OOPs concepts in python Introduction to Oops Concepts in Python If you are looking for OOPs concepts in Python, then you are in the right blog. Here you will get to know all about OOPs and OOPs concepts in Python. So, In Python, object-oriented programming (OOPs) is a programming paradigm that usesRead more
OOPs concepts in python
Introduction to Oops Concepts in Python
If you are looking for OOPs concepts in Python, then you are in the right blog. Here you will get to know all about OOPs and OOPs concepts in Python. So, In Python, object-oriented programming (OOPs) is a programming paradigm that uses objects and classes in programming. It aims to implement real-world entities like inheritance, polymorphisms, encapsulation, etc. in the programming. The main concept of OOPs is to bind the data and the functions that work on that together as a single unit so that no other part of the code can access this data.
Key OOPS Concepts in Python
- Class
- Objects
- Polymorphism
- Encapsulation
- Inheritance
- Data Abstraction
OOPs
Class
Class is one of the oops concepts in Python, and let us understand what it means and how it works.
A class is a collection of objects. A class contains the blueprints or prototypes from which the objects are being created. It is a logical entity that contains some attributes and methods.
To understand the need for creating a class let’s consider an example, let’s say you wanted to track the number of dogs that may have different attributes like breed, age. If a list is used, the first element could be the dog’s breed while the second element could represent its age. Let’s suppose there are 100 different dogs, then how would you know which element is supposed to be which? What if you wanted to add other properties to these dogs? This lacks organization and it’s the exact need for classes.
Some points on Python class:
- Classes are created by keyword class.
- Attributes are the variables that belong to a class.
- Attributes are always public and can be accessed using the dot (.) operator. Eg.: Myclass.Myattribute
Class Definition Syntax:
class ClassName:
# Statement-1
.
.
.
# Statement-N
Example: Creating an empty Class in Python
- Python
# Python3 program to
# demonstrate defining # a class
class Dog: pass |
In the above example, we have created a class named dog using the class keyword.
Objects
The object is an entity that has a state and behavior associated with it. It may be any real-world object like a mouse, keyboard, chair, table, pen, etc. Integers, strings, floating-point numbers, even arrays, and dictionaries, are all objects. More specifically, any single integer or any single string is an object. The number 12 is an object, the string “Hello, world” is an object, a list is an object that can hold other objects, and so on. You’ve been using objects all along and may not even realize it.
An object consists of :
- State: It is represented by the attributes of an object. It also reflects the properties of an object.
- Behavior: It is represented by the methods of an object. It also reflects the response of an object to other objects.
- Identity: It gives a unique name to an object and enables one object to interact with other objects.
To understand the state, behavior, and identity let us take the example of the class dog (explained above).
- The identity can be considered as the name of the dog.
- State or Attributes can be considered as the breed, age, or color of the dog.
- The behavior can be considered as to whether the dog is eating or sleeping.
OOPS Concepts in Python Example: Creating an object
- Python3
obj = Dog() |
This will create an object named obj of the class Dog defined above. Before diving deep into objects and class let us understand some basic keywords that will we used while working with objects and classes.
The self
- Class methods must have an extra first parameter in the method definition. We do not give a value for this parameter when we call the method, Python provides it
- If we have a method that takes no arguments, then we still have to have one argument.
- This is similar to this pointer in C++ and this reference in Java.
When we call a method of this object as myobject.method(arg1, arg2), this is automatically converted by Python into MyClass.method(myobject, arg1, arg2) – this is all the special self is about.
Note: For more information, refer to self in Python class
The __init__ method
The __init__ method is similar to constructors in C++ and Java. It is run as soon as an object of a class is instantiated. The method is useful to do any initialization you want to do with your object.
Now let us define a class and create some objects using the self and __init__ method.
