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Cloud tools for web scraping and data extraction
Deploy pre-built tools that crawl websites, extract structured data, and feed your applications. Reliable web data without maintaining scrapers.
Automate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
This project is a complete cross-platform (Windows, Linux) framework for Evolutionary Computation in pure python. See the project site at http://pyevolve.sourceforge.net or the blog at http://pyevolve.sourceforge.net/wordpress
The Location Containment Object Model(LCOM) is a simulation framework written in Python. LCOM provides a rule-based solution to handling partial object containment, object migration, message passing, and simulation observation.
Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
Run applications fast and securely in a fully managed environment
Cloud Run is a fully-managed compute platform that lets you run your code in a container directly on top of scalable infrastructure.
Run frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.
The co-simulation adapation platform serves as programming framework and middleware to enable coupling of distributed, heterogeneous numerical models. The framework facilitates the adaptation and integration of new sub-models into a common simulation platform.