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Python: Real-World Data Science

You're reading from   Python: Real-World Data Science Real-World Data Science

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Product type Course
Published in Jun 2016
Publisher
ISBN-13 9781786465160
Length 1255 pages
Edition 1st Edition
Languages
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Authors (5):
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Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
Robert Layton Robert Layton
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Robert Layton
Sebastian Raschka Sebastian Raschka
Author Profile Icon Sebastian Raschka
Sebastian Raschka
Martin Czygan Martin Czygan
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Martin Czygan
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Table of Contents (12) Chapters Close

Table of Contents FREE CHAPTER
Python: Real-World Data Science
Meet Your Course Guide
What's so cool about Data Science?
Course Structure
Course Journey
The Course Roadmap and Timeline
1. Course Module 1: Python Fundamentals 2. Course Module 2: Data Analysis 3. Course Module 3: Data Mining 4. Course Module 4: Machine Learning Index

Chapter 14. Concurrency

Concurrency is the art of making a computer do (or appear to do) multiple things at once. Historically, this meant inviting the processor to switch between different tasks many times per second. In modern systems, it can also literally mean doing two or more things simultaneously on separate processor cores.

Concurrency is not inherently an object-oriented topic, but Python's concurrent systems are built on top of the object-oriented constructs we've covered throughout the module. This chapter will introduce you to the following topics:

  • Threads
  • Multiprocessing
  • Futures
  • AsyncIO

Concurrency is complicated. The basic concepts are fairly simple, but the bugs that can occur are notoriously difficult to track down. However, for many projects, concurrency is the only way to get the performance we need. Imagine if a web server couldn't respond to a user's request until the previous one was completed! We won't be going into all the details of just...

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