Awesome

WebBotParser

WebBotParser is a Python package that adds basic parsing capabilities for search engine results scraped with our browser extension WebBot. With WebBotParser, you can parse search result pages saved from Google, DuckDuckGo, etc. using WebBot's download capabilities, or obtained through a different method for further analysis.

The following engines and search result types are currently supported out of the box:

Installation

For basic usage, simply clone this repository, or directly download webbotparser/webbotparser.py and add the script to your working directory.

Install the package with pip

If you want to use WebBotParser over multiple projects/directories, you can also install it as a Python package. Simply run

pip install git+https://github.com/gesiscss/WebBotParser

The webbotparser package is then available globally in your respective Python installation.

Usage

For the search engines and result types supported out of the box, simply run

from webbotparser import WebBotParser

and initialize the WebBotParser for the search engine and result type your are investigating, for example

parser = WebBotParser(engine = 'DuckDuckGo News')

Then, you can obtain the search results as a pandas DataFrame and metadata as a Python dictionary with

metadata, results = parser.get_results(file='path/to/the/result_page.html')

Furthermore, parser.get_metadata(file) can be used to only extract the metadata. parser.get_results_from_dir(dir) allows to directly extract search results spread over multiple pages, as Google text result are provided for instance.

For more details and examples also see WebBot tutorials.

Extracting images

WebBot archives images inline in the html file of the search results, i.e., they are neither external files on your drive nor fetched from the original source on viewing the downloaded search results page. This allows us to extract the images directly from the html file for further analysis. The engines and result types supported out of the box with WebBotParser allow for extracting images as well. Simply initialize WebBotParser as follows:

parser = WebBotParser(engine = 'Google Video', extract_images=True)

You can optionally specify extract_images_prefix, extract_images_format, and extract_images_to_dir. See example.ipynb for more details, including preview in Jupyter Notebooks.

Custom result types

WebBotParser out of the box only provides support for some search engines and result types. Even these parsers might stop working if the search engine providers decide to change their layout. However, WebBotParser can still be used in these cases by defining a custom result_selector, queries, and optionally a metadata_extractor function. In this case, a WebBotParser is initiated with these instead of with the engine attribute

parser = WebBotParser(queries, result_selector, metadata_extractor)

Under the hood, WebBotParser uses BeautifulSoup to

1. Parse the search result page's HTML via LXML
2. Disciminate the individual results on each page using a CSS selector called result_selector that matches a list of search results
3. For each of those results, extract available information through a list of queries

See the below example for available types of queries and their usage

queries = [
    # extract the text from inside a matched element, getting all the text over all its children
    {'name': 'abc', 'type': 'text', 'selector': 'h3'},
    
    # extract the value of an attribute of a matched element
    {'name': 'def', 'type': 'attribute', 'selector': 'a', 'attribute': 'href'},
    
    # whether or not a CSS selector matches, returns a Boolean
    {'name': 'ghi', 'type': 'exists', 'selector': 'ul'},

    # extract inline images and name them by a title
    {'name': 'jkl', 'type': 'image', 'selector': 'g-img > img', 'title_selector': 'h3'}
    
    # pass a custom query function
    {'name': 'mno', 'type': 'custom', 'function': my_function},
]

You can optionally provide a metadata_extractor(soup, file) function to extract metadata alongside the search results, or import one of the existing extractors, e.g. with

from webbotparser import GoogleParser
metadata_extractor = GoogleParser.google_metadata

Related projects

• WebBot is a browser extension for retrieving search engine results.
• webbotparseR is a similar R package for parsing WebBot results.
• WebBot tutorials contains tutorials of WebBot and parsing.
• WebSearcher is a Python package that facilitates obtaining and parsing search results from Google text search. Compared to WebBotParser, it supports parsing more diverse results (ads, knowledge boxes, etc.), but only Google text results (for now).

Authors

Georg Ahnert, Jun Sun