Python ebooks from the author of PythonInformer.com.
NumPy Recipes takes practical approach to the basics of NumPy
This book is primarily aimed at developers who have at least a small amount of Python experience, who wish to use the NumPy library for data analysis, machine learning, image or sound processing, or any other mathematical or scientific application. It only requires a basic understanding of Python programming.
Detailed examples show how to create arrays to optimise storage different types of information, and how to use universal functions, vectorisation, broadcasting and slicing to process data efficiently. Also contains an introduction to file i/o and data visualisation with Matplotlib.
The Pycairo library is a Python graphics library. This book covers the library in detail, with lots of practical code examples.
PyCairo is an efficient, fully featured, high quality graphics library, with similar drawing capabilities to other vector libraries and languages such as SVG, PDF, HTML canvas and Java graphics.
Typical use cases include: standalone Python scripts to create an image, chart, or diagram; server side image creation for the web (for example a graph of share prices that updates hourly); desktop applications, particularly those that involve interactive images or diagrams.
The power of Pycairo, with the expressiveness of Python, is also a great combination for making procedural images such as mathematical illustrations and generative art. It is also quite simple to generate image sequences that can be converted to video or animated gifs.
Python's best kept secret is its built in support for functional programming. Even better, it allows functional programming to be blended seamlessly with procedural and object oriented coding styles. This book explains what functional programming is, how Python supports it, and how you can use it to write clean, efficient and reliable code.
The book covers the basics of functional programming including function objects, immutability, recursion, iterables, comprehensions and generators. It also covers more advanced topics such as closures, memoization, partial functions, currying, functors and monads. No prior knowledge of functional programming is required, just a working knowledge of Python.
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