By Steven Lott
- Implement universal sensible programming layout styles and methods in Python
- Learn the best way to make a choice from relevant and useful techniques in accordance with expressiveness, readability, and performance
- Apply practical Python to universal Exploratory info research (EDA) programming problems
- Use Python's generator capabilities and generator expressions to paintings with collections in a non-strict (or lazy) manner
- Utilize Python library modules together with itertools, functools, multiprocessing, and concurrent.futures for effective practical programs
- Use Python strings with object-oriented suffix notation and prefix notation
- Avoid stateful periods through using households of tuples
- Design and enforce decorators to create composite functions
- Use features like max(), min(), map(), filter(), and sorted()
- Write complex higher-order functions
Python’s easy-to-learn and extensible skills provide a couple of sensible programming beneficial properties that you should carry into your workflow, in particular within the realm of information science.
If you’re a Python developer who desires to notice find out how to take the ability of useful programming and convey it into your individual courses then this booklet is vital for you, no matter if you recognize subsequent to not anything concerning the paradigm. beginning with a common review of sensible thoughts you’ll discover universal useful gains resembling first class and higher-order capabilities, natural features and extra, and the way those are complete in Python to offer you the center foundations you’ll construct upon. After that, you’ll notice universal useful optimizations for Python to assist your apps achieve even better speeds. You'll additionally discover information guidance ideas and knowledge exploration extensive, in addition to studying how the Python average library matches the practical programming version. ultimately, to refill your trip into the realm of functionality Python you’ll at examine the PyMonad undertaking and a few better examples to place every thing into perspective.
With practical Python Programming by means of your part you’ll comprehend the middle options of functionality Python, its impression at the programming workflow, and the way to enforce it in Python, providing you with the facility to take your purposes to a fair better level.
What you are going to learn
About the Author
Steven F. Lott has been programming because the 70s, while pcs have been huge, dear, and infrequent. As a freelance software program developer and architect, he has labored on thousands of initiatives, from very small to huge. He's been utilizing Python to unravel company difficulties for over 10 years.
Table of Contents
- Introducing useful Programming
- Introducing a few practical Features
- Functions, Iterators, and Generators
- Working with Collections
- Higher-order Functions
- Recursions and Reductions
- Additional Tuple Techniques
- The Itertools Module
- More Itertools Techniques
- The Functools Module
- Decorator layout Techniques
- The Multiprocessing and Threading Modules
- Conditional Expressions and the Operator Module
- The Pymonad Library
- A useful method of net Services
- Optimizations and Improvements
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Additional resources for Functional Python Programming
Since functions are objects with attributes, we can extract the docstring function or the name of a function, using special attributes such as __doc__ or __name__. We can also extract the body of the function via the __code__ attribute. In compiled languages, this introspection is relatively complex because of the source information that needs to be retained. In Python, it's quite simple. [ 39 ] Functions, Iterators, and Generators We can assign functions to variables, pass functions as arguments, and return functions as values.
This is quite a large prime number, with 27 digits. Using strings Since Python strings are immutable, they're an excellent example of functional programming objects. A Python string module has a number of methods, all of which produce a new string as the result. These methods are pure functions with no side effects. The syntax for string method functions is postfix, where most functions are prefix. This means that complex string operations can be hard to read when they're commingled with conventional functions.
When working with collections, however, we might need to have iterable-of-tuples or iterable-of-namedtuple constructs. The decision to use a tuple or namedtuple object is entirely a matter of convenience. We might be working with a sequence of values as a three tuple of the form (number, number, number) assuming that the triple is in red, green, and blue order. red instead of red(item). The functional programming application of tuples centers on the iterable-of-tuple design pattern. We'll look closely at a few iterable-of-tuple techniques.