sqlalembic 1.0.0

A comprehensive Python framework for SQLAlchemy model discovery, configuration management, and database migrations with Alembic integration

SqlAlembic Framework

A comprehensive Python framework for SQLAlchemy model discovery, configuration management, and database migrations with Alembic integration.

💡 Why SqlAlembic?

Modern Python projects often rely on SQLAlchemy for database management and Alembic for migrations. While both are powerful, integrating them smoothly can be a tedious, manual, and time-consuming process.

SqlAlembic solves this problem by providing a comprehensive, out-of-the-box framework that automates the most frustrating parts of the workflow.

• Saves Hours on Manual Setup: Forget about writing boilerplate code. SqlAlembic handles the configuration and project structure for you, so you can focus on building your application.

• Automated Model Discovery: Instead of manually registering your models, our framework intelligently scans your project and automatically discovers all your SQLAlchemy models, ensuring your migrations are always up to date.

• Seamless CLI Integration: We provide a powerful and intuitive command-line interface that integrates all core database and migration tasks into a single, unified tool.

🚀 Features

• Automatic Model Discovery: Intelligently scans your project for SQLAlchemy models
• Multi-format Configuration: Supports TOML, YAML, JSON, and environment variables
• Advanced Caching System: Caches discovered models for improved performance
• Comprehensive Logging: Structured logging with multiple output formats
• Error Handling: Robust error handling and validation
• Signal System: Event-driven architecture with signal dispatching
• Multiple Database Support: PostgreSQL, MySQL, SQLite
• Migration Management: Seamless Alembic integration
• Advanced CLI: A powerful command-line interface for managing all migration and database tasks

📁 Project Structure

sqlalembic/
├── sqlalembic/
│   ├── core/
│   │   ├── __init__.py
│   │   ├── config.py                       # Configuration management
│   │   ├── initialize_core.py              # Core components initialization
│   │   ├── migration.py                    # Migration management and utilities
│   │   ├── logging_setup.py                # Logging configuration
│   │   ├── error_handler.py                # Error handling and exceptions
│   │   ├── project_structure.py            # Project structure utilities
│   │   └── signals.py                      # Signal dispatching system
│   ├── conf/
│   │   ├── alembic_template/     
│   │   │   ├── alembic.ini.template       # Alembic configuration template
│   │   │   ├── env.py.template             # Alembic environment script template
│   │   |   ├── README.md.template          # Project README template
│   │   │   └── script.py.mako.template     # Migration script template
│   │   └── project_template/     
│   │       ├── .env.template               # Environment variables template
│   │       └── manage.py.template          # Management script template
│   ├── integrations/                       # Third-party integrations
│   │   ├── __init__.py
│   │   └── alembic_setup.py                # Alembic integration setup
│   └── main.py                             # Main entry point
├── tests/    
│   ├── __init__.py
│   ├── test_model_discoverer.py            # Model discovery tests
│   ├── test_config.py                      # config tests
│   ├── test_signals.py                     # signals tests
│   ├── test_project_structure.py           # project structure tests
│   └── tests_integration.py                # Integration tests
├── LICENSE                                 # MIT License file
├── MANIFEST.in                             # Package manifest file
├── README.md                               # Project documentation
├── requirements.txt                        # Python dependencies
└── setup.py                               # Package setup configuration

🛠️ Installation

pip install sqlalembic

🚀 Quick Start

1. Create a New Project

Use the startproject command to create a new project structure:

sqlalembic startproject myproject

2. Project Structure

A new folder named after your project will be created:

├── myproject/
│   ├── versions/
│   ├── env.py
|   ├── README.md 
│   └── script.py.mako  
├── .env                # Environment variables file (optional)
└── manage.py           # Command-line utility for project management

3. Run Your First Migration

python manage.py makemigrations "Initial migration"
python manage.py migrate

💻 Migration Commands

The framework provides a powerful command-line interface to manage all aspects of your database migrations.

