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* changes * changes * revert changes * changes * add changeset * notebooks script * changes * changes --------- Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Ali Abdalla <ali.si3luwa@gmail.com>
89 lines
2.3 KiB
Python
89 lines
2.3 KiB
Python
import os
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import gradio as gr
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import pandas as pd
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DB_USER = os.getenv("DB_USER")
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DB_PASSWORD = os.getenv("DB_PASSWORD")
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DB_HOST = os.getenv("DB_HOST")
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PORT = 8080
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DB_NAME = "bikeshare"
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connection_string = (
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f"postgresql://{DB_USER}:{DB_PASSWORD}@{DB_HOST}?port={PORT}&dbname={DB_NAME}"
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)
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def get_count_ride_type():
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df = pd.read_sql(
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"""
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SELECT COUNT(ride_id) as n, rideable_type
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FROM rides
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GROUP BY rideable_type
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ORDER BY n DESC
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""",
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con=connection_string,
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)
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return df
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def get_most_popular_stations():
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df = pd.read_sql(
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"""
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SELECT COUNT(ride_id) as n, MAX(start_station_name) as station
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FROM RIDES
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WHERE start_station_name is NOT NULL
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GROUP BY start_station_id
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ORDER BY n DESC
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LIMIT 5
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""",
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con=connection_string,
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)
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return df
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# Chicago Bike Share Dashboard
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This demo pulls Chicago bike share data for March 2022 from a postgresql database hosted on AWS.
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This demo uses psycopg2 but any postgresql client library (SQLAlchemy)
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is compatible with gradio.
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Connection credentials are handled by environment variables
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defined as secrets in the Space.
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If data were added to the database, the plots in this demo would update
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whenever the webpage is reloaded.
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This demo serves as a starting point for your database-connected apps!
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"""
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)
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with gr.Row():
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bike_type = gr.BarPlot(
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x="rideable_type",
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y='n',
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title="Number of rides per bicycle type",
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y_title="Number of Rides",
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x_title="Bicycle Type",
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vertical=False,
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tooltip=['rideable_type', "n"],
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height=300,
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width=300,
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)
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station = gr.BarPlot(
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x='station',
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y='n',
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title="Most Popular Stations",
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y_title="Number of Rides",
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x_title="Station Name",
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vertical=False,
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tooltip=['station', 'n'],
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height=300,
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width=300
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)
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demo.load(get_count_ride_type, inputs=None, outputs=bike_type)
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demo.load(get_most_popular_stations, inputs=None, outputs=station)
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if __name__ == "__main__":
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demo.launch()
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