Uber Traffic Analysis

This project analyzes Uber trip data using Flask API and Docker containerization.

Project Structure

.
├── Dockerfile
├── requirements.txt
├── app.py
└── README.md

Setup Instructions

1. Download the Dataset

wget https://github.com/fivethirtyeight/uber-tlc-foil-response/raw/master/uber-trip-data/uber-raw-data-janjune-15.csv.zip
unzip uber-raw-data-janjune-15.csv.zip
mv uber-raw-data-janjune-15.csv Uber-Jan-Feb-FOIL.csv
head -50000 Uber-Jan-Feb-FOIL.csv > Uber-small.csv

2. Install Docker

curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo systemctl start docker

3. Build Docker Image

sudo docker build -t uber-app .

4. Run Container

sudo docker run -p 5000:5000 uber-app

5. Test the API

# Test homepage
curl http://localhost:5000/

# Test traffic prediction
curl "http://localhost:5000/predict_traffic?timestamp=2015-01-01%2000:00:00"

API Endpoints

• GET / - Homepage
• GET /predict_traffic?timestamp=YYYY-MM-DD HH:MM:SS - Predict traffic for a given timestamp

Features

• Data preprocessing and cleaning
• Traffic pattern analysis
• Flask REST API
• Docker containerization
• Load testing with JMeter

Technologies Used

• Python 3.8
• Flask
• Pandas
• Docker
• JMeter