skillfed

wordcloud

A little word cloud generator

wordcloud v1.9.6 5.9M downloads/30d#2,021 on PyPI10,537
Permissive license MIT AGING released

What it is and what it does

wordcloud is a Python library that transforms text input into visual word clouds—images where words are rendered at sizes proportional to their frequency in the source text. It wraps numpy, pillow, and matplotlib to handle the computational and rendering work. The package is straightforward to use: instantiate a WordCloud object, call generate() with your text, and display the result via matplotlib or save it as an image file.

The library supports command-line usage via wordcloud_cli for direct generation from text files or piped input (e.g., from pdftotext), making it useful for quick one-off visualizations. It allows customization of colors, fonts, dimensions, and masking shapes. The core dependency on compiled C extensions means installation may require a C compiler on platforms without pre-built wheels, though wheels are available for recent Python versions on standard architectures.

Use it for:

  • Generate visual summaries of document or article text to quickly identify dominant themes and word frequency patterns.
  • Create word clouds from social media feeds, survey responses, or user-generated content for exploratory data analysis.
  • Produce publication-ready visualizations for reports, presentations, or blog posts showing text emphasis and topic prominence.
  • Batch-process multiple text files via the command-line tool to generate word clouds without writing Python code.
  • Analyze multilingual text (e.g., Arabic) by configuring appropriate fonts and language settings.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Generates word cloud visualizations from text input, displaying word frequency as varying text sizes in a graphical image.

Yes, if you need straightforward word cloud visualization. The package is stable, permissively licensed, and widely used (top 5000 on PyPI). Install friction is moderate due to C compilation requirements on some platforms, but wheels cover common Python versions and architectures. Maintenance is aging but the library is mature and has no known vulnerabilities. Suitable for exploratory text analysis, reporting, and publication graphics.

Install

wordcloud on PyPI

pip

pip install wordcloud

uv

uv add wordcloud

poetry

poetry add wordcloud

Installing wordcloud

Before you install

Medium install friction due to compiled C extensions; pre-built wheels available for Python 3.10–3.12 on common platforms (macOS, Linux, Windows). Requires a C compiler if wheels unavailable for your Python version. Aging maintenance status with last commit 2026-01-22 and no recent activity.

License in practice

MIT-licensed with permissive terms. Package includes DroidSansMono.ttf, an Apache-licensed Google font that is optional and can be replaced by setting font_path.

Quickstart

pip install wordcloud

from wordcloud import WordCloud
import matplotlib.pyplot as plt

wc = WordCloud().generate('your text here')
plt.imshow(wc)
plt.show()

Requires numpy, pillow, and matplotlib. If no wheel is available for your Python version and OS, a C compiler must be installed before pip install will succeed.

Verify before relying

  • Whether the aging maintenance status (last commit 2026-01-22, no recent activity) affects bug fixes or compatibility with newer Python/library versions.
  • Performance characteristics and memory usage for very large text inputs or high-resolution output images.

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.9)
Install friction medium — platform-specific wheel
Runtime dependencies 3 — numpy, pillow, matplotlib
Maintenance aging — 204 days since the last release
Last repo commit
First released
Downloads 5,869,157/month — #2,021 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: wordcloud-1.9.6-cp310-cp310-macosx_10_9_x86_64.whl; wordcloud-1.9.6-cp310-cp310-macosx_11_0_arm64.whl; wordcloud-1.9.6-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; wordcloud-1.9.6-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; wordcloud-1.9.6-cp310-cp310-musllinux_1_2_aarch64.whl; wordcloud-1.9.6-cp310-cp310-musllinux_1_2_x86_64.whl; wordcloud-1.9.6-cp310-cp310-win32.whl; wordcloud-1.9.6-cp310-cp310-win_amd64.whl; wordcloud-1.9.6-cp311-cp311-macosx_10_9_x86_64.whl; wordcloud-1.9.6-cp311-cp311-macosx_11_0_arm64.whl; wordcloud-1.9.6-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; wordcloud-1.9.6-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; wordcloud-1.9.6-cp311-cp311-musllinux_1_2_aarch64.whl; wordcloud-1.9.6-cp311-cp311-musllinux_1_2_x86_64.whl; wordcloud-1.9.6-cp311-cp311-win32.whl; wordcloud-1.9.6-cp311-cp311-win_amd64.whl; wordcloud-1.9.6-cp312-cp312-macosx_10_13_x86_64.whl; wordcloud-1.9.6-cp312-cp312-macosx_11_0_arm64.whl; wordcloud-1.9.6-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; wordcloud-1.9.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Tags

word cloud generatortext visualization frequencyword frequency imagetext to word cloudvisualize word frequencyword cloud from textgenerate word clouds
text-visualizationdata-exploration

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