Flight Delay Predictor - Weather and Flight Status Checker

This Jupyter notebook demonstrates the creation of a simple prototype that helps users check flight statuses and determine if weather conditions might cause delays.

Features

• Retrieves flight status using the AviationStack API.
• Fetches weather data for a specified city using the Visual Crossing Weather API.
• Analyzes weather conditions such as precipitation probability, wind speed, and general conditions to determine if the weather might impact flight delays.
• Displays the flight status and informs the user if bad weather conditions are likely to cause delays.

Prerequisites

To run this notebook, you need to set up API keys for:

• AviationStack API (for retrieving flight status information)
• Visual Crossing Weather API (for fetching weather data)

Make sure to add these API keys to the SECRETS tab in Google Colab or store them securely in your environment.

Usage

• Run the notebook cells in order.
• When prompted, enter:
  • A flight number (e.g., DL1087).

The notebook will automatically fetch the weather for both the departure and arrival cities based on the flight number.

The notebook will then display:

• The flight status (e.g., on-time, delayed).
• The current weather conditions in both the departure and arrival cities.
• Whether the flight might be affected by bad weather based on precipitation, wind speed, or weather conditions such as rain or snow.

Example Output

Enter the flight number (e.g., DL1087): DL1087

Flight Status for DL1087: on-time
Departure City: Dubai
Arrival City: Heathrow

Weather in Dubai: Rain, Overcast
Precipitation Probability: 100.0%
Wind Speed: 15.0 mph
Bad weather detected in Dubai.
The flight is currently on time, but bad weather might cause a delay.

Weather in Heathrow: Overcast
Precipitation Probability: 30.0%
Wind Speed: 10.0 mph