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SolPump Analyzer: AI-Powered Crypto Signal & Risk Analysis Bot

SolPump Analyzer is a Python-based crypto analytics and automation project designed to identify high-momentum Solana memecoins by combining real-time market data, social sentiment signals, risk checks, and automated trade logic. Built in Jupyter Notebook, the project uses APIs, web scraping, blockchain libraries, and rule-based scoring to rank tokens based on liquidity, volume, social hype, and safety indicators. The project solves a common problem in high-volatility crypto markets: traders often rely on scattered information across token charts, social media, and risk-checking platforms. SolPump Analyzer brings these signals into one automated workflow, helping identify trending tokens faster while applying structured risk filters before trade execution.

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Built a Python-based crypto signal analysis bot to identify high-momentum Solana memecoins using real-time market, social, and risk data.

Designed an automated data pipeline that extracts token metrics such as liquidity, volume, price movement, and token activity from crypto market sources.

Used requests and BeautifulSoup to collect and structure semi-structured web data for token discovery and ranking.

Integrated Dexscreener-style market data to evaluate token liquidity, volume strength, and short-term price movement.

Designed Raydium trade automation logic with configurable slippage, priority fees, take-profit, and stop-loss settings.

SolPump Analyzer: AI-Powered Crypto Signal & Risk Analysis Bot

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Impact & Metrics

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