Python Iterators: Part Five

Python iteratorAnother common use for list comprehensions is with files. A file object has a readlines method that loads the file into a list of line strings all at once; e.g.:

>>> fp = open('simple.py')
>>> lines = fp.readlines()
>>> lines
['a = [1, 2, 3, 4]\n', 'for x in a:\n', 'print(x)\n', 'print(x*2)\n','\n']

This will work, but the lines in the result all include the newline character. Perhaps we can use list comprehensions to get rid of all the newlines.

One way we could accomplish this is by running each line in the list through the string rstrip method to remove whitespaces on the right side. So now we have:

>>> lines = [line.rstrip() for line in lines]
>>> lines
['a = [1, 2, 3, 4]', 'for x in a:', 'print(x)', 'print(x*2)','']

This works as we expected. Because the list comprehensions are an iteration conect just like the for loop statements, however, we do not have to open the file ahead of time. If we open the file inside the expression, the list comprehension will automatically use the iteration protocol used earlier. It will read one line from the file at a time by calling the file’s next method, run the line through the rstrip expression, and add it to the result list. The code now looks like this:

>>> lines = [line.rstrip() for line in open('simple.py')]
>>> lines
['a = [1, 2, 3, 4]', 'for x in a:', 'print(x)', 'print(x*2)','']

Again, the code does what we want it to do. This expression does a lot implicitly, although we are getting a lot of work done for free. Python scans the file and builds a list of operation results automatically. It is also an efficient way to write the code: because most of the work is done inside the Python interpreter, it is likely much faster than the equivalent for statement. Especially for large files, the speed advantages of list comprehensions can be considerable.

List comprehensions are also expressive. For example, we can run any string operation on a file’s lines as we iterate. For example, we can use a list comprehension to convert the contents of the file to uppercase:

>>> [line.upper() for line in open('simple.py')]
['A = [1, 2, 3, 4]\n', 'FOR X IN A:\n', '\tPRINT(X)\n', '\tPRINT(X*2)\n', '\n']

If we also want to strip out the newline, we can do that too:

>>> [line.rstrip().upper() for line in open('script1.py')]
['A = [1, 2, 3, 4]', 'FOR X IN A:', '\tPRINT(X)', '\tPRINT(X*2)', '']

Beyond this complexity level, however, list comprehension expressions can become too compact for their own good. They are generally intended for simple types of iterations; for more involved programming statements, a simple for statement structure will likely be easier to understand and modify in the future.

External Links:

Python Iterators at Python Wiki

Python Iterator tutorial at bogotobogo.com