PythonInformer ebooks


Martin McBride, 2020-04-18
Categories book

Python ebooks from the author of PythonInformer.com.

Numpy Recipes

Buy now or download a free preview from Leanpub, or other bookstores.

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.

Computer Graphics in Python with Pycairo

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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.

Functional Programming in Python

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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.


Tag cloud

2d arrays abstract data type alignment and array arrays bezier curve built-in function close closure colour comparison operator comprehension context conversion data types design pattern device space dictionary duck typing efficiency encryption enumerate filter font font style for loop function function composition function plot functools generator gif gradient greyscale higher order function html image processing imagesurface immutable object index inner function input installing iter iterator itertools lambda function len linspace list list comprehension logical operator lru_cache mandelbrot map monad mutability named parameter numeric python numpy object open operator optional parameter or partial application path positional parameter print pure function radial gradient range recipes recursion reduce rgb rotation scaling sequence slice slicing sound spirograph str stream string subpath symmetric encryption template text text metrics transform translation transparency tuple unpacking user space vectorisation webserver website while loop zip

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