py-data-viewer 0.0.6

A python library to display data structure values for easier navigation and exploration.

Py-Data-Viewer

py-data-viewer is a Python library designed to help mushroom people (like me) explore and navigate complex data structures with ease. It provides a clear view of nested dictionaries, lists, objects, and more, making debugging and data analysis more efficient. Trees for complex data structures, Trees for simple data structures, Trees for everything!!

No more confusion with complex data structures or asking "what's inside this dictionary!?"

from py_data_viewer import vprint

async def some_async_fn():
    response = await some_api_call()
    vprint(response)

No more looking for properties in a long list of dictionaries or objects!

Features

• Tree View: Visualize data structures as a tree for better clarity.
• Colorized Output: Easily distinguish different parts of the data structure.
• Supports Multiple Data Types: Works with dictionaries, lists, objects, namedtuples, and mixed structures.
• API Response Exploration: Simplifies debugging and understanding of API responses, especially for complex outputs.
• Programmatic Usage: Integrate directly into your Python scripts with the vprint function.

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Installation

To install the package, use pip:

pip install py-data-viewer

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Usage

Programmatic Usage with vprint

The vprint function is the easiest way to explore data structures in your Python scripts. It provides a tree-like visualization of your data, making it ideal for debugging API responses, especially from frameworks!

Example: Exploring an API Response

from py_data_viewer import vprint

# Simulated API response
response = {
    "chat_message": {
        "source": "Assistant",
        "content": "This is a response from an LLM.",
        "metadata": {},
    },
    "inner_messages": [
        {
            "type": "ToolCallRequestEvent",
            "content": [{"name": "search", "arguments": '{"query":"example"}'}],
        },
        {
            "type": "ToolCallExecutionEvent",
            "content": [{"name": "search", "content": "Search result here."}],
        },
    ],
}

vprint(response, var_name="response")

Output:

response
├── response.chat_message = dict with 3 items
│   ├── response.chat_message.source = 'Assistant'
│   ├── response.chat_message.content = 'This is a response from an LLM.'
│   └── response.chat_message.metadata = dict with 0 items
└── response.inner_messages = list with 2 items
    ├── response.inner_messages[0] = dict with 2 items
    │   ├── response.inner_messages[0].type = 'ToolCallRequestEvent'
    │   └── response.inner_messages[0].content = list with 1 items
    │       └── response.inner_messages[0].content[0] = dict with 2 items
    │           ├── response.inner_messages[0].content[0].name = 'search'
    │           └── response.inner_messages[0].content[0].arguments = '{"query":"example"}'
    └── response.inner_messages[1] = dict with 2 items
        ├── response.inner_messages[1].type = 'ToolCallExecutionEvent'
        └── response.inner_messages[1].content = list with 1 items
            └── response.inner_messages[1].content[0] = dict with 2 items
                ├── response.inner_messages[1].content[0].name = 'search'
                └── response.inner_messages[1].content[0].content = 'Search result here.'

Example: Exploring a Complex Data Structure

from py_data_viewer import vprint

data = {
    "user": {"id": 1, "name": "Alice"},
    "actions": [
        {"type": "login", "timestamp": "2023-01-01T12:00:00Z"},
        {"type": "purchase", "details": {"item": "book", "price": 12.99}},
    ],
}

vprint(data, var_name="data", tree_view=True)

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Advanced Options

The vprint function supports several options to customize the output:

• var_name: Specify the variable name to display in the output.
• indent_size: Set the number of spaces for indentation (default: 2).
• colorize: Enable or disable colorized output (default: True).

Example:

vprint(data, var_name="custom_data_name", indent_size=4, colorize=False)

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Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Commit your changes and push the branch.
4. Open a pull request.

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License

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

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Links

• Homepage: GitHub Repository
• Issues: Report Issues