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Functional Python Programming

Functional Python Programming

3.7 (3)
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Functional Python Programming

Functional Python Programming

3.7 (3)

Overview of this book

If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.
Table of Contents (22 chapters)
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Title Page
Packt Upsell
Contributors
Preface
Index

Evaluating conditional expressions


Python imposes strict ordering on expressions; the notable exceptions are the short-circuit operators, and and or. It imposes strict ordering on statement evaluation. This makes it challenging to find optimizations because they would break the strict evaluation order.

Evaluating condition expressions is one way in which we can experiment with non-strict ordering of statements. The if, elif, and elsePython statements are evaluated in a strict order from first to last. Ideally, an optimizing language may relax this rule so that a compiler can find a faster order for evaluating the conditional expressions. This allows us to write the expressions in an order that makes sense to a reader, and lets the compiler find a faster evaluation order.

Lacking an optimizing compiler, the concept of non-strict ordering is a bit of a stretch for Python. Nonetheless, we do have alternative ways to express conditions that involve the evaluation of functions instead of the execution...

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