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Python Concurrency with asyncio [Matthew Fowler]
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Описание
Эта книга знакомит с асинхронным, параллельным и многопоточным программированием на практических примерах Python. Трудные для понимания темы параллелизма разбиты на простые блок-схемы, позволяющие легко увидеть, как выполняются ваши задачи. Вы узнаете, как преодолеть ограничения Python с помощью asyncio для ускорения медленных веб-серверов и микросервисов. Вы даже сможете комбинировать asyncio с традиционными методами многопроцессорной обработки для огромного повышения производительности.
Learn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library.
Use coroutines and tasks alongside async/await syntax to run code concurrently
Build web APIs and make concurrency web requests with aiohttp
Run thousands of SQL queries concurrently
Create a map-reduce job that can process gigabytes of data concurrently
Use threading with asyncio to mix blocking code with asyncio code
Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
It’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable.
About the book
Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance.
What's inside
Build web APIs and make concurrency web requests with aiohttp
Run thousands of SQL queries concurrently
Create a map-reduce job that can process gigabytes of data concurrently
Use threading with asyncio to mix blocking code with asyncio code
About the reader
For intermediate Python programmers. No previous experience of concurrency required.
Table of Contents:
01 Getting to know asyncio
02 asyncio basics
03 A first asyncio application
04 Concurrent web requests
05 Non-blocking database drivers
06 Handling CPU-bound work
07 Handling blocking work with threads
08 Streams
09 Web applications
10 Microservices
11 Synchronization
12 Asynchronous queues
13 Managing subprocesses
14 Advanced asyncio
About the author:
Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director.
Формат: PDF.
Language: English
Эта книга знакомит с асинхронным, параллельным и многопоточным программированием на практических примерах Python. Трудные для понимания темы параллелизма разбиты на простые блок-схемы, позволяющие легко увидеть, как выполняются ваши задачи. Вы узнаете, как преодолеть ограничения Python с помощью asyncio для ускорения медленных веб-серверов и микросервисов. Вы даже сможете комбинировать asyncio с традиционными методами многопроцессорной обработки для огромного повышения производительности.
Learn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library.
Use coroutines and tasks alongside async/await syntax to run code concurrently
Build web APIs and make concurrency web requests with aiohttp
Run thousands of SQL queries concurrently
Create a map-reduce job that can process gigabytes of data concurrently
Use threading with asyncio to mix blocking code with asyncio code
Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
It’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable.
About the book
Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance.
What's inside
Build web APIs and make concurrency web requests with aiohttp
Run thousands of SQL queries concurrently
Create a map-reduce job that can process gigabytes of data concurrently
Use threading with asyncio to mix blocking code with asyncio code
About the reader
For intermediate Python programmers. No previous experience of concurrency required.
Table of Contents:
01 Getting to know asyncio
02 asyncio basics
03 A first asyncio application
04 Concurrent web requests
05 Non-blocking database drivers
06 Handling CPU-bound work
07 Handling blocking work with threads
08 Streams
09 Web applications
10 Microservices
11 Synchronization
12 Asynchronous queues
13 Managing subprocesses
14 Advanced asyncio
About the author:
Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director.
Формат: PDF.
Language: English