000			03091cam a2200301zu 4500
001			88866863
003			FRCYB88866863
005			20251020123814.0
006			m o d
007			cr un
008			251020s2019 fr | o|||||0|0|||eng d
020			_a9781838551216
035			_aFRCYB88866863
040			_aFR-PaCSA _ben _c _erda
100	1		_aLanaro, Dr. Gabriele
245	0	1	_aAdvanced Python Programming _c['Lanaro, Dr. Gabriele', 'Nguyen, Quan', 'Kasampalis, Sakis']
264		1	_bPackt Publishing _c2019
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aLanaro, Dr. Gabriele
700	0		_aNguyen, Quan
700	0		_aKasampalis, Sakis
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88866863 _qtext/html _a
520			_aCreate 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.
999			_c1555457 _d1555457