What do you understand by database skills?

Understanding relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB, Redis).

Ability to design data schemas, create and modify tables, indexes, views.

Writing efficient SQL queries for data retrieval, insertion, updating, and deletion.

Using object-relational mappers (ORM), such as SQLAlchemy or Django ORM, for interacting with databases from Python code.

Experience with database migrations to manage schema changes over time (e.g., Alembic, Django Migrations).

Understanding the principles of ACID (Atomicity, Consistency, Isolation, Durability) for relational databases.

Knowledge of query and database performance optimization basics.

Ability to work with transactions to ensure data integrity.

Understanding caching principles at the database or application level (e.g., Redis).

Experience deploying and maintaining databases.

Example of using SQLAlchemy:

# sqlalchemy
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base

# Creating a database engine
# engine = create_engine('sqlite:///mydatabase.db')

# Defining the base class for declarative tables
# Base = declarative_base()

# Defining a model
# class User(Base):
#     __tablename__ = 'users'

#     id = Column(Integer, primary_key=True)
#     name = Column(String)
#     age = Column(Integer)

# Creating tables in the database (if they do not exist)
# Base.metadata.create_all(engine)

# Creating a session
# Session = sessionmaker(bind=engine)
# session = Session()

# Adding a new user
# new_user = User(name='Alice', age=30)
# session.add(new_user)
# session.commit()

# Querying users
# users = session.query(User).all()
# for user in users:
#     print(f"ID: {user.id}, Name: {user.name}, Age: {user.age}")

# Closing the session
# session.close()

Example of using an SQL query:

-- SQL
SELECT name, age FROM users WHERE age > 25;

Key differences between relational and non-relational databases:

Attribute	Relational DBs (e.g., PostgreSQL)	Non-relational DBs (e.g., MongoDB)
Data Structure	Tables with strict schema	Flexible schema, documents
Relations	Defined via foreign keys	Defined at the application level
Scaling	Vertical primarily	Easier horizontal scaling
Query Language	SQL	Various (depends on DB)
Use Cases	Transactions, complex analytics	Large data volumes, fast access