API参考

由 neevop 十二月 3, 2023

1. 文本

1.1 st.markdown

# st.markdown(body, unsafe_allow_html=False, *, help=None)

import streamlit as st

st.markdown('''
    :red[Streamlit] :orange[can] :green[write] :blue[text] :violet[in]
    :gray[pretty] :rainbow[colors].''')

st.markdown("Here's a bouquet —\
            :tulip::cherry_blossom::rose::hibiscus::sunflower::blossom:")

multi = '''If you end a line with two spaces,
a soft return is used for the next line.

Two (or more) newline characters in a row will result in a hard return.
'''
st.markdown(multi)

md = st.text_area('Type in your markdown string (without outer quotes)',
                  "Happy Streamlit-ing! :balloon:")

st.code(f"""
import streamlit as st

st.markdown('''{md}''')
""")

st.markdown(md)

1.2 st.title

# st.title(body, anchor=None, *, help=None)

1.3 st.header

# st.header(body, anchor=None, *, help=None, divider=False)

import streamlit as st

st.header('This is a header with a divider', divider='rainbow')

1.4 st.subheader

# st.subheader(body, anchor=None, *, help=None, divider=False)

import streamlit as st

st.subheader('This is a subheader with a divider', divider='rainbow')

1.5 st.caption

应用于标题、旁白、脚注、旁注和其他解释性文本。

# st.caption(body, unsafe_allow_html=False, *, help=None)

import streamlit as st

st.caption('This is a string that explains something above.')
st.caption('A caption with _italics_ :blue[colors] and emojis :sunglasses:')

1.6 st.code

# st.code(body, language="python", line_numbers=False)

import streamlit as st

code = '''def hello():
    print("Hello, Streamlit!")'''
st.code(code, language='python')

1.7 st.text

# st.text(body, *, help=None)

import streamlit as st

st.text('This is some text.')

1.8 st.latex

# st.latex(body, *, help=None)

import streamlit as st

st.latex(r'''
    a + ar + a r^2 + a r^3 + \cdots + a r^{n-1} =
    \sum_{k=0}^{n-1} ar^k =
    a \left(\frac{1-r^{n}}{1-r}\right)
    ''')

1.9 st.devider

# same effect with st.write("---") or even just "---" in your script (via magic).

import streamlit as st

st.divider()

2. 数据

2.1 st.dataframe

# st.dataframe(data=None, width=None, height=None, *, use_container_width=False, hide_index=None, column_order=None, column_config=None)

import streamlit as st
import pandas as pd
import numpy as np
import random

df = pd.DataFrame(np.random.randn(50, 20), columns=("col %d" % i for i in range(20)))
st.dataframe(df)  # Same as st.write(df)

# column_config, hide_index, column_order
df = pd.DataFrame(
    {
        "name": ["Roadmap", "Extras", "Issues"],
        "url": ["https://roadmap.streamlit.app", "https://extras.streamlit.app", "https://issues.streamlit.app"],
        "stars": [random.randint(0, 1000) for _ in range(3)],
        "views_history": [[random.randint(0, 5000) for _ in range(30)] for _ in range(3)],
    }
)
st.dataframe(
    df,
    column_config={
        "name": "App name",
        "stars": st.column_config.NumberColumn(
            "Github Stars",
            help="Number of stars on GitHub",
            format="%d ⭐",
        ),
        "url": st.column_config.LinkColumn("App URL"),
        "views_history": st.column_config.LineChartColumn(
            "Views (past 30 days)", y_min=0, y_max=5000
        ),
    },
    hide_index=True,
)

# use_container_width
@st.cache_data
def load_data():
    return pd.DataFrame(
        {
            "first column": [1, 2, 3, 4],
            "second column": [10, 20, 30, 40],
        }
    )

# Boolean to resize the dataframe, stored as a session state variable
st.checkbox("Use container width", value=False, key="use_container_width")

df = load_data()

