API Integration
Uses Python's Requests library to query the Open-Meteo REST API and process JSON forecast responses across multiple locations.
Automation / APIs
Weather Monitoring Bot
A Python-based weather monitoring utility that retrieves multi-location forecast data, identifies potentially disruptive weather conditions, groups consecutive events, and produces a readable operational report.
Overview
The Problem
Monitoring weather across multiple geographic locations can require repetitive manual checks, especially when the goal is not simply to view a forecast but to identify conditions that may require additional attention.
I built Weather Monitor to explore how that process could be automated. Instead of reviewing individual forecasts, the application collects weather data for multiple configured locations and surfaces notable conditions in a consolidated report.
Approach
The Solution
Weather Monitor is a Python command-line application that queries the Open-Meteo forecast API for a configurable list of locations. The returned JSON data is analyzed against predefined weather classifications and wind thresholds to identify potentially disruptive conditions.
Matching weather events occurring across consecutive days are grouped into date ranges, reducing repetitive output and producing a compact report that can be reviewed quickly.
Architecture
How It Works
01
Locations
Configured demo locations define which geographic areas should be monitored.
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02
REST API
Python requests daily forecast data from the Open-Meteo API.
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03
Analysis
Weather codes and wind gusts are evaluated against configurable monitoring criteria.
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04
Report
Consecutive events are grouped and converted into a readable multi-location report.
Under the Hood
Technical Details
Weather Classification
Maps numerical weather codes into readable conditions and identifies weather categories considered notable for monitoring.
Threshold Detection
Evaluates forecast wind gusts against a configurable threshold and surfaces high-wind events alongside significant weather.
Event Grouping
Detects matching conditions across consecutive forecast days and combines them into date ranges to reduce repetitive output.
Lessons Learned
Challenges & Iteration
Early testing revealed an important limitation in the original design. Although the application successfully retrieved forecast data, relying on daily weather classifications could miss operationally relevant conditions occurring over shorter periods or hazards communicated through active weather alerts.
This highlighted an important distinction between retrieving valid data and retrieving data with enough detail for the intended use case. Future versions are planned to incorporate more granular forecast analysis and active weather alert data.
The public version of the project also uses demonstration locations rather than locations associated with the environment that originally inspired the tool.
Example
Sample Output
Weather Monitor condenses forecast analysis into a simple command-line report designed for quick review.
weather_monitor.py
Weather Monitor - 08/25/2026
Seattle, WA: ☀️ Clear today, no notable upcoming weather
Denver, CO: ⛅ Partly cloudy today, upcoming ⛈️ Thunderstorms 08/27
Dallas, TX: 🌤️ Mainly clear today, no notable upcoming weather
Chicago, IL: 🌧️ Rain today, upcoming 💨 High wind gusts 48 mph 08/28
New York, NY: ☀️ Clear today, no notable upcoming weather