What are the disadvantages of using Monkey Patch if it is not related to testing?

• Unhealthy effect: Changes in the behavior of functions or objects become implicit and scattered across the codebase, making them difficult to track.
• Conflicts: Different parts of the program using monkey patching may override the same thing, causing unpredictable behavior.
• Debugging complexity: Modified functions are displayed with their original names, which makes it hard to understand which code is actually executing.
• Compatibility issues: Python packages may change with updates, and monkey patches made may stop working.
• Violation of encapsulation: Internal state or behavior of objects is altered, violating object-oriented programming principles.
• Maintenance difficulty: Code with monkey patching is harder for other developers to understand and maintain.

Example:

# Original function
import time

def expensive_operation():
    time.sleep(2)
    return "Result of a long operation"

# Monkey patch for speed-up (without tests!)
def fast_operation():
    return "Fast result (monkey patched)"

# Undesirable application of patch
# This hides the real long operation and makes the code unpredictable
# time.expensive_operation = fast_operation

Incorrect use of monkey patching outside testing leads to unreadable, hard-to-debug, and fragile code.