7.9. Summary¶
Miscommunication happens in every language, even in programming lan- guages. Python has a few gotchas that can trap the unwary. Even if they rarely come up, it’s best to know about them so you can quickly recognize and debug the problems they can cause.
Although it’s possible to add or remove items from a list while iterating over that list, it’s a potential source of bugs. It’s much safer to iterate over a copy of the list and then make changes to the original. When you do make copies of a list (or any other mutable object), remember that assignment statements copy only the reference to the object, not the actual object. You can use the copy.deepcopy() function to make copies of the object (and cop- ies of any objects it references).
You shouldn’t use mutable objects in def statements for default argu- ments, because they’re created once when the def statement is run rather than each time the function is called. A better idea is to make the default argument None , and then add code that checks for None and creates a muta- ble object when the function is called.
A subtle gotcha is the string concatenation of several smaller strings with the + operator in a loop. For small numbers of iteration, this syntax is fine. But under the hood, Python is constantly creating and destroying string objects on each iteration. A better approach is to append the smaller strings into a list and then call the join() operator to create the final string. The sort() method sorts by numeric code points, which isn’t the same as alphabetical order: uppercase Z is sorted before lowercase a. To fix this issue, you can call sort(key=str.lower) .
Floating-point numbers have slight rounding errors as a side effect of how they represent numbers. For most programs, this isn’t important. But if it does matter for your program, you can use Python’s decimal module. Never chain together != operators, because expressions like ‘cat’ != ‘dog’ != ‘cat’ will, confusingly, evaluate to True .
Although this chapter described the Python gotchas that you’re most likely to encounter, they don’t occur daily in most real-world code. Python does a great job of minimizing the surprises you might find in your programs. In the next chapter, we’ll cover some gotchas that are even rarer and downright bizarre. It’s almost impossible that you’ll ever encounter these Python language oddities if you aren’t searching for them, but it’ll be fun to explore the reasons they exist.