Python One-Liners

Python One-Liners

Write Concise, Eloquent Python Like a Professional
by Christian Mayer
April 2020 , 216 pages

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Python One-Liners

Python One-Liners will teach you how to read and write “one-liners”: concise statements of useful functionality packed into a single line of code. You'll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.

The book’s five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills.

You'll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments.

You’ll also learn how to:

  • Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution
  • Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggregating, and statistics
  • Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
  • Create more advanced regular expressions using grouping and named groups, negative lookaheads, escaped characters, whitespaces, character sets (and negative characters sets), and greedy/nongreedy operators
  • Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, prime numbers, Fibonacci numbers, obfuscation, searching, and algorithmic sorting

By the end of the book, you’ll know how to write Python at its most refined, and create concise, beautiful pieces of "Python art" in merely a single line.

Author Bio 

Christian Mayer has a PhD in computer science and is the founder of the popular Python site Finxter. Mayer is also the author of the Coffee Break Python series.

Table of contents 


Chapter 1: Python Refresher
Chapter 2: Python Tricks
Chapter 3:Data Science
Chapter 4: Machine Learning
Chapter 5: Regular Expressions
Chapter 6: Algorithms

View the detailed Table of Contents
View the Index


"This book is great for flexing in an interview or thinking of python in completely different ways." —Ian Mizer (Read More)

"A great resource for programmers who want to learn Python or get better with their Python skills." —JustJon (Read More)


Page 7: In step 2 of the first code listing:
l.insert(2, 3)
# [1, 2, 3, 4]

Should instead read:
l/insert(2, 2)
# [1, 2, 2, 4]

Under Removing Elements:
You can easily remove an element x from a list
Should instead read:
You can easily remove the first occurrence of element x from a list

Page 8: Under Indexing List Elements:
The method index(x) finds the first occurrence of the element x in the list and returns its index.
Should instead read:
The list.index(x) method returns the index of the element x in the list. You can use optional start and stop arguments to limit the index range to search.

Page 35: At the end of the paragraph How It Works, add:
You need to install the matplotlib library with pip install matplotlib in your terminal or shell to use this example in your own programs.

Page 40: In the text box:
[(True, s) if 'anonymous' in s else (False, s) for s in txt]
Should instead read:
[('anonymous' in s, s) for s in txt]

Page 65: Before the last sentence, "Listing 3-22 shows..." add the sentence:
Roughly speaking, the axis parameter controls which axis will be aggregated or collapsed when used in a NumPy operation such as np.sort().

Page 92: In the ## One-liner part of the code listing:
reshape(n,1), X…
Should instead read:

Page 168: Under The Basics:
...except for i and n
Should instead read:
...except for 1 and n