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Introduction
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Other talks
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About me
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Frameworks and tools
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Akamai
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Concurrent
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Parallel and asynchronous
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Threads and processes
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How it applies to Python
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Raymond Hettinger
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Amdahl Law
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Example
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Parallel vs coarsegrained problems
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Memory architectures
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Ctype objects
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Shared memory
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Managers
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Pullmap
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Pool
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Worker models
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Multiworking applications
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Multiple machines
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Hyper threading
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Slots
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Dont target 100 utilization
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How pipes are implemented
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deadlocks
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diamonds
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readpep
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what will you get
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run
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one obvious way
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summary
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questions
Description:
Explore parallel and asynchronous execution in Python through this comprehensive EuroPython 2017 conference talk. Delve into the distinctions between parallelism and concurrency, understand the impact of the Global Interpreter Lock (GIL), and learn when to leverage parallel programming in Python. Discover the differences between threads and processes, proper implementation techniques, and potential pitfalls in parallel execution. Investigate the combination of parallel and asynchronous code execution, its benefits, and implementation methods. Gain insights into multi-worker applications from a web development perspective, moving beyond traditional scientific use cases. Examine topics such as memory architectures, shared memory, worker models, and multi-machine setups. Acquire practical knowledge on avoiding deadlocks, utilizing pipes, and optimizing resource utilization in parallel Python programming.

Running Python Code in Parallel and Asynchronously

EuroPython Conference
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