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Built-In Containers

Метки: python

With languages like C++ and Java, containers are add-on libraries and not integral to the language. In Python, the essential nature of containers for programming is acknowledged by building them into the core of the language: both lists and associative arrays (a.k.a. maps, dictionaries, hash tables) are fundamental data types. This adds much to the elegance of the language.

In addition, the for statement automatically iterates through lists rather than just counting through a sequence of numbers. This makes a lot of sense when you think about it, since you’re almost always using a for loop to step through an array or a container. Python formalizes this by automatically making for use an iterator that works through a sequence. Here’s an example:

# PythonForProgrammers/list.py
list = [ 1, 3, 5, 7, 9, 11 ]
print(list)
list.append(13)
for x in list:
    print(x)

The first line creates a list. You can print the list and it will look exactly as you put it in (in contrast, remember that I had to create a special Arrays2 class in Thinking in Java in order to print arrays in Java). Lists are like Java containers - you can add new elements to them (here, append( ) is used) and they will automatically resize themselves. The for statement creates an iterator x which takes on each value in the list.

You can create a list of numbers with the range( ) function, so if you really need to imitate C’s for, you can.

Notice that there aren’t any type declarations - the object names simply appear, and Python infers their type by the way that you use them. It’s as if Python is designed so that you only need to press the keys that absolutely must. You’ll find after you’ve worked with Python for a short while that you’ve been using up a lot of brain cycles parsing semicolons, curly braces, and all sorts of other extra verbiage that was demanded by your non-Python programming language but didn’t actually describe what your program was supposed to do.