# Display the dataframe and allow the user to stretch the dataframe
# across the full width of the container, based on the checkbox value
st.dataframe(df, use_container_width=st.session_state.use_container_width)

2.2 st.data_editor

# st.data_editor(data, *, width=None, height=None, use_container_width=False, hide_index=None, column_order=None, column_config=None, num_rows="fixed", disabled=False, key=None, on_change=None, args=None, kwargs=None)

import streamlit as st
import pandas as pd

df = pd.DataFrame(
    [
       {"command": "st.selectbox", "rating": 4, "is_widget": True},
       {"command": "st.balloons", "rating": 5, "is_widget": False},
       {"command": "st.time_input", "rating": 3, "is_widget": True},
   ]
)

## num_rows
edited_df = st.data_editor(df, num_rows="dynamic")

favorite_command = edited_df.loc[edited_df["rating"].idxmax()]["command"]
st.markdown(f"Your favorite command is **{favorite_command}** 🎈")

## column_config, hide_index, column_order, disabled
edited_df = st.data_editor(
    df,
    column_config={
        "command": "Streamlit Command",
        "rating": st.column_config.NumberColumn(
            "Your rating",
            help="How much do you like this command (1-5)?",
            min_value=1,
            max_value=5,
            step=1,
            format="%d ⭐",
        ),
        "is_widget": "Widget ?",
    },
    disabled=["command", "is_widget"],
    hide_index=True,
)

favorite_command = edited_df.loc[edited_df["rating"].idxmax()]["command"]
st.markdown(f"Your favorite command is **{favorite_command}** 🎈")

2.3 st.column_config

根据各种数据类型定制您的列 - 从简单的文本和数字到列表、URL、图像等。st.dataframe st.data_editor


import pandas as pd
import streamlit as st
from datetime import datetime, date, time

data_df = pd.DataFrame(
    {
        "widgets": ["st.selectbox", "st.number_input", "st.text_area", "st.button"],
    }
)

# st.column_config.Column(label=None, *, width=None, help=None, disabled=None, required=None)
st.data_editor(
    data_df,
    column_config={
        "widgets": st.column_config.Column(
            "Streamlit Widgets",
            help="Streamlit **widget** commands 🎈",
            width="medium",
            required=True,
        )
    },
    hide_index=True,
    num_rows="dynamic",
)

# st.column_config.TextColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, max_chars=None, validate=None)
st.data_editor(
    data_df,
    column_config={
        "widgets": st.column_config.TextColumn(
            "Widgets",
            help="Streamlit **widget** commands 🎈",
            default="st.",
            max_chars=50,
            validate="^st\.[a-z_]+$",
        )
    },
    hide_index=True,
)

# st.column_config.NumberColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, format=None, min_value=None, max_value=None, step=None)
data_df = pd.DataFrame(
    {
        "price": [20, 950, 250, 500],
    }
)

st.data_editor(
    data_df,
    column_config={
        "price": st.column_config.NumberColumn(
            "Price (in USD)",
            help="The price of the product in USD",
            min_value=0,
            max_value=1000,
            step=1,
            format="$%d",
        )
    },
    hide_index=True,
)

# st.column_config.CheckboxColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None)
data_df = pd.DataFrame(
    {
        "widgets": ["st.selectbox", "st.number_input", "st.text_area", "st.button"],
        "favorite": [True, False, False, True],
    }
)

st.data_editor(
    data_df,
    column_config={
        "favorite": st.column_config.CheckboxColumn(
            "Your favorite?",
            help="Select your **favorite** widgets",
            default=False,
        )
    },
    disabled=["widgets"],
    hide_index=True,
)

# st.column_config.SelectboxColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, options=None)
data_df = pd.DataFrame(
    {
        "category": [
            "📊 Data Exploration",
            "📈 Data Visualization",
            "🤖 LLM",
            "📊 Data Exploration",
        ],
    }
)

st.data_editor(
    data_df,
    column_config={
        "category": st.column_config.SelectboxColumn(
            "App Category",
            help="The category of the app",
            width="medium",
            options=[
                "📊 Data Exploration",
                "📈 Data Visualization",
                "🤖 LLM",
            ],
            required=True,
        )
    },
    hide_index=True,
)

