Welcome back! So far, you have learned how to scan a codebase, extract commit history, and analyze code using a command-line interface. Until now, all the information about code files and commits has been stored in memory — meaning it disappears as soon as your program stops running.

In real-world applications, especially for tools like a code review assistant, it is important to keep this information organized and persistent. Storing data in a database allows you to:

• Save code and commit information for later use
• Query and analyze data efficiently
• Share data between different parts of your application

In this lesson, you will learn how to use a database to store code files and commit data using SQLAlchemy, a popular Python library for working with databases. This will make your code review assistant more powerful and reliable.

Before we begin working with databases, you need to install the required dependencies. SQLAlchemy is not part of Python's standard library, so it needs to be installed separately.

If you're working on your own machine, you'll need to install SQLAlchemy. Here are the installation commands:

Using pip:

pip install sqlalchemy

Using pip with a virtual environment (recommended):

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install SQLAlchemy
pip install sqlalchemy

Using conda:

conda install sqlalchemy

For this lesson, we'll also use SQLite as our database, which comes built-in with Python. If you want to use other databases like PostgreSQL or MySQL, you would need additional drivers:

# For PostgreSQL
pip install psycopg2-binary

# For MySQL
pip install pymysql

Note: On CodeSignal, the required libraries are already installed, so you do not need to worry about installation here. However, it is good practice to know how to set up your environment on your own device.

Before we dive in, let's quickly remind ourselves of what you have already built:

• You used Python data classes to represent code files and commits.
• You built a CLI tool that scanned a project directory and extracted commit history, displaying useful statistics.

In those lessons, all data was kept in memory using Python objects. Now, we will take the next step and store this data in a database so it can be accessed and updated over time.

To store data in a database, we need to define the structure of our tables. In SQLAlchemy, this is done by creating Python classes called models. Each model represents a table in the database.

Let's start by defining a model for a code file.

from sqlalchemy import Column, Integer, String, Text, DateTime
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class CodeFile(Base):
    __tablename__ = 'code_files'
    id = Column(Integer, primary_key=True)
    file_path = Column(String, unique=True)
    content = Column(Text)
    language = Column(String)
    last_updated = Column(DateTime)

Explanation:

• Base = declarative_base() sets up the base class for all our models.
• class CodeFile(Base): defines a table called code_files.
• Each attribute (like id, file_path, content) becomes a column in the table.
• id is the primary key, which uniquely identifies each row.
• file_path is marked as unique, so no two files can have the same path.

Now, let's define a model for a commit:

class Commit(Base):
    __tablename__ = 'commits'
    id = Column(Integer, primary_key=True)
    hash = Column(String, unique=True)
    message = Column(Text)
    author = Column(String)
    date = Column(DateTime)

Explanation:

• This class creates a commits table.
• Each commit has a unique hash, a message, an author, and a date.

Finally, we need a way to link files and commits together. For this, we use a third table:

from sqlalchemy import ForeignKey

class FileCommit(Base):
    __tablename__ = 'file_commits'
    id = Column(Integer, primary_key=True)
    file_id = Column(Integer, ForeignKey('code_files.id'))
    commit_id = Column(Integer, ForeignKey('commits.id'))
    diff_text = Column(Text)

Explanation:

• FileCommit links a code file to a commit, storing the changes (diff) made in that commit.
• file_id and commit_id are foreign keys, meaning they refer to rows in the code_files and commits tables.

Now that we have our models, we need to set up the database connection and create the tables.

First, let's set up the connection:

from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
import os

DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///code_review.db')
engine = create_engine(DATABASE_URL)
SessionLocal = sessionmaker(bind=engine)

Explanation:

• DATABASE_URL tells SQLAlchemy where to find the database. If the environment variable is not set, it uses a local SQLite file called code_review.db.
• create_engine() creates a connection to the database.
• SessionLocal is a factory for creating sessions, which are used to interact with the database.

Next, let's create the tables:

def init_database():
    Base.metadata.create_all(bind=engine)

Explanation:

• Base.metadata.create_all() creates all tables defined by our models if they do not already exist.

Finally, we need a helper function to get database sessions:

def get_session():
    return SessionLocal()

Explanation:

• get_session() creates and returns a new database session using the SessionLocal factory we defined earlier.
• This session is used to interact with the database — adding, updating, and querying data.

With the database ready, let's see how to add code files and commits to it. We will use our repository scanner and git history extractor from previous lessons, but now we will store the results in the database.

First, let's scan the repository and add code files:

from models import CodeFile
from database import get_session
from datetime import datetime

# Dummy scanner for demonstration
class RepositoryScanner:
    def scan_repository(self, repo_path):
        from collections import namedtuple
        File = namedtuple('File', ['file_path', 'content', 'language', 'last_updated'])
        return [
            File('main.py', 'print("Hello, World!")', 'Python', datetime.now())
        ]

session = get_session()
scanner = RepositoryScanner()
files = scanner.scan_repository('.')

for file_data in files:
    db_file = CodeFile(
        file_path=file_data.file_path,
        content=file_data.content,
        language=file_data.language,
        last_updated=file_data.last_updated
    )
    session.merge(db_file)
session.commit()

Explanation:

• We use a RepositoryScanner to get a list of code files.
• For each file, we create a CodeFile object and add it to the session.
• session.merge() adds the object to the database, updating it if it already exists.
• session.commit() saves the changes.

Now, let's add commits:

from models import Commit
from datetime import datetime

# Dummy git extractor for demonstration
class GitHistoryExtractor:
    def extract_commits(self, repo_path):
        from collections import namedtuple
        CommitData = namedtuple('CommitData', ['hash', 'message', 'author', 'date'])
        return [
            CommitData('abc123', 'Initial commit', 'Alice <alice@example.com>', datetime.now())
        ]

git_extractor = GitHistoryExtractor()
commits = git_extractor.extract_commits('.')

for commit_data in commits:
    db_commit = Commit(
        hash=commit_data.hash,
        message=commit_data.message,
        author=commit_data.author,
        date=commit_data.date
    )
    session.merge(db_commit)
session.commit()

Explanation:

• We use a GitHistoryExtractor to get a list of commits.
• For each commit, we create a Commit object and add it to the session.
• Again, session.merge() and session.commit() are used to save the data.

Sample Output:

Database populated successfully!

This message confirms that your code files and commits have been stored in the database.

In this lesson, you learned how to:

• Install and set up SQLAlchemy as a dependency for database operations
• Define SQLAlchemy models to represent code files, commits, and their relationships
• Set up and initialize a database connection
• Scan a repository and extract commit history
• Store code and commit data in a database for persistence

You are now ready to practice these skills by working with real code and seeing how data is stored and retrieved from the database. In the next exercises, you will get hands-on experience with database integration and persistence, making your code review assistant more robust and useful.