All Projects → johnbumgarner → wordhoard

johnbumgarner / wordhoard

Licence: MIT license
This Python module can be used to obtain antonyms, synonyms, hypernyms, hyponyms, homophones and definitions.

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to wordhoard

wn
A modern, interlingual wordnet interface for Python
Stars: ✭ 119 (+52.56%)
Mutual labels:  dictionary, wordnet, lexicon, wordnets
node-thesaurus-com
Look up synonyms/antonyms on thesaurus.com.
Stars: ✭ 17 (-78.21%)
Mutual labels:  synonyms, antonyms
gf-wordnet
A WordNet in GF
Stars: ✭ 15 (-80.77%)
Mutual labels:  wordnet, lexicon
langua
A suite of language tools
Stars: ✭ 29 (-62.82%)
Mutual labels:  dictionary, lexicon
syn
syn - the thesaurus
Stars: ✭ 45 (-42.31%)
Mutual labels:  synonyms, antonyms
Wordbook
Wordbook is a dictionary application built for GNOME.
Stars: ✭ 56 (-28.21%)
Mutual labels:  dictionary, wordnet
Safarikai
Safari extension for translating Japanese words.
Stars: ✭ 177 (+126.92%)
Mutual labels:  dictionary
Fairydict
FairyDict, a dictionary, a chrome extension
Stars: ✭ 206 (+164.1%)
Mutual labels:  dictionary
Emoji Ime Dictionary
日本語で絵文字入力をするための IME 追加辞書 📙 Google 日本語入力などで日本語から絵文字への変換を可能にする IME 拡張辞書です
Stars: ✭ 172 (+120.51%)
Mutual labels:  dictionary
Wiktextract
Wiktionary dump file parser and multilingual data extractor
Stars: ✭ 170 (+117.95%)
Mutual labels:  dictionary
Nonblocking
Implementation of a lock-free dictionary on .Net.
Stars: ✭ 237 (+203.85%)
Mutual labels:  dictionary
Core
Elm's core libraries
Stars: ✭ 2,634 (+3276.92%)
Mutual labels:  dictionary
Isearch
有道词典 命令行查询 柯林斯词典 单词管理 本地保存
Stars: ✭ 201 (+157.69%)
Mutual labels:  dictionary
Zydra
Stars: ✭ 178 (+128.21%)
Mutual labels:  dictionary
Python Benedict
dict subclass with keylist/keypath support, I/O shortcuts (base64, csv, json, pickle, plist, query-string, toml, xml, yaml) and many utilities. 📘
Stars: ✭ 204 (+161.54%)
Mutual labels:  dictionary
Ordereddictionary
Ordered dictionary data structure implementation in Swift
Stars: ✭ 176 (+125.64%)
Mutual labels:  dictionary
Collectable
High-performance immutable data structures for modern JavaScript and TypeScript applications. Functional interfaces, deep/composite operations API, mixed mutability API, TypeScript definitions, ES2015 module exports.
Stars: ✭ 233 (+198.72%)
Mutual labels:  dictionary
Sdcv
Stars: ✭ 171 (+119.23%)
Mutual labels:  dictionary
Richelieu
List of the most common French passwords
Stars: ✭ 199 (+155.13%)
Mutual labels:  dictionary
Vocabs
📚 A lightweight online dictionary integration to the command line. No browsers. No paperbacks.
Stars: ✭ 226 (+189.74%)
Mutual labels:  dictionary

Overviews

PyPI   License: MIT  GitHub issues  GitHub pull requests  Downloads 

Primary Use Case

Textual analysis is a broad term for various research methodologies used to qualitatively describe, interpret and understand text data. These methodologies are mainly used in academic research to analyze content related to media and communication studies, popular culture, sociology, and philosophy. Textual analysis allows these researchers to quickly obtain relevant insights from unstructured data. All types of information can be gleaned from textual data, especially from social media posts or news articles. Some of this information includes the overall concept of the subtext, symbolism within the text, assumptions being made and potential relative value to a subject (e.g. data science). In some cases it is possible to deduce the relative historical and cultural context of a body of text using analysis techniques coupled with knowledge from different disciplines, like linguistics and semiotics.

Word frequency is the technique used in textual analysis to measure the frequency of a specific word or word grouping within unstructured data. Measuring the number of word occurrences in a corpus allows a researcher to garner interesting insights about the text. A subset of word frequency is the correlation between a given word and that word's relationship to either antonyms and synonyms within the specific corpus being analyzed. Knowing these relationships is critical to improving word frequencies and topic modeling.

WordHoard was designed to assist researchers performing textual analysis to build more comprehensive lists of antonyms, synonyms, hypernyms, hyponyms and homophones.

Installation

Install the distribution via pip:

pip3 install wordhoard

General Package Utilization

Please reference the WordHoard Documentation for package usage guidance and parameters.

Sources

This package is currently designed to query these online sources for antonyms, synonyms, hypernyms, hyponyms and definitions:

  1. classicthesaurus.com
  2. collinsdictionary.com
  3. merriam-webster.com
  4. synonym.com
  5. thesaurus.com
  6. wordhippo.com
  7. wordnet.princeton.edu

Dependencies

This package has these core dependencies:

  1. backoff
  2. BeautifulSoup
  3. deckar01-ratelimit
  4. deepl
  5. lxml
  6. requests
  7. urllib3

Additional details on this package's dependencies can be found here.

Development Roadmap

If you would like to contribute to the WordHoard project please read the contributing guidelines.

Items currently under development:

  • Expanding the list of hypernyms, hyponyms and homophones
  • Adding part-of-speech filters in queries

Issues

This repository is actively maintained. Feel free to open any issues related to bugs, coding errors, broken links or enhancements.

You can also contact me at John Bumgarner with any issues or enhancement requests.

Sponsorship

If you would like to contribute financially to the development and maintenance of the WordHoard project please read the sponsorship information.

License

The MIT License (MIT). Please see License File for more information.

Author

Copyright (c) 2020 John Bumgarner

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].