# st.column_config.DatetimeColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, format=None, min_value=None, max_value=None, step=None, timezone=None)
data_df = pd.DataFrame(
    {
        "appointment": [
            datetime(2024, 2, 5, 12, 30),
            datetime(2023, 11, 10, 18, 0),
            datetime(2024, 3, 11, 20, 10),
            datetime(2023, 9, 12, 3, 0),
        ]
    }
)

st.data_editor(
    data_df,
    column_config={
        "appointment": st.column_config.DatetimeColumn(
            "Appointment",
            min_value=datetime(2023, 6, 1),
            max_value=datetime(2025, 1, 1),
            format="D MMM YYYY, h:mm a",
            step=60,
        ),
    },
    hide_index=True,
)

# st.column_config.DateColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, format=None, min_value=None, max_value=None, step=None)
data_df = pd.DataFrame(
    {
        "birthday": [
            date(1980, 1, 1),
            date(1990, 5, 3),
            date(1974, 5, 19),
            date(2001, 8, 17),
        ]
    }
)

st.data_editor(
    data_df,
    column_config={
        "birthday": st.column_config.DateColumn(
            "Birthday",
            min_value=date(1900, 1, 1),
            max_value=date(2005, 1, 1),
            format="DD.MM.YYYY",
            step=1,
        ),
    },
    hide_index=True,
)

# st.column_config.TimeColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, format=None, min_value=None, max_value=None, step=None)
data_df = pd.DataFrame(
    {
        "appointment": [
            time(12, 30),
            time(18, 0),
            time(9, 10),
            time(16, 25),
        ]
    }
)

st.data_editor(
    data_df,
    column_config={
        "appointment": st.column_config.TimeColumn(
            "Appointment",
            min_value=time(8, 0, 0),
            max_value=time(19, 0, 0),
            format="hh:mm a",
            step=60,
        ),
    },
    hide_index=True,
)

# st.column_config.ListColumn(label=None, *, width=None, help=None)
data_df = pd.DataFrame(
    {
        "sales": [
            [0, 4, 26, 80, 100, 40],
            [80, 20, 80, 35, 40, 100],
            [10, 20, 80, 80, 70, 0],
            [10, 100, 20, 100, 30, 100],
        ],
    }
)

# ! List columns are not editable at the moment
st.data_editor(
    data_df,
    column_config={
        "sales": st.column_config.ListColumn(
            "Sales (last 6 months)",
            help="The sales volume in the last 6 months",
            width="medium",
        ),
    },
    hide_index=True,
)

# st.column_config.LinkColumn(label=None, *, width=None, help=None, disabled=None, required=None, default=None, max_chars=None, validate=None)
data_df = pd.DataFrame(
    {
        "apps": [
            "https://roadmap.streamlit.app",
            "https://extras.streamlit.app",
            "https://issues.streamlit.app",
            "https://30days.streamlit.app",
        ],
    }
)

st.data_editor(
    data_df,
    column_config={
        "apps": st.column_config.LinkColumn(
            "Trending apps",
            help="The top trending Streamlit apps",
            validate="^https://[a-z]+\.streamlit\.app$",
            max_chars=100,
        )
    },
    hide_index=True,
)

# st.column_config.ImageColumn(label=None, *, width=None, help=None)
data_df = pd.DataFrame(
    {
        "apps": [
            "https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/5435b8cb-6c6c-490b-9608-799b543655d3/Home_Page.png",
            "https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/ef9a7627-13f2-47e5-8f65-3f69bb38a5c2/Home_Page.png",
            "https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/31b99099-8eae-4ff8-aa89-042895ed3843/Home_Page.png",
            "https://storage.googleapis.com/s4a-prod-share-preview/default/st_app_screenshot_image/6a399b09-241e-4ae7-a31f-7640dc1d181e/Home_Page.png",
        ],
    }
)

st.data_editor(
    data_df,
    column_config={
        "apps": st.column_config.ImageColumn(
            "Preview Image", help="Streamlit app preview screenshots"
        )
    },
    hide_index=True,
)

