- What is Python?
- How to Install Python?
- Python Variables and Operators
- Python Loops
- Python Functions
- Python Files
- Python Errors and Exceptions
- Python Packages
- Python Classes and Objects
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- PostgreSQL Data Types
- Python Generators and Decorators
- Python Dictionary
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- Python Multithreading and Synchronization
- Python Modules
- What is Python bytecode?
- Python Regular Expressions
Python Panda Tutorial
- Python Pandas Tutorial
- Python Pandas Features
- Advantages and Disadvantages of Python Pandas
- Pandas Library In Python
- Pandas Series To Frame
- Python Dataframeaggregate and Assign
- Pandas Dataframe Describe
- Pandas Dataframe Mean
- Pandas Hist
- Pandas Dataframe Sum
- How to convert Pandas DataFrame to Numpy array
- Pandas Concatenation
- Pandas Shift
- Pandas Rolling
- Data Analysis With Pandas and Python
- How Python Panda Are Helpful For With Data Science
- Selenium Basics
- Selenium with Python Introduction and Installation
- Navigating links using get method Selenium Python
- Locating Single Elements in Selenium Python
- Locating Multiple elements in Selenium Python
Python Flask Tutorial
- How to Install Django and Set Up a Virtual Environment in 6 Steps
- Django MTV Architecture
- Django Models
- Django Views
- Django Templates
- Django Template Language
- Django Project Layout
- Django Admin Interface
- Django Database
- Django URLs and URLConf
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- Types of Caching in Django
- Django Sessions
- Django Forms Handling & Validation
- Django Exceptions & Error-handling
- Django Forms Validation
- Django Redirects
- Django Admin Interface
- Django Bootstrap
- Ajax in Django
- Django Migrations and Database Connectivity
- Django Web Hosting and IDE
- Django Admin Customization
- What is CRUD?
- Django ORM
- Django Request-Response Cycle
- Django ORM
- Making a basic_api with DRF
- Django Logging
- Django Applications
- Difference between Flask vs Django
- Difference between Django vs PHP
- Numpy Introduction
- NumPy– Environment Setup
- NumPy - Data Types
- NumPy Histogram
- Matrix in NumPy
- NumPy Arrays
- NumPy Array Functions
- Matrix Multiplication in NumPy
- NumPy Matrix Transpose
- NumPy Array Append
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- NumPy Linear Algebra
- NumPy sum
- NumPy Normal Distribution
- NumPy correlation
- Why we learn and use Numpy?
- Introduction To Tensorflow
- INTRODUCTION TO DEEP LEARNING
- EXPLAIN NEURAL NETWORK?
- CONVOLUTIONAL AND RECURRENT NEURAL NETWORK
- INTRODUCTION TO TENSORFLOW
- INSTALLATION OF TENSORFLOW
- TENSORBOARD VISUALIZATION
- Linear regression in tensorflow
- Word Embedding
- Difference between CNN And RNN
- Explain Keras
- Program elements in tensorflow
- Recurrent Neural Network
- Tensorflow Object Detection
- EXPLAIN MULTILAYER PERCEPTRON
- GRADIENT DESCENT OPTIMIZATION
Interview Questions & Answers
Django ORM has been mentioned in all of the database & model tutorials. It is an amazing implementation to increase development speed.The other important topic is of Querysets. These are an important part of ORMs in general. We have used Querysets many times in our tutorials.
What is an ORM?
ORM is an acronym for the object-relational mapper. The ORM’s main goal is to transmit data between a relational database and application model. The ORM automates this transmission, such that the developer need not write any SQL.
ORM, as from the name, maps objects attributes to respective table fields. It can also retrieve data in that manner.
Django is shipped with its own ORM. It is a very efficient ORM and is tightly coupled with the Django framework. Django ORM is suitable for handling low-medium complexity queries. Although, some consider SQLAlchemy ORM to be a better option. The migrations feature by Django is also a part of Django ORM.
Django ORM vs SQLAlchemy?
In most cases, people prefer SQLAlchemy over Django ORM. The reason being SQLAlchemy is more adept to work with high-complexity data structures. Django ORM is powerful in its own way. The ORM provides features integrated with Django which are more important than just performance improvement.
Currently, Django ORM is not swappable with SQLAlchemy. There are some hacks to do it but it’s unofficial. Django’s future releases are expected to provide this functionality. Also, both SQLAlchemy and Django ORM is actively developed.
Querysets in Django
We all use queries to retrieve data from the database. Querysets are Django’s way to retrieve data from the database. The Django ORM lets us use Querysets.
A Queryset is a list of objects of a model. We use Querysets to filter and arrange our data. These make our work as a Python developer easier.
Different Relationships between Fields
Django ORM provides a level of abstraction which makes it easy to work with objects. ORM will automatically relate the object’s attributes to corresponding table fields. We are going to make some models and check their field relationships in other tables.
It is expected that you can make models and applications.
One to One Relationship
A one-to-one relationship exists between two tables. For each row in table1, there shall be a row/ entity in table2.
There are two tables here, Customer and Vehicle. Every customer owns only one vehicle. Thus, a one-to-one relationship exists. Now, paste this code in models.py to implement this.
from django.db import models #Ducatindia #DjangoTutorials # Create your models here. class Customer(models.Model): name = models.CharField(max_length=255) class Vehicle(models.Model): name = models.CharField(max_length=255) customer = models.OneToOneField( Customer, on_delete=models.CASCADE, related_name='vehicle' )
One to Many Relationships
Just like one to one we can have one-to-many relationships. We are going to use a different model for showcasing this.
A one to many relationships is where one object from table1 can have multiple relations with entities in table2. Although, table2 objects will have only one relation to the object of table1.
The code for this model is:
from django.db import models
#Ducatindia #DjangoTutorials # Create your models here. class Customer(models.Model): name = models.CharField(max_length=255) class Vehicle(models.Model): name = models.CharField(max_length=255) customer = models.ForeignKey( Customer, on_delete=models.CASCADE, related_name='Vehicle' )
Many to Many Relationships
We can also implement many to many relations in the database. In this case, we are taking examples of multiple drivers.
To implement the same in model, paste this code in models.py:
from django.db import models # Create your models here. #Ducatindia #Many to Many Relationship class Worker(models.Model): name = models.CharField(max_length=255) class Machine(models.Model): name = models.CharField(max_length=255) worker = models.ManyToManyField( Worker, related_name='Machine' )