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Product type Book
Published in Dec 2015
Publisher Packt
ISBN-13 9781783551712
Pages 442 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Mr. Fabrizio Romano

Learning Python
Credits
Acknowledgements
www.PacktPub.com
Preface
1. Introduction and First Steps – Take a Deep Breath 2. Built-in Data Types 3. Iterating and Making Decisions 4. Functions, the Building Blocks of Code 5. Saving Time and Memory 6. Advanced Concepts – OOP, Decorators, and Iterators 7. Testing, Profiling, and Dealing with Exceptions 8. The Edges – GUIs and Scripts 9. Data Science 10. Web Development Done Right 11. Debugging and Troubleshooting 12. Summing Up – A Complete Example Index

## Comprehensions

Python offers you different types of comprehensions: `list`, `dict`, and `set`.

We'll concentrate on the first one for now, and then it will be easy to explain the other two.

A `list` comprehension is a quick way of making a list. Usually the list is the result of some operation that may involve applying a function, filtering, or building a different data structure.

Let's start with a very simple example I want to calculate a list with the squares of the first 10 natural numbers. How would you do it? There are a couple of equivalent ways:

`squares.map.py`

```# If you code like this you are not a Python guy! ;)
>>> squares = []
>>> for n in range(10):
...     squares.append(n ** 2)
...
>>> list(squares)
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

# This is better, one line, nice and readable
>>> squares = map(lambda n: n**2, range(10))
>>> list(squares)
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
```

The preceding example should be nothing new for you. Let's see...

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