# st.column_config.LineChartColumn(label=None, *, width=None, help=None, y_min=None, y_max=None)
data_df = pd.DataFrame(
    {
        "sales": [
            [0, 4, 26, 80, 100, 40],
            [80, 20, 80, 35, 40, 100],
            [10, 20, 80, 80, 70, 0],
            [10, 100, 20, 100, 30, 100],
        ],
    }
)

st.data_editor(
    data_df,
    column_config={
        "sales": st.column_config.LineChartColumn(
            "Sales (last 6 months)",
            width="medium",
            help="The sales volume in the last 6 months",
            y_min=0,
            y_max=100,
         ),
    },
    hide_index=True,
)

# st.column_config.BarChartColumn(label=None, *, width=None, help=None, y_min=None, y_max=None)
st.data_editor(
    data_df,
    column_config={
        "sales": st.column_config.BarChartColumn(
            "Sales (last 6 months)",
            help="The sales volume in the last 6 months",
            y_min=0,
            y_max=100,
        ),
    },
    hide_index=True,
)

# st.column_config.ProgressColumn(label=None, *, width=None, help=None, format=None, min_value=None, max_value=None)
data_df = pd.DataFrame(
    {
        "sales": [200, 550, 1000, 80],
    }
)

st.data_editor(
    data_df,
    column_config={
        "sales": st.column_config.ProgressColumn(
            "Sales volume",
            help="The sales volume in USD",
            format="$%f",
            min_value=0,
            max_value=1000,
        ),
    },
    hide_index=True,
)

2.4 st.table

与st.dataframe 的不同之处在于，本例中的表是静态的：其全部内容直接布置在页面上。

st.table(data=None)

3. 图表

最基本的库是Matplotlib。还有交互式图表库，如Vega Lite（2D 图表）和 Deck.gl（地图和 3D 图表）。还提供了一些 Streamlit“原生”的图表类型，例如st.line_chart和st.area_chart。

4. 输入小组件

4.1 st.button

# st.button(label, key=None, help=None, on_click=None, args=None, kwargs=None, *, type="secondary", disabled=False, use_container_width=False)
import streamlit as st

st.button("Reset", type="primary")
if st.button('Say hello'):
    st.write('Why hello there')
else:
    st.write('Goodbye')

4.2 st.download_button

# st.download_button(label, data, file_name=None, mime=None, key=None, help=None, on_click=None, args=None, kwargs=None, *, type="secondary", disabled=False, use_container_width=False)
import streamlit as st
import pandas as pd

@st.cache_data
def convert_df(df):
    # IMPORTANT: Cache the conversion to prevent computation on every rerun
    return df.to_csv().encode('utf-8')

df = pd.DataFrame(
    [
       {"command": "st.selectbox", "rating": 4, "is_widget": True},
       {"command": "st.balloons", "rating": 5, "is_widget": False},
       {"command": "st.time_input", "rating": 3, "is_widget": True},
   ]
)
  
csv = convert_df(df)
st.download_button(
    label="Download data as CSV",
    data=csv,
    file_name='large_df.csv',
    mime='text/csv',
)

text_contents = '''This is some text'''
st.download_button('Download some text', text_contents)

binary_contents = b'example content'
# Defaults to 'application/octet-stream'
st.download_button('Download binary file', binary_contents)

with open("flower.png", "rb") as file:
    btn = st.download_button(
            label="Download image",
            data=file,
            file_name="flower.png",
            mime="image/png"
          )# st.download_button(label, data, file_name=None, mime=None, key=None, help=None, on_click=None, args=None, kwargs=None, *, type="secondary", disabled=False, use_container_width=False)
import streamlit as st

