What do you understand by database skills?

Understanding relational and non-relational databases, their differences, advantages, and disadvantages for various scenarios. Knowledge of SQL: writing queries for selection, insertion, updating, deletion of data, using JOIN, subqueries, aggregate functions. Experience with ORM such as SQLAlchemy or Django ORM for interacting with databases from Python code. Understanding normalization and denormalization principles. Experience in designing database schemas. Knowledge of index basics for query performance optimization. Understanding transactions and their properties (ACID). Experience with specific DBMS like PostgreSQL, MySQL, SQLite.

# Example of a simple SQL query using SQLAlchemy
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

# Creating a database engine (SQLite in this case)
engine = create_engine('sqlite:///:memory:')
Base = declarative_base()

# Defining a data model
class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    name = Column(String)
    age = Column(Integer)

# Creating tables
Base.metadata.create_all(engine)

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

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

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

session.close()

Concept	Description
Relational DBs	Tables, rows, columns, relationships between tables (PostgreSQL, MySQL)
Non-relational DBs	Documents, key-value, graph (MongoDB, Redis)
ORM	Object-Relational Mapping (SQLAlchemy, Django ORM)
Normalization	Minimizing data redundancy
Denormalization	Intentional redundancy to speed up queries
Indexes	Structures for fast data search
Transactions (ACID)	Atomicity, Consistency, Isolation, Durability