Featured Post

14 Top Data Pipeline Key Terms Explained

Image
 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...

3 Exclusive Access Modifiers in Python

Here are three access modifiers in Python - Public, Protect, and Private. Access modifiers control the access to a variable/or method. 

You may have a question that does python supports access modifiers? The answer is yes.

In general, all the variables/or methods are public. Which means accessible to other classes. The private and protect access modifiers will have some rules. And the notation for protect and private are different. The single underscore is for protected and the double underscore is for private. Here is how to find Python list frequent items.

Differences between Public, Protect and Private


Here's Why You Need Access Modifiers in Python



Public access modifier

Public variables are accessible outside the class. So in the output, the variables are displayed.

class My_employee:

    def __init__(self, my_name, my_age):
        self.my_name = my_name  #public
        self.my_age = my_age   # public


my_emp = My_employee('Raj',34)
print(my_emp.my_name)
print(my_emp.my_age)

my_emp.my_name = 'Rohan'
print(my_emp.my_name)

Output

Raj
34
Rohan

** Process exited - Return Code: 0 **
Press Enter to exit terminal

Protect access modifier

Method of protection can be accessible within the class and subclass. From child class, you can access it. However, you cannot access it from outside the class. 

class parent:
    def __init__(self):
        pass
    def _test1(self):  # protected
        print("I am in Parent")

class child(parent):
    def __init(self):
        pass
    def test2(self):  
        print("I am in child class")

obj1=child()
obj1._test1()


Output

I am in Parent

** Process exited - Return Code: 0 **
Press Enter to exit terminal

Private access modifier

Below, you will find an error in the output. It is because the method in the parent is private, and the child class tried to access it. The bottom line is only the parent class can access it - not possible even by the subclass, also outside the class.  

class parent:
    def __init__(self):
        pass
    def __test1(self):  #provate
        print("I am in Parent")

class child(parent):
    def __init(self):
        pass
    def test2(self):   
        print("I am in child class")

obj1=child()
obj1.__test1()

Output

Traceback (most recent call last):
  File "main.py", line 14, in <module>
    obj1.__test1()
AttributeError: 'child' object has no attribute '__test1'


** Process exited - Return Code: 1 **
Press Enter to exit terminal

We are restricting the access to methods and variables resulting in prevention of data from direct modification. So, the process of data binding is called encapsulation. It is one of the fundamental concepts in object-oriented programming (OOP).

Comments

Popular posts from this blog

How to Fix datetime Import Error in Python Quickly

SQL Query: 3 Methods for Calculating Cumulative SUM

Big Data: Top Cloud Computing Interview Questions (1 of 4)