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WebSearcher

Tools for conducting and parsing web searches

PyPI version

This package provides tools for conducting algorithm audits of web search and includes a scraper built on requests with tools for geolocating, conducting, and saving searches. It also includes a modular parser built on BeautifulSoup for decomposing a SERP into list of components with categorical classifications and position-based specifications.

Table of Contents

Getting Started

# Install pip version
pip install WebSearcher

# Install Github development version - less stable, more fun!
pip install git+https://github.com/gitronald/WebSearcher@dev

Usage

Example Search Script

There's an example search script that can be run from the command line with poetry with a search query argument (-q or --query).

poetry run demo-search -q "election news"

Search results are constantly changing, especially for news, but just now (see timestamp below), that search returned the following details (only a subset of columns are shown):

WebSearcher v0.4.2.dev0
Search Query: election news
Output Dir: data/demo-ws-v0.4.2.dev0

2024-11-11 10:55:27.362 | INFO | WebSearcher.searchers | 200 | election news

                type                                    title                                      url
0        top_stories  There’s a Lot of Fighting Over Why H...  https://slate.com/news-and-politics/...
1        top_stories  Dearborn’s Arab Americans feel vindi...  https://www.politico.com/news/2024/1...
2        top_stories  Former Kamala Harris aide says Joe B...  https://www.usatoday.com/story/news/...
3        top_stories  Election live updates: Control of Co...  https://apnews.com/live/house-senate...
4        top_stories  Undecided races of the 2024 election...  https://abcnews.go.com/538/live-upda...
5         local_news  These Southern California House race...  https://www.nbclosangeles.com/decisi...
6         local_news  Election Day is over in California. ...  https://www.sacbee.com/news/politics...
7         local_news  Why Haven’t Numerous California Hous...  https://www.democracydocket.com/news...
8         local_news  Anti-slavery measure Prop. 6 fails, ...  https://calmatters.org/politics/elec...
9            general  November 10, 2024, election and Trum...  https://www.cnn.com/politics/live-ne...
10           general  When do states have to certify 2024 ...  https://www.cbsnews.com/news/state-e...
11           general  US Election 2024 | Latest News & Ana...  https://www.bbc.com/news/topics/cj3e...
12           unknown                                     None                                     None
13           general                            2024 Election  https://www.npr.org/sections/elections/
14           general  Politics, Policy, Political News - P...                https://www.politico.com/
15           general  Presidential election highlights: No...  https://apnews.com/live/trump-harris...
16           general  Election 2024: Latest News, Top Stor...  https://calmatters.org/category/poli...
17  searches_related                                     None                                     None

By default, that script will save the outputs to a directory (data/demo-ws-{version}/) with the structure below. Within that, the script saves the HTML both to a single JSON lines file (serps.json), which is recommended because it includes metadata about the search, and to individual HTML files in a subdirectory (html/) for ease of viewing the SERPs (e.g., in a browser). The script also saves the parsed search results to a JSON file (results.json).

ls -hal data/demo-ws-v0.4.2.dev0/

total 1020K
drwxr-xr-x 3 user user 4.0K 2024-11-11 10:54 ./
drwxr-xr-x 8 user user 4.0K 2024-11-11 10:54 ../
drwxr-xr-x 2 user user 4.0K 2024-11-11 10:55 html/
-rw-r--r-- 1 user user  16K 2024-11-11 10:55 results.json
-rw-r--r-- 1 user user 990K 2024-11-11 10:55 serps.json

Step by Step

Example search and parse pipeline:

import WebSearcher as ws
se = ws.SearchEngine()                     # 1. Initialize collector
se.search('immigration news')              # 2. Conduct a search
se.parse_results()                         # 3. Parse search results
se.save_serp(append_to='serps.json')       # 4. Save HTML and metadata
se.save_results(append_to='results.json')  # 5. Save parsed results

1. Initialize Collector

import WebSearcher as ws

# Initialize collector with optional defaults (headers, logs, ssh tunnels)
se = ws.SearchEngine()

# Show collector settings
vars(se)
{'version': '0.4.1',
 'base_url': 'https://www.google.com/search',
 'headers': {'Host': 'www.google.com',
  'Referer': 'https://www.google.com/',
  'Accept': '*/*',
  'Accept-Encoding': 'gzip,deflate,br',
  'Accept-Language': 'en-US,en;q=0.5',
  'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/118.0'},
 'sesh': <requests.sessions.Session at 0x7f9ac018ece0>,
 'ssh_tunnel': None,
 'unzip': True,
 'params': {},
 'qry': None,
 'loc': None,
 'num_results': None,
 'url': None,
 'timestamp': None,
 'serp_id': None,
 'crawl_id': None,
 'response': None,
 'html': None,
 'results': [],
 'log': <Logger WebSearcher.searchers (DEBUG)>}

2. Conduct a Search

se.search('immigration news')
# 2024-08-19 14:09:18.502 | INFO | WebSearcher.searchers | 200 | immigration news

3. Parse Search Results

The example below is primarily for parsing search results as you collect HTML.
See ws.parse_serp(html) for parsing existing HTML data.

se.parse_results()

# Show first result
se.results[0]
{'section': 'main',
 'cmpt_rank': 0,
 'sub_rank': 0,
 'type': 'top_stories',
 'sub_type': None,
 'title': 'Biden citizenship program for migrant spouses in US launches',
 'url': 'https://www.newsnationnow.com/us-news/immigration/biden-citizenship-program-migrant-spouses-us-launches/',
 'text': None,
 'cite': 'NewsNation',
 'details': None,
 'error': None,
 'serp_rank': 0}

