textfsmgen 0.3.1a1
TextFSM Generator simplifies template creation by converting plain English snippets into reusable parsing rules, standardizing workflows and enhancing collaboration across teams.
License: BSD-3-Clause
Requires Python: >=3.9
Keywords: textfsm, textfsm generator, text parsing, automation, verification, validation, qa, robotframework, test script, test case, test plan, ai integration

# TextFSM Generator

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# 📖 Overview

The **TextFSM Generator** is a Python library designed to simplify and standardize the creation of TextFSM templates. Instead of manually writing complex parsing rules, developers can generate templates automatically from plain, English‑readable snippets. This approach works much like AI prompts, making template creation intuitive, reusable, and easy to share across teams.  

By reducing the complexity of manual template writing, TextFSM Generator empowers developers, testers, engineers, QA professionals, and other collaborators to work more effectively together. It streamlines workflows, improves consistency, and enhances efficiency in both development and testing processes.  

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## ✨ Features

- 📝 **Automatic Template Generation** – Build TextFSM templates directly from user‑provided snippets.  
- 📄 **Human‑Readable Input** – Use plain English snippets instead of complex regex syntax.  
- 🔄 **Reusable Templates** – Share and reuse templates across teams and projects.  
- ⚡ **Workflow Efficiency** – Reduce manual effort and accelerate text parsing tasks.  
- 🤝 **Collaboration Ready** – Designed for developers, testers, engineers, and QA professionals.  

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## 🚀 Benefits

- Simplifies template creation and reduces errors.  
- Improves consistency across projects and teams.  
- Accelerates development and testing cycles.  
- Enhances maintainability of parsing logic.  
- Makes text parsing scalable and reliable for modern environments.  

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## ⚙️ Installation  

You can install the **textfsmgen** package directly from PyPI using `pip`:  

```bash
pip install textfsmgen
```  

### ✅ Requirements  
- Python 3.9 or higher  
- Internet connection to fetch dependencies from PyPI

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## 📦 Dependencies  

This project depends on the following Python packages to provide core functionality and seamless integration:  

- [**textfsm**](https://pypi.org/project/textfsm/) – Template‑based state machine for parsing semi‑structured text.  
- [**PyYAML**](https://pypi.org/project/PyYAML/) – YAML parser and emitter, enabling structured configuration management.  
- [**genericlib**](https://pypi.org/project/genericlib/) – Lightweight utility library offering reusable functions to reduce boilerplate code.  
- [**regexapp**](https://pypi.org/project/regexapp/) – Regular expression utilities for advanced text processing.

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## 🐞 Bugs & Feature Requests  

If you encounter a bug or have a feature request, please submit it through the official [GitHub Issue Tracker](https://github.com/Geeks-Trident-LLC/textfsmgen/issues). This helps us track, prioritize, and resolve issues efficiently while keeping all feedback in one place.

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## 🛣️ Roadmap  

- ⚠️ **Deprecation Notice** - *TextFSM Generator Pro Edition* and *Enterprise Edition* will be deprecated and removed during the upcoming migration to 🚀 `textfsmgen` version **1.x**.   
- ✨ **Template Generation Improvements** – Ongoing refinements to TextFSM template creation, deeper integration with parsing libraries, and streamlined developer workflows.  
- 🐳 **Containerization** – Official Docker images and containerized deployment options for portability, scalability, and simplified setup.  
- 🔄 **CI/CD Integration** – Automated pipelines for testing, building, and releasing to ensure faster and more reliable delivery.  
- 🤖 **Robot Framework Support** – Native integration with Robot Framework for keyword‑driven acceptance testing and automation.  
- 🧩 **Flexibility & Robustness Verification** – Tools to validate template adaptability and resilience across diverse input conditions.  
- 🧪 **Testing & QA Strategy** – Comprehensive testing methodologies, regression suites, and formalized QA practices for higher reliability.  
- 📊 **Metrics & Reporting** – Built‑in performance metric analysis, automated reporting, and audit‑ready documentation.  
- 📈 **Forecasting & Projections** – Estimation tools for usage trends, scalability requirements, and performance forecasting.  
- 🛡️ **Quality & Maintenance** – Continuous monitoring, static analysis, and long‑term maintainability strategies to ensure code health.  
- 🤖 **AI Integration** – Advanced AI‑powered capabilities, including:  
  - Intelligent template suggestions and auto‑completion.  
  - Automated error detection and correction.  
  - Adaptive optimization based on usage patterns.  
  - Natural language → TextFSM template translation for non‑expert users.  
  - Predictive analytics for template performance, reliability, and optimization.  
- 🔍 **Testing & Feedback** - Early adopters are encouraged to experiment, validate new features, and provide feedback to shape the stable release.  

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## 📜 License  

This project is licensed under the **BSD 3‑Clause License**.  
You can review the full license text here:  
- [BSD 3‑Clause License](https://github.com/Geeks-Trident-LLC/textfsmgen/blob/develop/LICENSE)  

### 🔍 What the BSD 3‑Clause License Means  
- ✅ **Freedom to Use** – You may use this library in both open‑source and proprietary projects.  
- ✅ **Freedom to Modify** – You can adapt, extend, or customize the code to fit your needs.  
- ✅ **Freedom to Distribute** – Redistribution of source or binary forms is permitted, with or without modification.  
- ⚠️ **Conditions** – You must retain the copyright notice, license text, and disclaimers in redistributions.  
- ❌ **Restrictions** – You cannot use the names of the project or its contributors to endorse or promote derived products without prior permission.  

### ⚡ Why BSD 3‑Clause?  
The BSD 3‑Clause License strikes a balance between openness and protection. It allows broad usage and collaboration while ensuring proper attribution and preventing misuse of contributor names for marketing or endorsement.  

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## ⚠️ Disclaimer  

This package is currently in **pre‑beta development**. Features, APIs, and dependencies may change before the official 1.x release. While it is functional, please use it with caution in production environments and expect ongoing updates as the project matures.  

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