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import gradio as gr
import pandas as pd
import folium
from folium.plugins import MeasureControl, Fullscreen, Search
from geopy.geocoders import Nominatim
import tempfile
import warnings
import os
import time
import random
from datetime import datetime
warnings.filterwarnings("ignore")
# Updated Historical Tile Providers with reliable sources
HISTORICAL_TILES = {
"Historical 1700s-1800s": {
"url": "https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}",
"attr": "Esri",
"fallback": "https://server.arcgisonline.com/ArcGIS/rest/services/World_Topo_Map/MapServer/tile/{z}/{y}/{x}",
"years": (1700, 1900)
},
"Early 1900s": {
"url": "https://server.arcgisonline.com/ArcGIS/rest/services/World_Topo_Map/MapServer/tile/{z}/{y}/{x}",
"attr": "Esri",
"fallback": "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
"years": (1901, 1920)
},
"Modern Era": {
"url": "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
"attr": "OpenStreetMap",
"fallback": None,
"years": (1921, 2023)
},
# Additional reliable tile sources
"Terrain": {
"url": "https://server.arcgisonline.com/ArcGIS/rest/services/World_Terrain_Base/MapServer/tile/{z}/{y}/{x}",
"attr": "Esri",
"fallback": None,
"years": (1700, 2023)
},
"Toner": {
"url": "https://tiles.stadiamaps.com/tiles/stamen_toner/{z}/{x}/{y}.png", # Updated Stamen source
"attr": "Stadia Maps",
"fallback": None,
"years": (1700, 2023)
}
}
class SafeGeocoder:
def __init__(self):
user_agent = f"historical_mapper_v7_{random.randint(1000, 9999)}"
self.geolocator = Nominatim(user_agent=user_agent, timeout=10)
self.cache = {} # Simple cache to avoid repeated requests
self.last_request = 0
def _respect_rate_limit(self):
# Ensure at least 1 second between requests
current_time = time.time()
elapsed = current_time - self.last_request
if elapsed < 1.0:
time.sleep(1.0 - elapsed)
self.last_request = time.time()
def get_coords(self, location: str):
if not location or pd.isna(location):
return None
# Convert to string if needed
location = str(location).strip()
# Check cache first
if location in self.cache:
return self.cache[location]
try:
self._respect_rate_limit()
result = self.geolocator.geocode(location)
if result:
coords = (result.latitude, result.longitude)
self.cache[location] = coords
return coords
self.cache[location] = None
return None
except Exception as e:
print(f"Geocoding error for '{location}': {e}")
self.cache[location] = None
return None
def create_reliable_map(df, location_col, year):
"""Create a map with multiple layer options and better error handling"""
# Select appropriate default tile configuration based on year
default_tile_name = next(
(name for name, t in HISTORICAL_TILES.items()
if t["years"][0] <= year <= t["years"][1] and name in ["Historical 1700s-1800s", "Early 1900s", "Modern Era"]),
"Modern Era"
)
# Initialize map
m = folium.Map(location=[20, 0], zoom_start=2, control_scale=True)
# Add all tile layers with the appropriate one active
for name, config in HISTORICAL_TILES.items():
folium.TileLayer(
tiles=config["url"],
attr=f"{config['attr']} ({name})",
name=name,
overlay=False,
control=True,
show=(name == default_tile_name) # Only show the default layer initially
).add_to(m)
# Add plugins for better user experience
Fullscreen().add_to(m)
MeasureControl(position='topright', primary_length_unit='kilometers').add_to(m)
# Add markers
geocoder = SafeGeocoder()
coords = []
# Create marker cluster for better performance with many points
marker_cluster = folium.MarkerCluster(name="Locations").add_to(m)
# Process each location
processed_count = 0
for idx, row in df.iterrows():
if pd.isna(row[location_col]):
continue
location = str(row[location_col]).strip()
# Get additional info if available
additional_info = ""
for col in df.columns:
if col != location_col and not pd.isna(row[col]):
additional_info += f"<br><b>{col}:</b> {row[col]}"
# Geocode location
point = geocoder.get_coords(location)
if point:
# Create popup content
popup_content = f"""