All commands are run using:

python manage.py <command>

1. Core Migration Commands

Command	Description	Example
makemigrations [message]	Creates new migration files based on model changes.	makemigrations "Add user table"
makemigrations --empty	Creates an empty migration file.	makemigrations --empty "Initial setup"
migrate [version]	Applies migrations to the database.	migrate head
rollback [version]	Rolls back migrations to a previous state.	rollback -1
stamp [revision]	Stamps the database with a specific revision without running migrations.	stamp 1a2b3c4d5e
merge [revisions]	Merges multiple revision heads into a single new migration file.	merge head1 head2
fresh	Resets the database and reapplies all migrations from scratch.	fresh --confirm
reset	Rolls back all migrations to the initial state (base).	reset --confirm

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2. Information & Status Commands

Command	Description	Example
status	Shows the comprehensive migration status.	status
current	Displays the current migration revision.	current --verbose
history	Shows the full migration history.	history --range base:head
show [revision]	Displays the details of a specific migration revision.	show 1a2b3c4d5e
heads	Shows the current migration heads.	heads
branches	Displays all branches in the migration tree.	branches
list	Lists all migrations, with options to filter.	list --pending-only
check	Checks if there are any pending migrations to apply.	check
validate	Validates the current migration state and checks for issues.	validate

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3. Utility Commands

Command	Description	Example
clean	Cleans migration cache files and bytecode.	clean --cache-only

⚙️ Configuration

Configuration Priority

The framework loads configuration in the following order (highest to lowest priority):

1. Environment Variables
2. Configuration Files (TOML/YAML/JSON)
3. Default Values

Configuration Files

The framework automatically searches for configuration files in this order:

sqlalembic.toml
sqlalembic.yaml / sqlalembic.yml
sqlalembic.json
config.toml
config.yaml / config.yml
config.json
alembic.toml
alembic.yaml
alembic.json

Sample Configuration Files

TOML Configuration (sqlalembic.toml)

[general]
DEBUG = true
ENVIRONMENT = "development"
PROJECT_NAME = "My SQLAlchemy Project"

[database]
DB_ENGINE = "postgresql"
DB_HOST = "localhost"
DB_PORT = 5432
DB_USER = "myuser"
DB_PASS = "mypassword"
DB_NAME = "mydatabase"
DATABASE_ECHO = false

[migration]
MIGRATION_DIR = "alembic"
MIGRATION_VERSIONS_PATH = "versions"
MIGRATION_COMPARE_TYPE = true
MIGRATION_COMPARE_SERVER_DEFAULT = true
MIGRATION_TIMEZONE = "UTC"
MIGRATION_VERSION_TABLE = "alembic_version"

[logging]
LOGGING_LEVEL = "INFO"
LOGGING_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
LOGGING_FILE = "logs/sqlalembic.log"

[discovery]
AUTO_DISCOVER_MODELS = true
MODEL_DISCOVERY_PATHS = "models:app/models"
EXCLUDE_PATHS = "venv,.venv,__pycache__,env,.env,Lib,Include,Scripts,.git"

YAML Configuration (sqlalembic.yaml)

general:
  DEBUG: true
  ENVIRONMENT: development
  PROJECT_NAME: My SQLAlchemy Project

database:
  DB_ENGINE: postgresql
  DB_HOST: localhost
  DB_PORT: 5432
  DB_USER: myuser
  DB_PASS: mypassword
  DB_NAME: mydatabase
  DATABASE_ECHO: false

migration:
  MIGRATION_DIR: alembic
  MIGRATION_VERSIONS_PATH: versions
  MIGRATION_COMPARE_TYPE: true
  MIGRATION_COMPARE_SERVER_DEFAULT: true
  MIGRATION_TIMEZONE: UTC

logging:
  LOGGING_LEVEL: INFO
  LOGGING_FORMAT: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"

discovery:
  AUTO_DISCOVER_MODELS: true
  EXCLUDE_PATHS: venv,.venv,__pycache__,env,.env,Lib,Include,Scripts,.git

Environment Variables (.env)

