Of course this means that speed and sanity surrounding string features is important. One important feature of Python is string immutability. This opens up dozens of features, such as using strings as dictionary keys, but there are some downsides.
Immutable strings means that any string manipulation, such as splitting or appending, is making a copy of that string. This can become a performance problem, especially in a world where zero-copy is one of the favorite general optimization techniques. If you've done enough string mutation, you're probably aware of the following techniques:
Here, because adding an empty string does not change the value, z is the same exact string object as a. And it doesn't matter how many times you append an empty string:>>> a = 'a' * 1024 * 1024 # a 1 megabyte string >>> z = '' + a >>> z is a True
It even works when a is the only item in a list:>>> z = '' + '' + '' + a >>> z is a True
But it falls apart when you put an empty string in the list with a:>>> z = ''.join([a]) >>> z is a True
And unfortunately even the first example seems to make a copy on PyPy:>>> z = ''.join(['', a]) >>> z is a False
Although something more advanced may be going on under the covers, as is often the case with PyPy.>>>> a = 'a' * 1024 * 1024 # a 1 megabyte string again >>>> z = '' + a >>>> z is aFalse
I'm almost done stringing you along, but as a corollary reminder:
Never rely on "is" checks with ints, floats, and strings. "==" and other value checks are what you need. As a general rule, "is" is for objects, None, and sometimes True/False.
Keep on stringifying!