A practical guide to Fedora and Red Hat Enterprise Linux, 7th Edition (2014)

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Python interactive shell

From the Python interactive shell give the command help() to use the Python help feature. When you call it, this utility displays information to help you get started using it. Alternately, you can give the command help('object') where object is the name of an object you have instantiated or the name of a data structure or module such as list or pickle.

Web

Python home page: www.python.org

Documentation: docs.python.org

Index of Python Enhancement Proposals (PEPs): www.python.org/dev/peps

PEP 8 Style Guide for Python Code: www.python.org/dev/peps/pep-0008

PyPI (Python Package Index): pypi.python.org

Writing to Standard Output and Reading from Standard Input

raw_input()

Python makes it easy to write to standard output and read from standard input, both of which the shell (e.g., bash) connects to the terminal by default. The raw_input() function writes to standard output and reads from standard input. It returns the value of the string it reads after stripping the trailing control characters (RETURN-NEWLINE or NEWLINE).

In the following example, raw_input() displays its argument (Enter your name:) and waits for the user. When the user types something and presses RETURN, Python assigns the value returned by raw_input(), which is the string the user entered, to the variable my_in.

print

Within a print statement, a plus sign (+) catenates the strings on either side of it. The print statement in the example displays Hello, the value of my_in, and an exclamation point.

>>> my_in = raw_input ('Enter your name: ')
Enter your name: Neo
>>> print 'Hello, ' + my_in + '!'
Hello, Neo!

Functions and Methods

Functions

Functions in Python, as in most programming languages, are key to improving code readability, efficiency, and maintenance. Python has a number of builtin functions and functions you can immediately import into a Python program. These functions are available when you install Python. For example, the int() function returns the integer (truncated) part of a floating-point number:

>>> int(8.999)
8

Additional downloadable libraries hold more functions. For more information refer to “Using Libraries” on page 1103. Table 28-1 lists a few of the most commonly used functions.

Table 28-1 Commonly used functions

Methods

Functions and methods are very similar. The difference is that functions stand on their own while methods work on and are specific to objects. You will see the range() function used by itself [range(args)] and the readall() method used as an object method [f.readall(args), where f is the object (a file) readall() is reading from]. Table 28-2 on page 1089 and Table 28-4 on page 1097 list some methods.

Table 28-2 List methods

Table 28-3 File modes

Table 28-4 File object methods

Scalar Variables, Lists, and Dictionaries

This section discusses some of the Python builtin data types. Scalar data types include number and string types. Compound data types include dictionary and list types.

Scalar Variables

As in most programming languages, you declare and initialize a variable using an equal sign. Python does not require the SPACEs around the equal sign, nor does it require you to identify a scalar variable with a prefix (Perl and bash require a leading dollar sign). As explained in the tip on page 1083, you can use the print function to display the value of a variable or you can just specify the variable name as a command:

>>> lunch = 'Lunch time!'
>>> print lunch
Lunch time!
>>> lunch
'Lunch time!'

Python performs arithmetic as you might expect:

>>> n1 = 5
>>> n2 = 8
>>> n1 + n2
13

Floating-point numbers

Whether Python performs floating-point or integer arithmetic depends on the values it is given. If all of the numbers involved in a calculation are integers—that is, if none of the numbers includes a decimal point—Python performs integer arithmetic and will truncate answers that include a fractional part. If at least one of the numbers involved in a calculation is a floating-point number (includes a decimal point), Python performs floating-point arithmetic. Be careful when performing division: If the answer could include a fraction, be sure to include a decimal point in one of the numbers or explicitly specify one of the numbers as a floating-point number:

>>> 3/2
1
>>> 3/2.0
1.5
>>> float(3)/2
1.5

Lists

A Python list is an object that comprises one or more elements; it is similar to an array in C or Java. Lists are ordered and use zero-based indexing (i.e., the first element of a list is numbered zero). A list is called iterable because it can provide successive elements on each iteration through a looping control structure such as for; see page 1090 for a discussion.

This section shows one way to instantiate (create) a list. The following commands instantiate and display a list named a that holds four values:

>>> a = ['bb', 'dd', 'zz', 'rr']
>>> a
['bb', 'dd', 'zz', 'rr']

Indexes

You can access an element of a list by specifying its index (remember—the first element of a list is numbered zero). The first of the following commands displays the value of the third element of a; the next assigns the value of the first element of a to x and displays the value of x.

