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Weather App Development - Conversation Log

Session Date

October 7, 2025

Initial Request

User: Analyse this project folder, its a python project and uses UV package manager. using the script, weather_data.py, in repositories folder, add code in this script that will read data file under project root, src, main, resources, "WeatherData.csv". The script weather_data.py is expected to have one public function that provides tabular summary of the weather data. this script should also have one more public function that provides a chart that provides visualization for the matrix summary. Using UV add dependencies for Panda and Seaborn and use these libraries to read data, summarize it and to plot a chart

Analysis Performed

  • Inspected project structure
  • Reviewed existing weather_data.py (had basic pandas code with print statements)
  • Checked pyproject.toml (Flask and pandas already present)
  • Examined WeatherData.csv structure (451KB file with weather metrics)

Actions Taken

  1. Added Dependencies via UV 
    uv add seaborn matplotlib

  2. Installed: seaborn==0.13.2, matplotlib==3.10.6, plus dependencies

  3. Refactored weather_data.py

  4. Removed top-level print statements
  5. Added robust path handling using pathlib

  6. Created helper functions:

    • _get_csv_path() - Locates CSV relative to script
    • _load_weather_df() - Loads CSV into DataFrame

  7. Implemented Two Public Functions

Function 1: summarize_weather_data() -> pd.DataFrame - Loads weather data CSV - Selects numeric columns - Returns Pearson correlation matrix

Function 2: plot_summary_heatmap(corr_df=None, *, save_path=None, show=False) -> Path - Plots seaborn heatmap of correlation matrix - Optional parameters for saving and displaying - Returns path where chart was saved

Second Request

User: Now that we have the repository script written with two public methods, next within this project add uv dependencies for flask. create new script under src, main, folder. This new script is expected to create a simple web application to display the weather data summary table and heatmap from the functions created earlier. Please modularize the new code so that its divided into multiple scripts into appropriate folder structure

Actions Taken

  1. Verified Flask Dependency

  2. Flask already present in pyproject.toml

  3. Created Modular Flask Application Structure

Application Factory (src/main/app.py) - create_app() function - Registers blueprints - Configures Flask app

Service Layer (src/main/services/weather_service.py) - WeatherService class with static methods: - get_summary_table() - Returns correlation DataFrame - get_summary_html() - Returns HTML table with Bootstrap styling - generate_heatmap() - Generates and saves heatmap

Routes (src/main/routes/weather_routes.py) - Blueprint: weather_bp - Routes: - / - Home page - /summary - Correlation table view - /heatmap - Heatmap visualization - /static/<filename> - Static file serving

  1. Created HTML Templates

base.html - Base template with navbar - Bootstrap 5 styling - Gradient background - Responsive design

index.html - Home page with navigation cards - Two tiles: Correlation Matrix and Heatmap

summary.html - Displays correlation matrix as styled HTML table - Info alerts and navigation

heatmap.html - Displays heatmap image - Explanatory content

error.html - Error handling page

  1. Updated main.py
  2. Imports create_app()

  3. Runs Flask development server on port 5000

  4. Created Package Structure

  5. Added __init__.py files to all packages:

    • src/__init__.py
    • src/main/__init__.py
    • src/main/repositories/__init__.py
    • src/main/services/__init__.py
    • src/main/routes/__init__.py

  6. Created Documentation

  7. RUNNING.md - Instructions for running the app

Bug Fix Request

User: Can you check the "plot_summary_heatmap" function for an uncaught exception

Issue Identified

NSInternalInconsistencyException: 'NSWindow should only be instantiated on the main thread!'

Root Cause: Matplotlib was trying to create a GUI window in a Flask worker thread on macOS, which is not allowed.

Solution Applied

  1. Set Non-Interactive Backend 

    import matplotlib
matplotlib.use('Agg')  # Use non-interactive backend

  2. Improved Figure Management

  3. Changed to explicit fig, ax = plt.subplots()
  4. Always close figure with plt.close(fig)

  5. Changed return type from plt.Axes to Path

  6. Enhanced Function

  7. Better title styling
  8. bbox_inches='tight' for better output
  9. Proper memory management

Result: Application now runs without threading exceptions.

Feature Addition Request

User: Now that this application works, add new function that will show the visualization of average weather condition month over month for the year 2012; then use this new public function and add another tile and button to the web application to view the weather condition graph

Actions Taken

  1. Created New Public Function in weather_data.py

plot_monthly_weather_trends(year=2012, *, save_path=None, show=False) -> Path - Parses datetime from CSV - Filters data for specified year (2012) - Calculates monthly averages using groupby() - Creates 2x3 subplot layout (6 panels) - Visualizes: - Temperature (red, filled area) - Humidity (blue, filled area) - Wind Speed (green, filled area) - Pressure (purple, filled area) - Visibility (orange, filled area) - Dew Point Temperature (teal, filled area) - Each chart has: - Different marker styles - Month names on x-axis - Grid lines - Filled areas under curves - Distinct colors

  1. Updated Service Layer
  2. Added import for plot_monthly_weather_trends

  3. Created WeatherService.generate_monthly_trends(output_path, year=2012)

  4. Added New Route

  5. Route: /monthly-trends
  6. Generates chart to static/monthly_trends_2012.png
  7. Renders monthly_trends.html template

