By Steven Lott
- Implement universal useful programming layout styles and methods in Python
- Learn the right way to make a choice from critical and practical techniques according to expressiveness, readability, and performance
- Apply useful Python to universal Exploratory info research (EDA) programming problems
- Use Python's generator services 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 sensible programs
- Use Python strings with object-oriented suffix notation and prefix notation
- Avoid stateful periods via using households of tuples
- Design and enforce decorators to create composite functions
- Use services like max(), min(), map(), filter(), and sorted()
- Write complicated higher-order functions
Python’s easy-to-learn and extensible talents provide a couple of sensible programming gains so that you can deliver into your workflow, in particular within the realm of information science.
If you’re a Python developer who desires to notice tips on how to take the ability of practical programming and convey it into your personal courses then this booklet is vital for you, no matter if you recognize subsequent to not anything concerning the paradigm. beginning with a basic review of useful techniques you’ll discover universal sensible positive factors corresponding to top quality and higher-order features, natural services and extra, and the way those are finished in Python to provide you the center foundations you’ll construct upon. After that, you’ll detect universal useful optimizations for Python to assist your apps succeed in even larger speeds. You'll additionally discover facts training thoughts and knowledge exploration extensive, besides studying how the Python commonplace library suits the useful programming version. ultimately, to stock up your trip into the realm of functionality Python you’ll at examine the PyMonad undertaking and a few greater examples to place every little thing into perspective.
With practical Python Programming via your aspect you’ll comprehend the center ideas of functionality Python, its effect at the programming workflow, and the way to enforce it in Python, providing you with the facility to take your purposes to a fair larger level.
What you are going to learn
About the Author
Steven F. Lott has been programming because the 70s, while pcs have been huge, pricey, and infrequent. As a freelance software program developer and architect, he has labored on enormous quantities of tasks, from very small to huge. He's been utilizing Python to resolve enterprise difficulties for over 10 years.
Table of Contents
- Introducing useful Programming
- Introducing a few useful 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 internet Services
- Optimizations and Improvements
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Extra info for Functional Python Programming
The second evaluation of the sum() method found that the generator was now empty. We can only consume the values once. Generators have a stateful life in Python. While they're very nice for some aspects of functional programming, they're not quite perfect. tee() method to overcome the once-only limitation. We'll look at this in depth in Chapter 8, The Itertools Module. tee(iterable, 2) return max(max_tee), min(min_tee) We created two clones of the parameter generator expression, max_tee() and min_tee().
0207440659869462 In this case, there's some benefit in working from left to right. What's important for functional design is the idea that the + operator (or add() function) can be used in any order to produce the same results. The + operator has no hidden side effects that restrict the way this operator can be used. The stack of turtles When we use Python for functional programming, we embark down a path that will involve a hybrid that's not strictly functional. Python is not Haskell, OCaml, or Erlang.
In the next chapter, we'll look at the core concepts of pure functions and how these fit with Python's built-in data structures. Given this foundation, we can look at higher-order functions available in Python and how we can define our own higher-order functions. [ 36 ] Functions, Iterators, and Generators The core of functional programming is the use of pure functions to map values from the input domain to the output range. A pure function has no side effects, a relatively easy threshold for us to achieve in Python.