app.py

import streamlit as st
import pandas as pd
import numpy as np
import yfinance as yf
import altair as alt
import plotly.figure_factory as ff
import pydeck as pdk
from vega_datasets import data as vds
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from streamlit_image_comparison import image_comparison


def on_input_change():
    user_input = st.session_state.user_input
    st.session_state.past.append(user_input)
    st.session_state.generated.append(
        {"data": "The messages from Bot\nWith new line", "type": "normal"}
    )


def on_btn_click():
    del st.session_state.past[:]
    del st.session_state.generated[:]


def main():
    st.write("Hello, world!")
    st.header(" Al Generated this app - spotify recommendations")
    st.subheader(" this application contains the auto generated layout")
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        st.write("Hello, world!")
    with col2:
        option = st.selectbox(
            " gender / male / female", [" gender ", " male ", " female"]
        )
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        value = st.slider(
            " max predictions", min_value=0, max_value=100, value=50, key=39
        )
    with col2:
        value = st.slider(
            " num categories", min_value=0, max_value=100, value=50, key=81
        )
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        option = st.radio("Choose an option:", ["Option 1", "Option 2", "Option 3"])
    with col2:
        if st.checkbox("Check me"):
            st.write("Checkbox checked!")
    if st.button(" generate recommendations"):
        st.write("Button clicked!")
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        st.table(
            {
                "Country": ["USA", "Canada", "UK", "Australia"],
                "Population (millions)": [331, 38, 66, 25],
                "GDP (trillion USD)": [22.675, 1.843, 2.855, 1.488],
            }
        )
    with col2:
        st.line_chart(
            pd.DataFrame(
                {
                    "Apple": yf.download("AAPL", start="2023-01-01", end="2023-07-31")[
                        "Adj Close"
                    ],
                    "Google": yf.download(
                        "GOOGL", start="2023-01-01", end="2023-07-31"
                    )["Adj Close"],
                    "Microsoft": yf.download(
                        "MSFT", start="2023-01-01", end="2023-07-31"
                    )["Adj Close"],
                }
            )
        )
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        data = pd.DataFrame(
            {"X": [1, 2, 3, 4, 5], "Y1": [10, 16, 8, 14, 12], "Y2": [5, 8, 3, 6, 7]}
        )
        st.area_chart(data)
    with col2:
        st.bar_chart(
            pd.DataFrame(np.random.randn(20, 3), columns=["Apple", "Banana", "Cherry"])
        )
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        st.write("Hello, world!")
    with col2:
        df = px.data.gapminder().query("year == 2007").query("continent == 'Americas'")
        fig = px.pie(
            df,
            values="pop",
            names="country",
            title="Population of American continent",
            hover_data=["lifeExp"],
            labels={"lifeExp": "life expectancy"},
        )
        fig.update_traces(textposition="inside", textinfo="percent+label")
        st.plotly_chart(fig)
    source = vds.cars()
    chart = {
        "mark": "point",
        "encoding": {
            "x": {"field": "Horsepower", "type": "quantitative"},
            "y": {"field": "Miles_per_Gallon", "type": "quantitative"},
            "color": {"field": "Origin", "type": "nominal"},
            "shape": {"field": "Origin", "type": "nominal"},
        },
    }
    tab1, tab2 = st.tabs(["Streamlit theme (default)", "Vega-Lite native theme"])
    with tab1:
        st.vega_lite_chart(source, chart, theme="streamlit", use_container_width=True)
    with tab2:
        st.vega_lite_chart(source, chart, theme=None, use_container_width=True)
    (
        col1,
        col2,
    ) = st.columns(2)
    with col1:
        st.video("https://www.youtube.com/watch?v=50hVvC7gMR8&t=5s", format="video/mp4")
    with col2:
        st.image(
            "https://assets-global.website-files.com/59e16042ec229e00016d3a66/6441d5f76d21e1e4dee9ffa2_Gen%20AI%20blog_Blog%20hero.png",
            caption="Image Caption",
        )
    st.plotly_chart(
        ff.create_distplot(
            [np.random.randn(200) - 2, np.random.randn(200), np.random.randn(200) + 2],
            ["Negative Shift", "Normal", "Positive Shift"],
            bin_size=[0.1, 0.25, 0.5],
        ),
        use_container_width=True,
    )
    st.header(" auto generated by sketch2streamiit")


if __name__ == "__main__":
    main()