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Learn Python Programming

You're reading from   Learn Python Programming A comprehensive, up-to-date, and definitive guide to learning Python

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882948
Length 616 pages
Edition 4th Edition
Languages
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Authors (2):
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Heinrich Kruger Heinrich Kruger
Author Profile Icon Heinrich Kruger
Heinrich Kruger
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
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Toc

Table of Contents (11) Chapters Close

Learn Python Programming, Fourth Edition: A Comprehensive, Up-to-Date, and Definitive Guide to Learning Python FREE CHAPTER
1 A Gentle Introduction to Python 2 Built-In Data Types 3 Conditionals and Iteration 4 Functions, the Building Blocks of Code 5 Comprehensions and Generators 6 OOP, Decorators, and Iterators 7 Exceptions and Context Managers 8 Files and Data Persistence 9 Cryptography and Tokens 10 Testing

One last example

Before we finish this chapter, we will show you a simple problem that Fabrizio used to give to candidates for a Python developer role in a company he used to work for.

The problem is the following: write a function that returns the terms of the sequence 0 1 1 2 3 5 8 13 21 ..., up to some limit, N.

If you have not recognized it, that is the Fibonacci sequence, which is defined as F(0) = 0, F(1) = 1 and, for any n > 1, F(n) = F(n-1) + F(n-2). This sequence is excellent for testing knowledge about recursion, memoization techniques, and other technical details, but in this case, it was a good opportunity to check whether the candidate knew about generators.

Let us start with a rudimentary version, and then improve on it:

# fibonacci.first.py
def fibonacci(N):
    """Return all fibonacci numbers up to N."""
    result = [0]
    next_n = 1
    while next_n <= N:
        result.append(next_n)
        next_n = sum(result[-2:])
    return...
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