<div style="min-width: 200px; max-width: 300px">
<h4>{location}</h4>
<p><i>Historical View ({year})</i></p>
{additional_info}
</div>
"""
# Add marker
folium.Marker(
location=point,
popup=folium.Popup(popup_content, max_width=300),
tooltip=location,
icon=folium.Icon(color="blue", icon="info-sign")
).add_to(marker_cluster)
coords.append(point)
processed_count += 1
# Layer control
folium.LayerControl(collapsed=False).add_to(m)
# Set bounds if we have coordinates
if coords:
m.fit_bounds(coords)
# Add better tile error handling with JavaScript
m.get_root().html.add_child(folium.Element("""
<script>
// Wait for the map to be fully loaded
document.addEventListener('DOMContentLoaded', function() {
setTimeout(function() {
// Get the map instance
var maps = document.querySelectorAll('.leaflet-container');
if (maps.length > 0) {
var map = maps[0];
// Add error handler for tiles
var layers = map.querySelectorAll('.leaflet-tile-pane .leaflet-layer');
for (var i = 0; i < layers.length; i++) {
var layer = layers[i];
var tiles = layer.querySelectorAll('.leaflet-tile');
// Check if layer has no loaded tiles
var loadedTiles = layer.querySelectorAll('.leaflet-tile-loaded');
if (tiles.length > 0 && loadedTiles.length === 0) {
// Force switch to OpenStreetMap if current layer failed
var osmButton = document.querySelector('.leaflet-control-layers-list input[type="radio"]:nth-child(3)');
if (osmButton) {
osmButton.click();
}
console.log("Switched to fallback tile layer due to loading issues");
}
}
}
}, 3000); // Wait 3 seconds for tiles to load
});
</script>
"""))
return m._repr_html_(), processed_count
def process_data(file_obj, location_col, year):
try:
# Handle file reading
try:
df = pd.read_excel(file_obj.name)
except Exception as e:
return None, f"Error reading Excel file: {str(e)}", None
# Validate columns
if location_col not in df.columns:
return None, f"Column '{location_col}' not found. Available columns: {', '.join(df.columns)}", None
# Create map
map_html, processed_count = create_reliable_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
total_locations = df[location_col].count()
success_rate = (processed_count / total_locations * 100) if total_locations > 0 else 0
stats = f"Found {processed_count} of {total_locations} locations ({success_rate:.1f}%) from year {year}"
return (
f"<div style='width:100%; height:70vh; border:1px solid #ddd'>{map_html}</div>",
stats,
processed_path
)
except Exception as e:
import traceback
error_details = traceback.format_exc()
print(f"Error in processing: {error_details}")
return None, f"Error: {str(e)}", None
# Gradio Interface
with gr.Blocks(title="Historical Maps", theme=gr.themes.Soft()) as app:
gr.Markdown("# Historical Map Viewer")
gr.Markdown("Upload an Excel file with location data to visualize on historical maps.")
with gr.Row():
with gr.Column():
file_input = gr.File(
label="1. Upload Excel File",
file_types=[".xlsx", ".xls"],
type="filepath"
)
location_col = gr.Textbox(
label="2. Location Column Name",
value="location",
placeholder="e.g., 'city', 'address', or 'place'"
)
year = gr.Slider(
label="3. Historical Period (Year)",
minimum=1700,
maximum=2023,
value=1865,
step=1
)
btn = gr.Button("Generate Map", variant="primary")
gr.Markdown("""
### Tips:
- For best results, make sure location names are clear (e.g., "Paris, France" instead of just "Paris")
- If the map appears gray, try switching the tile layer using the layer control in the top-right
- You can measure distances and view the map in fullscreen using the controls
""")
with gr.Column():
map_display = gr.HTML(
label="Historical Map",
value="<div style='text-align:center;padding:2em;color:gray;border:1px solid #ddd;height:70vh'>"
"Map will appear here after generation</div>"
)
stats = gr.Textbox(label="Map Information")
download = gr.File(label="Download Processed Data")
btn.click(
process_data,
inputs=[file_input, location_col, year],
outputs=[map_display, stats, download]
)
if __name__ == "__main__":
app.launch() |