Example 1: Creating a class and object with class and instance attributes
- Python3
class Dog:
# class attribute attr1 = “mammal”
# Instance attribute def __init__(self, name): self.name = name
# Driver code # Object instantiation Rodger = Dog(“Rodger”) Tommy = Dog(“Tommy”)
# Accessing class attributes print(“Rodger is a {}”.format(Rodger.__class__.attr1)) print(“Tommy is also a {}”.format(Tommy.__class__.attr1))
# Accessing instance attributes print(“My name is {}”.format(Rodger.name)) print(“My name is {}”.format(Tommy.name)) |
Output
Rodger is a mammal
Tommy is also a mammal
My name is Rodger
My name is Tommy
OOPS Concepts in Python Example 2: Creating Class and objects with methods
- Python3
class Dog:
# class attribute attr1 = “mammal”
# Instance attribute def __init__(self, name): self.name = name
def speak(self): print(“My name is {}”.format(self.name))
# Driver code # Object instantiation Rodger = Dog(“Rodger”) Tommy = Dog(“Tommy”)
# Accessing class methods Rodger.speak() Tommy.speak() |
Output
My name is Rodger
My name is Tommy
Note: For more information, refer Python Classes and Objects
Inheritance
Inheritance of OOPS concepts in Python is the capability of one class to derive or inherit the properties from another class. The class that derives properties is called the derived class or child class and the class from which the properties are being derived is called the base class or parent class. The benefits of inheritance are:
- It represents real-world relationships well.
- It provides the reusability of a code. We don’t have to write the same code again and again. Also, it allows us to add more features to a class without modifying it.
- It is transitive in nature, which means that if class B inherits from another class A, then all the subclasses of B would automatically inherit from class A.
Types of Inheritance –
Single Inheritance:
Single-level inheritance enables a derived class to inherit characteristics from a single-parent class.
Multilevel Inheritance:
Multi-level inheritance enables a derived class to inherit properties from an immediate parent class which in turn inherits properties from his parent class.
Hierarchical Inheritance:
Hierarchical level inheritance enables more than one derived class to inherit properties from a parent class.
Multiple Inheritance:
Multiple level inheritance enables one derived class to inherit properties from more than one base class.
OOPS Concepts in Python Example: Inheritance in Python
- Python3
# Python code to demonstrate how parent constructors
# are called.
# parent class class Person(object):
# __init__ is known as the constructor def __init__(self, name, idnumber): self.name = name self.idnumber = idnumber
def display(self): print(self.name) print(self.idnumber)
def details(self): print(“My name is {}”.format(self.name)) print(“IdNumber: {}”.format(self.idnumber))
# child class class Employee(Person): def __init__(self, name, idnumber, salary, post): self.salary = salary self.post = post
# invoking the __init__ of the parent class Person.__init__(self, name, idnumber)
def details(self): print(“My name is {}”.format(self.name)) print(“IdNumber: {}”.format(self.idnumber)) print(“Post: {}”.format(self.post))
# creation of an object variable or an instance a = Employee(‘Rahul’, 886012, 200000, “Intern”)
# calling a function of the class Person using # its instance a.display() a.details() |
Output
Rahul
886012
My name is Rahul
IdNumber: 886012
Post: Intern
In the above article, we have created two classes i.e. Person (parent class) and Employee (Child Class). The Employee class inherits from the Person class. We can use the methods of the person class through employee class as seen in the display function in the above code. A child class can also modify the behavior of the parent class as seen through the details() method.
Note: For more information, refer to our Inheritance in Python tutorial.
Polymorphism in OOPS Concepts in Python
Polymorphism simply means having many forms. For example, we need to determine if the given species of birds fly or not, using polymorphism we can do this using a single function.
OOPS Concepts in Python Example: Polymorphism
Python3
class Bird:
def intro(self): print(“There are many types of birds.”)
def flight(self): print(“Most of the birds can fly but some cannot.”)
class sparrow(Bird):
def flight(self): print(“Sparrows can fly.”)
class ostrich(Bird):
def flight(self): print(“Ostriches cannot fly.”)
obj_bird = Bird() obj_spr = sparrow() obj_ost = ostrich()
obj_bird.intro() obj_bird.flight()
obj_spr.intro() obj_spr.flight()
obj_ost.intro() obj_ost.flight() |
Output
There are many types of birds.
Most of the birds can fly but some cannot.
There are many types of birds.
Sparrows can fly.
There are many types of birds.
Ostriches cannot fly.
Note: For more information, refer to our Polymorphism in Python Tutorial.
