Connecting to a Database

The data you wish to visualize may be stored in a database. Let's use SQLAlchemy to quickly extract database content into pandas Dataframe format so we can use it in gradio.

First install pip install sqlalchemy and then let's see some examples.

SQLite

from sqlalchemy import create_engine
import pandas as pd

engine = create_engine('sqlite:///your_database.db')

with gr.Blocks() as demo:
    gr.LinePlot(pd.read_sql_query("SELECT time, price from flight_info;", engine), x="time", y="price")

Let's see a a more interactive plot involving filters that modify your SQL query:

from sqlalchemy import create_engine
import pandas as pd

engine = create_engine('sqlite:///your_database.db')

with gr.Blocks() as demo:
    origin = gr.Dropdown(["DFW", "DAL", "HOU"], value="DFW", label="Origin")

    gr.LinePlot(lambda origin: pd.read_sql_query(f"SELECT time, price from flight_info WHERE origin = {origin};", engine), inputs=origin, x="time", y="price")

Postgres, mySQL, and other databases

If you're using a different database format, all you have to do is swap out the engine, e.g.

engine = create_engine('postgresql://username:password@host:port/database_name')

engine = create_engine('mysql://username:password@host:port/database_name')

engine = create_engine('oracle://username:password@host:port/database_name')