backend steps

1. create dir backend empty

2. create --init--.py

3. requirement.txt

4. database.py

download package using pip requiremnts.txt

add postgres real connection string in database.py

do alembic init

1. Open alembic.ini and set your DB URL:

sqlalchemy.url = postgresql+psycopg2://username:password@localhost:5432/yourdbname

why alembic migration

Good thinking 👍 You’re mixing two related but different concerns:

• Schema migration management (Alembic vs manual SQL)

• Security (SQL injection)

Let’s clarify both.

---

🔹 1. Is using Alembic “standard”?

Yes ✅

• In most Python projects with SQLAlchemy, Alembic is the de facto standard for handling database schema migrations.

• FastAPI, Flask, and Django projects usually include a migration tool (Alembic for SQLAlchemy, Flask-Migrate wrapper, Django migrations for Django).

• Enterprises rely on migration frameworks because:

  • They keep track of schema changes in version control.

  • They ensure repeatability (same migrations can run in dev, staging, prod).

  • They reduce human error (no forgetting which ALTER TABLE you ran last month).

---

🔹 2. What if I just run raw SQL commands (without Alembic)?

That’s still possible — many people do it in small projects. But:

• It’s not unsafe in terms of SQL injection, because schema changes are usually written by developers, not built from user input.

  ALTER TABLE users ADD COLUMN age INT;

  ← This won’t be SQL injected unless you dynamically build it from untrusted input (which no one does).

• The real problem is maintainability and consistency:

  • Hard to remember what SQL changes you applied in dev vs prod.

  • No automatic rollback if something goes wrong.

  • New team members won’t know the schema history.

---

🔹 3. What do enterprises prefer?

Enterprises almost always prefer migration frameworks like:

• Alembic (with SQLAlchemy / FastAPI / Flask).

• Liquibase or Flyway (database-agnostic, often used in Java/Spring apps).

• Django migrations (built into Django ORM).

Why?

• Version control of schema → part of Git history.

• Automated CI/CD pipelines can run migrations safely.

• Audit/compliance → easy to prove which migration changed what and when.

---

✅ Summary:

• Alembic is the standard with SQLAlchemy (not just “safe,” but essential for versioning).

• Raw SQL migrations aren’t unsafe but are hard to manage at scale.

• Enterprises always prefer migration tools (Alembic, Flyway, Liquibase) because they bring automation, consistency, and traceability.

---

👉 Do you want me to show you how a typical enterprise pipeline runs Alembic migrations automatically (e.g., in CI/CD before deploying a new FastAPI version)?

now open in alembic/env,py

make sure this line exist

from database import SQLALCHEMY_DATABASE_URL, Base  
target_metadata = Base.metadata

now run

alembic revision --autogenerate -m "init tables"

this createdd new migration under alembic/version/migration.py

apply migration to database

below cmd create table

alembic upgrade head

Note: Use new neon dB account otherwise this will erase all ur previous tables

alembic care

Good question 👍 — Alembic can be dangerous if migrations are not handled carefully, because it can drop/alter tables, which may lead to data loss. Here are the main things to take care of when using Alembic:

---

✅ Best Practices to Prevent Data Loss with Alembic

1. Never autogenerate blindly

   • alembic revision --autogenerate only detects schema changes, not whether dropping a column or table will cause data loss.

   • Always read the generated migration script before applying.

2. Back up your database

   • Always run a pg_dump (PostgreSQL) or equivalent backup before running migrations in staging/prod.

   • Example for Postgres:

     pg_dump yourdb > backup.sql

3. Use --sql flag in production first

   • Instead of running migrations directly, generate SQL scripts first:

     alembic upgrade head --sql > upgrade.sql

   • Review the script → if safe, then apply manually.

4. Be careful with column drops/renames

   • Alembic treats rename as drop + add (unless you explicitly tell it).

   • You may lose column data if you don’t handle it with a custom op.alter_column.

