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docs/development/architecture.md
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docs/development/architecture.md
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docs/development/contributing.md
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docs/development/contributing.md
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docs/development/database-migrations.md
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docs/development/database-migrations.md
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# Database Migrations Guide
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This guide covers advanced database migration workflows for developers working on schema changes.
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## Overview
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Our project uses Alembic for database migrations. All schema changes must go through the migration system to ensure:
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- Reproducible deployments
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- Team synchronization
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- Production safety
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- Rollback capability
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## Migration Commands Reference
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### Creating Migrations
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```bash
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# Auto-generate migration from model changes
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make migrate-create message="add_user_profile_table"
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# Create empty migration template for manual changes
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make migrate-create-manual message="add_custom_indexes"
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```
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### Applying Migrations
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```bash
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# Apply all pending migrations
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make migrate-up
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# Rollback last migration
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make migrate-down
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# Rollback to specific revision
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make migrate-down-to revision="abc123"
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```
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### Migration Status
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```bash
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# Show current migration status
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make migrate-status
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# Show detailed migration history
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alembic history --verbose
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# Show specific migration details
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make migrate-show revision="abc123"
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```
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### Backup and Safety
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```bash
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# Create database backup before major changes
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make backup-db
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# Verify database setup
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make verify-setup
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```
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## Development Workflows
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### Adding New Database Fields
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1. **Modify your SQLAlchemy model**:
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```python
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# In models/database/user.py
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class User(Base):
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# ... existing fields
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profile_image = Column(String, nullable=True) # NEW FIELD
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```
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2. **Generate migration**:
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```bash
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make migrate-create message="add_profile_image_to_users"
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```
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3. **Review generated migration**:
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```python
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# Check alembic/versions/xxx_add_profile_image_to_users.py
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def upgrade() -> None:
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op.add_column('users', sa.Column('profile_image', sa.String(), nullable=True))
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def downgrade() -> None:
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op.drop_column('users', 'profile_image')
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```
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4. **Apply migration**:
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```bash
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make migrate-up
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```
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### Adding Database Indexes
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1. **Create manual migration**:
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```bash
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make migrate-create-manual message="add_performance_indexes"
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```
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2. **Edit the migration file**:
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```python
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def upgrade() -> None:
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# Add indexes for better performance
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op.create_index('idx_products_marketplace_shop', 'products', ['marketplace', 'shop_name'])
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op.create_index('idx_users_email_active', 'users', ['email', 'is_active'])
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def downgrade() -> None:
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op.drop_index('idx_users_email_active', table_name='users')
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op.drop_index('idx_products_marketplace_shop', table_name='products')
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```
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3. **Apply migration**:
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```bash
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make migrate-up
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```
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### Complex Schema Changes
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For complex changes that require data transformation:
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1. **Create migration with data handling**:
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```python
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def upgrade() -> None:
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# Create new column
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op.add_column('products', sa.Column('normalized_price', sa.Numeric(10, 2)))
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# Migrate data
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connection = op.get_bind()
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connection.execute(
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text("UPDATE products SET normalized_price = CAST(price AS NUMERIC) WHERE price ~ '^[0-9.]+$'")
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)
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# Make column non-nullable after data migration
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op.alter_column('products', 'normalized_price', nullable=False)
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def downgrade() -> None:
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op.drop_column('products', 'normalized_price')
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```
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## Production Deployment
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### Pre-Deployment Checklist
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- [ ] All migrations tested locally
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- [ ] Database backup created
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- [ ] Migration rollback plan prepared
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- [ ] Team notified of schema changes
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### Deployment Process
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```bash
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# 1. Pre-deployment checks
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make pre-deploy-check
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# 2. Backup production database
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make backup-db
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# 3. Deploy with migrations
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make deploy-prod # This includes migrate-up
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```
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### Rollback Process
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```bash
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# If deployment fails, rollback
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make rollback-prod # This includes migrate-down
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```
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## Best Practices
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### Migration Naming