@st.cache_data
def convert_df(df):
    # IMPORTANT: Cache the conversion to prevent computation on every rerun
    return df.to_csv().encode('utf-8')

df = pd.DataFrame(
    [
       {"command": "st.selectbox", "rating": 4, "is_widget": True},
       {"command": "st.balloons", "rating": 5, "is_widget": False},
       {"command": "st.time_input", "rating": 3, "is_widget": True},
   ]
)
  
csv = convert_df(df)
st.download_button(
    label="Download data as CSV",
    data=csv,
    file_name='large_df.csv',
    mime='text/csv',
)

text_contents = '''This is some text'''
st.download_button('Download some text', text_contents)

binary_contents = b'example content'
# Defaults to 'application/octet-stream'
st.download_button('Download binary file', binary_contents)

with open("flower.png", "rb") as file:
    btn = st.download_button(
            label="Download image",
            data=file,
            file_name="flower.png",
            mime="image/png"
          )

# st.link_button(label, url, *, help=None, type="secondary", disabled=False, use_container_width=False)
import streamlit as st

st.link_button("Go to gallery", "https://streamlit.io/gallery")

4.3 st.checkbox

# st.checkbox(label, value=False, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st

agree = st.checkbox('I agree')

if agree:
    st.write('Great!')

4.4 st.toggle

# st.toggle(label, value=False, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st

on = st.toggle('Activate feature')

if on:
    st.write('Feature activated!')

4.5 st.radio

# st.radio(label, options, index=0, format_func=special_internal_function, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, horizontal=False, captions=None, label_visibility="visible")
import streamlit as st

genre = st.radio(
    "What's your favorite movie genre",
    [":rainbow[Comedy]", "***Drama***", "Documentary :movie_camera:"],
    captions = ["Laugh out loud.", "Get the popcorn.", "Never stop learning."],
    index=None,
    )

if genre == ':rainbow[Comedy]':
    st.write('You selected comedy.')
else:
    st.write("You didn\'t select comedy.")

# Store the initial value of widgets in session state
if "visibility" not in st.session_state:
    st.session_state.visibility = "visible"
    st.session_state.disabled = False
    st.session_state.horizontal = False

col1, col2 = st.columns(2)

with col1:
    st.checkbox("Disable radio widget", key="disabled")
    st.checkbox("Orient radio options horizontally", key="horizontal")

with col2:
    st.radio(
        "Set label visibility 👇",
        ["visible", "hidden", "collapsed"],
        key="visibility",
        label_visibility=st.session_state.visibility,
        disabled=st.session_state.disabled,
        horizontal=st.session_state.horizontal,
    )

4.6 st.selectbox

# st.selectbox(label, options, index=0, format_func=special_internal_function, key=None, help=None, on_change=None, args=None, kwargs=None, *, placeholder="Choose an option", disabled=False, label_visibility="visible")
import streamlit as st

option = st.selectbox(
    'How would you like to be contacted?',
    ('Email', 'Home phone', 'Mobile phone'),
    index=None,
    placeholder="Select contact method...",
    )

st.write('You selected:', option)

# Store the initial value of widgets in session state
if "visibility" not in st.session_state:
    st.session_state.visibility = "visible"
    st.session_state.disabled = False

col1, col2 = st.columns(2)

with col1:
    st.checkbox("Disable selectbox widget", key="disabled")
    st.radio(
        "Set selectbox label visibility 👉",
        key="visibility",
        options=["visible", "hidden", "collapsed"],
    )

with col2:
    option = st.selectbox(
        "How would you like to be contacted?",
        ("Email", "Home phone", "Mobile phone"),
        label_visibility=st.session_state.visibility,
        disabled=st.session_state.disabled,
    )

