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# PyTraceX | ||
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**PyTraceX** is a lightweight and extensible Python library designed for **execution flow tracing**, **audit logging**, **correlation ID tracking**, **ML pipeline monitoring**, and **file I/O tracing**. It provides a seamless way to capture, analyze, and manage system interactions, all while maintaining a minimal footprint and high configurability. | ||
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## ✨ Features | ||
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- **Function Execution Tracing** | ||
Capture function calls, execution time, and input arguments automatically. | ||
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- **Audit Logging** | ||
Securely log critical operations with tamper-proof signatures. | ||
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- **Correlation ID Tracking** | ||
Associate correlation IDs with requests to enable distributed tracing across microservices. | ||
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- **ML Pipeline Monitoring** | ||
Track data transformations, preprocessing, and model training workflows. | ||
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- **File I/O Tracing** | ||
Monitor file operations such as reading, writing, and closing files with built-in tracking. | ||
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- **Real-Time Execution Monitoring** *(Optional)* | ||
A web-based dashboard for interactive monitoring and visualization. | ||
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- **Configurable and Extensible** | ||
Supports in-memory storage by default, with the option to integrate databases or other external systems. | ||
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## 📌 Key Benefits | ||
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- **Minimal Dependencies** | ||
Uses only standard Python libraries by default, ensuring lightweight deployment. | ||
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- **Plug-and-Play Decorators** | ||
Easily add tracing, logging, and monitoring to existing functions with simple annotations. | ||
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- **Production-Ready** | ||
Designed for both local development and large-scale distributed systems. | ||
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- **Security & Compliance** | ||
Includes tamper-proof event logging and configurable **PII masking** for data protection. | ||
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## 🛠 Configuration | ||
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PyTraceX is **highly configurable**, allowing users to define: | ||
- Custom logging formats and verbosity. | ||
- Secure hashing mechanisms for audit logs. | ||
- PII masking rules to anonymize sensitive data. | ||
- Storage backends for trace event persistence. | ||
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All configurations are easily adjustable to fit different use cases. | ||
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## 📊 Real-Time Monitoring *(Optional)* | ||
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For those who require **real-time trace visibility**, PyTraceX offers an optional web-based dashboard. | ||
This allows users to: | ||
- View recorded function calls and events. | ||
- Monitor live execution logs. | ||
- Filter and search trace events dynamically. | ||
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## 🎯 Use Cases | ||
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PyTraceX is designed for a wide range of applications, including: | ||
- **Debugging complex execution flows** in microservices and distributed systems. | ||
- **Enhancing observability** in data pipelines and machine learning workflows. | ||
- **Ensuring compliance** with secure logging for sensitive operations. | ||
- **Tracking file interactions** in automated workflows and backend systems. | ||
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Its modular design makes it adaptable to both **small-scale scripts** and **enterprise-level applications**. | ||
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## 📜 License | ||
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PyTraceX is released under the **MIT License**. | ||
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Users are free to modify, distribute, and use the library in both personal and commercial projects. | ||
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## 🤝 Contributing | ||
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We welcome contributions to improve and expand PyTraceX. | ||
- **Report issues** to help identify bugs and areas for improvement. | ||
- **Suggest features** that could enhance usability and functionality. | ||
- **Submit pull requests** to contribute directly to the project. | ||
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Your feedback and participation help make PyTraceX better for everyone! | ||
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## 📬 Contact | ||
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For any inquiries, support, or feature requests, please reach out through the issues or discussion parts of the repository. | ||
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