>>> a[2]
'zz'

>>> x = a[0]
>>> x
'bb'

When you specify a negative index, Python counts from the end of the array.

>>> a[-1]
'rr'

>>> a[-2]
'zz'

Replacing an element

You can replace an element of a list by assigning a value to it.

>>> a[1] = 'qqqq'
>>> a
['bb', 'qqqq', 'zz', 'rr']

Slicing

The next examples show how to access a slice or portion of a list. The first example displays elements 0 up to 2 of the list (elements 0 and 1):

>>> a[0:2]
['bb', 'dd']

If you omit the number that follows the colon, Python displays from the element with the index specified before the colon through the end of the list. If you omit the number before the colon, Python displays from the beginning of the list up to the element with the number specified after the colon.

>>> a[2:]
['zz', 'rr']
>>> a[:2]
['bb', 'dd']

You can use negative numbers when slicing a list. The first of the following commands displays element 1 up to the last element of the list (element –1); the second displays from the next-to-last element of the list (element –2) through the end of the list.

>>> a[1:-1]
['dd', 'zz']
>>> a[-2:]
['zz', 'rr']

remove()

Following Python’s object-oriented paradigm, the list data type includes builtin methods. The remove(x) method removes the first element of a list whose value is x, and decreases the length of the list by 1. The following command removes the first element of list a whose value is bb.

>>> a.remove('bb')
>>> a
['dd', 'zz', 'rr']

append()

The append(x) method appends an element whose value is x to the list, and increases the length of the list by 1.

>>> a.append('mm')
>>> a
['dd', 'zz', 'rr', 'mm']

reverse()

The reverse() method does not take an argument. It is an efficient method that reverses elements of a list in place, overwriting elements of the list with new values.

>>> a.reverse()
>>> a
['mm', 'rr', 'zz', 'dd']

sort()

The sort() method does not take an argument. It sorts the elements in a list in place, overwriting elements of the list with new values.

>>> a.sort()
>>> a
['dd', 'mm', 'rr', 'zz']

sorted()

If you do not want to alter the contents of the list (or other iterable data structure) you are sorting, use the sorted() function. This function returns the sorted list and does not change the original list.

>>> b = sorted(a)
>>> a
['mm', 'rr', 'zz', 'dd']
>>> b
['dd', 'mm', 'rr', 'zz']

len()

The len() function returns the number of elements in a list or other iterable data structure.

>>> len(a)
4

Table 28-2 lists some of the methods that work on lists. The command help(list) displays a complete list of methods you can use with a list.

Working with Lists

Passing a list by reference

Python passes all objects, including lists, by reference. That is, it passes an object by passing a pointer to the object. When you assign one object to another, you are simply creating another name for the object—you are not creating a new object. When you change the object using either name, you can view the change using either name. In the following example, names is instantiated as a list that holds the values sam, max, and zach; copy is set equal to names, setting up another name for (reference to) the same list. When the value of the first element of copy is changed, displaying names shows that its first element has also changed.

>>> names = ['sam', 'max', 'zach']
>>> copy = names
>>> names
['sam', 'max', 'zach']
>>> copy[0] = 'helen'
>>> names
['helen', 'max', 'zach']

Copying a list

When you use the syntax b = a[:] to copy a list, each list remains independent of the other. The next example is the same as the previous one, except copy2 points to a different location than names because the list was copied, not passed by reference: Look at the difference in the values of the first element (zero index) of both lists.

>>> names = ['sam', 'max', 'zach']
>>> copy2 = names[:]
>>> copy2[0] = 'helen'
>>> names
['sam', 'max', 'zach']
>>> copy2
['helen', 'max', 'zach']

Lists Are Iterable

An important feature of lists is that they are iterable, meaning a control structure such as for (page 1095) can loop (iterate) through each item in a list. In the following example, the for control structure iterates over the list a, assigning one element of a to item each time through the loop. The loop terminates after it has assigned each of the elements of a to item. The comma at the end of the print statement replaces the NEWLINE print normally outputs with a SPACE. You must indent lines within a control structure (called a logical block; page 1092).

