The book "Fast Python: High Performance Techniques for Large Datasets" by Tiago Rodrigues Antao is considered an essential resource for developers working with large volumes of data. The author shares advanced methods and tools designed to significantly enhance the performance of Python programs.
This guide is aimed at professionals seeking to optimize their applications and efficiently process large datasets. We recommend downloading "Fast Python" by Tiago Rodrigues Antao today. It is an indispensable resource for anyone working with big data and striving to optimize the performance of their Python programs.
What You Will Learn from the Book?
- Effective Handling of Large Datasets. Learn techniques for working with large data volumes using Python.
- Code Optimization. Master techniques to optimize your code for better performance.
- Utilizing Data Libraries. Efficiently use libraries designed for data handling.
- Parallel Computing. Implement parallel computing techniques to speed up data processing.
- Memory Management. Optimize memory usage to handle large datasets more effectively.
- Asynchronous Programming. Incorporate asynchronous programming to enhance performance.
- Working with NumPy and pandas. Use these powerful libraries to manage and analyze data.
- Introduction to Cython. Learn how to leverage Cython for performance improvements.
- I/O Optimization. Optimize input/output operations for better efficiency.
Who Should Read This Guide?
- Developers Working with Big Data. Understand how to optimize data processing and enhance program performance.
- Data Scientists. Gain methods for the effective analysis and processing of large datasets.
- Researchers and Analysts. Learn how to use Python to expedite data analysis and improve result accuracy.
- Students and Educators. Utilize this book in academic courses on data analysis and programming, with practical examples and exercises.
More About the Author of the Book
FAQ for "Fast Python"
What are the main topics covered in "Fast Python"?
The guide covers code optimization, parallel computing, memory management, asynchronous programming, and the use of libraries such as NumPy and pandas.
Is the book suitable for beginners?
Yes, it is suitable for beginners as it provides fundamental knowledge and step-by-step instructions to master key performance enhancement techniques.
What tools are discussed in the guide?
The book discusses various tools, including NumPy, pandas, Cython, and libraries for parallel computing and asynchronous programming.
What practical examples are included in the publication?
It contains code examples demonstrating the application of optimization techniques, including handling large datasets and I/O optimization.
How does the book assist with memory management?
The author offers methods for managing memory efficiently, helping to utilize system resources effectively and avoid memory leaks when working with large datasets.
How does this guide aid in parallel computing?
It explores methods for parallel computing, including multithreading and multiprocessing, significantly speeding up the processing of large data volumes.
Information
| Author: | Tiago Rodrigues Antao | Language: | English |
| Publisher: | Manning | ISBN-13: | 978-1617297939 |
| Publication Date: | May 23, 2023 | ISBN-10: | 1617297933 |
| Print Length: | 304 pages |
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*The book is taken from free sources and is presented for informational purposes only. The contents of the book are the intellectual property of the author and express his views. After reading, we insist on purchasing the official publication on Amazon!
