One, thread-based parallel programming
- How to use the Python threading module
- How to define a thread
- How to probe a thread
- How to use threads in a subclass
Lock
and RLock
Implement thread synchronization
- Signal Implementation thread Synchronization
- Conditions (condition) for thread synchronization
- Event to implement thread synchronization
- How to use
with
statements
- Using queues for thread message delivery
- How to evaluate the performance of multithreaded applications
- The danger of cashing into programming
Second, process-based parallel programming
- How to use the Python
multiprocessing
module
- How to build a process
- How to name a process
- How to run a process in the background
- How to kill a process
- How to use a process in a subclass
- How to Exchange objects between processes
- Using queues to swap objects between processes
- Using pipelines to swap objects between processes
- How to Implement Process synchronization
- How to manage the status between different processes
- How to use a process pool
- How to use the Python
mpi4py
module
- End-to-segment communication
- Avoid deadlock problems
- Use broadcast (broadcast) for group-to-room communication
- Use the scatter (scatter) function for group-to-room communication
Three, asynchronous programming
- How to use
concurrent.futures
modules
Asyncio
Event Loop Management
Asyncio
Processing co-process
Asyncio
Task management
- Dealing with Asyncio and Futures
- Gevent
- Tornado
- twsited
Iv. distributed python
- distributing tasks using celery
- How to create a task from celery
- Scoop scientific calculation
- Scoop Handling Map Functions
- Pyro4 Remote Method invocation
- Pyro4 Object Group Chain
- Develop customer/service applications using Pyro4
- PYCSP Process Serialization Communication
- The MapReduce use of disco
- RPYC Remote Program calls
Reference:
- "Python Parallel Programming Cookbook"
- Https://www.quora.com/What-are-some-of-the-asynchronous-frameworks-in-Python
Several key points of Python parallel programming