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https://github.com/abhimanyu-gaurav/portfolio
This repository contains my personal portfolio website, showcasing my skills and projects as a Software Developer. Built using FastAPI, python,Bootstrap, and HTML/CSS,Docker. This portfolio highlights my expertise in Python, FastAPI, and web scraping. Feel free to explore my work and connect with me!
https://github.com/abhimanyu-gaurav/portfolio
css docker docker-container docker-image dockerfile fastapi html python render
Last synced: 12 days ago
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This repository contains my personal portfolio website, showcasing my skills and projects as a Software Developer. Built using FastAPI, python,Bootstrap, and HTML/CSS,Docker. This portfolio highlights my expertise in Python, FastAPI, and web scraping. Feel free to explore my work and connect with me!
- Host: GitHub
- URL: https://github.com/abhimanyu-gaurav/portfolio
- Owner: Abhimanyu-Gaurav
- License: mit
- Created: 2024-10-07T12:25:25.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-10-21T11:09:01.000Z (18 days ago)
- Last Synced: 2024-10-21T15:30:52.729Z (17 days ago)
- Topics: css, docker, docker-container, docker-image, dockerfile, fastapi, html, python, render
- Language: HTML
- Homepage: https://abhimanyuhub.onrender.com/
- Size: 159 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: License
Awesome Lists containing this project
README
# My Portfolio Website
## Requirements
- FastAPI
- Python 3.8+
- Docker
- Bootstrap (CSS framework)
---
## Table of Contents
- [Introduction](#introduction)
- [Technologies Used](#technologies-used)
- [Setup](#setup)
- [How to Run](#how-to-run)
- [Docker Setup](#docker-setup)
- [Auto Deployment](#auto-deployment)
- [License](#license)
---
## Introduction
This is a personal portfolio website built using FastAPI and Bootstrap. It features sections like skills, education, work experience, and contact information, along with social media links and a simple dark-themed design.
**Feature:**
- Responsive design
- Integration with Google Analytics
- Auto deployment pipeline with Render
- Contact form or project showcase
---
## Technologies Used
- **python**:
- **FastAPI**: Backend framework
- **Docker**: To deploy or run
- **Git & GitHub**: To push and deploy
- **Bootstrap**: CSS framework for responsive design
- **FontAwesome**: For social media icons
- **Google Analytics**: For tracking user activity
---
## Setup
1. **Clone the repository**:
```bash
git clone https://github.com/yourusername/your-portfolio.git
cd your-portfolio
2. **Install dependencies**: Create a virtual environment and install dependencies from the requirements.txt file:
```bash
python -m venv env
source env/bin/activate # On Windows: env\Scripts\activate
pip install -r requirements.txt
3. **Google Analytics Integration**:
If you want to track visitor activity using Google Analytics, follow these steps:
- Go to Google Analytics.
- Create an account and a property for your portfolio.
- Get the Tracking ID (starts with "UA-").
- Add the following script to the head section of your index.html file (or equivalent):
```bash
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'YOUR_TRACKING_ID');
- Replace YOUR_TRACKING_ID with your actual tracking ID.
- Deploy your portfolio, and Google Analytics will start collecting data.
4. **Configure Docker**: Build your Docker image
```bash
docker build -t fastapi-portfolio:v1.0 .
5. **Run the Docker container**:
```bash
docker run -d -p 8000:8000 --name portfolio -v my_volume:/app/data fastapi-portfolio:v1.0
---
## How to Run
1. Locally:
- Run FastAPI using uvicorn:
```bash
uvicorn app:app --reload
2. API will be running at:
```bash
http://127.0.0.1:8000/
3. Open your browser (Safari, Chrome, Brave) and enter the URL:
```bash
http://localhost:8000/
---
## Docker Setup
**To containerize and run the portfolio using Docker, follow these steps:**
1. Build Docker Image:
Every time you make changes to your code, you need to create a new Docker image. Run the following command to build a new image:
```bash
docker build -t fastapi-portfolio:v1.0 .
2. Run Docker Container:
After building the image, use the following command to run the Docker container:
```bash
docker run -d -p 8000:8000 --name portfolio -v my_volume:/app/data fastapi-portfolio:v1.0
- -d runs the container in detached mode.
- -p 8000:8000 maps the container’s port 8000 to your local machine’s port 8000.
- -v my_volume:/app/data mounts a volume for persistent storage (optional based on your needs).
3. Access the Application:
Once the container is running, navigate to http://localhost:8000 in your browser to view the portfolio.
---
## Auto Deployment
- This portfolio is automatically deployed on Render whenever new changes are pushed to the main branch on GitHub.
**How It Works:**
1. Auto-Trigger: When you push your code to GitHub, Render detects the changes and triggers a new deployment.
2. Live Update: The updated portfolio goes live once the deployment is complete.
**To set up a similar auto-deployment system on Render:**
1. Create an account on Render.
2. Connect your GitHub repository.
3. Set up a new web service, and Render will handle the rest.
---
## License
- This project is licensed under the MIT License - see the [License](License) file for details.
---