Encapsulation
Encapsulation is one of the fundamental concepts in object-oriented programming (OOP). It describes the idea of wrapping data and the methods that work on data within one unit. This puts restrictions on accessing variables and methods directly and can prevent the accidental modification of data. To prevent accidental changes, an object’s variable can only be changed by the object’s method. Those types of variables are known as private variables.
A class is an example of encapsulation as it encapsulates all the data that is member functions, variables, etc.
OOPS Concepts in Python Example: Encapsulation in Python
- Python3
# Python program to
# demonstrate private members
# Creating a Base class class Base: def __init__(self): self.a = “GeeksforGeeks” self.__c = “GeeksforGeeks”
# Creating a derived class class Derived(Base): def __init__(self):
# Calling constructor of # Base class Base.__init__(self) print(“Calling private member of base class: “) print(self.__c)
# Driver code obj1 = Base() print(obj1.a)
# Uncommenting print(obj1.c) will # raise an AttributeError
# Uncommenting obj2 = Derived() will # also raise an AtrributeError as # private member of base class # is called inside derived class |
Output
GeeksforGeeks
In the above example, we have created the c variable as the private attribute. We cannot even access this attribute directly and can’t even change its value.
Note: For more information, refer to our Encapsulation in Python Tutorial.
Data Abstraction
It hides the unnecessary code details from the user. Also, when we do not want to give out sensitive parts of our code implementation, this is where data abstraction comes in.
Data Abstraction in Python can be achieved by creating abstract classes. When using OOPs concepts in Python, it is important to understand the principles of abstraction in order to write simple and brief code.
Understanding oops concepts in python is important for developing fast and reliable programs.
Conclusion
In conclusion, implementing the “OOPs concepts in Python” is a must for developers looking to create scalable and efficient applications. By incorporating fundamental elements like as encapsulation, inheritance, and polymorphism into the “OOPs concepts in Python,” code becomes modular and reusable, showing an organized approach. Understanding of these concepts helps developers to design adaptable programs that prioritize safety and quick problem-solving within the framework of the “OOPs concepts in Python.”
We hope you understand all oops concepts in python. And will help you in future.
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Primary key in database Introduction to primary key in database If you’re getting started with databases, it’s important to understand what a primary key is and the role of a primary key in database. A primary key is a special type of unique identifier used to identify records in a database. It helpRead more
Primary key in database
Introduction to primary key in database
If you’re getting started with databases, it’s important to understand what a primary key is and the role of a primary key in database. A primary key is a special type of unique identifier used to identify records in a database. It helps to identify each row uniquely and efficiently.
A primary key must always contain unique values, ensuring that no two records are the same. In addition, it allows databases to quickly and easily locate specific records and retrieve the relevant information from them. A superkey is another type of unique identifier, but it contains more than one attribute, which helps with identifying records in a table.
When creating a primary key in database, certain constraints need to be taken into consideration. Firstly, NULL values are not allowed as they cannot be used as a unique identifier. Furthermore, duplicate values should be avoided so that each row remains distinct and identifiable.
If you want to use several attributes (columns) as your primary key identifier, then you can create what’s known as a composite key or compound key. This is often used when there isn’t one single column that uniquely identifies records on its own. Finally, you may also choose to use what’s known as a surrogate key—this is an artificial primary key that has no physical meaning but still allows rows to be uniquely identified in the database table.
In summary, understanding how primary keys work can help you better manage data within your databases for efficient and accurate data retrieval processes.
Benefits of primary key in database
Primary keys are an incredibly important part of any database and should never be overlooked. They are the backbone of relational databases, and they provide several benefits that help to ensure data accuracy, referential integrity, and performance primary key in database. Let’s take a look at some of the key benefits of using primary keys in your database.
The primary key in database provides a significant advantage by uniquely identifying each entry. The primary key’s recognizing role as a unique identifier for each entry in a table is critical for ensuring database correctness since it effectively avoids duplication. The need for primary keys to be unique guarantees that each entry has its own primary key in database, which helps to prevent duplication and reinforces data integrity. In addition, the unique character of primary keys makes it simple to identify certain entries inside the database whenever needed, improving the efficiency of data access and operations through consistent usage of primary key in database.
Ensures Referential Integrity: Primary keys also provide referential integrity for relationships between other tables. This means that when data is added or deleted from one table, the values in related tables will also be updated correctly. By ensuring referential integrity across multiple tables, primary keys help you keep your data uptodate and consistent throughout your entire database.
