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利用并发和分布式处理技术构建高性能,可伸缩的python应用程序

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BigBigRadish/python_high_performance

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Name		Name	Last commit message	Last commit date
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.settings		.settings
Concurrent		Concurrent
Cpython_dmeo		Cpython_dmeo
Cython_dmeo		Cython_dmeo
Distribute_process		Distribute_process
JIT_tools		JIT_tools
base_standard_profiler		base_standard_profiler
high_performance_design		high_performance_design
numpy_pandas		numpy_pandas
parallel_processing		parallel_processing
python_optimization		python_optimization
.project		.project
.pydevproject		.pydevproject
python高性能优化——ppt.pdf		python高性能优化——ppt.pdf
readme.md		readme.md
用Mars来并行和分布式执行NumPy.pdf		用Mars来并行和分布式执行NumPy.pdf

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python高性能

利用并发和分布式处理技术构建高性能,可伸缩的python应用程序

一.基准测试与剖析

二.纯粹的python优化

三.执行Numpy和Pandas快速执行数组操作

四.使用Cpython获得c语言性能

五.探索编译器

六.实现并发

七.并行处理

八.分布式处理

9.高性能设计

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利用并发和分布式处理技术构建高性能,可伸缩的python应用程序

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python cpython dask numba

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