Bridging the Gap: Using Object-Relational Mappers (ORMs) for Easier Database Access

# Python with SQLAlchemy (an ORM)

class User(Base):
  __tablename__ = 'users'  # Name of the database table

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

This code defines a class named User that represents the users table in the database. Each attribute of the class (id, name, and email) maps to a column in the table.

Creating a New Database Entry (Object):

# Python with SQLAlchemy

new_user = User(name="Alice", email="[email protected]")

# ORM translates this into SQL and adds data to the database
session.add(new_user)
session.commit()

Here, we create a new User object with data for a new user. The ORM then takes care of converting this object into an SQL statement and adding the new user data to the users table in the database.

Retrieving Data from the Database:

# Python with SQLAlchemy

# Find a user by email
user = session.query(User).filter_by(email="[email protected]").first()

# Print the user's name
print(user.name)

This code retrieves a user from the database by email. The ORM translates the query for the user with the specified email address into an SQL statement and retrieves the data. Finally, it creates a User object from the retrieved data.

Here's a table summarizing the pros and cons: