shoten 0.1.0

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Helper functions to find word trends (i.e. extract tokens, lemmatize and filter).

Installation

pip/pip3 install -U git+https://github.com/adbar/shoten.git

Usage

Input

Two possibilities for input data:

• XML-TEI files as generated by trafilatura:

  1. from shoten import gen_wordlist

  2. myvocab = gen_wordlist(mydir, ['de', 'en'])

• TSV-file contaning a word list: word form + TAB + date (YYYY-MM-DD format) + possible 3rd column (source)

  1. from shoten import load_wordlist

  2. myvocab = load_wordlist(myfile, ['de', 'en'])

Language codes: optional list of languages to be considered for lemmatization, ordered by relevance. ISO 639-1 codes, see the list of supported languages.

Optional argument maxdiff: maximum number of days to consider (default: 1000, i.e. going back up to 1000 days from today).

Filters

from shoten.filters import *

• hapax_filter(myvocab, freqcount=2): (default frequency: <= 2)

• shortness_filter(myvocab, threshold=20): length threshold in percent of word lengths

• frequency_filter(myvocab, max_perc=50, min_perc=.001): maximum and minimum frequencies in percent

• oldest_filter(myvocab, threshold=50): discard the oldest words (threshold in percent)

• freshness_filter(myvocab, percentage=10): keep the X% freshest words

• ngram_filter(myvocab, threshold=90, verbose=False): retains X% words based on character n-gram frequencies; runs out of memory if the vocabulary is too large (8 GB RAM recommended)

• sources_freqfilter(myvocab, threshold=2): remove words which are only present in less than x sources

• sources_filter(myvocab, myset): only keep the words for which the source contains a string listed in the input set

• wordlist_filter(myvocab, mylist, keep_words=False): keep or discard words present in the input list

Reduce vocabulary size with a filter:

myvocab = oldest_filter(myvocab)

They can be chained:

myvocab = oldest_filter(shortness_filter(myvocab))

Output

# print one-by-one
for word in sorted(myvocab):
    print(word)
# transfer to a list
results = [w for w in myvocab]

CLI

shoten --help

Additional information

Shoten = focal point in Japanese (焦点).

Project webpage: Webmonitor.