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Database Access with ORM (ObjectRelational Mapping) in Python

Introduction
Setting Up Your Python Environment
Installing Python and PyCharm IDE Creating and Running Your First Python Program
Python Data Types
Numeric Types String Types Boolean Types None Type
Operators and Expressions
Arithmetic Operators Comparison Operators Logical Operators Bitwise Operators Assignment Operators Operator Precedence
Control Flow Statements
Conditional Statements Loops Break and Continue Statements Exception Handling
Functions and Modules
Defining and Calling Functions Function Arguments and Return Values Lambda Functions Modules and Packages
Python Data Structures
Lists Tuples Dictionaries Sets Arrays
ObjectOriented Programming in Python
Classes and Objects Attributes and Methods Inheritance and Polymorphism Abstract Classes and Interfaces
File Handling
Opening and Closing Files Reading and Writing Text Files Reading and Writing Binary Files CSV Files
Regular Expressions
Basic Regular Expressions and Metacharacters Anchors and Quantifiers Grouping and Capturing Lookarounds
Datetime and Timezones
Date and Time Objects Date and Time Formatting Timezone and Daylight Saving Time Handling
Debugging and Testing
Debugging Techniques Debugging Tools in PyCharm Unit Testing with PyTest
Web Scraping with Python
Requesting Data with urllib Parsing HTML with Beautiful Soup Extracting and Storing Data
Database Handling with Python
Connecting to Databases Performing CRUD Operations Database Access with ORM (ObjectRelational Mapping)
Introduction to Data Science with Python
NumPy Pandas Matplotlib ScikitLearn
GUI Programming with Python
Creating GUI Applications GUI Toolkits (Tkinter, PyQt, wxWidgets)
Network Programming with Python
Socket Programming Creating and Running a Simple Web Server Connecting to APIs
Best Practices and Tips
Python Coding Standards Code Organization Writing Efficient Code Tips and Tricks for Python Development
Conclusion and Next Steps.

Database Access with ORM (ObjectRelational Mapping)

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Object-Relational Mapping (ORM) is a programming technique that maps data from a relational database into a set of objects that are used within an application. An ORM makes it easier for developers to interact with the database by abstracting the low-level SQL queries and operations and instead providing a high-level interface for creating, reading, updating, and deleting objects within the database.

In Python, there are several popular ORMs including SQLAlchemy and Django ORM. These ORMs provide developers with a simple and intuitive way to interact with a database using Python code. The basic idea behind using an ORM is to define classes that map to database tables, and to use these classes to perform database operations.

For example, let's say we have a table called "users" in our database with columns for "id", "name", and "email". With an ORM, we would define a class called "User" which would map to this table.

In SQLAlchemy, the User class would look something like this:

 
                    
from sqlalchemy import Column, Integer, String

class User(Base):
    __tablename__ = 'users'

    id = Column(Integer, primary_key=True)
    name = Column(String)
    email = Column(String)

We can now use this class to perform operations on the "users" table.

For example, to create a new user record in the database, we would do something like this:

 
                    
new_user = User(name='John Doe', email='john.doe@email.com')
session.add(new_user)
session.commit()

Here, we create a new instance of the User class and pass in the name and email parameters. We then add this new instance to the session (which manages transactions with the database) and commit the transaction.

ORMs make it easy to write Python code that interacts with a database without having to worry about the low-level details of SQL queries and operations. They simplify database access and can make code more maintainable and easier to read.

March 25, 2023

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