4. Save HTML and Metadata

Recommended: Append html and meta data as lines to a json file for larger or ongoing collections.

se.save_serp(append_to='serps.json')

Alternative: Save individual html files in a directory, named by a provided or (default) generated serp_id. Useful for smaller qualitative explorations where you want to quickly look at what is showing up. No meta data is saved, but timestamps could be recovered from the files themselves.

se.save_serp(save_dir='./serps')

5. Save Parsed Results

Save to a json lines file.

se.save_results(append_to='results.json')

Localization

To conduct localized searches--from a location of your choice--you only need
one additional data point: The "Canonical Name" of each location. These are
available online, and can be downloaded using a built in function
(ws.download_locations()) to check for the most recent version.

A brief guide on how to select a canonical name and use it to conduct a
localized search is available in a jupyter notebook here.

Contributing

Happy to have help! If you see a component that we aren't covering yet, please add it using the process below. If you aren't sure about how to write a parser, you can also create an issue and I'll try to check it out. When creating that type of issue, providing the query that produced the new component and the time it was seen are essential, a screenshot of the component would be helpful, and the HTML would be ideal. Feel free to reach out if you have questions or need help.

Repair or Enhance a Parser

  1. Examine parser names in /component_parsers/__init__.py
  2. Find parser file as /component_parsers/{cmpt_name}.py.

Add a Parser

  1. Add classifier to classifiers/{main,footer,headers}.py
  2. Add parser as new file in /component_parsers
  3. Add new parser to imports and catalogue in /component_parsers/__init__.py

Testing

Run tests:

pytest

Update snapshots:

pytest --snapshot-update

Running pytest with the -vv flag will show a diff of the snapshots that have changed:

pytest -vv

With the -k flag you can run a test for a specific html file:

pytest -k "1684837514.html"

Recent Changes

0.4.1 - Added notices component types, including query edits, suggestions, language tips, and location tips.

0.4.0 - Restructured parser for component classes, split classifier into submodules for header, main, footer, etc., and rewrote extractors to work with component classes. Various bug fixes.

0.3.13 - New footer parser, broader extraction coverage, various bug and deprecation fixes.

0.3.12 - Added num_results to search args, added handling for local results text and labels (made by the SE), ignore hidden_survey type at extraction.

0.3.11 - Added extraction of labels for ads (made by the SE), use model validation, cleanup and various bug fixes.

0.3.10 - Updated component classifier for images, added exportable header text mappings, added gist on localized searches.

0.3.9 - Small fixes for video url parsing

0.3.8 - Using SERP pydantic model, added github pip publishing workflow

0.3.7 - Fixed localization, parser and classifier updates and fixes, image subtypes, changed rhs component handling.

0.3.0 - 0.3.6 - Parser updates for SERPs from 2022 and 2023, standalone extractors file, added pydantic, reduced redundancies in outputs.

2020.0.0, 2022.12.18, 2023.01.04 - Various updates, attempt at date versioning that seemed like a good idea at the time ¯\_(ツ)_/¯

<!-- refs/tags/v2022.12.18 --> <!-- refs/tags/v2023.01.04 -->

0.2.15 - Fix people-also-ask and hotel false positives, add flag for left-hand side bar

0.2.14 - Add shopping ads carousel and three knowledge subtypes (flights, hotels, events)

0.2.13 - Small fixes for knowledge subtypes, general subtypes, and ads

0.2.12 - Try to brotli decompress by default

0.2.11 - Fixed local result parser and no return in general extra details

0.2.10 - a) Add right-hand-side knowledge panel and top image carousel, b) Add knowledge and general component subtypes, c) Updates to component classifier, footer, ad, and people_also_ask components

0.2.9 - Various fixes for SERPs with a left-hand side bar, which are becoming more common and change other parts of the SERP layout.

0.2.8 - Small fixes due to HTML changes, such as missing titles and URLs in general components

0.2.7 - Added fix for parsing twitter cards, removed pandas dependencies and several unused functions, moving towards greater package simplicity.

0.2.6 - Updated ad parser for latest format, still handles older ad format.

0.2.5 - Google Search, like most online platforms, undergoes changes over time. These changes often affect not just their outward appearance, but the underlying code that parsers depend on. This makes parsing a goal with a moving target. Sometime around February 2020, Google changed a few elements of their HTML structure which broke this parser. I created this patch for these changes, but have not tested its backwards compatibility (e.g. on SERPs collected prior to 2/2020). More generally, there's no guarantee on future compatibility. In fact, there is almost certainly the opposite: more changes will inevitably occur. If you have older data that you need to parse and the current parser doesn't work, you can try using 0.2.1, or send a pull request if you find a way to make both work!

Similar Packages

Many of the packages I've found for collecting web search data via python are no longer maintained, but others are still ongoing and interesting or useful. The primary strength of WebSearcher is its parser, which provides a level of detail that enables examinations of SERP composition by recording the type and position of each result, and its modular design, which has allowed us to (itermittenly) maintain it for so long and to cover such a wide array of component types (currently 25 without considering sub_types). Feel free to add to the list of packages or services through a pull request if you are aware of others:

License

Copyright (C) 2017-2024 Ronald E. Robertson rer@acm.org

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.