https://github.com/yllvar/gmgn-trendinganalyzer
Analyze gmgn.ai token data over multiple timeframes, groups by token address, computes the aggregated metrics (including a consistency count), filters out tokens based on volume and market cap thresholds, and then sorts the results.
https://github.com/yllvar/gmgn-trendinganalyzer
cryptocurrency gmgnai memecoin solana
Last synced: about 1 month ago
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Analyze gmgn.ai token data over multiple timeframes, groups by token address, computes the aggregated metrics (including a consistency count), filters out tokens based on volume and market cap thresholds, and then sorts the results.
- Host: GitHub
- URL: https://github.com/yllvar/gmgn-trendinganalyzer
- Owner: yllvar
- Created: 2025-02-03T11:07:42.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-03T11:52:55.000Z (over 1 year ago)
- Last Synced: 2025-04-03T09:44:49.574Z (about 1 year ago)
- Topics: cryptocurrency, gmgnai, memecoin, solana
- Language: Python
- Homepage:
- Size: 523 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🚀 GMGN Trending Token Analyzer
---
A sophisticated tool for analyzing trending cryptocurrency tokens across multiple timeframes using the GMGN.ai wrapper. The analyzer aggregates data, filters tokens based on key metrics, and provides visual analytics along with expert analysis.
---
## 🔥 Features
- 📊 **Multi-timeframe token trend analysis** (1m, 5m, 1h, 6h, 24h)
- 📈 **Data aggregation and filtering** based on volume, market cap, and consistency
- 🎨 **Automated visualization generation**
- ⏳ **Continuous monitoring** with automated refresh
## 📌 Technical Analysis Components
### 🏷️ Token Analysis Logic
- Fetches trending tokens across multiple timeframes
- Collects key metrics:
- 🆔 Token ID, 🔗 Chain, 🏠 Address
- 🔤 Symbol, 💰 Price, 📊 Volume
- 🌎 Market Cap, 📉 Price Change Percentage
- 🚨 Error handling for API requests
- 🔍 Validation of token data integrity
### 📊 Aggregation Logic
- Groups tokens by address
- Calculates key aggregated metrics:
- 📈 Average price and volume
- 📏 Median market cap
- 🔀 Price change trends
- 🔁 **Consistency count** (appearance across timeframes)
- **Filtering criteria:**
- ✅ Minimum **volume threshold**: 1000
- ✅ Minimum **market cap threshold**: 10000
- ✅ Minimum **consistency count**: 3 timeframes
### 📉 Visualization Logic
- Generates **scatter plot visualization**:
- 📍 X-axis: **Median Market Cap** (log scale)
- 📍 Y-axis: **Average Volume** (log scale)
- 🎈 Bubble size: **Consistency count**
- 🎨 Color gradient: **Average price change**
- 🔤 Includes **token symbol annotations**
- 🖼️ Saves **high-resolution plot** (300 DPI)
## 🛠 Installation
1️⃣ Clone the repository:
```bash
git clone https://github.com/yllvar/gmgn-TrendingAnalyzer.git
cd gmgn-TrendingAnalyzer
```
2️⃣ Create and activate a **virtual environment** (optional but recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3️⃣ Install dependencies:
```bash
pip install -r requirements.txt
```
## 🚀 Usage
Run the analyzer:
```bash
python analyzer.py
```
The script will:
- 📡 Fetch trending tokens **every 60 seconds**
- 🧠 Generate **analysis and visualizations**
- 🖼️ Save plots as **'trending_analysis_plot.png'**
- 📑 Save analysis as **'trending_analysis.csv'**
- 🖥️ Display token data and analysis in the **console**
To stop the script, press **Ctrl+C**.
## 📤 Output
The analyzer produces:
- 📑 **Tabulated token data** with key metrics
- 🔗 **List of token addresses** for easy reference
- 📊 **Visual plot saved** as `'trending_analysis_plot.png'`
## 📦 Dependencies
- 🐍 `pandas` – Data manipulation and analysis
- 📊 `matplotlib` – Data visualization
- 📜 `tabulate` – Console table formatting
- 🔑 `python-dotenv` – Environment variable management
# ⚠️ Notes
## 💡 Acknowledgments
This project is based on the work of 1f1n and his repository: [gmgnai-wrapper](https://github.com/1f1n/gmgnai-wrapper).
Big shoutout to 1f1n for his amazing work! 🙌
## 🤝 Contributing
Feel free to fork this repository, make improvements, and submit a pull request. Contributions are always welcome!
## 📜 License
This project is open-source and free to use. Modify it as you see fit!
---