# Database Configuration
DB_ENGINE=postgresql
DB_HOST=localhost
DB_PORT=5432
DB_USER=myuser
DB_PASS=mypassword
DB_NAME=mydatabase
DATABASE_URL=postgresql://user:pass@localhost/db
DATABASE_ECHO=false

# General Settings
DEBUG=true
ENVIRONMENT=development
PROJECT_NAME=My SQLAlchemy Project

# Logging
LOGGING_LEVEL=INFO
LOGGING_FILE=logs/app.log

# Model Discovery
AUTO_DISCOVER_MODELS=true
MODEL_DISCOVERY_PATHS=models:app/models
EXCLUDE_PATHS=venv,.venv,__pycache__,env,.env

🗃️ Database Support

PostgreSQL

[database]
DB_ENGINE = "postgresql"
DB_HOST = "localhost"
DB_PORT = 5432
DB_USER = "username"
DB_PASS = "password"
DB_NAME = "database_name"

Or use connection URL:

DATABASE_URL=postgresql://username:password@localhost:5432/database_name

MySQL

[database]
DB_ENGINE = "mysql"
DB_HOST = "localhost"
DB_PORT = 3306
DB_USER = "username"
DB_PASS = "password"
DB_NAME = "database_name"

SQLite

[database]
DB_ENGINE = "sqlite"
DB_NAME = "database.db"  # File will be created in project root

Or absolute path:

DB_NAME=/path/to/database.db

📝 Model Definition Examples

Basic Model

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

Base = declarative_base()

class User(Base):
    __tablename__ = 'users'
    
    id = Column(Integer, primary_key=True)
    username = Column(String(80), unique=True, nullable=False)
    email = Column(String(120), unique=True, nullable=False)
    is_active = Column(Boolean, default=True)
    created_at = Column(DateTime, default=datetime.utcnow)

Model with Relationships

from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.orm import relationship

class Post(Base):
    __tablename__ = 'posts'
    
    id = Column(Integer, primary_key=True)
    title = Column(String(200), nullable=False)
    content = Column(String, nullable=False)
    user_id = Column(Integer, ForeignKey('users.id'), nullable=False)
    
    # Relationship
    author = relationship("User", back_populates="posts")

# Add to User model
User.posts = relationship("Post", back_populates="author")

Advanced Model with Indexes and Constraints

from sqlalchemy import Column, Integer, String, Index, UniqueConstraint, CheckConstraint

class Product(Base):
    __tablename__ = 'products'
    
    id = Column(Integer, primary_key=True)
    name = Column(String(100), nullable=False)
    price = Column(Integer, nullable=False)  # Price in cents
    category = Column(String(50), nullable=False)
    sku = Column(String(50), unique=True, nullable=False)
    
    # Table constraints
    __table_args__ = (
        Index('idx_product_category', 'category'),
        Index('idx_product_name_category', 'name', 'category'),
        UniqueConstraint('name', 'category', name='unique_name_category'),
        CheckConstraint('price > 0', name='positive_price'),
    )

🔍 Model Discovery Process

The framework uses a sophisticated process to discover SQLAlchemy models:

1. File Scanning

• Recursively scans the project directory
• Excludes specified directories (venv, pycache, etc.)
• Identifies Python files with SQLAlchemy indicators

2. AST Analysis

Uses Python's AST (Abstract Syntax Tree) to detect:

# SQLAlchemy indicators
- from sqlalchemy import ...
- import sqlalchemy
- Column(...)
- __tablename__ = "..."
- declarative_base()
- DeclarativeBase
- relationship(...)
- ForeignKey(...)
- Table(...)

3. Safe Import Process

• Uses subprocess isolation for safety
• Dynamically imports discovered files
• Extracts model classes and metadata
• Handles import errors gracefully

4. Metadata Consolidation

• Combines all discovered tables
• Avoids duplicate tables
• Creates unified MetaData object

Signal System

The Sqlalembic framework includes a powerful signal system that allows you to hook into various events throughout the migration process.

