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Managing data in Python can be done using flat files (CSV, JSON) or databases like SQLite with SQLAlchemy for ORM-based access. Below is a concise example using SQLite and SQLAlchemy to store, query, and update structured data.
from sqlalchemy import create_engine, Column, Integer, String, ForeignKey, funcfrom sqlalchemy.orm import declarative_base, relationship, sessionmaker# Define ORM baseBase = declarative_base()# Define modelsclass Author(Base):__tablename__ = "author"author_id = Column(Integer, primary_key=True)first_name = Column(String)last_name = Column(String)books = relationship("Book", back_populates="author")class Book(Base):__tablename__ = "book"book_id = Column(Integer, primary_key=True)title = Column(String)author_id = Column(Integer, ForeignKey("author.author_id"))author = relationship("Author", back_populates="books")# Create SQLite DB and sessionengine = create_engine("sqlite:///library.db")Base.metadata.create_all(engine)Session = sessionmaker(bind=engine)session = Session()# Insert dataauthor = Author(first_name="Stephen", last_name="King")book1 = Book(title="The Shining", author=author)book2 = Book(title="It", author=author)session.add_all([author, book1, book2])session.commit()# Query dataresults = session.query(Author.first_name, Author.last_name, func.count(Book.title).label("total_books"))\.join(Book)\.group_by(Author.author_id)\.all()for first, last, total in results:print(f"{first} {last} has written {total} books.")# Update databook_to_update = session.query(Book).filter_by(title="It").first()book_to_update.title = "It (Updated Edition)"session.commit()# Delete databook_to_delete = session.query(Book).filter_by(title="The Shining").first()session.delete(book_to_delete)session.commit()Copied!✕Copy Free Python Intro on DataCamp | Learn Python in 15 Hours
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