telelog-python 0.3.0

High-performance structured logging library with component tracking and visualization

Telelog is a Rust-first logging library that combines structured logging, performance profiling, and architectural visualization. It provides rich console output and generates Mermaid diagrams to help you understand your application's execution flow.

Features

• Performance Profiling - Automatic timing with RAII guards and context managers
• Component Tracking - Track architectural components and their relationships
• Visualization - Generate Mermaid flowcharts, timelines, and Gantt charts
• Context Management - Add persistent context to all log messages
• Rich Console Output - Clean, colored output for development
• Python Bindings - Use from Python with Rust-backed performance
• Type Hints - Full static type checking support for Python (mypy, pyright)
• High Performance - Thread-local buffer pooling reduces allocations (~788ns per log)
• Async Support - Bounded async channels with backpressure (requires async feature)

Example Visualizations

Quick Start

Rust

use telelog::Logger;

let logger = Logger::new("my_app");

// Basic logging
logger.info("Application started");
logger.warning("This is a warning");

// Context management
logger.add_context("user_id", "12345");
logger.info("Processing request"); // Includes context

// Performance profiling
{
    let _timer = logger.profile("database_query");
    // Your operation here
} // Automatically logs duration

// Component tracking
{
    let _component = logger.track_component("web_server");
    logger.info("Handling request");
}

Python

# Install via pip
pip install telelog-python

import telelog as tl

logger = tl.Logger("my_app")

# Basic logging with context
logger.add_context("user_id", "12345")
logger.info("Processing request")

# Performance profiling
with logger.profile("database_query"):
    # Your operation here
    pass

# Component tracking with visualization
with logger.track_component("data_pipeline"):
    logger.info("Processing data")

# Generate flowchart
chart = logger.generate_visualization("flowchart")
print(f"Generated chart with {len(chart)} characters")

Visualization

Generate Mermaid diagrams from component tracking:

use telelog::{Logger, MermaidGenerator, ChartConfig, ChartType};

let logger = Logger::new("app");

// Track nested components
{
    let _pipeline = logger.track_component("data_pipeline");
    {
        let _extract = logger.track_component("extract");
        // extraction logic
    }
    {
        let _transform = logger.track_component("transform");
        // transformation logic
    }
}

// Generate visualization
let tracker = logger.get_component_tracker();
let config = ChartConfig::new().with_chart_type(ChartType::Flowchart);
let generator = MermaidGenerator::new(config);
let diagram = generator.generate_diagram(tracker)?;

Supported chart types:

• Flowchart - Component relationships and dependencies
• Timeline - Execution order and timing
• Gantt - Component durations and overlaps

View generated diagrams at mermaid.live or in VS Code with the Mermaid extension.

Documentation

📖 Comprehensive documentation is available in the Telelog Wiki

The wiki includes:

• Getting started guides for both Rust and Python
• Detailed feature documentation (profiling, component tracking, visualization)
• Configuration and customization guides
• Cookbook with real-world examples
• Framework integration guides (Flask, FastAPI, Axum, Actix, etc.)
• Complete API references
• Migration guides from other logging libraries
• Troubleshooting and FAQ

Examples

See the examples/ directory for comprehensive usage examples in both Rust and Python.

# Try the examples
cargo run --example 01_basic_logging
cargo run --example 04_component_tracking
cargo run --example 05_visualization

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. See the examples directory for comprehensive usage patterns.

License

This project is licensed under the MIT License.

Built with ❤️ by Vedant Asati