Understanding Data Hiding in Python: Concept, Examples, Advantages & Disadvantages

Data hiding in Python is a technique used in object-oriented programming (OOP) to hide information or data within a computer code, ensuring that data is not directly accessible from outside the class. By restricting access to class members, it maintains the integrity of the object and prevents unintended or unauthorized modifications. 

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 is achieved by using private members, typically denoted with a double underscore prefix, which limits access to the class's data and enhances system security and reliability.

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What is 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. 

In Python, the process of encapsulation and data hiding works simultaneously. Data encapsulation hides the private methods on the other hand data hiding hides only the data components. The robustness of the data is also increased with data hiding. The private access specifier is used to achieve data hiding. There are three types of access specifiers, private, public, and protected.

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Example of Data Hiding in Python

#!/usr/bin/python

class JustCounter:

   __secretCount = 0

   def count(self):

      self.__secretCount += 1

      print self.__secretCount

counter = JustCounter()

counter.count()

counter.count()

print counter.__secretCount

Output

1

2

Traceback (most recent call last):

   File “test.py”, line 12, in <module>

      print counter.__secretCount

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:

…………………….

print counter._JustCounter__secretCount

Then it works, and the output is:

1

2

2 

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Advantages of Data Hiding in Python

• 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.
• A user outside from the organisation cannot attain the access to the data.
• Within the organisation/ system only specific users get the access. This allows better operation.
• The class objects may sometimes also be disconnected from the irrelevant stream of data.

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Disadvantages of Data Hiding in Python

• 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.
• Sometimes the programmers would have to write lengthy codes, although they may be hidden from the clientele.

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.

And in totality, the data hiding in software engineering also plays a big role. It is a technique in software development especially in the Object-Oriented-Programming (OOP) to hide the data of internal members. And data hiding in oops also prevent the misuse of the data and makes sure that the class objects are disconnected from the data that is irrelevant

This data hiding feature in software engineering ensures that there is exclusive access to the data and that the data is not placed in a vulnerable situation. The data is accessible only to the class members when the data is hidden in the software engineering. This answers one of the most pertinent questions asked, “ What is data hiding in software engineering?”

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Conclusion 

With an in-depth discussion on data hiding in Python, we can reinforce the importance of the concept of data hiding in terms of enhancing security, preventing accidental modifications, maintaining object integrity, safeguarding data and eventually improving system reliability.

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