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Showing 10 open source projects for "python data analysis"
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Earn up to 16% annual interest with Nexo.Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
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python-binance
Binance Exchange API python implementation for automated trading
This is an unofficial Python wrapper for the Binance exchange REST API v3. I am in no way affiliated with Binance, use at your own risk. Implementation of all General, Market Data and Account endpoints. Asyncio implementation. Testnet Support for Spot, Futures, and Vanilla Options. Simple handling of authentication. No need to generate timestamps yourself, the wrapper does it for you. -
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Freqtrade
Free, open source crypto trading bot
...We strongly recommend you have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. -
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OctoBot
Cryptocurrency trading bot for TA, arbitrage and social trading
OctoBot is a trading robot that is designed to be easy to use and infinitely customizable. OctoBot is built for people who don't have much time or do not easily trust crypto-world projects. Many trading automation tools exist but most of them are complicated to use, expensive, do not behave as intended, or are meant to be used by professional traders. Moreover, when a favorable trend is spotted, it can be difficult to maximize profit from it: trading takes a lot of time, and when it's done... -
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crypto scanner v6.0.0
AI‑powered signals, risk analysis, and automated trading bot
Advanced Crypto Scanner v6.0.0 All‑in‑one Windows crypto tool – real‑time data, signals, risk analysis, AI learning, and automated trading bot. Live Data: Prices, volume, market cap (CoinMarketCap/CoinGecko), BTC dominance, market sentiment. Smart Signals: Basic (price/volume) & Advanced (RSI, MACD, Bollinger, Stochastic, ADX) with confirmation gate. Risk Rating: Low/Medium/High based on liquidity, volatility, category, technicals. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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5
SolanaMevBotGui
Solana Trade Bot is an open-source tool for automated trading on the
This open-source, AI-powered bot is a versatile tool designed to run seamlessly on both Windows and macOS platforms. It automates various tasks and accelerates decision-making processes tailored to user needs. With advanced algorithms, it can analyze complex data, learn, and provide intuitive solutions. Developed in popular languages like Python, it is fully customizable and open for community contributions and improvements. -
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JesseAi
Advanced AI-Powered Python Crypto Trading Bot 2026 - Free Backtesting
Jesse Bot: Advanced AI-Powered Python Best Crypto Trading Bot & Framework (2026) Jesse Bot — free open-source Python crypto trading bot & robust framework for cryptocurrency markets. Build, backtest, AI-optimize, and execute precise automated strategies with zero look-ahead bias. Use JesseGPT — built-in AI assistant — to write, debug, and refine strategies effortlessly, even as a beginner. Secure live trading on Binance, Bybit & major exchanges, full risk management, leverage/futures... -
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MONITOR BINANCE LIQUIDATIONS
Real-time monitoring of futures liquidations on the Binance exchange.
✅ Requirements: WINDOWS 10 🆓 FREEWARE 🟢 REAL-TIME MONITORING OF FUTURES LIQUIDATIONS ON THE BINANCE EXCHANGE. 🟢 МОНИТОРИНГ ЛИКВИДАЦИЙ ФЬЮЧЕРСОВ НА БИРЖЕ BINANCE В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ. ⚫ Use a FILTER to monitor the coins you need. Input currency pairs from one or more into the filter. To monitor several coins, in the filter field input them one by one with a comma separator. FOR EXAMPLE: BTCUSDT,ETHUSDT,CfxUSdt You can enter both uppercase and lowercase... -
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Algobot
Cryptocurrency trading bot with a graphical user interface
...Telegram integration has been added to support easier and remote trading. Please note that Algobot requires TA-LIB. You can view instructions on how to download TA-LIB. For Windows users, it's best to download the .whl package for your Python install and pip install it. For Linux and MacOS users, there's excellent documentation available. Create graphs with real time data and/or moving averages. Run simulations with parameters configured. Run custom backtests with parameters configured. Run live bots with parameters configured. Telegram integration that allows users to trade or view statistics. ... -
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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10
Catalyst
An Algorithmic Trading Library for Crypto-Assets in Python
Catalyst is an algorithmic trading library for crypto-assets written in Python, originally developed to let quants and developers design, backtest, and deploy trading strategies in a unified environment. It builds on top of Zipline, extending that ecosystem to support crypto exchanges and high-resolution historical data (daily and minute bars). Users can express strategies in Python, run backtests against historical price data, and analyze performance through built-in metrics and analytics to evaluate profitability, risk, and behavior under different market conditions. ...
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