Quick Start

from sqlalembic.core.signals import dispatcher

# Define your handler
def my_handler(sender, **kwargs):
    print(f"Migration event: {kwargs}")

# Connect to a signal
dispatcher.connect("command_finished", my_handler)

# That's it! Your handler will be called when migrations complete

How It Works

The signal system follows the observer pattern:

1. Connect handlers to specific signals
2. When events occur, the framework sends signals
3. All connected handlers are automatically called

SignalDispatcher API

dispatcher.connect(signal_name, handler)

Register a function to be called when a signal is sent.

Parameters:

• signal_name (str): Name of the signal to listen for
• handler (callable): Function to call when signal is sent

def on_migration_complete(sender, **kwargs):
    print(f"{kwargs['command_name']} completed!")

dispatcher.connect("command_finished", on_migration_complete)

dispatcher.disconnect(signal_name, handler)

Remove a handler from a signal.

dispatcher.disconnect("command_finished", on_migration_complete)

dispatcher.send(signal_name, sender=None, **kwargs)

Send a signal (usually called by the framework, not by you).

Returns: List of (handler, result) tuples

Built-in Signals

Command Lifecycle

• command_finished - Command completed successfully
• command_failed - Command failed with an error

def log_results(sender, **kwargs):
    if 'success' in kwargs:
        print(f"{kwargs['command_name']} succeeded")
    elif 'exception' in kwargs:
        print(f"{kwargs['command_name']} failed: {kwargs['exception']}")

dispatcher.connect("command_finished", log_results)
dispatcher.connect("command_failed", log_results)

Migration Commands

Each migration command sends a signal when it starts:

# Listen for specific commands
dispatcher.connect("migration_migrate_command", on_migrate_start)
dispatcher.connect("migration_rollback_command", on_rollback_start)
dispatcher.connect("migration_makemigrations_command", on_makemigrations_start)

# Or listen for all commands
def on_any_command(sender, **kwargs):
    command = kwargs.get('command_name', 'unknown')
    print(f"Starting {command}")

# Connect to all command signals
commands = [
    "migration_migrate_command",
    "migration_rollback_command", 
    "migration_makemigrations_command",
    "migration_history_command",
    "migration_current_command"
]

for cmd in commands:
    dispatcher.connect(cmd, on_any_command)

All Available Signals

Command Lifecycle

• command_finished - Any command completed successfully
• command_failed - Any command failed

Specific Commands

• migration_makemigrations_command - Create new migration
• migration_migrate_command - Apply migrations
• migration_rollback_command - Rollback migrations
• migration_history_command - Show migration history
• migration_current_command - Show current migration
• migration_show_command - Show specific migration
• migration_heads_command - Show head migrations
• migration_branches_command - Show migration branches
• migration_stamp_command - Mark migration as applied
• migration_merge_command - Merge migration branches
• migration_squash_command - Combine migrations
• migration_check_command - Validate migrations
• migration_validate_command - Check migration syntax
• migration_reset_command - Reset migration state
• migration_fresh_command - Fresh migration setup
• migration_clean_command - Clean migration files
• migration_status_command - Show migration status
• migration_list_command - List all migrations

Alembic Process

• alembic_command_started - Before Alembic runs
• alembic_command_completed - Alembic succeeded
• alembic_command_failed - Alembic failed

🚨 Error Handling

Configuration Errors

from sqlalembic.core.config import ConfigurationError

try:
    config = Config()
except ConfigurationError as e:
    print(f"Configuration error: {e}")

Common Issues and Solutions

Model Discovery Issues

Problem: No models discovered

# Check if auto-discovery is enabled
config.AUTO_DISCOVER_MODELS = True

# Check excluded paths
print(config.EXCLUDE_PATHS)

# Enable debug mode
discoverer = ModelDiscoverer(dependencies, debug=True)

Problem: Import errors during discovery

# Check Python path
import sys
sys.path.insert(0, '/path/to/your/project')

# Check for circular imports
# Move import statements inside functions if needed

Database Connection Issues

Problem: Connection refused

# Check if database server is running
sudo service postgresql start  # PostgreSQL
sudo service mysql start       # MySQL

Problem: Authentication failed

# Verify credentials in configuration
print(config.DATABASE_URI)

# Test connection manually
from sqlalchemy import create_engine
engine = create_engine(config.DATABASE_URI)
engine.connect()

