What is Data Hiding?
It is a method used in object-oriented programming (OOP) to hide with the intention of hiding information/ data within a computer code. Internal object details, such as data members, are hidden within a class. It guarantees restricted access to the data to class members while maintaining object integrity. Data hiding includes a process of combining the data and functions into a single unit to conceal data within a class by restricting direct access to the data from outside the class.
Data hiding helps computer programmers create classes with unique data sets and functions by avoiding unnecessary entrance from other classes in the program. Being a software development technique in OOP, it ensures exclusive data access and prevents intended or unintended changes in the data. These limited interdependencies in software components help reduce system complexity and increase the robustness of the program.
Data hiding is also known as information hiding or data encapsulation. The data encapsulation is done to hide the application implementation details from its users. As the intention behind both is the same, encapsulation is also known as data hiding. When a data member is mentioned as private in the class, it is accessible only within the same class and inaccessible outside that class.
Data Hiding in Python
Python is becoming a popular programming language as it applies to all sectors and has easy program implementation tools and libraries. Python document defines Data Hiding as isolating the client from a part of program implementation. Some objects in the module are kept internal, invisible, and inaccessible to the user.
Modules in the program are open enough to understand how to use the application, but users cannot know how the application works. Thus, data hiding provides security, along with avoiding dependency. Data hiding in Python is the method to prevent access to specific users in the application.
Data hiding in Python is done by using a double underscore before (prefix) the attribute name. This makes the attribute private/ inaccessible and hides them from users. Python has nothing secret in the real sense. Still, the names of private methods and attributes are internally mangled and unmangled on the fly, making them inaccessible by their given names.
Example of Data Hiding in Python
__secretCount = 0
self.__secretCount += 1
counter = JustCounter()
Traceback (most recent call last):
File “test.py”, line 12, in <module>
AttributeError: JustCounter instance has no attribute ‘__secretCount’
Python internally changes the names of members in the class that is accessed by object._className__attrName.
If the last line is changed as:
Then it works, and the output is:
Advantages of Data Hiding
- The objects within the class are disconnected from irrelevant data.
- It heightens the security against hackers that are unable to access confidential data.
- It prevents programmers from accidental linkage to incorrect data. If the programmer links this data in the code, it will only return an error by indicating corrections in the mistake.
- It isolates objects as the basic concept of OOP.
- It helps to prevent damage to volatile data by hiding it from the public.
Disadvantages of Data Hiding
- It may sometimes force the programmer to use extra coding.
- The link between the visible and invisible data makes the objects work faster, but data hiding prevents this linkage.
- Data hiding can make it harder for a programmer and need to write lengthy codes to create effects in the hidden data.
Thus, data hiding is helpful in Python when it comes to privacy and security to specific information within the application. It increases work for programmers while linking hidden data in the code. But, the advantages it offers are truly unavoidable.
Also Read: Python Interview Questions & Answers
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