4.7 st.multiselect

# st.multiselect(label, options, default=None, format_func=special_internal_function, key=None, help=None, on_change=None, args=None, kwargs=None, *, max_selections=None, placeholder="Choose an option", disabled=False, label_visibility="visible")
import streamlit as st

options = st.multiselect(
    'What are your favorite colors',
    ['Green', 'Yellow', 'Red', 'Blue'],
    ['Yellow', 'Red'])

st.write('You selected:', options)

4.8 st.slider

# st.slider(label, min_value=None, max_value=None, value=None, step=None, format=None, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st
from datetime import time, datetime

age = st.slider('How old are you?', 0, 130, 25)
st.write("I'm ", age, 'years old')

values = st.slider(
    'Select a range of values',
    0.0, 100.0, (25.0, 75.0))
st.write('Values:', values)

appointment = st.slider(
    "Schedule your appointment:",
    value=(time(11, 30), time(12, 45)))
st.write("You're scheduled for:", appointment)

start_time = st.slider(
    "When do you start?",
    value=datetime(2020, 1, 1, 9, 30),
    format="MM/DD/YY - hh:mm")
st.write("Start time:", start_time)

4.9 st.select_slider

# st.select_slider(label, options=(), value=None, format_func=special_internal_function, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st

color = st.select_slider(
    'Select a color of the rainbow',
    options=['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet'])
st.write('My favorite color is', color)

start_color, end_color = st.select_slider(
    'Select a range of color wavelength',
    options=['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet'],
    value=('red', 'blue'))
st.write('You selected wavelengths between', start_color, 'and', end_color)

4.10 st.text_input

# st.text_input(label, value="", max_chars=None, key=None, type="default", help=None, autocomplete=None, on_change=None, args=None, kwargs=None, *, placeholder=None, disabled=False, label_visibility="visible")
import streamlit as st

title = st.text_input('Movie title', 'Life of Brian')
st.write('The current movie title is', title)

# Store the initial value of widgets in session state
if "visibility" not in st.session_state:
    st.session_state.visibility = "visible"
    st.session_state.disabled = False

col1, col2 = st.columns(2)

with col1:
    st.checkbox("Disable text input widget", key="disabled")
    st.radio(
        "Set text input label visibility 👉",
        key="visibility",
        options=["visible", "hidden", "collapsed"],
    )
    st.text_input(
        "Placeholder for the other text input widget",
        "This is a placeholder",
        key="placeholder",
    )

with col2:
    text_input = st.text_input(
        "Enter some text 👇",
        label_visibility=st.session_state.visibility,
        disabled=st.session_state.disabled,
        placeholder=st.session_state.placeholder,
    )

    if text_input:
        st.write("You entered: ", text_input

4.11 st.number_input

# st.number_input(label, min_value=None, max_value=None, value="min", step=None, format=None, key=None, help=None, on_change=None, args=None, kwargs=None, *, placeholder=None, disabled=False, label_visibility="visible")
import streamlit as st

number = st.number_input('Insert a number')
st.write('The current number is ', number)

number = st.number_input("Insert a number", value=None, placeholder="Type a number...")
st.write('The current number is ', number)

4.12 st.text_area

# st.text_area(label, value="", height=None, max_chars=None, key=None, help=None, on_change=None, args=None, kwargs=None, *, placeholder=None, disabled=False, label_visibility="visible")
import streamlit as st

txt = st.text_area(
    "Text to analyze",
    "It was the best of times, it was the worst of times, it was the age of "
    "wisdom, it was the age of foolishness, it was the epoch of belief, it "
    "was the epoch of incredulity, it was the season of Light, it was the "
    "season of Darkness, it was the spring of hope, it was the winter of "
    "despair, (...)",
    )

st.write(f'You wrote {len(txt)} characters.')

