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A Tutorial Introduction
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The for loop is one of Python s most powerful language features because you can create custom iterator objects and generator functions that supply it with sequences of values More details about iterators and generators can be found later in this chapter and in 6, Functions and Functional Programming
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Functions
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You use the def statement to create a function, as shown in the following example:
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def remainder(a,b): q = a // b r = a - q*b return r # // is truncating division
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To invoke a function, simply use the name of the function followed by its arguments enclosed in parentheses, such as result = remainder(37,15)You can use a tuple to return multiple values from a function, as shown here:
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def divide(a,b): q = a // b r = a - q*b return (q,r) # If a and b are integers, q is integer
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When returning multiple values in a tuple, you can easily unpack the result into separate variables like this:
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To assign a default value to a function parameter, use assignment:
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When default values are given in a function definition, they can be omitted from subsequent function callsWhen omitted, the argument will simply take on the default value Here s an example:
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You also can invoke functions by using keyword arguments and supplying the arguments in arbitrary order However, this requires you to know the names of the arguments in the function definition Here s an example:
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When variables are created or assigned inside a function, their scope is localThat is, the variable is only defined inside the body of the function and is destroyed when the function returnsTo modify the value of a global variable from inside a function, use the global statement as follows:
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# Changes the global variable count
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Generators
Generators
Instead of returning a single value, a function can generate an entire sequence of results if it uses the yield statement For example:
def countdown(n): print "Counting down!" while n > 0: yield n # Generate a value (n) n -= 1
Any function that uses yield is known as a generator Calling a generator function creates an object that produces a sequence of results through successive calls to a next() method (or _ _next_ _() in Python 3) For example:
>>> c = countdown(5) >>> cnext() Counting down! 5 >>> cnext() 4 >>> cnext() 3 >>>
The next() call makes a generator function run until it reaches the next yield statement At this point, the value passed to yield is returned by next(), and the function suspends executionThe function resumes execution on the statement following yield when next() is called againThis process continues until the function returns Normally you would not manually call next() as shown Instead, you hook it up to a for loop like this:
>>> for i in countdown(5): print i, Counting down! 5 4 3 2 1 >>>
Generators are an extremely powerful way of writing programs based on processing pipelines, streams, or data flow For example, the following generator function mimics the behavior of the UNIX tail -f command that s commonly used to monitor log files:
# tail a file (like tail -f) import time def tail(f): fseek(0,2) # Move to EOF while True: line = freadline() # Try reading a new line of text if not line: # If nothing, sleep briefly and try again timesleep(01) continue yield line
Here s a generator that looks for a specific substring in a sequence of lines:
def grep(lines, searchtext): for line in lines: if searchtext in line: yield line
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A Tutorial Introduction
Here s an example of hooking both of these generators together to create a simple processing pipeline:
# A python implementation of Unix "tail -f | grep python" wwwlog = tail(open("access-log")) pylines = grep(wwwlog,"python") for line in pylines: print line,
A subtle aspect of generators is that they are often mixed together with other iterable objects such as lists or files Specifically, when you write a statement such as for item in s, s could represent a list of items, the lines of a file, the result of a generator function, or any number of other objects that support iterationThe fact that you can just plug different objects in for s can be a powerful tool for creating extensible programs