5. Split destructive vs non-destructive migrations

   • Example: First add a new column → backfill data → then drop old column in a separate migration.

6. Test migrations locally before production

   • Always apply migrations on a local/staging copy of the DB to check behavior.

7. Version control migration scripts

   • Never delete or overwrite migration files once pushed to a shared repo.

   • Each migration should represent a historical step in schema evolution.

8. Have a rollback strategy

   • Alembic doesn’t guarantee down migrations will work in all cases (especially destructive ones).

   • If migration fails, you’ll need backups or manual SQL fixes.

---

👉 Rule of thumb:

• Development DB → You can reset/drop if needed.

• Production DB → Always backup, review migration script, and test before applying.

---

Do you want me to also show you how to safely rename a column without losing data in Alembic?

now table created

now create schema.py

crud.py

main.py

run app

uvicorn main:app --reload

swagger url to test crud operation

http://127.0.0.1:8000/docs

now local test done now push to prod

create github repo

git init git remote add origin https://github.com//myrepo

ssh -T [email protected] --< check current configured user

create gitignore and add

gitignore

# Python cache
__pycache__/
*.pyc
*.pyo
*.pyd
*.db

# Virtual env
.env
.venv/
env/
venv/

# IDE/editor files
.vscode/
.idea/

# Alembic cache
alembic/__pycache__/

# OS files
.DS_Store
Thumbs.db

ad dockerfile

dockerfile

FROM python:3.11-slim

# Set workdir
WORKDIR /app

# Install dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy app code
COPY . .

# Run FastAPI
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

create repo in Docker hub

create credential token to add in GitHub secrets

pavan8767/3-tier-backend - repo

docker login -u pavan8767

read write token dckr_pat_1sPXfDvNsWivt-oLnbV1um4KvEg

dckr_pat_1sPXfDvNsWivt-oLnbV1um4KvEg

github workflow

name: CI - Build & Push Docker Image

on:
  push:
    branches: [ "main" ]
  pull_request:
    branches: [ "main" ]
  workflow_dispatch: # allows manual trigger

jobs:
  build:
    runs-on: ubuntu-latest

    steps:
    # 1️⃣ Checkout the code
    - name: Checkout repository
      uses: actions/checkout@v3

    # 2️⃣ Extract metadata (tags, labels) for Docker
    - name: Extract Docker metadata
      id: meta
      uses: docker/metadata-action@v5
      with:
        images: pavan8767/3-tier-backend
        tags: |
          type=ref,event=branch
          type=ref,event=pr
          type=semver,pattern={{version}}
          type=sha

    # 3️⃣ Set up Docker Buildx (multi-platform support)
    - name: Set up Docker Buildx
      uses: docker/setup-buildx-action@v2

    # 4️⃣ Cache Docker layers (speed up builds)
    - name: Cache Docker layers
      uses: actions/cache@v3
      with:
        path: /tmp/.buildx-cache
        key: ${{ runner.os }}-buildx-${{ github.sha }}
        restore-keys: |
          ${{ runner.os }}-buildx-

    # 5️⃣ Login to DockerHub securely
    - name: Login to DockerHub
      uses: docker/login-action@v2
      with:
        username: ${{ secrets.DOCKER_USERNAME }}
        password: ${{ secrets.DOCKER_PASSWORD }}

    # 6️⃣ Build and push Docker image
    - name: Build and push
      uses: docker/build-push-action@v4
      with:
        context: .
        push: true
        tags: ${{ steps.meta.outputs.tags }}
        labels: ${{ steps.meta.outputs.labels }}
        cache-from: type=local,src=/tmp/.buildx-cache
        cache-to: type=local,dest=/tmp/.buildx-cache-new,mode=max

    # 7️⃣ Move cache for next run
    - name: Move Docker cache
      run: |
        rm -rf /tmp/.buildx-cache
        mv /tmp/.buildx-cache-new /tmp/.buildx-cache