data.py

import gradio as gr
import pandas as pd
import folium
from geopy.geocoders import Nominatim
from geopy.extra.rate_limiter import RateLimiter
import tempfile
from typing import Optional, Tuple
import warnings

# Suppress warnings
warnings.filterwarnings("ignore")

# Historical Tile Providers
HISTORICAL_TILES = {
    "David Rumsey (1790)": {
        "url": "https://map1.davidrumsey.com/tiles/rumsey/SDSC1790/{z}/{x}/{y}.png",
        "attr": "David Rumsey Map Collection",
        "min_year": 1700,
        "max_year": 1800
    },
    "David Rumsey (1860)": {
        "url": "https://map1.davidrumsey.com/tiles/rumsey/SDSC1860/{z}/{x}/{y}.png",
        "attr": "David Rumsey Map Collection", 
        "min_year": 1801,
        "max_year": 1900
    },
    "Stamen (1915)": {
        "url": "https://stamen-tiles.a.ssl.fastly.net/toner-lite/{z}/{x}/{y}.png",
        "attr": "Stamen Maps",
        "min_year": 1901,
        "max_year": 1920
    },
    "OpenHistoricalMap": {
        "url": "https://tile.openhistoricalmap.org/{z}/{x}/{y}.png",
        "attr": "OpenHistoricalMap",
        "min_year": 1700,
        "max_year": 2023
    }
}

class Geocoder:
    def __init__(self):
        self.geolocator = Nominatim(user_agent="historical_mapper", timeout=10)
        self.geocode = RateLimiter(self.geolocator.geocode, min_delay_seconds=1)
        self.cache = {}
    
    def get_coords(self, location: str) -> Optional[Tuple[float, float]]:
        if not location or pd.isna(location):
            return None
        if location in self.cache:
            return self.cache[location]
        
        try:
            result = self.geocode(location)
            if result:
                coords = (result.latitude, result.longitude)
                self.cache[location] = coords
                return coords
        except Exception as e:
            print(f"Geocoding failed for '{location}': {str(e)}")
        
        self.cache[location] = None
        return None

def get_tile_layer(year: int):
    """Select the most appropriate tile layer for the given year"""
    for name, config in HISTORICAL_TILES.items():
        if config["min_year"] <= year <= config["max_year"]:
            return folium.TileLayer(
                tiles=config["url"],
                attr=config["attr"],
                name=name,
                overlay=False
            )
    return folium.TileLayer("OpenStreetMap")

def create_historical_map(df: pd.DataFrame, location_col: str, year: int = 1900) -> str:
    geocoder = Geocoder()
    
    # Create map with historical base layer
    base_layer = get_tile_layer(year)
    m = folium.Map(location=[40, -10], zoom_start=2, control_scale=True)
    base_layer.add_to(m)
    
    # Add all other historical layers as options
    for name, config in HISTORICAL_TILES.items():
        if config["url"] != base_layer.tiles:
            folium.TileLayer(
                tiles=config["url"],
                attr=config["attr"],
                name=f"{name} ({config['min_year']}-{config['max_year']})",
                overlay=False
            ).add_to(m)
    
    # Add markers with historical styling
    coords_list = []
    for loc in df[location_col].dropna().unique():
        coords = geocoder.get_coords(str(loc))
        if coords:
            folium.Marker(
                location=coords,
                popup=f"<b>{loc}</b><br>Year: {year}",
                icon=folium.Icon(
                    color="red",
                    icon="info-sign",
                    prefix="fa"
                )
            ).add_to(m)
            coords_list.append(coords)
    
    # Add layer control and fit bounds
    folium.LayerControl().add_to(m)
    if coords_list:
        m.fit_bounds(coords_list)
    
    return m._repr_html_()

def process_file(file_obj, location_col, year):
    try:
        # Read input file
        df = pd.read_excel(file_obj.name)
        
        # Validate column exists
        if location_col not in df.columns:
            return None, f"Column '{location_col}' not found", None
        
        # Create historical map
        map_html = create_historical_map(df, location_col, year)
        
        # Save processed data
        with tempfile.NamedTemporaryFile(suffix=".xlsx", delete=False) as tmp:
            df.to_excel(tmp.name, index=False)
            processed_path = tmp.name
        
        # Generate stats
        stats = (
            f"Total locations: {len(df)}\n"
            f"Unique places: {df[location_col].nunique()}\n"
            f"Map year: {year}"
        )
        
        return (
            f"<div style='width:100%; height:70vh'>{map_html}</div>",
            stats,
            processed_path
        )
    
    except Exception as e:
        return None, f"Error: {str(e)}", None

# Gradio Interface
with gr.Blocks(title="Historical Map Explorer", theme=gr.themes.Soft()) as app:
    gr.Markdown("# Historical Location Mapper")
    
    with gr.Row():
        with gr.Column():
            file_input = gr.File(
                label="Upload Excel File",
                file_types=[".xlsx", ".xls"],
                type="filepath"
            )
            location_col = gr.Textbox(
                label="Location Column Name",
                value="locations",
                placeholder="Enter exact column name with locations"
            )
            year = gr.Slider(
                minimum=1700,
                maximum=2023,
                value=1900,
                step=1,
                label="Map Year"
            )
            map_btn = gr.Button("Generate Historical Map", variant="primary")
        
        with gr.Column():
            map_display = gr.HTML(
                label="Historical Map",
                value="<div style='text-align:center;padding:20px;'>"
                      "Map will appear here after processing</div>"
            )
            stats_output = gr.Textbox(label="Statistics")
            download_output = gr.File(label="Download Processed Data")

    map_btn.click(
        process_file,
        inputs=[file_input, location_col, year],
        outputs=[map_display, stats_output, download_output]
    )

if __name__ == "__main__":
    app.launch()