This is product 3</p>
            <span class="price">$15.99</span>
            <div class="hidden stock">Out of stock</div>
          </article>
        </div>
      </section>
      
      <section id="reviews">
        <h2>Customer Reviews</h2>
        <div class="review-list">
          <div class="review" data-rating="5">
            <p class="review-text">Great product!</p>
            <span class="reviewer">John Doe</span>
          </div>
          <div class="review" data-rating="4">
            <p class="review-text">Good value for money.</p>
            <span class="reviewer">Jane Smith</span>
          </div>
        </div>
      </section>
    </main>
    <script id="page-data" type="application/json">
      {
        "lastUpdated": "2024-09-22T10:30:00Z",
        "totalProducts": 3
      }
    </script>
  </body>
</html>

Starting with loading raw HTML above like this

from scrapling.parser import Adaptor
page = Adaptor(html_doc)
page  # <data='<html><head><title>Complex Web Page</tit...'>

Get all text content on the page recursively

page.get_all_text(ignore_tags=('script', 'style'))
# 'Complex Web Page\nHome\nAbout\nContact\nProducts\nProduct 1\nThis is product 1\n$10.99\nIn stock: 5\nProduct 2\nThis is product 2\n$20.99\nIn stock: 3\nProduct 3\nThis is product 3\n$15.99\nOut of stock\nCustomer Reviews\nGreat product!\nJohn Doe\nGood value for money.\nJane Smith'

Finding elements

If there's an element you want to find on the page, you will! Your creativity level is the only limitation!

Finding the first HTML section element

section_element = page.find('section')
# <data='<section id="products" schema='{"jsonabl...' parent='<main><section id="products" schema='{"j...'>

Find all section elements

section_elements = page.find_all('section')
# [<data='<section id="products" schema='{"jsonabl...' parent='<main><section id="products" schema='{"j...'>, <data='<section id="reviews"><h2>Customer Revie...' parent='<main><section id="products" schema='{"j...'>]

Find all section elements whose id attribute value is products

section_elements = page.find_all('section', {'id':"products"})
# Same as
section_elements = page.find_all('section', id="products")
# [<data='<section id="products" schema='{"jsonabl...' parent='<main><section id="products" schema='{"j...'>]

Find all section elements that its id attribute value contains product

section_elements = page.find_all('section', {'id*':"product"})

Find all h3 elements whose text content matches this regex Product \d

page.find_all('h3', re.compile(r'Product \d'))
# [<data='<h3>Product 1</h3>' parent='<article class="product" data-id="1"><h3...'>, <data='<h3>Product 2</h3>' parent='<article class="product" data-id="2"><h3...'>, <data='<h3>Product 3</h3>' parent='<article class="product" data-id="3"><h3...'>]

Find all h3 and h2 elements whose text content matches regex Product only

page.find_all(['h3', 'h2'], re.compile(r'Product'))
# [<data='<h3>Product 1</h3>' parent='<article class="product" data-id="1"><h3...'>, <data='<h3>Product 2</h3>' parent='<article class="product" data-id="2"><h3...'>, <data='<h3>Product 3</h3>' parent='<article class="product" data-id="3"><h3...'>, <data='<h2>Products</h2>' parent='<section id="products" schema='{"jsonabl...'>]

Find all elements that its text content matches exactly Products (Whitespaces are not taken into consideration)

page.find_by_text('Products', first_match=False)
# [<data='<h2>Products</h2>' parent='<section id="products" schema='{"jsonabl...'>]

Or find all elements whose text content matches regex Product \d

page.find_by_regex(r'Product \d', first_match=False)
# [<data='<h3>Product 1</h3>' parent='<article class="product" data-id="1"><h3...'>, <data='<h3>Product 2</h3>' parent='<article class="product" data-id="2"><h3...'>, <data='<h3>Product 3</h3>' parent='<article class="product" data-id="3"><h3...'>]

Find all elements that are similar to the element you want

target_element = page.find_by_regex(r'Product \d', first_match=True)
# <data='<h3>Product 1</h3>' parent='<article class="product" data-id="1"><h3...'>
target_element.find_similar()
# [<data='<h3>Product 2</h3>' parent='<article class="product" data-id="2"><h3...'>, <data='<h3>Product 3</h3>' parent='<article class="product" data-id="3"><h3...'>]

Find the first element that matches a CSS selector

page.css_first('.product-list [data-id="1"]')
# <data='<article class="product" data-id="1"><h3...' parent='<div class="product-list"> <article clas...'>

Find all elements that match a CSS selector

page.css('.product-list article')
# [<data='<article class="product" data-id="1"><h3...' parent='<div class="product-list"> <article clas...'>, <data='<article class="product" data-id="2"><h3...' parent='<div class="product-list"> <article clas...'>, <data='<article class="product" data-id="3"><h3...' parent='<div class="product-list"> <article clas...'>]

