This tutorial covers Python namespaces, the structures used to organize the symbolic names assigned to objects in a Python program.
The previous tutorials in this series have emphasized the importance of objects in Python. Objects are everywhere! Virtually everything that your Python program creates or acts on is an object.
An assignment statement creates a symbolic name that you can use to reference an object. The statement x = 'foo' creates a symbolic name x that refers to the string object 'foo'.
In a program of any complexity, you’ll create hundreds or thousands of such names, each pointing to a specific object. How does Python keep track of all these names so that they don’t interfere with one another?
In this tutorial, you’ll learn:
- How Python organizes symbolic names and objects in namespaces
- When Python creates a new namespace
- How namespaces are implemented
- How variable scope determines symbolic name visibility
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Namespaces in Python
A namespace is a collection of currently defined symbolic names along with information about the object that each name references. You can think of a namespace as a dictionary in which the keys are the object names and the values are the objects themselves. Each key-value pair maps a name to its corresponding object.
Namespaces are one honking great idea—let’s do more of those!
— The Zen of Python, by Tim Peters
As Tim Peters suggests, namespaces aren’t just great. They’re honking great, and Python uses them extensively. In a Python program, there are four types of namespaces:
- Built-In
- Global
- Enclosing
- Local
These have differing lifetimes. As Python executes a program, it creates namespaces as necessary and deletes them when they’re no longer needed. Typically, many namespaces will exist at any given time.
The Built-In Namespace
The built-in namespace contains the names of all of Python’s built-in objects. These are available at all times when Python is running. You can list the objects in the built-in namespace with the following command:
>>> dir(__builtins__)
['ArithmeticError', 'AssertionError', 'AttributeError',
'BaseException','BlockingIOError', 'BrokenPipeError', 'BufferError',
'BytesWarning', 'ChildProcessError', 'ConnectionAbortedError',
'ConnectionError', 'ConnectionRefusedError', 'ConnectionResetError',
'DeprecationWarning', 'EOFError', 'Ellipsis', 'EnvironmentError',
'Exception', 'False', 'FileExistsError', 'FileNotFoundError',
'FloatingPointError', 'FutureWarning', 'GeneratorExit', 'IOError',
'ImportError', 'ImportWarning', 'IndentationError', 'IndexError',
'InterruptedError', 'IsADirectoryError', 'KeyError', 'KeyboardInterrupt',
'LookupError', 'MemoryError', 'ModuleNotFoundError', 'NameError', 'None',
'NotADirectoryError', 'NotImplemented', 'NotImplementedError', 'OSError',
'OverflowError', 'PendingDeprecationWarning', 'PermissionError',
'ProcessLookupError', 'RecursionError', 'ReferenceError', 'ResourceWarning',
'RuntimeError', 'RuntimeWarning', 'StopAsyncIteration', 'StopIteration',
'SyntaxError', 'SyntaxWarning', 'SystemError', 'SystemExit', 'TabError',
'TimeoutError', 'True', 'TypeError', 'UnboundLocalError',
'UnicodeDecodeError', 'UnicodeEncodeError', 'UnicodeError',
'UnicodeTranslateError', 'UnicodeWarning', 'UserWarning', 'ValueError',
'Warning', 'ZeroDivisionError', '_', '__build_class__', '__debug__',
'__doc__', '__import__', '__loader__', '__name__', '__package__',
'__spec__', 'abs', 'all', 'any', 'ascii', 'bin', 'bool', 'bytearray',
'bytes', 'callable', 'chr', 'classmethod', 'compile', 'complex',
'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod', 'enumerate',
'eval', 'exec', 'exit', 'filter', 'float', 'format', 'frozenset',
'getattr', 'globals', 'hasattr', 'hash', 'help', 'hex', 'id', 'input',
'int', 'isinstance', 'issubclass', 'iter', 'len', 'license', 'list',
'locals', 'map', 'max', 'memoryview', 'min', 'next', 'object', 'oct',
'open', 'ord', 'pow', 'print', 'property', 'quit', 'range', 'repr',
'reversed', 'round', 'set', 'setattr', 'slice', 'sorted', 'staticmethod',
'str', 'sum', 'super', 'tuple', 'type', 'vars', 'zip']
You’ll see some objects here that you may recognize from previous tutorials—for example, the StopIteration exception, built-in functions like max() and len(), and object types like int and str.
The Python interpreter creates the built-in namespace when it starts up. This namespace remains in existence until the interpreter terminates.
The Global Namespace
The global namespace contains any names defined at the level of the main program. Python creates the global namespace when the main program body starts, and it remains in existence until the interpreter terminates.
Strictly speaking, this may not be the only global namespace that exists. The interpreter also creates a global namespace for any module that your program loads with the import statement. For further reading on main functions and modules in Python, see these resources:
- Defining Main Functions in Python
- Python Modules and Packages—An Introduction
- Course: Python Modules and Packages
You’ll explore modules in more detail in a future tutorial in this series. For the moment, when you see the term global namespace, think of the one belonging to the main program.
The Local and Enclosing Namespaces
As you learned in the previous tutorial on functions, the interpreter creates a new namespace whenever a function executes. That namespace is local to the function and remains in existence until the function terminates.
Read the full article at https://realpython.com/python-namespaces-scope/ »
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