README

Solana Blockchain Analysis

This project focuses on analyzing the Solana blockchain to extract and process token transfer data across a range of blocks. By leveraging Solana's RPC API, we fetch transaction data, parse token transfers, and perform data analysis, such as aggregating transfer amounts and visualizing trends over time.

Getting Started

Prerequisites

• Python 3.6 or higher
• Installed Python packages:
  • requests
  • pandas
  • matplotlib

Install the required packages using:

pip install requests pandas matplotlib

Setting Up an Alchemy RPC URL

To interact with the Solana blockchain, you need access to an RPC endpoint. We recommend using Alchemy to obtain a reliable and high-performance Solana RPC URL.

Steps:

1. Sign Up for Alchemy:

   • Visit the Alchemy website and create a free account.
   • Follow the registration process to set up your account.

2. Create a New App:

   • After logging in, navigate to your dashboard.
   • Click on "Create App".
   • Name your app and select "Solana" as the blockchain.
   • Choose the network (e.g., "Mainnet") for your app.

3. Retrieve Your RPC URL:

   • Once the app is created, you'll see your Solana RPC URL.
   • Click on "View Key" or "Show URL" to reveal the full endpoint.
   • Copy the URL; you'll need it to configure the project.

Note: Ensure you keep your API key secure and do not expose it publicly.

Configuration

In your Python script, set the SOLANA_RPC_URL & ETHEREUM_RPC_URL variable to your Alchemy RPC URLs:

SOLANA_RPC_URL = "YOUR RPC URL"
ETHEREUM_RPC_URL = "YOUR RPC URL"

Handling Data

• DataFrame Operations: Utilize pandas DataFrame capabilities to manipulate and analyze the data.
• Visualization: Use matplotlib to create plots for data visualization.
• Saving Data: Export the DataFrame to CSV or Excel files for further analysis or record-keeping.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please feel free to submit a pull request or open an issue on GitHub. Or feel free to DM me on X

License

This project is licensed under the MIT License.

---

Disclaimer: This project is intended for educational and analytical purposes. Always ensure you comply with the terms of service of the APIs and platforms you use.

---