Key Word In Context

Locates the lemmas of a query in the context that attests them.

Installation

Requirements

• Python 3.12 or later

From PyPI

pip install kwic

A search reads with spaCy, whose pipelines are published apart from the library:

python -m spacy download en_core_web_sm

The other engines are extras:

pip install "kwic[stanza]"
pip install "kwic[lemminflect]"

Usage

A search takes one context and the lemmas to look for.

from kwic import Locator, POS, Query

locator = Locator()

locator.find("She found the keys she had lost.", [Query("find", POS.VERB)])
# (Match(lemma='find', pos=POS.VERB, form='found', word_index=1, offsets=(4, 9)),)

Query

The engine cuts the lemma into words, and a space and a hyphen are one to it.

locator.find("It was hunky-dory.", [Query("hunky dory")])
# (Match(lemma='hunky dory', pos=POS.ADJ, form='hunky-dory', word_index=2, offsets=(7, 17)),)

A phrasal verb written apart runs from the verb to the particle.

locator.find("She gave the money up.", [Query("give up")])
# (Match(lemma='give up', pos=POS.VERB, form='gave the money up', word_index=1, offsets=(4, 21)),)

Match

Contexts

A context is a text, or the words it was split into. The second has no range.

locator.find(("She", "found", "the", "keys"), [Query("find")])
# (Match(lemma='find', pos=POS.VERB, form='found', word_index=1, offsets=None),)

Many contexts

find_all takes context and lemmas in pairs, and reads a batch at a time.

for occurrences in locator.find_all(searches):
    ...

Engines

An engine reads the context; the search reads the engine.

from kwic.engines.stanza import StanzaEngine

locator = Locator(StanzaEngine())

An extra is imported from the module wrapping it, so a package without it still loads.

SpacyEngine takes the pipeline to load, StanzaEngine the language. Both parse unless told otherwise:

Locator(SpacyEngine(parse=False))

Accuracy

English-EWT test section: 2,077 sentences, 417 lemmas, 3,619 occurrences.