Advanced Python Programming
Language: English
Published by Packt Publishing Limited, GB, 2019
- Softcover
- New
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
AbeBooks seller since June 11, 2025
Condition: New
£ 43.02
Quantity: Over 20 available
Add to basketItem description from seller
Seller Inventory # LU-9781838551216
- Title
- Advanced Python Programming
- Author
- Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis
- Publisher
- Packt Publishing Limited, GB
- Publication year
- 2019
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1838551212
- ISBN 13
- 9781838551216
Create distributed applications with clever design patterns to solve complex problems
Key Features:
- Set up and run distributed algorithms on a cluster using Dask and PySpark
- Master skills to accurately implement concurrency in your code
- Gain practical experience of Python design patterns with real-world examples
Book Description:
This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing.
By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems.
This Learning Path includes content from the following Packt products:
- Python High Performance - Second Edition by Gabriele Lanaro
- Mastering Concurrency in Python by Quan Nguyen
- Mastering Python Design Patterns by Sakis Kasampalis
What You Will Learn:
- Use NumPy and pandas to import and manipulate datasets
- Achieve native performance with Cython and Numba
- Write asynchronous code using asyncio and RxPy
- Design highly scalable programs with application scaffolding
- Explore abstract methods to maintain data consistency
- Clone objects using the prototype pattern
- Use the adapter pattern to make incompatible interfaces compatible
- Employ the strategy pattern to dynamically choose an algorithm
Who this book is for:
This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.
"Synopsis" may belong to another edition of this title.
About the Author
Quan Nguyen is a Python enthusiast and data scientist. He is currently a data analysis engineer at Micron Technology, Inc. With a strong background in mathematics and statistics, Quan is interested in the fields of scientific computing and machine learning. With data analysis being his focus, Quan also enjoys incorporating technology automation into everyday tasks through programming. Quan's passion for Python programming has led him to be heavily involved in the Python community. He started as a primary contributor for the book Python for Scientists and Engineers and various open source projects on GitHub. Quan is also a writer for the Python Software Foundation and an occasional content contributor for DataScience (part of Oracle)
Sakis Kasampalis is a software engineer living in the Netherlands. He is not dogmatic about particular programming languages and tools; his principle is that the right tool should be used for the right job. One of his favorite tools is Python because he finds it very productive. Sakis was also the technical reviewer of Mastering Object-oriented Python and Learning Python Design Patterns, published by Packt Publishing.
"About the title" may belong to another edition of this title.
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