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WikipediaQL: querying structured data from Wikipedia

WikipediaQL is an experimental query language and Python library for querying structured data from Wikipedia. It looks like this:

$ wikipedia_ql --page "Guardians of the Galaxy (film)" \
    '{
      page@title as "title";
      section[heading="Cast"] as "cast" >> {
          li >> text:matches("^(.+?) as (.+?):") >> {
              text-group[group=1] as "actor";
              text-group[group=2] as "character"
          }
      };
      section[heading="Critical response"] >> {
          sentence:contains("Rotten Tomatoes") as "RT ratings" >> {
              text:matches("\d+%") as "percent";
              text:matches("(\d+) (critic|review)") >> text-group[group=1] as "reviews";
              text:matches("[\d.]+/10") as "overall"
          }
      }
    }'

RT ratings:
  overall: 7.8/10
  percent: 92%
  reviews: '334'
cast:
- actor: Chris Pratt
  character: Peter Quill / Star-Lord
- actor: Zoe Saldaña
  character: Gamora
- actor: Dave Bautista
  character: Drax the Destroyer
- actor: Vin Diesel
  character: Groot
- actor: Bradley Cooper
  character: Rocket CREDITED ONLY AS "Rocket" PER OFFICIAL SYNOPSIS!
- actor: Lee Pace
  character: Ronan the Accuser
- actor: Michael Rooker
  character: Yondu Udonta
- actor: Karen Gillan
  character: Nebula
- actor: Djimon Hounsou
  character: Korath
- actor: John C. Reilly
  character: Rhomann Dey
- actor: Glenn Close
  character: Irani Rael
- actor: Benicio del Toro
  character: Taneleer Tivan / The Collector
title: Guardians of the Galaxy (film)

How?

WikipediaQL-the-tool does roughly this:

The WikipediaQL development is covered in ongoing series of articles: (newest first)

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Why?

“Sometimes magic is just someone spending more time on something than anyone else might reasonably expect.” — Raymond Joseph Teller

Wikipedia is the most important open knowledge project: basically, the "table of contents" of all the human data. While it might be incomplete or misleading in details, the amount of data is incredible, and its organization makes all the data accessible to humans.

OTOH, the data is semi-structured and quite hard to extract automatically. This project is an experiment in making this data accessible to machines—or, rather, to humans with programming languages. The main goal is to develop an easy to use and memorize, unambiguous and powerful query language and support it by the reference implementation.

See FAQ below for justifications of parsing Wikipedia instead of just using already formalized Wikidata (and of parsing HTML instead of Wikipedia markup).

Usage

$ pip install wikipedia_ql

$ wikipedia_ql --page "Page name" query_text
# or
$ wikipedia_ql query_text_with_page

Usage as Python library:

from wikipedia_ql import media_wiki

wikipedia = media_wiki.Wikipedia()

data = wikipedia.query(query_text)

Full WikipediaQL query looks like this:

from <source> {
  <selectors>
}

When using --page parameter to the executable, you need only to pass selectors in the query text.

Source is Wikipedia article name, or category name, or (in the future) other ways of specifying multiple pages. Selectors are similar to CSS; they are nested in one another with selector { other; selectors }, or (shortcut) selector >> other_selector. All terminal selectors (e.g., doesn't having others nested) produce values in the output; the value can be associated with a name with as "valuename".

See below for a list of selectors and sources currently supported and the future ones.

Examples

Simple query for some info from the page:

$ wikipedia_ql --page "Pink Floyd" \
    'section[heading="Discography"] >> li >> {
        a as "title";
        text:matches("\((.+)\)") >> text-group[group=1] as "year";
    }'

- title: The Piper at the Gates of Dawn
  year: '1967'
- title: A Saucerful of Secrets
  year: '1968'
- title: More
  year: '1969'
- title: Ummagumma
  year: '1969'
#     ...and so on...

Multi-page query from pages of some category (only from inside Python):

query = r'''
from category:"2020s American time travel television series" {
    page@title as "title";
    section[heading="External links"] >> {
      li >> text:matches("^(.+?) at IMDb") >> text-group[group=1] >> a@href as "imdb"
    }
}
'''

# iquery returns generator, fetching pages as you go
for row in wikipedia.iquery(query):
  print(row)
# {'title': 'Agents of S.H.I.E.L.D.', 'imdb': 'https://www.imdb.com/title/tt2364582/'}
# {'title': 'The Flash (2014 TV series)', 'imdb': 'https://www.imdb.com/title/tt3107288/'}
# {'title': 'Legends of Tomorrow', 'imdb': 'https://www.imdb.com/title/tt4532368/'}
# ....