📊 Logging

Configuration

# Enable SQL logging
DATABASE_ECHO = true

# Set log level
LOGGING_LEVEL = "DEBUG"

# Log to file
LOGGING_FILE = "logs/sqlalembic.log"

Log Levels

• DEBUG: Detailed information for debugging
• INFO: General information about framework operation
• WARNING: Warning messages for potential issues
• ERROR: Error messages for handled exceptions
• CRITICAL: Critical errors that may stop the application

Example Log Output

2024-01-15 10:30:45 - sqlalembic.config - INFO - Configuration initialized from: /project/sqlalembic.toml
2024-01-15 10:30:45 - sqlalembic.discovery - INFO - Starting model discovery in: /project
2024-01-15 10:30:45 - sqlalembic.discovery - INFO - Found 3 potential model files
2024-01-15 10:30:46 - sqlalembic.discovery - INFO - Successfully discovered 5 tables

🧪 Testing

Unit Tests

import unittest
from sqlalembic.core.config import Config
from sqlalembic.intergrations.alembic_setup import ModelDiscoverer

class TestModelDiscovery(unittest.TestCase):
    def setUp(self):
        self.config = Config()
        self.dependencies = {
            "config": self.config,
            "logger": logging.getLogger(__name__)
        }
    
    def test_model_discovery(self):
        discoverer = ModelDiscoverer(self.dependencies)
        metadata = discoverer.discover()
        self.assertGreater(len(metadata.tables), 0)
    
    def test_cache_functionality(self):
        discoverer = ModelDiscoverer(self.dependencies, use_cache=True)
        # First call - should populate cache
        metadata1 = discoverer.discover()
        # Second call - should use cache
        metadata2 = discoverer.discover()
        self.assertEqual(len(metadata1.tables), len(metadata2.tables))

Integration Tests

from sqlalembic.core.initialize_core import initialize_core_components

def test_full_initialization():
    """Test complete framework initialization"""
    components = initialize_core_components()
    
    assert "config" in components
    assert "logger" in components
    assert "error_handler" in components
    assert "dispatcher" in components
    
    # Test database connection
    from sqlalchemy import create_engine
    engine = create_engine(components["config"].DATABASE_URI)
    connection = engine.connect()
    connection.close()

Common Use Cases

1. Notifications

def send_slack_notification(sender, **kwargs):
    if kwargs.get('success'):
        send_to_slack(f"Migration {kwargs['command_name']} completed")
    else:
        send_to_slack(f"Migration failed: {kwargs.get('exception')}")

dispatcher.connect("command_finished", send_slack_notification)
dispatcher.connect("command_failed", send_slack_notification)

2. Custom Logging

import logging

migration_logger = logging.getLogger('migrations')

def log_migration_events(sender, **kwargs):
    command = kwargs.get('command_name', 'unknown')
    migration_logger.info(f"Migration command: {command}", extra=kwargs)

dispatcher.connect("command_finished", log_migration_events)

3. Database Cleanup

def cleanup_after_rollback(sender, **kwargs):
    if kwargs.get('command_name') == 'rollback':
        # Clean up temporary data
        cleanup_temp_tables()

dispatcher.connect("command_finished", cleanup_after_rollback)

4. Performance Monitoring

import time

start_times = {}

def track_performance_start(sender, **kwargs):
    command = kwargs.get('command_name')
    start_times[command] = time.time()

def track_performance_end(sender, **kwargs):
    command = kwargs.get('command_name')
    if command in start_times:
        duration = time.time() - start_times[command]
        print(f"⏱️  {command} took {duration:.2f} seconds")

dispatcher.connect("migration_migrate_command", track_performance_start)
dispatcher.connect("command_finished", track_performance_end)

