colab-print 0.1.0.post1

Enhanced display utilities for Jupyter/Colab notebooks with customizable styles

Colab Print

Colab Print is a Python library that enhances the display capabilities of Jupyter and Google Colab notebooks, providing beautiful, customizable HTML outputs for text, lists, dictionaries, tables, and pandas DataFrames.

Features

• 🎨 Rich Text Styling - Display text with predefined styles or custom CSS
• 📊 Beautiful DataFrame Display - Present pandas DataFrames with extensive styling options
• 📑 Customizable Tables - Create HTML tables with headers, rows, and custom styling
• 📜 Formatted Lists - Display Python lists and tuples as ordered or unordered HTML lists.
• 📖 Readable Dictionaries - Render dictionaries as structured definition lists.
• 🎭 Extensible Themes - Use built-in themes or create your own custom styles
• 📏 Smart Row/Column Limiting - Automatically display large DataFrames with sensible limits
• 🔍 Cell Highlighting - Highlight specific rows, columns, or individual cells in tables and DataFrames
• 🔄 Graceful Fallbacks - Works even outside Jupyter/IPython environments

Installation

pip install colab-print

Quick Start

from colab_print import Printer
import pandas as pd

# Create a printer with default styles
printer = Printer()

# Display styled text
printer.display("Hello, World!", style="highlight")

# Display a list
my_list = ['apple', 'banana', ['nested', 'item'], 'cherry']
printer.display_list(my_list, ordered=True, style="info")

# Display a dictionary
my_dict = {
    'name': 'Alice', 
    'age': 30, 
    'address': {'street': '123 Main St', 'city': 'Anytown'}
}
printer.display_dict(my_dict, style="success")

# Display a simple table
headers = ["Name", "Age", "City"]
rows = [
    ["Alice", 28, "New York"],
    ["Bob", 34, "London"],
    ["Charlie", 22, "Paris"]
]
printer.display_table(headers, rows, style="default")

# Display a pandas DataFrame with styling
df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [28, 34, 22],
    'City': ['New York', 'London', 'Paris']
})
printer.display_df(df, 
                  highlight_cols=['Name'],
                  highlight_cells={(0, 'Age'): "background-color: #FFEB3B;"},
                  caption="Sample DataFrame")

Styling Options

Predefined Styles

• default - Clean, professional styling
• highlight - Stand-out text with emphasis
• info - Informational blue text
• success - Positive green message
• warning - Attention-grabbing yellow alert
• error - Critical red message
• muted - Subtle gray text

Custom Styling

You can add your own styles:

printer = Printer()
printer.add_style("custom", "color: purple; font-size: 20px; font-weight: bold;")
printer.display("Custom styled text", style="custom")

Display Methods

• printer.display(text, style="default", **inline_styles): Displays styled text.
• printer.display_list(items, ordered=False, style="default", item_style=None, **inline_styles): Displays lists/tuples.
• printer.display_dict(data, style="default", key_style=None, value_style=None, **inline_styles): Displays dictionaries.
• printer.display_table(headers, rows, style="default", **table_options): Displays basic tables.
• printer.display_df(df, style="default", **df_options): Displays pandas DataFrames with many options.

DataFrame Display Options

The display_df method supports numerous customization options:

printer.display_df(df,
                  style='default',           # Base style
                  max_rows=20,               # Max rows to display
                  max_cols=10,               # Max columns to display
                  precision=2,               # Decimal precision for floats
                  header_style="...",        # Custom header styling
                  odd_row_style="...",       # Custom odd row styling
                  even_row_style="...",      # Custom even row styling
                  index=True,                # Show index
                  width="100%",              # Table width
                  caption="My DataFrame",    # Table caption
                  highlight_cols=["col1"],   # Highlight columns
                  highlight_rows=[0, 2],     # Highlight rows
                  highlight_cells={(0,0): "..."}, # Highlight specific cells
                  font_size="14px",          # Custom font size for all cells
                  text_align="center")       # Text alignment for all cells

Advanced Usage

Creating Custom Themes

custom_themes = {
    'dark': 'color: white; background-color: #333; font-size: 16px;',
    'fancy': 'color: #8A2BE2; font-family: "Brush Script MT", cursive; font-size: 20px;'
}

printer = Printer(additional_styles=custom_themes)
printer.display("Dark theme", style="dark")
printer.display("Fancy theme", style="fancy")

Handling Non-Notebook Environments

The library gracefully handles non-IPython environments by printing fallback text representations:

# This will work in regular Python scripts
printer.display_list([1, 2, 3])
printer.display_dict({'a': 1})
printer.display_df(df)

Full Examples

For a comprehensive demonstration of all features, please see the example script:

example.py

This script covers:

• Text, List, Dictionary, Table, and DataFrame display
• Using built-in styles and inline styles
• Adding custom styles
• Creating a Printer instance with custom themes
• Highlighting options for DataFrames
• Fallback behavior notes (though the script runs outside a notebook)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.