🏋️ ACEest Fitness & Gym – DevOps CI/CD Pipeline

A Flask-based fitness and gym management web application with a fully automated CI/CD pipeline using GitHub Actions and Jenkins.

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📋 Table of Contents

• Project Overview
• Features
• Tech Stack
• Project Structure
• Local Setup & Execution
• Running Tests Manually
• Docker Usage
• CI/CD Pipeline Overview
  • GitHub Actions
  • Jenkins Integration
• API Endpoints
• Version History

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🎯 Project Overview

ACEest Fitness & Gym is a web application designed for managing gym clients, tracking workouts, generating AI-style training programs, monitoring membership status, and calculating BMI. The project demonstrates modern DevOps practices including:

• Version Control with Git/GitHub (descriptive commits, branch management)
• Unit Testing with Pytest (30+ test cases)
• Containerization with Docker (optimized, non-root image)
• CI/CD Automation with GitHub Actions & Jenkins

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✨ Features

Feature	Description
Client Management	Full CRUD operations for gym clients
Workout Tracking	Log and retrieve workout sessions per client
AI Program Generator	Generate workout plans based on program type and experience
BMI Calculator	Calculate BMI and get WHO category classification
Calorie Estimator	Estimate daily calorie needs based on weight and program
Membership Tracking	Check active/expired membership status with expiry dates
Health Check Endpoint	/health endpoint for container orchestration and monitoring

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🛠 Tech Stack

Layer	Technology
Backend	Python 3.12 + Flask
Database	SQLite3
Testing	Pytest
Linting	Flake8
Containerization	Docker
CI/CD	GitHub Actions
Build Server	Jenkins

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📁 Project Structure

devopsAssignment1/
├── app.py                          # Flask application (main source)
├── test_app.py                     # Pytest test suite
├── requirements.txt                # Python dependencies
├── Dockerfile                      # Docker image definition
├── Jenkinsfile                     # Jenkins pipeline definition
├── .gitignore                      # Git ignore rules
├── .github/
│   └── workflows/
│       └── main.yml                # GitHub Actions CI/CD workflow
├── templates/
│   └── index.html                  # Landing page template
└── README.md                       # This file

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🚀 Local Setup & Execution

Prerequisites

• Python 3.10+ installed
• pip (Python package manager)
• Git
• Docker (optional, for container testing)

Steps

# 1. Clone the repository
git clone https://github.com/saaiarjun27/devopsAssignment1.git
cd devopsAssignment1

# 2. Create a virtual environment (recommended)
python -m venv venv
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Run the application
python app.py

The application will start on http://localhost:5000

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🧪 Running Tests Manually

# Run the full test suite with verbose output
pytest test_app.py -v

# Run with detailed failure info
pytest test_app.py -v --tb=long

# Run a specific test class
pytest test_app.py::TestBMICalculation -v

# Run with coverage (install pytest-cov first)
pip install pytest-cov
pytest test_app.py --cov=app --cov-report=term-missing

Test Coverage Summary

The test suite validates:

• ✅ Health-check endpoint
• ✅ Home page rendering
• ✅ BMI calculation logic + endpoint (including edge cases)
• ✅ Calorie estimation with all program types
• ✅ AI program generation (beginner / intermediate / advanced)
• ✅ Client CRUD (create, read, update, delete)
• ✅ Workout logging & retrieval
• ✅ Membership status checking (active / expired / not found)
• ✅ Programs listing endpoint
• ✅ Error handling (missing fields, invalid data)

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🐳 Docker Usage

Build the Docker Image

docker build -t aceest-fitness:latest .

Run the Container

docker run -p 5000:5000 aceest-fitness:latest

Visit http://localhost:5000 in your browser.

Run Tests Inside the Container

docker run --rm aceest-fitness:latest python -m pytest test_app.py -v

Docker Image Highlights

• Base image: python:3.12-slim (minimal footprint)
• Non-root user: Runs as aceest user for security
• Layer caching: Dependencies installed before copying source
• Health check: Built-in HEALTHCHECK instruction

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⚙️ CI/CD Pipeline Overview

GitHub Actions

The pipeline is defined in .github/workflows/main.yml and is triggered on every push or pull_request to the main branch.

┌─────────────────────┐     ┌──────────────────────┐     ┌─────────────────────────┐
│  Stage 1:           │     │  Stage 2:            │     │  Stage 3:               │
│  Build & Lint       │────▶│  Docker Image        │────▶│  Automated Testing      │
│                     │     │  Assembly            │     │  (Pytest in Container)  │
│  • Install deps     │     │  • docker build      │     │  • Run test_app.py      │
│  • flake8 lint      │     │  • Verify image      │     │  • All 30+ tests        │
│  • Verify imports   │     │                      │     │                         │
└─────────────────────┘     └──────────────────────┘     └─────────────────────────┘

Stage	What It Does
Build & Lint	Installs dependencies, runs flake8 syntax/error checks
Docker Assembly	Builds the Docker image and verifies it was created
Automated Testing	Runs the full Pytest suite inside the Docker container

Jenkins Integration

The Jenkinsfile defines a declarative pipeline with:

1. Checkout – Pulls latest code from GitHub
2. Install Dependencies – pip install -r requirements.txt
3. Lint – Runs flake8 for syntax validation
4. Test – Executes Pytest suite
5. Docker Build – Builds and tags Docker image

Jenkins Setup Steps

1. Install Jenkins on your server/local machine
2. Install required plugins: Git, Pipeline, Docker Pipeline
3. Create a New Pipeline job
4. Under Pipeline → Definition, select Pipeline script from SCM
5. Set SCM to Git and enter the repository URL:

   https://github.com/saaiarjun27/devopsAssignment1.git
   

6. Set Script Path to Jenkinsfile
7. Save and click Build Now

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📡 API Endpoints

Method	Endpoint	Description
GET	/	Landing page
GET	/health	Health check
GET	/api/programs	List available programs
GET	/api/clients	List all clients
POST	/api/clients	Create/update a client
GET	/api/clients/<name>	Get a specific client
DELETE	/api/clients/<name>	Delete a client
GET	/api/workouts/<client_name>	Get workouts for a client
POST	/api/workouts	Log a new workout
POST	/api/bmi	Calculate BMI
POST	/api/generate-program	Generate AI workout program
GET	/api/membership/<client_name>	Check membership status

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📜 Version History

Version	Description
1.0	Initial Tkinter GUI – basic program display
1.1	Added client profile inputs, calorie estimation
1.1.2	Multi-client support, CSV export, progress chart
2.0.1	SQLite database integration
2.1.2	Database schema with workouts and exercises tables
2.2.1	Role-based login system
2.2.4	Full dashboard with AI program generator and PDF reports
3.0.1	Membership management and billing
3.1.2	Refactored UI with modal login and analytics tab
3.2.4	Streamlined codebase, workout treeview
4.0	Flask web app + Docker + CI/CD pipeline (current)

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👤 Author

Sai Arjun – Junior DevOps Engineer
GitHub: @saaiarjun27

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📄 License

This project is developed as part of a DevOps academic assignment.