Generate stylistic wordclouds, including gradients and icon shapes!
stylecloud is a Python package that leverages the popular word_cloud package, adding useful features to create truly unique word clouds!
- Icon shapes (of any size!) for wordclouds (via Font Awesome 5.13.0 Free, or your own Font Awesome Pro)
- Support for advanced color palettes (via palettable)
- Manual color selection for text and backgrounds,
- Directional gradients w/ the aforementioned palettes.
- Supports reading text files and CSVs (either one-column w/ texts, or two columns w/ words+weights).
- Command Line Interface!
This package is a more formal implementation of my stylistic word cloud project from 2016.
You can install stylecloud via pip:
pip3 install stylecloudYou can use stylecloud in a Python script or as a standalone CLI app. For example, let's say you have a text of the U.S. Constitution constitution.txt.
Python script:
import stylecloud
stylecloud.gen_stylecloud(file_path='constitution.txt')
But you can do so much more! You can use the free Font Awesome icons to change the shape, change the color palette to one from palettable for a custom style, change the background color, and, most importantly, add a gradient so the colors flow in a specified direction!
import stylecloud
stylecloud.gen_stylecloud(file_path='constitution.txt',
icon_name='fas fa-dog',
palette='colorbrewer.diverging.Spectral_11',
background_color='black',
gradient='horizontal')
You can also use the CLI for even faster stylecloud generation! For the simple flag stylecloud above:
stylecloud --file_path constitution.txtFor the more complex dog-gradient stylecloud:
stylecloud --file_path constitution.txt --icon_name 'fas fa-dog' --palette colorbrewer.diverging.Spectral_11 --background_color black --gradient horizontalYou can find more examples of styleclouds, including how to make styleclouds from Twitter and Reddit data, in the stylecloud-examples repo.
You can manually specify the color(s) of the text with the colors parameter, overriding the palettes. This can be useful for specific branding, or high-contrast visualizations. However, manual color selection will not work with gradients.
import stylecloud
stylecloud.gen_stylecloud(file_path='constitution.txt',
colors=['#ecf0f1', '#3498db', '#e74c3c'],
background_color='#1A1A1A')stylecloud --file_path constitution.txt --colors "['#ecf0f1', '#3498db', '#e74c3c']" --background_color '#1A1A1A'
In order to filter out stopwords in non-English languages or use custom stopwords, you can pass a list of words to the custom_stopwords parameter:
import stylecloud
my_long_list = ["thereof", "may", "state", "united states"]
stylecloud.gen_stylecloud(file_path='constitution.txt',
custom_stopwords=my_long_list)stylecloud --file_path constitution.txt --custom_stopwords "[thereof, may, state, united states]"Good resources for stopwords in other languages are the stop-words Python package and the ISO stopword collections.
These parameters are valid for both the Python function and the CLI (you can use stylecloud -h to get this information as well).
- text: Input text. Best used if calling the function directly.
- file_path: File path of the input text/CSV. Best used on the CLI.
- gradient: Direction of gradient. (if not None, the stylecloud will use a directional gradient) [default:
None] - size: Size (length and width in pixels) of the stylecloud, or a two-element tuple representing the width and height of the stylecloud (e.g.
'(1024, 512)'for a 1024x512 stylecloud). [default:512] - icon_name: Icon Name for the stylecloud shape. (e.g. 'fas fa-grin') [default:
fas fa-flag] - palette: Color palette (via palettable) [default:
cartocolors.qualitative.Bold_5] - colors: Color(s) to use as the text colors. Overrides both gradient and palette if specified [default:
None] - background_color: Background color (name or hex) [default:
white] - max_font_size: Maximum font size in the stylecloud. [default:
200] - max_words: Maximum number of words to include in the stylecloud. [default:
2000] - stopwords: Boolean to filter out common stopwords. [default:
True] - custom_stopwords: list of custom stopwords. e.g: For other languages than english [default:
STOPWORDS, viaword_cloud] - output_name: Output file name of the stylecloud. [default:
stylecloud.png] - font_path: Path to .ttf file for font to use in stylecloud. [default: uses included Staatliches font]
- random_state: Controls random state of words and colors. [default:
None] - collocations: Whether to include collocations (bigrams) of two words. Same behavior as base
word_cloudpackage. [default:True] - invert_mask: Whether to invert the icon mask, so the words fill the space except the icon mask. [default:
False] - pro_icon_path: Path to Font Awesome Pro .ttf file if using FA Pro. [default:
None] - pro_css_path: Path to Font Awesome Pro .css file if using FA Pro. [default:
None]
- The primary goal of this package is to create data visualizations of text that provide a unique aesthetic. Word clouds have tradeoffs in terms of a statistically robust data visualization, but this is explicitly prioritizing coolness!
- This package is released as a separate package from
word_clouddue to the increase in scope and Python dependencies. - The ideal fonts for generating a good stylecloud are a) bold/high weight in order to increase readability, and b) condensed/low kerning to fit more text. Both of these traits are why Staatliches is the default font for stylecloud (overriding Droid Sans in the base
word_cloud). - You may want to consider doing post-processing after generating a stylecloud: for example, adding color masks, adding perception skew, feed it to a style transfer AI model, etc.
- The default
max_font_sizeof200is calibrated for the defaultsizeof512. If you increase thesize, you may want to consider increasingmax_font_sizeas well. - Due to the size of the included Font Awesome font files, they will not be updated on every new minor FA release.
- It's recommended to use FA icons which are large with heavy weight; thin icons might constrain the text too much.
- If using the default random-color-sampling method, it's recommended to use a qualitative palette. Inversely, if using a gradient, it's recommended to use a nonqualitative palette (e.g. a sequential palette).
- twcloud — Python package + CLI to generate wordclouds of Twitter tweets.
Max Woolf (@minimaxir)
Max's open-source projects are supported by his Patreon and GitHub Sponsors. If you found this project helpful, any monetary contributions to the Patreon are appreciated and will be put to good creative use.
MIT
Font Awesome icon font files included per the terms in its SIL OFL 1.1 License.
Staatliches font included per the terms in its SIL OFL 1.1 License.
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