  8. Passes year parameter to template

  9. Created New Template (monthly_trends.html)

  10. Info cards showing:
    • Metrics tracked (6 variables)
    • Time period (12 months)
    • Temperature patterns
    • Wind & Pressure trends
  11. Large chart display area
  12. Navigation buttons to other views

  13. Educational section explaining each chart type

  14. Updated Home Page (index.html)

  15. Changed from 2-column to 3-column layout
  16. Added third tile: "Monthly Trends"

  17. Card includes:

    • 📈 emoji icon
    • Description of feature
    • Button linking to /monthly-trends

  18. Updated Navigation Bar (base.html)

  19. Added "Monthly Trends" link to navbar

  20. Active state highlighting for new route

  21. Created Feature Documentation

  22. FEATURES.md - Comprehensive feature list and architecture

Final Request

User: Can you please save all the conversation into a markdown file in the projects root folder. name that file as prompt_interaction.md

Action: Created this file documenting the entire development session.

Final Project Structure

weather_app/
├── main.py                          # Flask application entry point
├── pyproject.toml                   # UV dependencies
├── uv.lock                          # Dependency lock file
├── README.md                        # Original project README
├── RUNNING.md                       # How to run the application
├── FEATURES.md                      # Feature documentation
├── prompt_interaction.md            # This conversation log
└── src/
    └── main/
        ├── app.py                   # Flask app factory
        ├── routes/
        │   ├── __init__.py
        │   └── weather_routes.py    # Route handlers (4 routes)
        ├── services/
        │   ├── __init__.py
        │   └── weather_service.py   # Business logic layer
        ├── repositories/
        │   ├── __init__.py
        │   └── weather_data.py      # Data access (3 public functions)
        ├── templates/               # HTML templates
        │   ├── base.html            # Base template with navbar
        │   ├── index.html           # Home page (3 tiles)
        │   ├── summary.html         # Correlation table
        │   ├── heatmap.html         # Correlation heatmap
        │   ├── monthly_trends.html  # Monthly trends chart
        │   └── error.html           # Error page
        ├── static/                  # Generated charts
        │   ├── correlation_heatmap.png
        │   └── monthly_trends_2012.png
        └── resources/
            └── WeatherData.csv      # Weather dataset (451KB)

Public API Functions

weather_data.py

  1. summarize_weather_data() -> pd.DataFrame

  2. Returns correlation matrix of numeric weather variables

  3. plot_summary_heatmap(corr_df=None, *, save_path=None, show=False) -> Path

  4. Generates correlation heatmap visualization
  5. Uses seaborn with 'coolwarm' colormap

  6. Saves to specified path

  7. plot_monthly_weather_trends(year=2012, *, save_path=None, show=False) -> Path

  8. Generates 6-panel monthly trends visualization
  9. Shows averages for: Temp, Humidity, Wind, Pressure, Visibility, Dew Point
  10. 2x3 subplot layout with filled line charts

Technologies Used

  • Python 3.12+
  • UV - Package manager
  • Flask 3.1.2 - Web framework
  • Pandas 2.3.2 - Data manipulation
  • Matplotlib 3.10.6 - Plotting library
  • Seaborn 0.13.2 - Statistical visualization
  • Bootstrap 5 - Frontend styling

Key Design Decisions

  1. Matplotlib Backend
  2. Used 'Agg' backend for thread-safe operation in Flask

  3. Prevents GUI window creation issues on macOS

  4. Modular Architecture

  5. Separation of concerns: Routes → Services → Repositories
  6. Blueprint pattern for route organization

  7. Service layer for business logic

  8. Path Handling

  9. Used pathlib.Path for cross-platform compatibility

  10. Relative path resolution from script location

  11. Visualization Choices

  12. Correlation matrix: Heatmap with annotations
  13. Monthly trends: Multi-panel layout for comprehensive view

  14. Filled area charts for better visual impact

  15. UI/UX

  16. Gradient background for modern look
  17. Card-based navigation on home page
  18. Consistent navbar across all pages
  19. Responsive Bootstrap layout
  20. Info alerts and educational content

How to Run

# Navigate to project directory
cd /Users/amitrajpurkar/workspace/pyprojects/weather_app

# Ensure dependencies are synced
uv sync

# Run the application
python main.py

# Open browser to
http://127.0.0.1:5000

Available Routes

  1. / - Home page with 3 navigation tiles
  2. /summary - Correlation matrix table view
  3. /heatmap - Correlation heatmap visualization
  4. /monthly-trends - Monthly weather trends for 2012

Development Timeline

  1. ✅ Analyzed existing project structure
  2. ✅ Added pandas/seaborn dependencies
  3. ✅ Implemented correlation analysis functions
  4. ✅ Created modular Flask application
  5. ✅ Built HTML templates with Bootstrap
  6. ✅ Fixed matplotlib threading issue
  7. ✅ Added monthly trends visualization
  8. ✅ Updated UI with new feature
  9. ✅ Created comprehensive documentation

End of Session

Status: All features implemented and working Application: Fully functional weather data analysis web application Documentation: Complete with RUNNING.md, FEATURES.md, and this conversation log