Best Practices

1. Keep handlers lightweight - Signals are called synchronously
2. Handle exceptions - Failing handlers don't stop the migration
3. Use descriptive names - Make your handler functions self-documenting
4. Disconnect when done - Clean up handlers you no longer need

# Good: Clear, specific handler
def notify_team_on_production_migration(sender, **kwargs):
    if is_production() and kwargs.get('success'):
        send_notification("Production migration completed")

# Better: Include error handling
def safe_notification_handler(sender, **kwargs):
    try:
        notify_team_on_production_migration(sender, **kwargs)
    except Exception as e:
        logger.error(f"Notification failed: {e}")

🔧 Advanced Usage

Custom Model Discovery Paths

# Specify custom paths to search for models
MODEL_DISCOVERY_PATHS = "app/models:src/database/models:custom/path"

Custom Exclusions

# Add custom directories to exclude
EXCLUDE_PATHS = "venv,.venv,__pycache__,tests,docs,build,dist"

Programmatic Configuration

from sqlalembic.core.config import Config

# Create config with custom settings
config = Config(config_file="custom_config.toml", load_env=False)

# Modify configuration at runtime
config.set("DEBUG", True)
config.set("LOGGING_LEVEL", "DEBUG", section="logging")

# Export configuration
config_dict = config.to_dict()

🚀 Performance Optimization

Caching

The framework includes an intelligent caching system:

• File-based caching: Stores discovered metadata to disk
• Hash validation: Detects changes in model files
• Automatic invalidation: Clears cache when files change

Best Practices

1. Use caching in production:

   discoverer = ModelDiscoverer(dependencies, use_cache=True)
   

2. Exclude unnecessary directories:

   EXCLUDE_PATHS = "venv,tests,docs,build,dist,node_modules"
   

3. Minimize model file complexity:

   • Avoid complex imports in model files
   • Use lazy loading for relationships
   • Keep models focused and simple

🐛 Troubleshooting

Common Issues

Issue: "No models discovered"

Solutions:

1. Check that AUTO_DISCOVER_MODELS = True
2. Verify model files contain SQLAlchemy indicators
3. Check excluded paths don't include model directories
4. Enable debug mode: debug=True

Issue: "Import errors during discovery"

Solutions:

1. Check for circular imports
2. Ensure all dependencies are installed
3. Verify Python path includes project root
4. Check for syntax errors in model files

Issue: "Database connection failed"

Solutions:

1. Verify database server is running
2. Check connection credentials
3. Test DATABASE_URI manually
4. Check network connectivity and firewall settings

Issue: "Configuration file not found"

Solutions:

1. Place config file in project root
2. Use supported file names (sqlalembic.toml, config.yaml, etc.)
3. Specify config file path explicitly
4. Use environment variables as fallback

Debug Mode

Enable debug mode for detailed logging:

# In model discovery
discoverer = ModelDiscoverer(dependencies, debug=True)

# In configuration
config = Config()
config.DEBUG = True

# Set logging level
import logging
logging.basicConfig(level=logging.DEBUG)

🤝 Contributing

Development Setup

1. Clone the repository

2. Create virtual environment:

   python -m venv venv
   source venv/bin/activate  # Linux/Mac
   venv\Scripts\activate     # Windows
   

3. Install dependencies:

   pip install -r requirements-dev.txt
   

4. Run tests:

   python -m pytest tests/
   

Code Style

• Follow PEP 8
• Use type hints
• Add docstrings for all public methods
• Write unit tests for new features

📄 License

This project is licensed under the MIT License.

🆘 Support

• Documentation: Check this README and code comments
• Issues: Report bugs and feature requests via GitHub issues
• Discussions: Use GitHub Discussions for questions and ideas

📋 Changelog

Version 1.0.0

• Initial release
• Basic model discovery
• Configuration management
• Multi-database support
• Caching system
• Logging integration

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