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# WordCloud
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A comprehensive Python library for generating word cloud visualizations from text data. WordCloud enables the creation of visually appealing word clouds with advanced features including arbitrary shape masking, intelligent word placement algorithms, customizable color schemes, and multi-language support.
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## Package Information
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- **Package Name**: wordcloud
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- **Language**: Python
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- **Installation**: `pip install wordcloud`
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- **Dependencies**: numpy, pillow, matplotlib
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## Core Imports
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```python
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from wordcloud import WordCloud
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```
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Common imports for full functionality:
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```python
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from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator
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from wordcloud import random_color_func, get_single_color_func
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```
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## Basic Usage
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```python
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from wordcloud import WordCloud
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import matplotlib.pyplot as plt
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# Simple word cloud from text
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text = "Python programming is fun and exciting. Python is powerful and easy to learn."
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# Generate word cloud
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wordcloud = WordCloud(width=800, height=400, background_color='white').generate(text)
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# Display using matplotlib
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plt.figure(figsize=(10, 5))
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plt.imshow(wordcloud, interpolation='bilinear')
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plt.axis('off')
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plt.show()
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# Save to file
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wordcloud.to_file('wordcloud.png')
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```
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## Architecture
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WordCloud uses a collision-free placement algorithm based on integral image queries to efficiently position words without overlap. The core components include:
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- **WordCloud Class**: Main interface for generating and rendering word clouds
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- **Text Processing**: Tokenization, stopword filtering, and frequency analysis
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- **Layout Engine**: Collision detection and word placement using integral images
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- **Color Generation**: Multiple color schemes including random, single-color, and image-based
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- **Rendering**: Support for multiple output formats (PIL Image, numpy array, PNG, SVG)
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## Capabilities
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### Core Word Cloud Generation
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Primary functionality for creating word clouds from text or frequency data, with comprehensive customization options for appearance, layout, and text processing.
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```python { .api }
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class WordCloud:
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def __init__(self, font_path=None, width=400, height=200, **kwargs): ...
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def generate(self, text): ...
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def generate_from_frequencies(self, frequencies, max_font_size=None): ...
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def to_image(self): ...
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def to_file(self, filename): ...
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```
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[Core Generation](./core-generation.md)
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### Color Generation and Styling
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Advanced color customization including random colors, single-color variations, matplotlib colormap integration, and image-based color extraction for sophisticated styling.
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```python { .api }
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def random_color_func(**kwargs): ...
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def get_single_color_func(color): ...
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class ImageColorGenerator:
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def __init__(self, image, default_color=None): ...
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```
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[Color Generation](./color-generation.md)
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### Text Processing and Tokenization
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Text analysis capabilities including tokenization, stopword filtering, plural normalization, and statistical bigram detection for meaningful phrase extraction.
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```python { .api }
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# Import from wordcloud.tokenization
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def unigrams_and_bigrams(words, stopwords, normalize_plurals=True, collocation_threshold=30): ...
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def process_tokens(words, normalize_plurals=True): ...
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```
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[Text Processing](./text-processing.md)
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### Command Line Interface
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Complete command-line tool with comprehensive options for generating word clouds directly from text files with full parameter control and input/output redirection support.
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```python { .api }
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def main(args, text, imagefile): ...
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def parse_args(arguments): ...
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```
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[Command Line Interface](./cli-interface.md)
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## Constants and Utilities
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```python { .api }
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STOPWORDS: set[str] # Default English stopwords set
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FONT_PATH: str # Default font file path (DroidSansMono.ttf)
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```
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The `STOPWORDS` constant provides a comprehensive set of common English words to filter from word cloud generation.
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The `FONT_PATH` constant provides the default path to the DroidSansMono font file used when no custom font is specified.