4.13 st.date_input

# st.date_input(label, value="today", min_value=None, max_value=None, key=None, help=None, on_change=None, args=None, kwargs=None, *, format="YYYY/MM/DD", disabled=False, label_visibility="visible")
import datetime
import streamlit as st

d = st.date_input("When's your birthday", datetime.date(2019, 7, 6))
st.write('Your birthday is:', d)

today = datetime.datetime.now()
next_year = today.year + 1
jan_1 = datetime.date(next_year, 1, 1)
dec_31 = datetime.date(next_year, 12, 31)

d = st.date_input(
    "Select your vacation for next year",
    (jan_1, datetime.date(next_year, 1, 7)),
    jan_1,
    dec_31,
    format="MM.DD.YYYY",
)
d

4.14 st.time_input

# st.time_input(label, value="now", key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible", step=0:15:00)
import datetime
import streamlit as st

t = st.time_input('Set an alarm for', datetime.time(8, 45))
st.write('Alarm is set for', t)

t = st.time_input('Set an alarm for', value=None)
st.write('Alarm is set for', t)

4.15 st.file_uploader

# st.file_uploader(label, type=None, accept_multiple_files=False, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st
import pandas as pd
from io import StringIO

uploaded_file = st.file_uploader("Choose a file")
if uploaded_file is not None:
    # To read file as bytes:
    bytes_data = uploaded_file.getvalue()
    st.write(bytes_data)

    # To convert to a string based IO:
    stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
    st.write(stringio)

    # To read file as string:
    string_data = stringio.read()
    st.write(string_data)

    # Can be used wherever a "file-like" object is accepted:
    dataframe = pd.read_csv(uploaded_file)
    st.write(dataframe)

# accepts multiple files at a time
uploaded_files = st.file_uploader("Choose a CSV file", accept_multiple_files=True)
for uploaded_file in uploaded_files:
    bytes_data = uploaded_file.read()
    st.write("filename:", uploaded_file.name)
    st.write(bytes_data)

4.16 st.camera_input

# st.camera_input(label, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st
from PIL import Image
import numpy as np

img_file_buffer = st.camera_input("Take a picture")

if img_file_buffer is not None:
    # To read image file buffer as a PIL Image:
    img = Image.open(img_file_buffer)

    # To convert PIL Image to numpy array:
    img_array = np.array(img)

    # Check the type of img_array:
    # Should output: <class 'numpy.ndarray'>
    st.write(type(img_array))

    # Check the shape of img_array:
    # Should output shape: (height, width, channels)
    st.write(img_array.shape)
    
if img_file_buffer is not None:
    # To read image file buffer with OpenCV:
    bytes_data = img_file_buffer.getvalue()
    cv2_img = cv2.imdecode(np.frombuffer(bytes_data, np.uint8), cv2.IMREAD_COLOR)

    # Check the type of cv2_img:
    # Should output: <class 'numpy.ndarray'>
    st.write(type(cv2_img))

    # Check the shape of cv2_img:
    # Should output shape: (height, width, channels)
    st.write(cv2_img.shape)

4.17 st.color_picker

# st.color_picker(label, value=None, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False, label_visibility="visible")
import streamlit as st

color = st.color_picker('Pick A Color', '#00f900')
st.write('The current color is', color)

5. 多媒体

5.1 st.image

# st.image(image, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
import streamlit as st
from PIL import Image

st.image('https://cos.neevop.com/blog/open_txt/image-20221030181919022.png', caption='Sunrise by the mountains')

5.2 st.audio

# st.audio(data, format="audio/wav", start_time=0, *, sample_rate=None)
import streamlit as st
import numpy as np

audio_file = open('myaudio.ogg', 'rb')
audio_bytes = audio_file.read()

st.audio(audio_bytes, format='audio/ogg')

sample_rate = 44100  # 44100 samples per second
seconds = 2  # Note duration of 2 seconds
frequency_la = 440  # Our played note will be 440 Hz
# Generate array with seconds*sample_rate steps, ranging between 0 and seconds
t = np.linspace(0, seconds, seconds * sample_rate, False)
# Generate a 440 Hz sine wave
note_la = np.sin(frequency_la * t * 2 * np.pi)

st.audio(note_la, sample_rate=sample_rate)

