MIT License

项目介绍

DogukanUrker/Tamga 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 MIT License 许可证,目前获得 71 个 Star、2 次 Fork。

仓库全名
DogukanUrker/Tamga
开源许可证
MIT License
Star 数
71
Fork 数
2
未关闭 Issue
1

README 摘要

A modern, high-performance logging utility for Python with multiple output formats and colorful console output. 🤖 AI Integration: For AI/LLM integration, see LLMs.txt or access documentation directly via Context7 tam·ga /ˈtæmɡə/ · noun An ancient Turkic symbol or seal used for marking ownership, identity, or lineage. ✨ Features 🎨 Beautiful Console Output - Colorful, formatted logs using Tailwind CSS colors ⚡ High…

完整内容见 GitHub 原始 README 或本页 。

常见问题

Tamga 用什么语言开发?

主要使用 Python 编写,采用 MIT License 许可证,目前有 71 个 Star。

Tamga 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 Tamga 的源码?

可以直接克隆仓库:git clone https://github.com/DogukanUrker/Tamga.git,默认分支为 main;安装与运行步骤见仓库 README。

Tamga 最近还在维护吗?

仓库最近一次更新为 7月21日,当前有 1 个未关闭 Issue;Star 数为 71,可作为社区活跃度的参考。

关于

A modern, high-performance logging utility for Python with multiple output formats and colorful console output.

描述取自 GitHub 官方 API,中文内容由 GitRead 中文社区 编辑团队整理。

简要分析

热度分
76
价值分
43
活跃状态
活跃

语言占比

Python

Release

README

Tamga PyPI Downloads

A modern, high-performance logging utility for Python with multiple output formats and colorful console output.

Installation

🤖 AI Integration: For AI/LLM integration, see LLMs.txt or access documentation directly via Context7

tam·ga /ˈtæmɡə/ · noun An ancient Turkic symbol or seal used for marking ownership, identity, or lineage.

Terminal

✨ Features

  • 🎨 Beautiful Console Output - Colorful, formatted logs using Tailwind CSS colors
  • ⚡ High Performance - Buffered writing system (10x faster than traditional logging)
  • 📊 Multiple Outputs - Console, file, JSON, SQLite, MongoDB
  • 🔄 Automatic Rotation - File size management with backup support
  • 🧵 Thread-Safe - Safe for multi-threaded applications
  • 🔔 Notifications - Multi-service notifications via Apprise (Discord, Slack, Email, SMS, and more)
  • 🔍 Structured Logging - Key-value data support with all log methods

🚀 Quick Start

See examples/simple_usage.py for a full script.

from tamga import Tamga

# Create logger with default settings
logger = Tamga()

# Log messages
logger.info("Application started")
logger.warning("Memory usage at 85%")
logger.error("Failed to connect to API")
logger.success("User registered successfully")
logger.debug("Cache initialized with 1000 entries")

🧑‍💻 Examples

See examples/ for ready-to-run scripts:

  • simple_usage.py — basic logging
  • fastapi_webapp.py — FastAPI integration
  • advanced_config.py — production config
  • high_performance.py — high-speed big data logging demo

📦 Installation

pip install tamga                    # Basic installation
pip install tamga[mongo]             # With MongoDB support
pip install tamga[notifications]     # With notification support
pip install tamga[all]               # All features

🎯 Usage Examples

Basic Configuration

logger = Tamga(
    # Display settings
    colored_output=True,     # Colored output
    show_time=True,          # Include timestamp
    show_timezone=False,     # Include timezone

    # Output destinations
    file_output=True,        # Log to file
    file_path="app.log",     # Log file path
    buffer_size=50,          # Buffer size for performance
)

Structured Logging

# Log with key-value data using any log method
logger.info("User action",
    user_id="123",
    action="login",
    ip_address="192.168.1.1",
    success=True
)

# Works with all log levels
logger.error("Database connection failed",
    host="localhost",
    port=5432,
    timeout=30,
    retry_count=3
)

logger.success("Payment processed",
    amount=99.99,
    currency="USD",
    method="credit_card",
    transaction_id="tx_123"
)

Production Setup

logger = Tamga(
    # File rotation
    file_output=True,
    max_file_size_mb=50,     # 50MB max file size
    enable_backup=True,      # Create backups

    # Performance
    buffer_size=200,         # Larger buffer for production
    console_output=False,    # Disable console for speed

    # External services
    mongo_output=True,
    mongo_uri="mongodb://...",

    # Multi-service notifications
    notify_services=[
        "discord://webhook_id/webhook_token",
        "slack://tokenA/tokenB/tokenC/#alerts",
        "mailto://user:[email protected]:587/[email protected]",
        "twilio://SID:Token@+1234567890/+0987654321",
    ],
    notify_levels=["CRITICAL", "ERROR", "NOTIFY"],
)

📋 Log Levels

Level Color Method Use Case
INFO Sky logger.info() General information
WARNING Amber logger.warning() Warning messages
ERROR Rose logger.error() Error messages
SUCCESS Emerald logger.success() Success messages
DEBUG Indigo logger.debug() Debug information
CRITICAL Red logger.critical() Critical issues
DATABASE Green logger.database() Database operations
NOTIFY Purple logger.notify() Send notifications
METRIC Cyan logger.metric() Performance metrics
TRACE Gray logger.trace() Detailed trace info
CUSTOM Any logger.custom() Custom levels

🔧 Advanced Features

Notifications

# Configure notification services (supports 80+ services via Apprise)
logger = Tamga(
    notify_services=[
        "discord://webhook_id/webhook_token",
        "slack://tokenA/tokenB/tokenC/#channel",
    ],
    notify_levels=["CRITICAL", "ERROR", "NOTIFY"],
    notify_title="{appname}: {level} Alert",
    notify_format="markdown",  # text, markdown, or html
)

# Send notification
logger.notify("Payment received from user #123")

# Critical logs also trigger notifications
logger.critical("Database connection lost")

Custom Log Levels

logger.custom("Deploy completed", "DEPLOY", "purple")
logger.custom("Payment received", "PAYMENT", "green")

Buffer Control

# Force write all buffered logs
logger.flush()

File Rotation

When log files reach max_file_size_mb, Tamga automatically:

  • Creates timestamped backups (if enabled)
  • Clears the original file
  • Continues logging seamlessly

📊 Performance

Tamga uses a buffered writing system that delivers significantly faster performance compared to traditional logging. The buffering mechanism provides optimal throughput for high-volume logging scenarios while maintaining thread safety.

🤝 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.


Made with ❤️ by Doğukan Ürker

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