In Python, module dependency refers to the relationships between different Python modules in a program, indicating which modules depend on others to function correctly. When you write a Python program, you often split your code into multiple modules to organize it better and make it more manageable. These modules can depend on each other in various ways:

1. Import Statements: The most common form of module dependency is created through import statements. When you import a module into another module using the `import` keyword, you establish a dependency on the imported module. For example:

   # Module A.py

   import B

   In this example, module A depends on module B because it imports and uses symbols from module B.

2. Function Calls and Object Usage: Dependencies can also exist when one module calls functions or uses objects defined in another module. This is not limited to using `import`. For instance:

   # Module A.py

   from B import some_function

   def do_something():

       result = some_function()

   In this case, module A depends on module B because it relies on `some_function` defined in module B.

3. Inheritance and Subclassing: In object-oriented programming, module dependency can occur when one class or module inherits from or subclasses another. This establishes a dependency because the subclass relies on the behavior and attributes of the parent class or module.

4. Circular Dependencies: Sometimes, modules can have circular dependencies, where module A depends on module B, and module B also depends on module A. This can lead to issues and should be avoided or carefully managed.

Understanding module dependencies is crucial for maintaining a clean and efficient codebase. Properly managing dependencies ensures that your code is organized, easy to maintain, and less prone to errors. Tools like package managers (e.g., pip) and virtual environments can help you manage and resolve module dependencies effectively, especially when working with external libraries and packages.

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