PinescriptV6-docs-crawler: Python Tool for Pine Script V6 Documentation
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
PinescriptV6-docs-crawler is a Python tool designed to crawl and process TradingView's Pine Script V6 documentation. Utilizing the Crawl4Ai framework, it efficiently extracts, cleans, and organizes this documentation into searchable markdown files. This makes it significantly easier for developers to reference and analyze Pine Script features and syntax.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
The PinescriptV6-docs-crawler is a robust Python-based tool specifically engineered to automate the extraction and processing of TradingView's Pine Script V6 documentation. Built upon the powerful Crawl4Ai framework, this project streamlines the often-tedious task of gathering comprehensive technical information. It transforms raw web content into structured, clean, and easily searchable markdown files, providing developers with an invaluable resource for understanding and utilizing Pine Script V6.
Installation
To get started with PinescriptV6-docs-crawler, follow these simple steps:
Clone the repository:
git clone https://github.com/FaustoS88/PinescriptV6-docs-crawler cd PinescriptV6-docs-crawlerInstall required dependencies:
pip install -r requirements.txt
Examples
Once installed, using the PinescriptV6-docs-crawler involves two main stages:
Crawling Documentation:
Execute the main script to collect documentation URLs, download content, and save it.python pinescriptV6docs.pyProcessing Documentation:
After crawling, run the processing script to clean and organize the content, extracting code examples and function documentation.python process_docs.py
The output will be organized into a pinescript_docs/ directory, containing individual pages, a combined documentation file, and a processed/ subdirectory with enhanced content.
Why Use
This tool offers significant advantages for anyone working with Pine Script V6. It automates the entire documentation gathering process, saving countless hours of manual effort. Key benefits include:
- Automated Extraction: Effortlessly pulls documentation directly from TradingView's website.
- Clean & Organized Output: Transforms raw HTML into readable markdown, preserving code blocks and formatting.
- Searchable Content: Creates individual and combined markdown files, making it easy to search and reference specific features or syntax.
- Enhanced Analysis: Provides a structured dataset for deeper analysis of Pine Script V6 functionalities.
- Customization: Allows configuration of crawling behavior and content processing to suit specific needs.
Links
For more detailed information, contributions, or to report issues, please visit the official GitHub repository:
Related repositories
Similar repositories that may be relevant next.

Mergoo: Efficiently Merge and Train Multiple LLM Experts
July 7, 2026
Mergoo is an open-source Python library designed to simplify the merging of multiple Large Language Model (LLM) experts. It enables efficient training of these merged LLMs, allowing users to integrate knowledge from various generic or domain-specific models. The library supports several merging methods, including Mixture-of-Experts and Mixture-of-Adapters, across popular base models.

Ludwig: Low-Code Declarative Deep Learning for LLMs and AI Models
July 6, 2026
Ludwig is a powerful, low-code declarative deep learning framework designed for building custom LLMs, neural networks, and other AI models. It simplifies the process of training, fine-tuning, and deploying models, from LLM fine-tuning to tabular classification, using a simple YAML configuration without boilerplate Python code. This makes advanced AI development accessible and efficient for a wide range of applications.

Lamini: The Official Python Client for Generative AI API
July 6, 2026
Lamini is the official Python client and SDK designed to interact with the Lamini API, enabling developers to create their own Generative AI applications. It provides a straightforward interface for integrating powerful AI capabilities into Python projects. This package simplifies the process of building and deploying generative AI solutions.
xTuring: Build, Personalize, and Control Your Own LLMs
July 6, 2026
xTuring is an open-source framework designed to simplify the process of building, personalizing, and controlling Large Language Models (LLMs). It provides an easy way to fine-tune open-source LLMs on your own data, offering features from data pre-processing to efficient training and inference. This tool empowers developers to create private, personalized LLMs locally or in their private cloud environments.
Source repository
Open the original repository on GitHub.