How to Use the TradingView Chart Data Extractor

If you’re looking to extract data from TradingView charts, you’re in the right place. This guide will walk you through the process of using the Chart Data Extractor, enabling you to gather invaluable trading insights with ease. Grab your virtual toolbox and let’s get started!

Getting Started

The first step is to ensure that you have everything set up correctly. Here’s how to start:

• Ensure your TradingView chart displays the oldest date you want to capture.
• Avoid using too many indicators and too low a time resolution, as this can overload the server.
• If needed, run the extraction script on your local machine or scrape in smaller chunks.

Usage Instructions

To use the TradingView Chart Data Extractor, you will need to append the URL of the chart idea published on TradingView to the provided link configuration. Remember, it must not be the URL of a security’s chart, but rather a link to a user-published chart. For example:

https://tradingview-data.herokuapp.com/quotes?url=https://www.tradingview.com/chart/SPYvjYfwgMu-SPY-Export-Test

Installation Process

Before using the extractor, you’ll need to install a few prerequisites:

1. Install virtualenv: pip3 install virtualenv
2. Create a new virtual environment: python3 -m venv .
3. Activate the environment: source bin/activate
4. Install required packages: pip3 install -r requirements.txt
5. Initialize a git repository: git init
6. Create a Heroku app: heroku create
7. Set the Heroku remote: heroku git:remote -a projectname
8. Set the Heroku stack: heroku stack:set heroku-16
9. Add Puppeteer Buildpack: heroku buildpacks:add https://github.com/jontewksp/puppeteer-heroku-buildpack.git
10. Add Python Buildpack: heroku buildpacks:add heroku/python
11. Add and commit your changes: git add . and git commit -am fix
12. Push your code to Heroku: git push heroku master

Troubleshooting Tips

If you encounter any issues during this process, here are a few troubleshooting ideas:

• Ensure your environment is correctly activated before running any commands.
• Check the URL for formatting errors when appending the TradingView link.
• Monitor the output for error messages; they often indicate what went wrong.
• If the server is overloaded, consider reducing the number of indicators.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Understanding the Code with an Analogy

Think of the installation and usage of the TradingView Chart Data Extractor like setting up a new kitchen to bake a cake:

• The ingredients and utensils: Just like gathering the ingredients before baking, you need to install packages and set up the environment correctly.
• The recipe: The order of steps outlined in the installation process is like following a recipe; each step leads to the successful completion of a complex task.
• The oven: Hosting your application on Heroku is similar to placing your cake in the oven. You need the right temperature (in this case, the correct stack and buildpacks) for it to rise properly.
• Troubleshooting: If the cake doesn’t bake right, you would check the oven’s temperature or the ingredients. Similarly, if your extraction process fails, checking the output or reformatting the URL can help you identify the issue.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Conclusion

Now you’re armed with the knowledge to extract data from TradingView charts effectively. With a little patience and care, you can gather all the insights you need for informed trading decisions. Happy trading!