Inside any one module, we can specify variables, classes, or functions. They can be a handy way to store the global state without namespace conflicts. For example, we have been importing the Database class into various modules and then instantiating it, but it might make more sense to have only one database object globally available from the database module. The database module might look like this:
class Database:
# the database implementation
pass
database = Database()
Then we can use any of the import methods we've discussed to access the database object, for example:
from ecommerce.database import database
A problem with the preceding class is that the database object is created immediately when the module is first imported, which is usually when the program starts up. This isn't always ideal, since connecting to a database can take a while, slowing down startup, or the database connection information may not yet be available. We could delay creating the database until it is actually needed by calling an initialize_database function to create a module-level variable:
class Database:
# the database implementation
pass
database = None
def initialize_database():
global database
database = Database()
The global keyword tells Python that the database variable inside initialize_database is the module level one we just defined. If we had not specified the variable as global, Python would have created a new local variable that would be discarded when the method exits, leaving the module-level value unchanged.
As these two examples illustrate, all module-level code is executed immediately at the time it is imported. However, if it is inside a method or function, the function will be created, but its internal code will not be executed until the function is called. This can be a tricky thing for scripts that perform execution (such as the main script in our e-commerce example). Sometimes, we write a program that does something useful, and then later find that we want to import a function or class from that module into a different program. However, as soon as we import it, any code at the module level is immediately executed. If we are not careful, we can end up running the first program when we really only meant to access a couple of functions inside that module.
To solve this, we should always put our start up code in a function (conventionally, called main) and only execute that function when we know we are running the module as a script, but not when our code is being imported from a different script. We can do this by guarding the call to main inside a conditional statement, demonstrated as follows:
class UsefulClass:
"""This class might be useful to other modules."""
pass
def main():
"""Creates a useful class and does something with it for our module."""
useful = UsefulClass()
print(useful)
if __name__ == "__main__":
main()
Every module has a __name__ special variable (remember, Python uses double underscores for special variables, such as a class's __init__ method) that specifies the name of the module when it was imported. When the module is executed directly with python module.py, it is never imported, so the __name__ is arbitrarily set to the "__main__" string. Make it a policy to wrap all your scripts in an if __name__ == "__main__": test, just in case you write a function that you may want to be imported by other code at some point in the future.
So, methods go in classes, which go in modules, which go in packages. Is that all there is to it?
Actually, no. This is the typical order of things in a Python program, but it's not the only possible layout. Classes can be defined anywhere. They are typically defined at the module level, but they can also be defined inside a function or method, like this:
def format_string(string, formatter=None):
"""Format a string using the formatter object, which
is expected to have a format() method that accepts
a string."""
class DefaultFormatter:
"""Format a string in title case."""
def format(self, string):
return str(string).title()
if not formatter:
formatter = DefaultFormatter()
return formatter.format(string)
hello_string = "hello world, how are you today?"
print(" input: " + hello_string)
print("output: " + format_string(hello_string))
The output would be as follows:
input: hello world, how are you today? output: Hello World, How Are You Today?
The format_string function accepts a string and optional formatter object, and then applies the formatter to that string. If no formatter is supplied, it creates a formatter of its own as a local class and instantiates it. Since it is created inside the scope of the function, this class cannot be accessed from anywhere outside of that function. Similarly, functions can be defined inside other functions as well; in general, any Python statement can be executed at any time.
These inner classes and functions are occasionally useful for one-off items that don't require or deserve their own scope at the module level, or only make sense inside a single method. However, it is not common to see Python code that frequently uses this technique.