>>> a
['bb', 'dd', 'zz', 'rr']
>>> for item in a:
... print item,
...
bb dd zz rr

The next example returns the largest element in a list. In this example, the list is embedded in the code; see page 1106 for a similar program that uses random numbers. The program initializes my_rand_list as a list holding ten numbers and largest as a scalar with a value of –1. The forstructure retrieves the elements of my_rand_list in order, one each time through the loop. It assigns the value it retrieves to item. Within the for structure, an if statement tests to see if item is larger than largest. If it is, the program assigns the value of item to largest and displays the new value (so you can see how the program is progressing). When control exits from the for structure, the program displays a message and the largest number. Be careful when a logical block (a subblock) appears within another logical block: You must indent the subblock one level more than its superior logical block.

$ cat my_max.py
#!/usr/bin/python

my_rand_list = [5, 6, 4, 1, 7, 3, 2, 0, 9, 8]
largest = -1
for item in my_rand_list:
if (item > largest):
largest = item
print largest,
print
print 'largest number is ', largest
$ ./my_max.py
5 6 7 9
largest number is 9

See page 1107 for an easier way to find the maximum value in a list.

Dictionaries

A Python dictionary holds unordered key–value pairs in which the keys must be unique. Other languages refer to this type of data structure as an associative array, hash, or hashmap. Like lists, dictionaries are iterable. A dictionary provides fast lookups. The class name for dictionary is dict; thus you must type help(dict) to display the help page for dictionaries. Use the following syntax to instantiate a dictionary:

dict = { key1 : value1, key2 : value2, key3 : value3 ... }

Working with Dictionaries

The following example instantiates and displays a telephone extension dictionary named ext. Because dictionaries are unordered, Python does not display a dictionary in a specific order and usually does not display it in the order it was created.

>>> ext = {'sam': 44, 'max': 88, 'zach': 22}
>>> ext
{'max': 88, 'zach': 22, 'sam': 44}

keys() and values()

You can use the keys() and values() methods to display all keys or values held in a dictionary:

>>> ext.keys()
['max', 'zach', 'sam']
>>> ext.values()
[88, 22, 44]

You can add a key–value pair:

>>> ext['helen'] = 92
>>> ext
{'max': 88, 'zach': 22, 'sam': 44, 'helen': 92}

If you assign a value to a key that is already in the dictionary, Python replaces the value (keys must be unique):

>>> ext['max'] = 150
>>> ext
{'max': 150, 'zach': 22, 'sam': 44, 'helen': 92}

The following example shows how to remove a key–value pair from a dictionary:

>>> del ext['max']
>>> ext
{'zach': 22, 'sam': 44, 'helen': 92}

You can also query the dictionary. Python returns the value when you supply the key:

>>> ext['zach']
22

items()

The items() method returns key–value pairs as a list of tuples (pairs of values). Because a dictionary is unordered, the order of the tuples returned by items() can vary from run to run.

>>> ext.items()
[('zach', 22), ('sam', 44), ('helen', 92)]

Because dictionaries are iterable, you can loop through them using for.

>>> ext = {'sam': 44, 'max': 88, 'zach': 22}
>>> for i in ext:
... print i
...
max
zach
sam

Using this syntax, the dictionary returns just keys; it is as though you wrote for i in ext.keys(). If you want to loop through values, use for i in ext.values().

Keys and values can be of different types within a dictionary:

>>> dic = {500: 2, 'bbbb': 'BBBB', 1000: 'big'}
>>> dic
{1000: 'big', 'bbbb': 'BBBB', 500: 2}

Control Structures

Control flow statements alter the order of execution of statements within a program. Starting on page 982, Chapter 27 discusses bash control structures in detail and includes flow diagrams of their operation. Python control structures perform the same functions as their bash counterparts, although the two languages use different syntaxes. The description of each control structure in this section references the discussion of the same control structure under bash.

In this section, the bold italic words in the syntax description are the items you supply to cause the structure to have the desired effect; the nonbold italic words are the keywords Python uses to identify the control structure. Many of these structures use an expression, denoted as expr, to control their execution. The examples in this chapter delimit expr using parentheses for clarity and consistency; the parentheses are not always required.