Increases Performance/Optimizes Queries: Primary keys can also help increase performance because they allow common queries to be faster and more efficient when searching for records within the database. Because each row has a unique identifier, queries that involve searching for specific records can be optimized much faster than if you were to search without a primary key. In addition, indexing is automatically included with primary keys which further helps with performance optimization by making searches even faster.
Prevents Data Anomalies: By providing consistency across different tables, primary keys also help prevent data anomalies from occurring within your database.
Types of Primary Key in database
Primary keys are an essential element of database design and serve as the foundation for normalizing data within a database. Identifying the right type of primary key can be a challenge, so let’s take a closer look at the different types of primary keys.
Singlecolumn is a Primary Key in database
Singlecolumn is a primary key in database and also composed of one individual attribute or column that serves as the primary key for an entire database table. These types of primary keys are the most common and straightforward to implement, but they have some limitations that should be taken into consideration. For instance, single column primary keys require that all values in the column must be unique and cannot be null. Additionally, any updates to the column also have to remain unique.
MultiColumn is a Primary Key in database
The multicolumn is a primary key in database and a variation on the singlecolumn primary key, where multiple columns must be combined in order to generate a unique identifier for each row in the table. This type of primary key is more complex than a single column and has more stringent restrictions when it comes to updating existing columns or deleting rows. Multicolumns also require additional disk space, as each combination must fit into a single record within the table.
Compound is a Primary Key in database
Compound primary keys are similar to multicolumns, except they combine two or more individual attributes that represent an entity or concept, such as a customer name or address. Compound keys allow for greater flexibility when it comes to data updates since individual elements can be modified without affecting uniqueness across rows in the table. However, compound primaries also require significant setup before being used effectively and often result in poor performance unless carefully maintained by skilled engineers and administrators.
Implementing a primary key in database
If you’re working with databases, you know how important it is to have a reliable primary key in database. A primary key is a data field used to uniquely identify each row of a table. It’s an important part of database structure that helps make sure all data relationships are correctly managed and facilitates finding and quickly sorting records within the database.
To implement a primary key in database, the first step is to determine which column can be used to uniquely identify each row in the table. A good primary key should be short, easy to remember, and not contain any duplicate values throughout its rows. Once you’ve identified the column you want to use as your primary key, it must be indexed for fast retrieval of records. This will help speed up any search functions within your database structure.
Having a primary key also helps maintain database integrity constraints, like preventing inserting or updating duplicates or null values across multiple columns. Since the primary key ensures each row is unique and non duplicative, it helps ensure that your database reflects accurate and consistent data by ensuring that there are no duplicates or overlapping records. Furthermore, by using a primary key to normalize your database, it becomes possible to break down larger tables into smaller related tables, allowing for better structured data relationships between entities stored within the database.
Primary keys are an essential part of relational databases, and their implementation will help ensure cohesive data relationships between different entities in the system as well as quick retrieval of records from searches. With the right implementation strategy, you can easily add additional functionality and features while maintaining the accuracy of data throughout your system structure.
Using Unique and Non-Unique Constraints with Primary Keys
After the topic of primary key in databases, let’s learn about using unique and non unique constraints with primary keys. When it comes to maintaining data integrity with your database, the use of unique and nonunique constraints with primary keys is invaluable. A primary key is a combination of columns or values that uniquely identify each row in a table. It’s important to ensure that this combination of values never repeats in any other row. This ensures data integrity and prevents any duplicates from entering your database.
Unique constraints guarantee that each value in a particular column or group of columns must be distinct, while non unique constraints allow multiple NULLs or duplicate values. A unique constraint can either be defined as part of the table itself or through an index on the table column. If a unique constraint is violated, it will raise an error and prevent further action until the violation has been resolved. Non constraints, on the other hand, will only give you warnings if there are repeated values but will not prevent any action from continuing until they are recognized and fixed by you, the user.
Primary keys are essential for enforcing referential integrity within your database, as they create links between different tables within your database, allowing information to be retrieved quickly and accurately without having to search through all rows in a table manually. When using primary keys with unique and nonunique constraints together, it allows you to ensure that all data entered into your database abides by specific rules that you have set up while still being able to maintain overall data integrity throughout your entire system.
