4. More Control Flow Tools

Perhaps the most well-known statement type is the if statement. For example:

There can be zero or more elif parts, and the else part is optional. The keyword ‘ elif ’ is short for ‘ else if ’, and is useful to avoid excessive indentation. An if … elif … elif … sequence is a substitute for the switch or case statements found in other languages.

The for statement in Python differs a bit from what you may be used to in C or Pascal. Rather than always iterating over an arithmetic progression of numbers (like in Pascal), or giving the user the ability to define both the iteration step and halting condition (as C), Python’s for statement iterates over the items of any sequence (a list or a string), in the order that they appear in the sequence. For example (no pun intended):

If you need to modify the sequence you are iterating over while inside the loop (for example to duplicate selected items), it is recommended that you first make a copy. Iterating over a sequence does not implicitly make a copy. The slice notation makes this especially convenient:

With for w in words:, the example would attempt to create an infinite list, inserting defenestrate over and over again.

If you do need to iterate over a sequence of numbers, the built-in function range() comes in handy. It generates arithmetic progressions:

The given end point is never part of the generated sequence; range(10) generates 10 values, the legal indices for items of a sequence of length 10. It is possible to let the range start at another number, or to specify a different increment (even negative; sometimes this is called the ‘step’):

To iterate over the indices of a sequence, you can combine range() and len() as follows:

In most such cases, however, it is convenient to use the enumerate() function, see Looping Techniques.

A strange thing happens if you just print a range:

In many ways the object returned by range() behaves as if it is a list, but in fact it isn’t. It is an object which returns the successive items of the desired sequence when you iterate over it, but it doesn’t really make the list, thus saving space. We say such an object is iterable, that is, suitable as a target for functions and constructs that expect something from which they can obtain successive items until the supply is exhausted. We have seen that the for statement is such an iterator. The function list() is another; it creates lists from iterables:

Later we will see more functions that return iterables and take iterables as argument.

The break statement, like in C, breaks out of the innermost enclosing for or while loop.

Loop statements may have an else clause; it is executed when the loop terminates through exhaustion of the list (with for ) or when the condition becomes false (with while), but not when the loop is terminated by a break statement. This is exemplified by the following loop, which searches for prime numbers:

(Yes, this is the correct code. Look closely: the else clause belongs to the for loop, not the if statement.)

When used with a loop, the else clause has more in common with the else clause of a try statement than it does that of if statements: a try statement’s else clause runs when no exception occurs, and a loop’s else clause runs when no break occurs. For more on the try statement and exceptions, see Handling Exceptions.

The continue statement, also borrowed from C, continues with the next iteration of the loop:

The pass statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example:

This is commonly used for creating minimal classes:

Another place pass can be used is as a place-holder for a function or conditional body when you are working on new code, allowing you to keep thinking at a more abstract level. The pass is silently ignored:

Now that you are about to write longer, more complex pieces of Python, it is a good time to talk about coding style. Most languages can be written (or more concise, formatted ) in different styles; some are more readable than others. Making it easy for others to read your code is always a good idea, and adopting a nice coding style helps tremendously for that.

For Python, PEP 8 has emerged as the style guide that most projects adhere to; it promotes a very readable and eye-pleasing coding style. Every Python developer should read it at some point; here are the most important points extracted for you:

• Use 4-space indentation, and no tabs. 4 spaces are a good compromise between small indentation (allows greater nesting depth) and large indentation (easier to read). Tabs introduce confusion, and are best left out.
• Wrap lines so that they don’t exceed 79 characters. This helps users with small displays and makes it possible to have several code files side-by-side on larger displays.
• Use blank lines to separate functions and classes, and larger blocks of code inside functions.
• When possible, put comments on a line of their own.
• Use docstrings.
• Use spaces around operators and after commas, but not directly inside bracketing constructs: a = f(1, 2) + g(3, 4).
• Name your classes and functions consistently; the convention is to use CamelCase for classes and lower_case_with_underscores for functions and methods. Always use self as the name for the first method argument (see A First Look at Classes for more on classes and methods).
• Don’t use fancy encodings if your code is meant to be used in international environments. Python’s default, UTF-8, or even plain ASCII work best in any case.
• Likewise, don’t use non-ASCII characters in identifiers if there is only the slightest chance people speaking a different language will read or maintain the code.