Add app

app.py

@@ -0,0 +1,49 @@
+import osmnx as ox
+import gradio as gr
+import pandas as pd
+import plotly.express as px
+from pub_crawl_script import pub_crawl
+
+df = pd.read_csv('galway_pubs.csv')
+G =  ox.io.load_graphml('galway.graphml')
+
+def galway_map():
+    fig = px.scatter_mapbox(df, lat='latitude', lon='longitude', hover_name='name', 
+                                  # hover_data=f"Address: {str(df['address'])}", 
+                                  color_discrete_sequence=["fuchsia"], 
+                                  zoom=14, height=300, opacity=0.8, size=[1]*len(df), size_max=12)
+    fig.update_layout(mapbox_style='open-street-map',
+                      margin={"r": 0, "t": 0, "l": 0, "b": 0},
+                      mapbox_bounds={"west": -9.0644, "east": -9.0456, "south": 53.2691, "north": 53.2763})
+    return fig
+
+def execute_crawl_optimiser(start_pub, pubs_considered):
+    crawler = pub_crawl(df, G)
+    crawler.optimise(start_pub, pubs_considered)
+    route_str = ''
+    for i in range(len(crawler.optimal_route)-1):
+        route_str += f'{crawler.optimal_route[i]} --> '
+    route_str += crawler.optimal_route[-1]
+    return crawler.optimal_distance, route_str, crawler.plot_route(crawler.optimal_route)
+
+with gr.Blocks() as pub_crawl_ui:
+    with gr.Row():
+        with gr.Column():
+            map = gr.Plot(galway_map, label='Galway Map')
+        with gr.Column():
+            start_pub = gr.Dropdown(df['name'].to_list(), value='Caribou', label="Start Pub")
+            pubs_considered = gr.CheckboxGroup(df['name'].to_list(), label='Pubs to Visit', 
+            info='Please make sure "Start Pub" is selected')
+    with gr.Row():
+        run_btn = gr.Button("Run")
+    with gr.Row():
+        with gr.Column(scale=1):
+            distance = gr.Number(value=None, label="Route Distance (meters)")
+        with gr.Column(scale=3):
+            route = gr.Textbox(label="Route")
+    with gr.Row():
+        route_plot = gr.Plot(label="Route Map", height=1200)
+    
+    run_btn.click(fn=execute_crawl_optimiser, inputs=[start_pub, pubs_considered], outputs=[distance, route, route_plot], api_name="pub_crawl")
+
+pub_crawl_ui.launch()