Dispy
Dispy is an open-source distributed and parallel computing framework for Python. It allows execution of Python functions asynchronously and in parallel on multiple computers.
distributed
parallel
python
framework
Dispy: Open-Source Parallel Computing Framework for Python
Dispy is an open-source distributed and parallel computing framework for Python. It allows execution of Python functions asynchronously and in parallel on multiple computers.
What is Dispy?
Dispy is an open-source distributed and parallel computing framework for Python. It allows easy distribution of Python computations across multiple processors and computers. Some key features:
- It can distribute Python functions and scripts across nodes/processors for parallel execution
- It has support for computation intensive jobs as well as interactive control
- It uses TCP/IP sockets for communication between nodes
- It has fault tolerance features like automated load balancing, job scheduling, status messaging etc.
- It works with shared storage so nodes can access common files
- It provides APIs for monitoring and control of remote computations
Dispy is well suited for data parallel problems where the same computation needs to be performed on different data. It can help utilize multiple cores and nodes efficiently to speed up Python applications. Its failure handling makes it reliable for long running jobs.
Dispy Features
Features
- Distributed computing
- Parallel execution
- Load balancing
- Fault tolerance
- Python functions can be executed asynchronously
- Minimal overhead
- Uses multiprocessing and multithreading
Pricing
- Open Source
Pros
Easy to use API
Highly scalable
Good performance
Handles failures automatically
Open source and free
Cons
Limited documentation
Not ideal for CPU intensive tasks
Setup can be complex for clusters
Official Links
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