Minimize Global Variables

By default, names assigned in functions are locals, so if you want to change names outside functions you have to write extra code (e.g., global statements). This is by design—as is common in Python, you have to say more to do the potentially “wrong” thing. Although there are times when globals are useful, variables assigned in a def are local by default because that is normally the best policy. Changing globals can lead to well-known software engineering problems: because the variables’ values are dependent on the order of calls to arbitrarily distant functions, programs can become difficult to debug.

Consider this module file, for example:

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X = 99
def func1():
    global X
    X = 88

def func2():
    global X
    X = 77

Now, imagine that it is your job to modify or reuse this module file. What will the value of X be here? Really, that question has no meaning unless it’s qualified with a point of reference in time—the value of X is timing-dependent, as it depends on which function was called last (something we can’t tell from this file alone).

The net effect is that to understand this code, you have to trace the flow of control through the entire program. And, if you need to reuse or modify the code, you have to keep the entire program in your head all at once. In this case, you can’t really use one of these functions without bringing along the other. They are dependent on (that is, coupled with) the global variable. This is the problem with globals—they generally make code more difficult to understand and use than code consisting of self-contained functions that rely on locals.

On the other hand, short of using object-oriented programming and classes, global variables are probably the most straightforward way to retain shared state information (information that a function needs to remember for use the next time it is called) in Python—local variables disappear when the function returns, but globals do not. Other techniques, such as default mutable arguments and enclosing function scopes, can achieve this, too, but they are more complex than pushing values out to the global scope for retention.

Some programs designate a single module to collect globals; as long as this is expected, it is not as harmful. In addition, programs that use multithreading to do parallel processing in Python commonly depend on global variables—they become shared memory between functions running in parallel threads, and so act as a communication device.[38]

For now, though, especially if you are relatively new to programming, avoid the temptation to use globals whenever you can—try to communicate with passed-in arguments and return values instead. Six months from now, both you and your coworkers will be happy you did.