Blog_Banner_Asset
    Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow iconData Hiding In Python: What is, Advantages & Disadvantages [With Coding Example]

Data Hiding In Python: What is, Advantages & Disadvantages [With Coding Example]

Last updated:
25th Aug, 2022
Views
Read Time
10 Mins
share image icon
In this article
Chevron in toc
View All
Data Hiding In Python: What is, Advantages & Disadvantages [With Coding Example]

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.    

The feature of data hiding, ides the feature of internal data. The feature prevents free access and the access is given to limited access. There are various benefits to having a data hiding feature, one of those is preventing the vulnerability of the data and safeguarding it from potential breaches.

In Python, the data hiding isolates the features, data, class, program, etc from the users. The users do not get free access. This feature of data hiding enhances the security of the system and initiates better reliability. Only a few or very specific people get access.

During the data hiding features, the implementation of the program cannot be seen by the users. This is attained by declaring the class members as private. And a special function is also used for the same, that is a double underscore (__) as a prefix. Apart from enhancing the security the data hiding feature also facilitates in avoiding security.

Some of the data hiding example is the detail of salary. This data is secured and hidden from the rest of the employees. The other employees cannot push a button and access the salary information. And this information is known to very specific users in the system.

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.

upGrad’s Exclusive Data Science Webinar for you –

Transformation & Opportunities in Analytics & Insights

Explore our Popular Data Science Courses

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 

Our learners also read: Top Python Free Courses

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.
  • 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.

Also Read: Python Interview Questions & Answers

Top Data Science Skills to Learn

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.
  • 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. 

Read our popular Data Science Articles

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?”

Check out all trending Python tutorial concepts in 2024

Conclusion 

To join our Python online course free, you only have to follow these steps:

  • Head to our upStart page
  • Select the “Python for Data Science” course
  • Click on Register
  • Complete the registration process

That’s it. You can learn Python online free through our newly-launched upStart program and kickstart your data science journey. You’d only have to invest 30 minutes a day for a few weeks. This program requires no monetary investment.

Sign up today and get started. 

If you have any questions or suggestions regarding this topic, please let us know in the comments below. We’d love to hear from you.

If you are curious to learn about data science, check out IIIT-B & upGrad’s Executive PG Programme in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

Profile

Rohit Sharma

Blog Author
Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Frequently Asked Questions (FAQs)

1What 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”.

2What 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:
Advantages
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.
Disadvantages
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.

3How 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.

4How is data hiding done?

In Python, data hiding is achieved using a feature of double underscore (__) as a prefix. This initiates the hiding feature in the attribute. As the attribute becomes inaccessible for the users.

5Is data hiding and encapsulation the same?

Data hiding and encapsulation prioritise different things. Data hiding focuses on maintaining and ensuring the security is tight and maintained throughout. Whereas, data encapsulation focuses on the encapsulation/ wrapping of the data in such a way that the view becomes simpler for the users. Another difference is the presence, for example by the term it is certain in data hiding the data is definitely private. Whereas, in data encapsulation, the data can be either private or public.

6What is the importance of information hiding?

The importance of information hiding is very crucial. The information’s access is restricted and is available only to those users who are supposed to be having access. Another importance of information hiding is the security that it enables, the data can be encrypted in such a way that it remains protected from potential breaches and unauthorized access from attackers.

7How do you hide a function in Python?

Double underscore (__) can be used to hide. It can be added in front of the variable by doing this the function can be hidden while accessing.

8What is a datatype in Python?

Data types are the categorisation of the knowledge items. There are various kinds of data types. And in python, there are six kinds of data types- Numeric String List Tuple Set Dictionary

9 What is __init__ in Python?

__init__ is a function in Python. Whenever the object is created from a class the __init__ function is called. And this function is used only within the classes.

10What is data abstraction with example?

Data abstraction is a way to reduce a particular body of data into its simplified version. Only the essential elements remain by reducing the characteristics. Therefore, in abstraction, only the essential characteristics are shown and the background details or implementations remain hidden. Answering a phone is one example of data abstraction, a person driving a car, or responding to texts are some examples of data abstraction.

Explore Free Courses

Suggested Blogs

Python Developer Salary in India in 2024 [For Freshers &#038; Experienced]
906195
Wondering what is the range of Python developer salary in India? Before going deep into that, do you know why Python is so popular now? Python has be
Read More

by Sriram

11 Feb 2024

6 Types of Filters in Tableau: How You Should Use Them
64377
Tableau is one of the most popular tools in data visualization and analysis that facilitates brands across all domains to leverage the reckoning poten
Read More

by Rohit Sharma

04 Feb 2024

Data Cleaning Techniques: Learn Simple &#038; Effective Ways To Clean Data
51779
Data cleansing is an essential part of data science. Working with impure data can lead to many difficulties. And today, we’ll be discussing the same.
Read More

by Rohit Sharma

04 Feb 2024

13 Exciting Data Science Project Ideas &#038;  Topics for Beginners [2024]
944770
Summary: In this Article, you will learn about 13 exciting data science project ideas & topics for beginners. 1. Beginner Level | Data Science P
Read More

by Rohit Sharma

28 Jan 2024

Top 15 Python AI &#038; Machine Learning Open Source Projects
35770
Machine learning and artificial intelligence are some of the most advanced topics to learn. So you must employ the best learning methods to make sure
Read More

by Pavan Vadapalli

28 Jan 2024

Most Common Binary Tree Interview Questions &#038; Answers [For Freshers &#038; Experienced]
4303
fIntroduction Data structures are one of the most fundamental concepts in object-oriented programming. To explain it simply, a data structure is a pa
Read More

by Rohit Sharma

28 Jan 2024

Cluster Analysis in Data Mining: Applications, Methods &#038; Requirements
110021
Here we are going to discuss Cluster Analysis in Data Mining. So first let us know about what is clustering in data mining then its introduction and t
Read More

by Rohit Sharma

26 Jan 2024

What is Linear Data Structure? List of Data Structures Explained
52984
Data structures are the data structured in a way for efficient use by the users. As the computer program relies hugely on the data and also requires a
Read More

by Rohit Sharma

24 Jan 2024

Python Free Online Course with Certification [2024]
129117
Summary: In this Article, you will learn about python free online course with certification. Programming with Python: Introduction for Beginners Le
Read More

by Rohit Sharma

24 Jan 2024

Schedule 1:1 free counsellingTalk to Career Expert
icon
footer sticky close icon