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. If you are a beginner in data science and want to gain expertise, check out our data science courses from top universities.
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.
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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:
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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.
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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.
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What is data hiding in Python?
Data hiding is one of the core concepts of Object-Oriented programming which restricts the access of the data from the outside world. Details such as data members are kept hidden with the help of the “Private” access specifier. Consider the following example for better understanding.
Suppose we have a class called myClass and a private member called __privateCounter. Inside this class, we have a function called myFunc that increments the value of __privateCounter by 1 and prints it. Outside the class, we have created an object of the class and called the myFunc using this object. Now, if we try to print __privateCounter using this object, it will throw an error.
In the above example, the “__privateCounter” is by default a private member of the class “myClass”. Since we have performed data hiding on it, it can not be accessed outside the class in which it has been declared. To access the private members, we have to define a member function, which in this case is “myFunc”.
What are the advantages and disadvantages of data hiding?
Although data hiding is a core concept of OOPs and has many advantages, it has some disadvantages too. The following are some of the most significant advantages and disadvantages of data hiding in Python:
1. It helps to prevent the misuse and manipulation of volatile data by declaring it as private.
2. The data members of the class are delinked from the irrelevant data.
3. It isolates objects as the basic concept of OOP.
1. Programmers often are forced to write lengthy codes in order to protect the volatile data from the clients.
2. The objects work comparatively slower as the linkage between the visible and invisible data makes it work fast and the data hiding prevents this linkage.
How does data hiding differ from data abstraction?
Data hiding supports the idea of restricting the data so that it cannot be accessed or modified by the outside world. For example, the salary details of an employee are hidden from other employees. In Python, this is achieved by using the “private access modifier”.
Data abstraction refers to the idea of concealing the internal implementation and only showing the features to the outer world. For example, in a calculator, you are only shown the operations performed by the calculator. However, you cannot see the internal working of these operations. In Python, different access specifiers are used to implement this.