Find the first element that matches an XPath selector

page.xpath_first("//*[@id='products']/div/article")
# <data='<article class="product" data-id="1"><h3...' parent='<div class="product-list"> <article clas...'>

Find all elements that match an XPath selector

page.xpath("//*[@id='products']/div/article")
# [<data='<article class="product" data-id="1"><h3...' parent='<div class="product-list"> <article clas...'>, <data='<article class="product" data-id="2"><h3...' parent='<div class="product-list"> <article clas...'>, <data='<article class="product" data-id="3"><h3...' parent='<div class="product-list"> <article clas...'>]

With this, we just scratched the surface of these functions; more advanced options with these selection methods are shown later.

Accessing elements' data

It's as simple as

>>> section_element.tag
'section'
>>> print(section_element.attrib)
{'id': 'products', 'schema': '{"jsonable": "data"}'}
>>> section_element.attrib['schema'].json()  # If an attribute value can be converted to json, then use `.json()` to convert it
{'jsonable': 'data'}
>>> section_element.text  # Direct text content
''
>>> section_element.get_all_text()  # All text content recursively
'Products\nProduct 1\nThis is product 1\n$10.99\nIn stock: 5\nProduct 2\nThis is product 2\n$20.99\nIn stock: 3\nProduct 3\nThis is product 3\n$15.99\nOut of stock'
>>> section_element.html_content  # The HTML content of the element
'<section id="products" schema=\'{"jsonable": "data"}\'><h2>Products</h2>\n        <div class="product-list">\n          <article class="product" data-id="1"><h3>Product 1</h3>\n            <p class="description">This is product 1</p>\n            <span class="price">$10.99</span>\n            <div class="hidden stock">In stock: 5</div>\n          </article><article class="product" data-id="2"><h3>Product 2</h3>\n            <p class="description">This is product 2</p>\n            <span class="price">$20.99</span>\n            <div class="hidden stock">In stock: 3</div>\n          </article><article class="product" data-id="3"><h3>Product 3</h3>\n            <p class="description">This is product 3</p>\n            <span class="price">$15.99</span>\n            <div class="hidden stock">Out of stock</div>\n          </article></div>\n      </section>'
>>> print(section_element.prettify())  # The prettified version
'''
<section id="products" schema='{"jsonable": "data"}'><h2>Products</h2>
    <div class="product-list">
      <article class="product" data-id="1"><h3>Product 1</h3>
        <p class="description">This is product 1</p>
        <span class="price">$10.99</span>
        <div class="hidden stock">In stock: 5</div>
      </article><article class="product" data-id="2"><h3>Product 2</h3>
        <p class="description">This is product 2</p>
        <span class="price">$20.99</span>
        <div class="hidden stock">In stock: 3</div>
      </article><article class="product" data-id="3"><h3>Product 3</h3>
        <p class="description">This is product 3</p>
        <span class="price">$15.99</span>
        <div class="hidden stock">Out of stock</div>
      </article>
    </div>
</section>
'''
>>> section_element.path  # All the ancestors in the DOM tree of this element
[<data='<main><section id="products" schema='{"j...' parent='<body> <header><nav><ul><li> <a href="#h...'>,
 <data='<body> <header><nav><ul><li> <a href="#h...' parent='<html><head><title>Complex Web Page</tit...'>,
 <data='<html><head><title>Complex Web Page</tit...'>]
>>> section_element.generate_css_selector
'#products'
>>> section_element.generate_full_css_selector
'body > main > #products > #products'
>>> section_element.generate_xpath_selector
"//*[@id='products']"
>>> section_element.generate_full_xpath_selector
"//body/main/*[@id='products']"

Using the elements we found above

>>> section_element.parent
<data='<main><section id="products" schema='{"j...' parent='<body> <header><nav><ul><li> <a href="#h...'>
>>> section_element.parent.tag
'main'
>>> section_element.parent.parent.tag
'body'
>>> section_element.children
[<data='<h2>Products</h2>' parent='<section id="products" schema='{"jsonabl...'>,
 <data='<div class="product-list"> <article clas...' parent='<section id="products" schema='{"jsonabl...'>]
>>> section_element.siblings
[<data='<section id="reviews"><h2>Customer Revie...' parent='<main><section id="products" schema='{"j...'>]
>>> section_element.next  # gets the next element, the same logic applies to `quote.previous`
<data='<section id="reviews"><h2>Customer Revie...' parent='<main><section id="products" schema='{"j...'>
>>> section_element.children.css('h2::text')
['Products']
>>> page.css_first('[data-id="1"]').has_class('product')
True

If your case needs more than the element's parent, you can iterate over the whole ancestors' tree of any element like the one below

for ancestor in quote.iterancestors():
    # do something with it...