Indenting logical blocks

In most programming languages, control structures are delimited by pairs of parentheses, brackets, or braces; bash uses keywords (e.g., if...fi, do...done). Python uses a colon (:) as the opening token for a control structure. While including SPACEs (or TABs) at the beginning of lines in a control structure is good practice in other languages, Python requires these elements; they indicate a logical block, or section of code, that is part of a control structure. The last indented line marks the end of the control structure; the change in indent level is the closing token that matches the opening colon.

if

Similar to the bash if...then control structure (page 983), the Python if control structure has the following syntax:

if expr:
...

As with all Python control structures, the control block, denoted by ..., must be indented.

In the following example, my_in != '' (if my_in is not an empty string) evaluates to true if the user entered something before pressing RETURN. If expr evaluates to true, Python executes the following indented print statement. Python executes any number of indented statements that follow anif statement as part of the control structure. If expr evaluates to false, Python skips any number of indented statements following the if statement.

$ cat if1.py
#!/usr/bin/python
my_in = raw_input('Enter your name: ')
if (my_in != ''):
print 'Thank you, ' + my_in
print 'Program running, with or without your input.'

$ ./if1.py
Enter your name: Neo
Thank you, Neo.
Program running, with or without your input.

if...else

Similar to the bash if...then...else control structure (page 987), the if...else control structure implements a two-way branch using the following syntax:

if expr:
...
else:
...

If expr evaluates to true, Python executes the statements in the if control block. Otherwise, it executes the statements in the else control block. The following example builds on the previous one, displaying an error message and exiting from the program if the user does not enter something.

$ cat if2.py
#!/usr/bin/python
my_in = raw_input('Enter your name: ')
if (my_in != ''):
print 'Thank you, ' + my_in
else:
print 'Program requires input to continue.'
exit()
print 'Program running with your input.'
$ ./if2.py
Enter your name: Neo
Thank you, Neo
Program running with your input.

$ ./if2.py
Enter your name:
Program requires input to continue.

if...elif...else

Similar to the bash if...then...elif control structure (page 989), the Python if...elif...else control structure implements a nested set of if...else structures using the following syntax:

if (expr):
...
elif (expr):
...
else:
...

This control structure can include as many elif control blocks as necessary. In the following example, the if statement evaluates the Boolean expression following it within parentheses and enters the indented logical block below the statement if the expression evaluates to true. The if, elif, andelse statements are part of one control structure and Python will execute statements in only one of the indented logical blocks.

The if and elif statements are each followed by a Boolean expression. Python executes each of their corresponding logical blocks only if their expression evaluates to true. If none of the expressions evaluates to true, control falls through to the else logical block.

$ cat bignum.py
#!/usr/bin/python
input = raw_input('Please enter a number: ')
if (input == '1'):
print 'You entered one.'
elif (input == '2'):
print 'You entered two.'
elif (input == '3'):
print 'You entered three.'
else:
print 'You entered a big number...'
print 'End of program.'

In the preceding program, even though the user enters an integer/scalar value, Python stores it as a string. Thus each of the comparisons checks whether this value is equal to a string. You can use int() to convert a string to an integer. If you do so, you must remove the quotation marks from around the values:

...
input = int(raw_input('Please enter a number: '))
if (input == 1):
print 'You entered one.'
...

while

The while control structure (page 999) evaluates a Boolean expression and continues execution while the expression evaluates to true. The following program, run using the Python interactive shell, displays 0 through 9. As you enter the command, Python displays its secondary prompt (...) when it requires more input to complete a statement; you must still enter SPACE or TAB characters to indent the logical block.

First, the program initializes count to 0. The first time through the loop, the while expression evaluates to true and Python executes the indented statements that make up the while control structure logical block. The comma at the end of the print statement causes print to output a SPACEinstead of a NEWLINE after each string, and the count += 1 statement increments count each time through the loop. When control reaches the bottom of the loop, Python returns control to the while statement, where count is now 1. The loop continues while count is less than or equal to 10. When count equals 11, the while statement evaluates to false and control passes to the first statement after the logical block (the first statement that is not indented; there is none in this example).

>>> count = 0
>>> while (count <= 10):
... print count,
... count += 1
...
0 1 2 3 4 5 6 7 8 9 10