SQLAlchemy allows the user to write database-agnostic code that can work with a variety of relational databases such as SQLite, MySQL, PostgreSQL, Oracle, and Microsoft SQL Server. The ORM layer in SQLAlchemy allows developers to map Python classes to database tables. This means you can interact with your database using Python objects instead of writing raw SQL queries.

pip install sqlalchemy mysql-connector-python

* If not installed, you can install them using the above command in terminal,

* Create a connection with the database using the following code snippet:

from sqlalchemy import create_engine

Base = declarative_base()

* The connection string **DATABASE_URL** is passed as an argument to **create_engine** function which is used to create a connection to the database. This connection string contains the database credentials such as the database type, username, password, and database name.

* The **sessionmaker** function is used to create a session object which is used to interact with the database

* The **declarative_base** function is used to create a base class for all the database models. This base class is used to define the structure of the database tables.

* The following code snippet creates a table named **"products"** in the database:

from sqlalchemy import Column, Integer, String, Float

Base.metadata.create_all(engine)

* The **Product class** inherits from **Base**, which is a base class for all the database models.

* The **Base.metadata.create_all(engine)** statement is used to create the table in the database. The engine object is a connection to the database that was created earlier.

* The following code snippet inserts data into the **"products"** table:

products = [

session.add_all(products)

session.commit()

* A list of **Product** objects is created. Each Product object represents a row in the **products table** in the database.

* The **add_all** method of the session object is used to add all the Product objects to the session. This method takes a **list of objects as an argument** and adds them to the session.

* The **commit** method of the session object is used to commit the changes made to the database.

SQLAlchemy provides functions that correspond to SQL aggregation functions and are available in the **sqlalchemy.func module**.

The **COUNT** function returns the number of rows in a result set. It can be demonstrated using the following code snippet:

from sqlalchemy import func

total_products = session.query(func.count(Product.id)).scalar()

print(f'Total products: {total_products}')

The **SUM** function returns the sum of all values in a column. It can be demonstrated using the following code snippet:

total_price = session.query(func.sum(Product.price)).scalar()

print(f'Total price of all products: {total_price}')

The **AVG** function returns the average of all values in a column. It can be demonstrated by the following code snippet:

average_price = session.query(func.avg(Product.price)).scalar()

print(f'Average price of products: {average_price}')

The **MAX** function returns the maximum value in a column. It can be demonstrated using the following code snippet :

max_price = session.query(func.max(Product.price)).scalar()

print(f'Maximum price of products: {max_price}')

The **MIN** function returns the minimum value in a column. It can be demonstrated using the following code snippet:

min_price = session.query(func.min(Product.price)).scalar()