Search Results for "data capture framework"
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Showing 11 open source projects for "data capture framework"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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1
Chainlink
node of the decentralized oracle network
...Build on a flexible framework that can retrieve data from any API, connect with existing systems, and integrate with any current or future blockchain. Integrate pre-built, time-tested oracle solutions that already secure tens of billions in smart contract value for market-leading decentralized applications. Use a decentralized network of Chainlink Automation nodes to automate contracts, mitigating risk of manual interventions and centralized servers. -
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Jesse
An advanced crypto trading bot written in Python
Jesse is an open-source AI agent framework designed to help developers build and orchestrate intelligent workflows that combine large language models (LLMs) with external tools, automation logic, and real-world actions. It acts as an agent manager where you can define tasks, contexts, and tool integrations so that AI reasoning is reliably connected to deterministic procedures like API calls, data retrieval, and task execution. -
3
Crypto Trading Bot
Cryptocurrency trading bot in javascript for Bitfinex
...It aims to go beyond basic buy-and-sell signal bots by supporting more practical trading mechanics such as stop-loss or stop-limit-style behavior where available. The project is explicitly not production-ready, so it should be treated as an educational and experimental trading framework rather than a safe financial automation system. It is useful for developers learning algorithmic trading architecture, exchange APIs, market data handling, and strategy testing. -
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Ninjabot
A fast cryptocurrency platform for trading bot in Go
A fast cryptocurrency trading bot framework implemented in Go. Ninjabot permits users to create and test custom strategies for spot markets. Ninjabot is an open-source platform that provides tools to implement custom strategies and backtests for trading cryptocurrencies in Go. Ninjabot CLI provides utilities commands to support backtesting and bot development. Currently, we only support Binance exchange. If you want to include support for other exchanges, you need to implement a new struct... -
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Cortex AI Infrastructure
Open-source multi-chain data routing & low-latency scanning framework.
...The framework is non-custodial, -
6
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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This project provides a framework for scanning and executing various trading strategies on the TON blockchain ecosystem. It retrieves market data from multiple decentralized exchanges (DEXs) and applies a range of trading strategies to identify potential opportunities. This open-source, AI-powered bot is a versatile tool designed to run seamlessly on both Windows and macOS platforms.
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8
Blankly
Easily build, backtest and deploy your algo in just a few lines
Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable... -
9
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. Beyond backtesting, Catalyst was designed to support live trading on multiple crypto exchanges such as Binance, Bitfinex, Bittrex, and Poloniex, bridging simulation and production within the same framework. -
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10
fooltrader
Quant framework for stock
Build a standard data schema, and then implement various connectors to import systems you are familiar with for analysis. fooltrader is a quantitative analysis trading system designed using big data technology, including data capture, cleaning, structuring, calculation, display, backtesting and trading. Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and trading. ... -
11
SQUEEZER
Squeezer framework, build serverless dApps
Squeezer is a platform that empowers new-entry blockchain developers to build serverless dApps simply as dead. The main usage of the ChainKit is to unify top blockchains interfaces into a single normalized API interface, therefore you can build blockchain dApps easily without digging into blockchain complex infrastructure. Bi-directional on-chain transactions (inbound and outbound). Build dApps connecting to smart contracts using chain kit agnostic connector. Quick intuitive code deployments...
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