import os import gradio as gr import matplotlib import matplotlib.pyplot as plt import pandas as pd matplotlib.use("Agg") DB_USER = os.getenv("DB_USER") DB_PASSWORD = os.getenv("DB_PASSWORD") DB_HOST = os.getenv("DB_HOST") PORT = 8080 DB_NAME = "bikeshare" connection_string = f"postgresql://{DB_USER}:{DB_PASSWORD}@{DB_HOST}?port={PORT}&dbname={DB_NAME}" def get_count_ride_type(): df = pd.read_sql( """ SELECT COUNT(ride_id) as n, rideable_type FROM rides GROUP BY rideable_type ORDER BY n DESC """, con=connection_string ) fig_m, ax = plt.subplots() ax.bar(x=df['rideable_type'], height=df['n']) ax.set_title("Number of rides by bycycle type") ax.set_ylabel("Number of Rides") ax.set_xlabel("Bicycle Type") return fig_m def get_most_popular_stations(): df = pd.read_sql( """ SELECT COUNT(ride_id) as n, MAX(start_station_name) as station FROM RIDES WHERE start_station_name is NOT NULL GROUP BY start_station_id ORDER BY n DESC LIMIT 5 """, con=connection_string ) fig_m, ax = plt.subplots() ax.bar(x=df['station'], height=df['n']) ax.set_title("Most popular stations") ax.set_ylabel("Number of Rides") ax.set_xlabel("Station Name") ax.set_xticklabels( df['station'], rotation=45, ha="right", rotation_mode="anchor" ) ax.tick_params(axis="x", labelsize=8) fig_m.tight_layout() return fig_m with gr.Blocks() as demo: gr.Markdown( """ # Chicago Bike Share Dashboard This demo pulls Chicago bike share data for March 2022 from a postgresql database hosted on AWS. This demo uses psycopg2 but any postgresql client library (SQLAlchemy) is compatible with gradio. Connection credentials are handled by environment variables defined as secrets in the Space. If data were added to the database, the plots in this demo would update whenever the webpage is reloaded. This demo serves as a starting point for your database-connected apps! """ ) with gr.Row(): bike_type = gr.Plot() station = gr.Plot() demo.load(get_count_ride_type, inputs=None, outputs=bike_type) demo.load(get_most_popular_stations, inputs=None, outputs=station) demo.launch()