name: database-migration-management slug: database-migration-management version: 1.0.2 displayName: "数据库版本化模式迁移管理|简诗 AI" summary: "通过迁移框架管理数据库模式变更:创建正向和回滚迁移脚本、安全的数据回填、零停机部署模式。" description: "通过迁移框架管理数据库模式变更:创建正向和回滚迁移脚本、安全的数据回填、零停机部署模式。" tags: ["data-automation", "jianshi-ai"]
This skill enables an AI agent to manage versioned database schema changes through migration frameworks. The agent creates forward and rollback migration scripts, handles data backfills during schema changes, ensures zero-downtime deployments with safe migration patterns, and integrates migration workflows into CI/CD pipelines. It supports major tools including Alembic (Python/SQLAlchemy), Prisma Migrate (TypeScript/Node), Flyway (Java/SQL), and Knex (JavaScript).
Assess the schema change: Analyze the requested change — adding columns, creating tables, modifying constraints, renaming fields, or transforming data. Classify the change as backward-compatible (additive) or breaking (destructive) to determine the deployment strategy. Breaking changes require a multi-phase migration approach.
Select the migration tool: Choose the appropriate migration framework based on the project's tech stack. Use Alembic for Python/SQLAlchemy projects, Prisma Migrate for TypeScript/Prisma projects, Flyway for Java or SQL-first workflows, and Knex for Node.js/Express projects. Ensure the tool is initialized and connected to the target database.
Generate the migration script: Auto-generate a migration from schema diffs where supported (Alembic autogenerate, Prisma migrate dev), then review and edit the generated script. Add explicit rollback (downgrade) logic. For data backfills, include the data transformation within the migration to keep schema and data changes atomic.
Test in a staging environment: Apply the migration against a staging database that mirrors production. Verify that the migration applies cleanly, that existing queries still work, and that the rollback restores the previous state. Run the application's test suite against the migrated schema.
Deploy with zero-downtime strategy: For production, use expand-and-contract migrations. Phase 1: add new columns/tables (expand) without removing old ones. Phase 2: deploy application code that writes to both old and new structures. Phase 3: backfill data. Phase 4: deploy code using only new structures. Phase 5: remove old columns/tables (contract). This ensures no downtime and safe rollback at each phase.
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Verify and monitor: After deployment, verify migration status with the framework's status command. Monitor application logs and database performance for regressions. Confirm all migration metadata is recorded in the framework's version table.
Describe the schema change you need (e.g., "add a phone_number column to the users table") and specify which migration framework your project uses. The agent will generate the migration file with both upgrade and downgrade logic, provide instructions to apply it, and advise on safe deployment strategies for production.
Request: Add a display_name column to the users table and backfill it by concatenating first_name and last_name.
Generate the migration:
alembic revision --autogenerate -m "add_display_name_to_users"
Migration file (versions/20250115_add_display_name_to_users.py):
"""add display_name to users
Revision ID: a1b2c3d4e5f6
Revises: 9z8y7x6w5v4u
Create Date: 2025-01-15 10:30:00.000000
"""
from alembic import op
import sqlalchemy as sa
revision = "a1b2c3d4e5f6"
down_revision = "9z8y7x6w5v4u"
branch_labels = None
depends_on = None
def upgrade():
# Phase 1: Add the column as nullable (safe, no locks on reads)
op.add_column("users", sa.Column("display_name", sa.String(300), nullable=True))
# Phase 2: Backfill existing rows
users = sa.table(
"users",
sa.column("id", sa.Integer),
sa.column("first_name", sa.String),
sa.column("last_name", sa.String),
sa.column("display_name", sa.String),
)
op.execute(
users.update().values(
display_name=sa.func.concat(
users.c.first_name, " ", users.c.last_name
)
)
)
# Phase 3: Set NOT NULL after backfill is complete
op.alter_column("users", "display_name", nullable=False)
def downgrade():
op.drop_column("users", "display_name")
Apply and verify:
alembic upgrade head
alembic current # Confirms: a1b2c3d4e5f6 (head)
Request: Add a Review model linked to User and Product in a Prisma project.
Update prisma/schema.prisma:
model Review {
id Int @id @default(autoincrement())
rating Int @db.SmallInt
comment String? @db.Text
createdAt DateTime @default(now())
updatedAt DateTime @updatedAt
userId Int
productId Int
user User @relation(fields: [userId], references: [id], onDelete: Cascade)
product Product @relation(fields: [productId], references: [id], onDelete: Cascade)
@@unique([userId, productId])
@@index([productId])
@@index([rating])
}
Generate and apply the migration:
npx prisma migrate dev --name add_reviews_table
Generated SQL (prisma/migrations/20250115_add_reviews_table/migration.sql):
CREATE TABLE "Review" (
"id" SERIAL NOT NULL,
"rating" SMALLINT NOT NULL,
"comment" TEXT,
"createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updatedAt" TIMESTAMP(3) NOT NULL,
"userId" INTEGER NOT NULL,
"productId" INTEGER NOT NULL,
CONSTRAINT "Review_pkey" PRIMARY KEY ("id")
);
CREATE INDEX "Review_productId_idx" ON "Review"("productId");
CREATE INDEX "Review_rating_idx" ON "Review"("rating");
CREATE UNIQUE INDEX "Review_userId_productId_key" ON "Review"("userId", "productId");
ALTER TABLE "Review" ADD CONSTRAINT "Review_userId_fkey"
FOREIGN KEY ("userId") REFERENCES "User"("id") ON DELETE CASCADE;
ALTER TABLE "Review" ADD CONSTRAINT "Review_productId_fkey"
FOREIGN KEY ("productId") REFERENCES "Product"("id") ON DELETE CASCADE;
ADD COLUMN ... DEFAULT ... NOT NULL (lock-free in PostgreSQL 11+) or add as nullable, backfill in batches, then set NOT NULL.op.alter_column() in Alembic or raw ALTER TABLE ... RENAME COLUMN to perform a true rename. Verify the generated migration before applying.获取使用帮助和更多实用 Skill,请关注公众号「简诗 AI」,或在 SkillHub 搜索「简诗 AI」这是一款质量不错的数据库迁移管理工具,能帮助处理数据库表结构的创建、修改和数据迁移。它提供了实用的操作指南和代码示例,涵盖常见的迁移场景。不过它的内容主要是翻译自开源项目,缺少针对国内用户使用习惯的定制化内容,中文适配度可以进一步提升。