Navigating through pages in one query (note the -> which means "perform subquery in the page by link"):

$ wikipedia_ql --page Björk \
    'section[heading="Discography"] >> li >> a -> {
        page@title as "title";
        .infobox-image >> img >> @src as "cover"
    }'

- cover: https://upload.wikimedia.org/wikipedia/en/thumb/7/77/Bj%C3%B6rk-Debut-1993.png/220px-Bj%C3%B6rk-Debut-1993.png
  title: Debut (Björk album)
- cover: https://upload.wikimedia.org/wikipedia/en/thumb/3/3f/Bjork_Post.png/220px-Bjork_Post.png
  title: Post (Björk album)
- cover: https://upload.wikimedia.org/wikipedia/en/thumb/a/af/Bj%C3%B6rk_-_Homogenic.png/220px-Bj%C3%B6rk_-_Homogenic.png
  title: Homogenic
...

As the page source should be fetched from Wikipedia every time, and it can be a major slowdown when experimenting, wikipedia_ql implements super-naive caching:

wikipedia = media_wiki.Wikipedia(cache_folder='some/folder')
wikipedia.query('from "Pink Floyd" { page@title }') # fetches page from Wikipedia, then runs query
wikipedia.query('from "Pink Floyd" { page@title }') # gets the cached by prev.request contents from some/folder

(Caution! as it was said, for now, the cache is super-naive: it just stores page contents in the specified folder forever. You might delete it from the cache manually, though: there are just PageName.meta.json and PageName.json files.)

Current state & Planned features

Query language

from <source> {
  <selectors>
}

Source can be:

Selectors are CSS-alike selectors, type.class[attr="value"][otherattr="othervalue"]. Note, that unlike CSS, nesting (any child inside parent) is performed not with spaces (parent child), but with parent >> child.

Other features/problems

Roadmap

FAQ

Why not use Wikidata (or other structured Wikipedia-based data source, like DBPedia)?

Wikidata is a massive effort to represent Wikipedia in a computable form. But currently, it contains much less data than Wikipedia itself; and much less accessible for investigatory data extraction (TODO: good examples!) While it gets improved constantly, I wanted to tackle the problem from a different angle and see how accessible we can make Wikipedia itself, with all of its semi-structuredness.

Why not fetch and parse page sources in Wikitext?

Some similar projects (say, wtf_wikipedia) work by fetching page source in Wikitext form, and parsing it for data extraction. This road looks pretty tempting (and for several years, I went it myself with the previous iteration: infoboxer Ruby project). The problem here is that at first sight, Wikitext is better structured: large chunks of data are represented by templates like {{Infobox; field=value, ...}} so it really seems like a better source for data extraction. There are two huge problems with this approach, though:

  1. The list of templates is infinite and unpredictable. While ten city-related pages would have {{Infobox city in a pretty similar form, the eleventh will have {{Geobox capital with all the different fields and conventions—but in HTML they would render to the similarly-looking <table class="infobox". Or, some TV series will represent a list of episodes with just a plain table markup, while the other will use a sophisticated {{Episode list template. And it all might change with time (some spring cleanup replacing all the template names or converting some regular text to a template). The HTML version is much more stable and predictable.
  2. To library/QL users, having Wikitext&templates as the base would mean that writing queries requires intimate knowledge of Wikitext format and conventions and frequently looking at the page's source (via "Edit") to find out how something is represented in Wikitext. OTOH, HTML/CSS-based approach relies on widely known elements like headers, lists, links, tables, and simple grouping objects, like sections and sentences. Most of them are unambiguously deduced by looking at the page in the browser or, in the worst case, by "inspect element" (to find out its particular class/id).

Prior work

This project is the N-th iteration of the ideas about providing "common knowledge" in a computable form. Most of the previous work was done in Ruby and centered around Reality project; and included, amongst other things, Infoboxer the Wikipedia parser/high-level client, and MediaWiktory the idiomatic low-level MediaWiki client. Some of that work still to be incorporated into WikipediaQL and sister projects.

That project was once inspired by "integrated knowledge" feature of Wolfram Language, I've talked about it (and other topics leading to this project) in a Twitter thread (yes).

The WikipediaQL syntax seems to be subconsciously inspired by qsx selectors language. (By subconsciously I mean I don't remember thinking "Oh, I should do something similar", but the day I've published WikipediQL, past.codes service have reminded me I starred qsx in December 2020. I started to think about WikipediaQL syntax in June 2021, but there are striking similarities, so it should be related to some indirect inspiration by that project.)

License

MIT