You can search for a specific ancestor of an element that satisfies a function; all you need to do is to pass a function that takes an Adaptor object as an argument and return True if the condition satisfies or False otherwise like below:

>>> section_element.find_ancestor(lambda ancestor: ancestor.css('nav'))
<data='<body> <header><nav><ul><li> <a href="#h...' parent='<html><head><title>Complex Web Page</tit...'>

Fetching websites

Instead of passing the raw HTML to Scrapling, you can get a website's response directly through HTTP requests or by fetching it from browsers.

A fetcher is made for every use case.

HTTP Requests

For simple HTTP requests, there's a Fetcher class that can be imported as below:

from scrapling.fetchers import Fetcher

But that's class, so you will need to create an instance of the Fetcher first like this:

from scrapling.fetchers import Fetcher
fetcher = Fetcher()
page = fetcher.get('https://httpbin.org/get')

This is intended, and you will find it with all fetchers because there are settings you can pass to Fetcher() initialization, but more on this later.

If you are going to use the default settings anyway, you can do this instead for a cleaner approach:

from scrapling.fetchers import Fetcher
page = Fetcher.get('https://httpbin.org/get')

With that out of the way, here's how to do all HTTP methods:

>>> from scrapling.fetchers import Fetcher
>>> page = Fetcher.get('https://httpbin.org/get', stealthy_headers=True, follow_redirects=True)
>>> page = Fetcher.post('https://httpbin.org/post', data={'key': 'value'}, proxy='http://username:password@localhost:8030')
>>> page = Fetcher.put('https://httpbin.org/put', data={'key': 'value'})
>>> page = Fetcher.delete('https://httpbin.org/delete')

For Async requests, you will just replace the import like below:

>>> from scrapling.fetchers import AsyncFetcher
>>> page = await AsyncFetcher.get('https://httpbin.org/get', stealthy_headers=True, follow_redirects=True)
>>> page = await AsyncFetcher.post('https://httpbin.org/post', data={'key': 'value'}, proxy='http://username:password@localhost:8030')
>>> page = await AsyncFetcher.put('https://httpbin.org/put', data={'key': 'value'})
>>> page = await AsyncFetcher.delete('https://httpbin.org/delete')

Note: You have the stealthy_headers argument, which, when enabled, makes requests to generate real browser headers and use them, including a referer header, as if this request came from Google's search of this URL's domain. It's enabled by default.

This is just the tip of this fetcher; check the full page from here

Dynamic loading

We have you covered if you deal with dynamic websites like most today!

The PlayWrightFetcher class provides many options to fetch/load websites' pages through browsers.

>>> from scrapling.fetchers import PlayWrightFetcher
>>> page = PlayWrightFetcher.fetch('https://www.google.com/search?q=%22Scrapling%22', disable_resources=True)  # Vanilla Playwright option
>>> page.css_first("#search a::attr(href)")
'https://github.com/D4Vinci/Scrapling'
>>> # The async version of fetch
>>> page = await PlayWrightFetcher.async_fetch('https://www.google.com/search?q=%22Scrapling%22', disable_resources=True)
>>> page.css_first("#search a::attr(href)")
'https://github.com/D4Vinci/Scrapling'

It's named like that because it's built on top of Playwright, and it currently provides 4 main run options that can be mixed as you want:

Vanilla Playwright without any modifications other than the ones you chose.
Stealthy Playwright with custom stealth mode explicitly written for it. It's not top-tier stealth mode but bypasses many online tests like Sannysoft's. Check out the StealthyFetcher class below for more advanced stealth mode.
Real browsers by passing the real_chrome argument or the CDP URL of your browser to be controlled by the Fetcher, and most of the options can be enabled on it.
NSTBrowser's docker browserless option by passing the CDP URL and enabling nstbrowser_mode option.

Note: All requests done by this fetcher are waited by default for all javascript to be fully loaded and executed. In detail, it waits for the load and domcontentloaded load states to be reached; you can make it wait for the networkidle load state by passing 'network_idle=True', as you will see later.

Again, this is just the tip of this fetcher. Check out the full page from here for all details and the complete list of arguments.

Dynamic anti-protection loading

We also have you covered if you deal with dynamic websites with annoying anti-protections!

The StealthyFetcher class uses a modified Firefox browser called Camoufox, bypassing most anti-bot protections by default. Scrapling adds extra layers of flavors and configurations to further increase performance and undetectability.

>>> page = StealthyFetcher().fetch('https://www.browserscan.net/bot-detection')  # Running headless by default
>>> page.status == 200
True
>>> page = StealthyFetcher().fetch('https://www.browserscan.net/bot-detection', humanize=True, os_randomize=True) # and the rest of arguments...
>>> # The async version of fetch
>>> page = await StealthyFetcher().async_fetch('https://www.browserscan.net/bot-detection')
>>> page.status == 200
True