5.3 st.video

# st.video(data, format="video/mp4", start_time=0)

6. 框架

6.1 st.sidebar

# st.sidebar
import streamlit as st
import time

# Using object notation
add_selectbox = st.sidebar.selectbox(
    "How would you like to be contacted?",
    ("Email", "Home phone", "Mobile phone")
)

# Using "with" notation
with st.sidebar:
    add_radio = st.radio(
        "Choose a shipping method",
        ("Standard (5-15 days)", "Express (2-5 days)")
    )
    
# The only elements that aren't supported using object notation are st.echo, st.spinner, and st.toast. To use these elements, you must use with notation.
with st.sidebar:
    with st.echo():
        st.write("This code will be printed to the sidebar.")

    with st.spinner("Loading..."):
        time.sleep(5)
    st.success("Done!")

6.2 st.columns

插入多个并排放置的多元素容器并返回容器对象的列表。要将元素添加到返回的容器中，您可以使用“with”表示法（首选）或直接在返回的对象上调用方法。列只能放置在其他列内，最多只能嵌套一层。

# st.columns(spec, *, gap="small")
import streamlit as st
import numpy as np

col1, col2, col3 = st.columns(3)

with col1:
   st.header("A cat")
   st.image("https://static.streamlit.io/examples/cat.jpg")

with col2:
   st.header("A dog")
   st.image("https://static.streamlit.io/examples/dog.jpg")

with col3:
   st.header("An owl")
   st.image("https://static.streamlit.io/examples/owl.jpg")
  
col1, col2 = st.columns([3, 1])
data = np.random.randn(10, 1)

col1.subheader("A wide column with a chart")
col1.line_chart(data)

col2.subheader("A narrow column with the data")
col2.write(data)

6.3 st.tabs

插入多个多元素容器作为选项卡。选项卡是一种导航元素，允许用户在相关内容组之间轻松移动。使用“with”表示法（首选）或直接在返回的对象上调用方法。

# st.tabs(tabs)
import streamlit as st

tab1, tab2, tab3 = st.tabs(["Cat", "Dog", "Owl"])

with tab1:
   st.header("A cat")
   st.image("https://static.streamlit.io/examples/cat.jpg", width=200)

with tab2:
   st.header("A dog")
   st.image("https://static.streamlit.io/examples/dog.jpg", width=200)

with tab3:
   st.header("An owl")
   st.image("https://static.streamlit.io/examples/owl.jpg", width=200)
  
tab1, tab2 = st.tabs(["📈 Chart", "🗃 Data"])
data = np.random.randn(10, 1)

tab1.subheader("A tab with a chart")
tab1.line_chart(data)

tab2.subheader("A tab with the data")
tab2.write(data)

6.4 st.expander

将一个容器插入到您的应用程序中，该容器可用于容纳多个元素，并且可由用户展开或折叠。折叠时，所有可见的都是提供的标签。

# st.expander(label, expanded=False)
import streamlit as st

st.bar_chart({"data": [1, 5, 2, 6, 2, 1]})

with st.expander("See explanation"):
    st.write("""
        The chart above shows some numbers I picked for you.
        I rolled actual dice for these, so they're *guaranteed* to
        be random.
    """)
    st.image("https://static.streamlit.io/examples/dice.jpg")

st.bar_chart({"data": [1, 5, 2, 6, 2, 1]})

expander = st.expander("See explanation")
expander.write("""
    The chart above shows some numbers I picked for you.
    I rolled actual dice for these, so they're *guaranteed* to
    be random.
""")
expander.image("https://static.streamlit.io/examples/dice.jpg")

6.5 st.container

将一个不可见的容器插入到您的应用程序中，可用于容纳多个元素。

# st.container()
import streamlit as st

with st.container():
   st.write("This is inside the container")

   # You can call any Streamlit command, including custom components:
   st.bar_chart(np.random.randn(50, 3))

st.write("This is outside the container")

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