Using unique and nonunique constraints in conjunction with primary keys allows you to maintain accurate data records in your database while also ensuring all entries abide by your preestablished criteria. These tools offer great advantages when it comes to maintaining data integrity within your system.
Ensuring Data Integrity with Foreign Key Constraints
Now that you know the primary key in database, let’s understand data integrity with foreign key constraints. Data integrity is essential for efficient and effective operations in any organization. One way to ensure the accuracy of your data is to use foreign key constraints. In a database, primary keys are used to uniquely identify records and entries. A foreign key constraint then builds a relationship between two tables by relying on the primary key from one table and referencing it in another. This helps protect against data inconsistencies, predict changes as needed, and maintain the overall integrity of the database.
By using foreign key constraints, you can establish referential integrity throughout your database. Referential integrity means that changes are done consistently across different tables and will not cause any errors or inconsistencies with the related data. With referential integrity established through foreign key constraints, you can also more easily anticipate and respond to changes in data over time.
In addition, relying on foreign key constraints ensures that certain ACID principles are adhered to—Atomicity, Consistency, Isolation, Durability—which support both transaction processing and data retrieval processes in a database. Ensuring that all of these aspects of your database remain stable helps you maintain the highest level of accuracy when it comes to collecting, storing, managing, and protecting your data.
Foreign key constraints are an incredibly versatile tool for ensuring data integrity in databases by establishing table relationships via primary keys and maintaining referential integrity across them for improved accuracy over time. By utilizing this tool properly, organizations can ensure their databases remain reliable sources of information for years to come!
Secondary Indexes and Their Use With Database Tables
Secondary indexes are an essential tool for any database table and are often times used in conjunction with primary keys. A secondary index is a data structure that allows users to quickly locate data without knowing the exact primary key. It can also be used to refer to the same records when the same search criteria is used in more than one query. By having a secondary index, it provides users with an alternate way of looking up data, which makes searching faster, easier, and more efficient.
Understanding what a primary key does? is important when utilizing a second index for your database table. As mentioned, the primary key in database creates an individual identity for a row or record within a database table and acts as a sort of “address” for that particular row or record. In order to create this identity, all entries within the column must be unique and different from any other row or record in the table. Primary keys are typically indexed, which allows for faster search speeds when looking up information by this ID or address.
Secondary indexes offer many benefits, including improved query performance, quick access to sorted values, and the simplification of certain operations such as joins and ordering of results. When using single columns as secondary indexes, it is important to remember that these values must always be unique in order to allow access to each individual row; otherwise, duplicate values could lead to issues with data integrity. Some popular types of single column secondary indexes include hash based indexes, which provide very fast search speed; B-tree style indexes, which allow users to sort records according to their value; and text based indexes, which can optimize string matching operations like those found in LIKE clauses.
Conclusion
When it comes to understanding the primary key in database,? It’s important to understand the concept of the primary key. A primary key is a column or set of columns that uniquely identifies a record in a database table. This means that each row in the table has its own distinct key, which helps to ensure entity integrity.
Unique values are also essential in relational databases. Unique values can help prevent data duplication and ensure that each row contains meaningful information that is not shared among other rows in the same table. Additionally, unique values can create relationships between different tables within the same database, allowing for more efficient data accessibility and retrieval.
Data accessibility can also be improved with keys and indexes. Keys are used to form relationships between tables, allowing for efficient retrieval of data from those tables. Indexes are special types of keys used to improve search performance when retrieving data from large databases.
Finally, it’s important to keep data normalized within your databases as much as possible. Data normalization helps to reduce unnecessary duplication of data while ensuring that entities maintain their integrity across different tables. Normalization also makes sure your databases remain manageable and readable by sorting information into related units or “normal forms” so you know what you’re dealing with at a glance.
In conclusion, no matter what type of database you use, understanding how primary keys, unique values and other aspects of relational databases work together is essential if you want your database setup to run smoothly and effectively. With the right organization, relational databases can provide reliable access to large stores of data and facilitate reliable transactions over time making them invaluable tools for any business or enterprise!
We hope you understand all primary key in database.
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