Welcome to You Need a Dictionary

Summary

You Need a Dictionary is a project that goes beyond simple translation and word definitions. It’s an interactive tool for exploring how language choices shape meaning and sentiment. Users can analyze sentences, experiment with word substitutions, and visualize the emotional impact of their linguistic decisions. This tool assists writers and data scientists in understanding how specific vocabulary changes the sentiment and meaning of their text.

List of Functions

• analyze_sentiment: Analyzes the preprocessed text using NLP techniques to derive a sentiment polarity score, helping users understand the emotional tone of their input.
• fetch_definition: Module that fetches the definition, synonyms and antonyms of a given word using WordNet
• word_replacement: Replaces a specific word in the user’s sentence with a synonym or antonym specified by the user and automatically re-runs the sentiment analysis to compare the emotional shift in polarity score.
• translate_sentence: Translates the entire input sentence into a target language using LibreTranslate.
• create_wordcloud: Generates a visual word cloud of synonyms and antonyms for a specific word, providing a pictorial representation of related words.

Documentation

Full documentation, tutorials, and examples are available on the project website.

You Need a Dictionary's Relevance to the Python Ecosystem:

There are several existing Python packages for NLP and dictionary lookups, such as PyDictionary for definitions and TextBlob or NLTK for sentiment analysis. However, You Need a Dictionary fills a specific gap by integrating these functionalities into a single workflow. Rather than returning isolated outputs like a sentiment score from TextBlob or a standalone definition from PyDictionary, our package provides a cohesive experience providing insight into both the meaning of a word and its impact on the sentiment of a sentence. You Need a Dictionary also enables users to experiment how substituting a single word within a sentence can shift the overall sentiment, making it especially valuable for linguists, writers, and developers who need to understand not just what a word means, but how its replacement alters the emotional and semantic impact of text.

Language Codes

The following language codes are supported for translation:

Language codes

Language	Code
Albanian	sq
Arabic	ar
Azerbaijani	az
Basque	eu
Bengali	bn
Bulgarian	bg
Catalan	ca
Chinese (traditional)	zt
Chinese	zh
Czech	cs
Danish	da
Dutch	nl
English	en
Esperanto	eo
Estonian	et
Finnish	fi
French	fr
Galician	gl
German	de
Greek	el
Hebrew	he
Hindi	hi
Hungarian	hu
Indonesian	id
Irish	ga
Italian	it
Japanese	ja
Korean	ko
Kyrgyz	ky
Latvian	lv
Lithuanian	lt
Malay	ms
Norwegian	nb
Persian	fa
Polish	pl
Portuguese	pt
Portuguese (Brazil)	pb
Romanian	ro
Russian	ru
Slovak	sk
Slovenian	sl
Spanish	es
Swedish	sv
Tagalog	tl
Thai	th
Turkish	tr
Ukranian	uk
Urdu	ur
Vietnamese	vi

Get started

You can install this package into your preferred Python environment using pip:

pip install -i https://test.pypi.org/simple/ you-need-a-dictionary

For more information, you can find the package on Test-PyPi here.

Example usage in Python:

import you_need_a_dictionary as ynd
nltk.download('vader_lexicon')
nltk.download('wordnet')
ynd.analyze_sentiment("I love programming!")

The model returns a sentiment label and a confidence score. A higher score means the model is more confident in its prediction.

{
  "neg": 0.0,
  "neu": 0.182,
  "pos": 0.818,
  "compound": 0.6696
}

Dev notes

To contribute to the development of this package, please follow these steps after cloning the repository: Set up a virtual environment using conda:

conda env create -f environment.yml
conda activate you_need_a_dictionary

To install the package locally:

pip install -e .

To test the package locally: Open a terminal in the project root directory and run:

pip install -e .[tests] # setup test dependencies
pytest

To build documentation locally:

pip install -e .[docs] # setup documentation dependencies
quartodoc --build
quarto render

To determine package version:

pip install -e .[dev]
hatch build
python
import you_need_a_dictionary as ynd
ynd.__version__

Contributors

• Eric Wong
• Mailys Guedon
• Godsgift Braimah
• Mara Sanchez

Copyright

• Copyright © 2026 Mailys Guedon, Mara Sanchez, Godsgift Braimah, Eric Wong.
• Free software distributed under the MIT License.