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Use clear, descriptive names:
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```bash
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# Good examples
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make migrate-create message="add_user_profile_table"
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make migrate-create message="remove_deprecated_product_fields"
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make migrate-create message="add_indexes_for_search_performance"
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# Avoid vague names
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make migrate-create message="update_database" # Too vague
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make migrate-create message="fix_stuff" # Not descriptive
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```
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### Safe Schema Changes
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**Always Safe**:
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- Adding nullable columns
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- Adding indexes
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- Adding new tables
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- Increasing column size (varchar(50) → varchar(100))
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**Potentially Unsafe** (require careful planning):
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- Dropping columns
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- Changing column types
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- Adding non-nullable columns without defaults
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- Renaming tables or columns
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**Multi-Step Process for Unsafe Changes**:
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```python
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# Step 1: Add new column
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def upgrade() -> None:
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op.add_column('users', sa.Column('email_new', sa.String(255)))
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# Step 2: Migrate data (separate migration)
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def upgrade() -> None:
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connection = op.get_bind()
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connection.execute(text("UPDATE users SET email_new = email"))
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# Step 3: Switch columns (separate migration)
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def upgrade() -> None:
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op.drop_column('users', 'email')
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op.alter_column('users', 'email_new', new_column_name='email')
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```
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### Testing Migrations
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1. **Test on copy of production data**:
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```bash
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# Restore production backup to test database
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# Run migrations on test database
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# Verify data integrity
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```
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2. **Test rollback process**:
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```bash
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make migrate-up # Apply migration
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# Test application functionality
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make migrate-down # Test rollback
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# Verify rollback worked correctly
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```
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## Advanced Features
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### Environment-Specific Migrations
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Use migration context to handle different environments:
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```python
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from alembic import context
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def upgrade() -> None:
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# Only add sample data in development
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if context.get_x_argument(as_dictionary=True).get('dev_data', False):
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# Add development sample data
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pass
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# Always apply schema changes
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op.create_table(...)
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```
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Run with environment flag:
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```bash
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alembic upgrade head -x dev_data=true
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```
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### Data Migrations
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For large data transformations, use batch processing:
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```python
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def upgrade() -> None:
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connection = op.get_bind()
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# Process in batches to avoid memory issues
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batch_size = 1000
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offset = 0
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while True:
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result = connection.execute(
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text(f"SELECT id, old_field FROM products LIMIT {batch_size} OFFSET {offset}")
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)
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rows = result.fetchall()
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if not rows:
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break
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for row in rows:
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# Transform data
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new_value = transform_function(row.old_field)
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connection.execute(
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text("UPDATE products SET new_field = :new_val WHERE id = :id"),
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{"new_val": new_value, "id": row.id}
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)
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offset += batch_size
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```
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## Troubleshooting
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### Common Issues
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**Migration conflicts**:
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```bash
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# When multiple developers create migrations simultaneously
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# Resolve by creating a merge migration
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alembic merge -m "merge migrations" head1 head2
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```
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**Failed migration**:
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```bash
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# Check current state
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make migrate-status
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# Manually fix database if needed
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# Then mark migration as applied
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alembic stamp head
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```
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**Out of sync database**:
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```bash
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# Reset to known good state
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make backup-db
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alembic downgrade base
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make migrate-up
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```
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### Recovery Procedures
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1. **Database corruption**: Restore from backup, replay migrations
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2. **Failed deployment**: Use rollback process, investigate issue
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3. **Development issues**: Reset local database, pull latest migrations
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## Integration with CI/CD
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Our deployment pipeline automatically:
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1. Runs migration checks in CI
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2. Creates database backups before deployment
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3. Applies migrations during deployment
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4. Provides rollback capability
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Migration failures will halt deployment to prevent data corruption.
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## Further Reading
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- [Alembic Official Documentation](https://alembic.sqlalchemy.org/)
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- [Database Schema Documentation](database-schema.md)
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- [Deployment Guide](../deployment/production.md)
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*This documentation is under development.*
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