Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách Python Concurrency with asyncio (sách keo gáy, bìa mềm)
Categories:Computers - Programming
Year:2022
Language:english
Pages:378
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.
About the technology
It’s
easy to overload standard Python and watch your programs slow to a
crawl. The 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.
About the author
Matthew
Fowler has over 15 years of software engineering experience in roles
from architect to engineering director.
Không có đánh giá!
Thêm đánh giá