# Essential Checklist for Production-Ready Python Projects
URL: https://madhudadi.in/blog/posts/production-ready-python-project-checklist-for-developers
Published: 2026-06-26
Tags: python, DevOps, Best Practices
Read time: 32 min
Difficulty: intermediate
> A practical production-ready Python project checklist covering structure, README, dependencies, tests, Ruff, configuration, secrets, logging, data files, Git, CI, documentation, and release readiness.# Production-Ready Python Project Checklist: Before GitHub, Portfolio, CI, or Deployment

## Quick Answer

Before publishing or deploying a Python project, verify:

- setup is documented
- dependencies are reproducible
- tests pass
- lint and formatting checks pass
- secrets are not committed
- logs are useful
- config is documented
- CI runs automatically

This checklist is for learners, portfolio builders, and developers preparing a Python project for public review or production use.

Last verified: June 26, 2026.

## 1. Project Structure Checklist

Your project should have:

```text
README.md
.gitignore
.env.example
src/ or app code folder
tests/
pyproject.toml or requirements.txt
```

For packages and serious apps, prefer:

```text
src/
  package_name/
    __init__.py
```

For data projects, add:

```text
data/
  raw/
  processed/
notebooks/
outputs/
```

## 2. README Checklist

Your README should answer:

- What does the project do?
- Why does it exist?
- Which Python version is required?
- How do I create the environment?
- How do I install dependencies?
- How do I run the project?
- How do I run tests?
- Which environment variables are required?
- What are the main folders?

Minimum commands:

```bash
python -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt
pytest
```

For `pyproject.toml`:

```bash
python -m pip install -e ".[dev]"
pytest
```

## 3. Dependency Checklist

Confirm:

- dependencies are listed
- dev dependencies are separated when possible
- dependency file is committed
- `.venv` is not committed
- install command works from a fresh clone

Acceptable beginner setup:

```text
requirements.txt
```

Preferred modern setup:

```text
pyproject.toml
```

uv setup:

```text
pyproject.toml
uv.lock
```

## 4. Testing Checklist

Confirm:

- tests live in `tests/`
- tests run with `pytest`
- important success cases are covered
- important error cases are covered
- tests do not depend on your desktop paths
- tests do not call real paid APIs
- file tests use temporary paths
- config tests use isolated environment variables

Run:

```bash
pytest
```

Optional coverage:

```bash
pytest --cov=src --cov-report=term-missing
```

## 5. Code Quality Checklist

Run:

```bash
ruff check .
ruff format --check .
```

Confirm:

- imports are sorted
- no unused imports
- no undefined names
- formatting is consistent
- functions are reasonably small
- names describe intent
- exceptions are specific

If the project is important, add pre-commit.

## 6. Configuration Checklist

Confirm:

- `.env` is ignored
- `.env.example` exists
- required variables are documented
- defaults are safe for local development
- production values are not hard-coded
- missing required config fails clearly

Example `.env.example`:

```text
DATABASE_URL=sqlite:///local.db
API_KEY=
LOG_LEVEL=INFO
```

## 7. Secrets Checklist

Search before publishing:

```bash
rg "api_key|secret|password|token|BEGIN PRIVATE KEY|sk-"
```

Confirm:

- no real API keys
- no database passwords
- no private tokens
- no `.env` in Git
- no secrets in logs
- no secrets in screenshots or notebooks

If a secret was committed, rotate it.

## 8. Logging Checklist

Confirm:

- app code uses `logging`, not only `print`
- log level is configurable
- errors include useful context
- secrets are masked
- background jobs log start and finish
- failures are visible

Basic setup:

```python
import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
```

## 9. Data Checklist

For data projects:

- raw data is preserved
- private data is not committed
- sample data is safe and small
- generated outputs are ignored unless needed
- cleaning steps are reproducible
- notebooks do not contain hidden secrets

Good `.gitignore` additions:

```gitignore
data/private/
outputs/
*.sqlite
*.db
```

Commit small synthetic examples when they help users run the project.

## 10. Git Checklist

Before pushing:

```bash
git status
git diff --check
```

Confirm:

- commits are focused
- commit messages are clear
- generated junk is not staged
- `.gitignore` is working
- README is updated
- tests pass

Good commit:

```text
Add pytest coverage for config loader
```

Weak commit:

```text
final changes
```

## 11. CI Checklist

For GitHub Actions, run:

- install dependencies
- lint
- format check
- tests

Example:

```yaml
name: Python checks

on: [push, pull_request]

jobs:
  checks:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"
      - run: python -m pip install -e ".[dev]"
      - run: ruff check .
      - run: ruff format --check .
      - run: pytest
```

CI should match local commands.

## 12. Documentation Checklist

Add docs when the project has:

- setup complexity
- environment variables
- commands
- architecture decisions
- APIs
- data pipelines

Useful docs:

```text
docs/
  architecture.md
  decisions.md
  operations.md
```

Do not write huge docs nobody updates. Write small docs that answer real questions.

## 13. Release Checklist

Before a release:

- version is updated
- changelog is updated
- tests pass
- CI is green
- README examples still work
- migration steps are documented
- rollback plan exists for deployed apps
- secrets are configured outside Git

For packages, verify build:

```bash
python -m build
```

For apps, verify start command from a clean environment.

## 14. Portfolio Checklist

If this project is for your portfolio:

- README has screenshots or sample output
- problem statement is clear
- setup takes less than 10 minutes
- demo data is included
- tests are present
- code is organized
- no secrets or private files
- project has a clear "What I learned" section

Recruiters and reviewers should understand the project quickly.

## 15. Final Scorecard

Use this scorecard:

| Area | Ready? |
|---|---|
| Structure is clear | |
| README is useful | |
| Environment is reproducible | |
| Tests pass | |
| Ruff passes | |
| Secrets are safe | |
| Config is documented | |
| Logs are useful | |
| CI runs | |
| Data is safe to publish | |

If any row is weak, fix it before publishing.

## 16. FAQ

### Does every Python project need CI?

No. Use CI for projects you share, deploy, or maintain over time.

### Does every project need `pyproject.toml`?

No. Beginner scripts can use `requirements.txt`. Use `pyproject.toml` for modern apps, packages, and tool configuration.

### How many tests are enough?

Enough to protect important behavior. Start with critical parsing, validation, calculations, and error cases.

### Should I publish my `.env.example`?

Yes. It documents required variables without exposing real values.

### Should I publish sample data?

Yes, if it is small, safe, and synthetic or publicly reusable. Do not publish private or copyrighted data.