💻 Open Code

Explore the open-source code of Deeptrail on GitHub! Feel free to contribute, report issues, or check out the latest updates and enhancements

📈 Formulas for MVP Features

1. Risk Heat Map 🔥

• Smart Logic: Calculates the risk score of tokens based on the historical data, including volume changes, price swings, and transactions.

function calculateRiskHeatMap(tokenData) {
  const riskFactor = (tokenData.volumeChange + tokenData.priceChange) / tokenData.averagePrice;
  return riskFactor > 0.5 ? "High Risk" : "Low Risk";
}

Where: volumeChange: Change in the token's trading volume. priceChange: Price change compared to the previous trading period. averagePrice: Average token price over a specified period.

1. Digital Trails 🛤️ Smart Logic: Tracks the movement history of a specific token using the DexScreener API.

def track_token_movement(token_address):
    url = f"https://api.dexscreener.com/token/{token_address}"
    response = requests.get(url)

    if response.status_code == 200:
        data = response.json()
        return data.get("tokenMovementHistory", [])
    else:
        print(f"Error fetching data: {response.status_code}")
        return []

Where: tokenAddress: The address of the token being tracked. tokenMovementHistory: A history of token movements retrieved from DexScreener.

1. Phantom Fingerprint 👻 Smart Logic: Scores tokens based on the frequency and nature of traceable activities associated with the token.

function calculateFingerprintScore(tokenData) {
  const score = (tokenData.transactionCount / tokenData.totalAddresses) * 100;
  return score > 75 ? "High Trust" : "Low Trust";
}

Where: transactionCount: Number of transactions involving the token. totalAddresses: Number of unique addresses interacting with the token.