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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources

Chapter 12.  Performance Tuning, Profiling, and Concurrency

 

"Premature optimization is the root of all evil"

 
 --Donald Knuth, a renowned computer scientist and mathematician

For real-world applications, performance is as important as features, robustness, maintainability, testability, and usability. Performance is directly proportional to the scalability of an application. Ending this book without looking at performance enhancement was never an option. In fact, we delayed discussing the topic of performance until the last chapter of the book to avoid premature optimization. In this chapter, we will give hints on improving performance using profiling as the key technique. We will also discuss the relevant frameworks for multicore, distributed systems. We will discuss the following topics in this chapter:

  • Profiling the code
  • Installing Cython
  • Calling the C code
  • Creating a pool process with multiprocessing
  • Speeding up embarrassingly parallel for loops with Joblib...
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