Showing 8 open source projects for "framework python"

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  • 1

    pycos

    Python framework for concurrent, asynchronous, distributed tasks

    Python framework for concurrent, asynchronous, distributed communicating tasks for broad range of use cases, including public / private / hybrid cloud computing, fog / edge computing.
    Downloads: 1 This Week
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  • 2

    dispy

    Distributed and Parallel Computing with/for Python.

    dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently.
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    Downloads: 2 This Week
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  • 3

    asyncoro

    Python framework for asynchronous, concurrent, distributed programming

    asyncoro is a Python framework for developing concurrent, distributed, network programs with asynchronous completions and coroutines. Asynchronous completions implemented in asyncoro are sockets (non-blocking sockets), database cursors, sleep timers and locking primitives. Programs developed with asyncoro have same logic and structure as Python programs with threads, except for a few syntactic changes. asyncoro supports socket I/O notification mechanisms epoll, kqueue, /dev/poll (and poll and select, where necessary), and Windows I/O Completion Ports (IOCP) for high performance and scalability, and SSL for security
    Downloads: 0 This Week
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  • 4
    NetWorkSpaces, developed by Scientific Computing Associates Inc., provides a framework to coordinate programs written in Python, making it easier to write distributed applications.
    Downloads: 0 This Week
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  • Create and run cloud-based virtual machines. Icon
    Create and run cloud-based virtual machines.

    Secure and customizable compute service that lets you create and run virtual machines.

    Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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  • 5
    UPDATE: Chromium is no longer updated or maintained. The project is frozen. Chromium is a flexible framework for scalable real-time rendering on clusters of workstations, derived from the Stanford WireGL project code base.
    Downloads: 0 This Week
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  • 6
    java-based complete Agent (Artificial Intelligence) Framework with all the features you might expect in an Agent Framework: Mobility, Autonomy, Distributed communication, Agents can be written in Java, Jython, or Beanshell.
    Downloads: 0 This Week
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  • 7
    Momoko is a framework for developing distributed, multi-user, network-aware applications. It includes facilities for storing objects in a tree structure, a shell for manipulating the object database, orthogonal persistence, scripting support, and a trans
    Downloads: 0 This Week
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  • 8
    Recall is a framework for building distributed, fault-tolerant, replicated storage servers.
    Downloads: 0 This Week
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