1# Cài đặt
2pip install streamlit
3 
4# Chạy app
5streamlit run app.py

1# app.py
2import streamlit as st
3
4st.title("Hello Streamlit! 👋")
5st.write("This is my first Streamlit app")
6
7# Text elements
8st.header("This is a header")
9st.subheader("This is a subheader")
10st.text("Fixed width text")
11st.markdown("**Bold** and *italic* text")
12st.caption("Small caption text")
13
14# Code
15st.code("print('Hello World')", language="python")
16
17# LaTeX
18st.latex(r"E = mc^2")

1import streamlit as st
2
3# Text input
4name = st.text_input("Enter your name", "MinAI")
5st.write(f"Hello, {name}!")
6
7# Text area
8description = st.text_area("Description", "Enter text here...")
9
10# Number input
11age = st.number_input("Age", min_value=0, max_value=120, value=25)
12
13# Password
14password = st.text_input("Password", type="password")

1# Selectbox
2option = st.selectbox(
3    "Choose a color",
4    ["Red", "Green", "Blue"]
5)
6
7# Multiselect
8options = st.multiselect(
9    "Select fruits",
10    ["Apple", "Banana", "Cherry", "Date"],
11    ["Apple", "Banana"]  # Default
12)
13
14# Radio
15choice = st.radio(
16    "Pick one",
17    ["Option 1", "Option 2", "Option 3"]
18)
19
20# Checkbox
21agree = st.checkbox("I agree to terms")
22if agree:
23    st.write("Thanks for agreeing!")

1# Slider
2value = st.slider("Select value", 0, 100, 50)
3
4# Range slider
5values = st.slider("Select range", 0.0, 100.0, (25.0, 75.0))
6
7# Date input
8date = st.date_input("Select date")
9
10# Time input  
11time = st.time_input("Select time")
12
13# Color picker
14color = st.color_picker("Pick a color", "#00f900")

1# Button
2if st.button("Click me!"):
3    st.write("Button clicked!")
4
5# Download button
6st.download_button(
7    label="Download CSV",
8    data="col1,col2\n1,2\n3,4",
9    file_name="data.csv",
10    mime="text/csv"
11)
12
13# File uploader
14uploaded_file = st.file_uploader("Choose a file", type=["csv", "xlsx"])
15if uploaded_file:
16    df = pd.read_csv(uploaded_file)
17    st.dataframe(df)

1import streamlit as st
2import pandas as pd
3import numpy as np
4
5# Sample data
6df = pd.DataFrame({
7    "Name": ["Alice", "Bob", "Charlie"],
8    "Age": [25, 30, 35],
9    "Salary": [50000, 60000, 70000]
10})
11
12# Display as static table
13st.table(df)
14
15# Display as interactive dataframe
16st.dataframe(df)
17
18# Editable dataframe
19edited_df = st.data_editor(df)
20
21# With styling
22st.dataframe(df.style.highlight_max(axis=0))
23
24# Metrics
25col1, col2, col3 = st.columns(3)
26col1.metric("Revenue", "$10,000", "+5%")
27col2.metric("Users", "1,234", "-2%")
28col3.metric("Rating", "4.5", "+0.2")

1import streamlit as st
2import pandas as pd
3import numpy as np
4
5# Sample data
6chart_data = pd.DataFrame(
7    np.random.randn(20, 3),
8    columns=["A", "B", "C"]
9)
10
11# Line chart
12st.line_chart(chart_data)
13
14# Area chart
15st.area_chart(chart_data)
16
17# Bar chart
18st.bar_chart(chart_data)
19
20# Scatter chart (Streamlit native)
21st.scatter_chart(chart_data, x="A", y="B")

1import streamlit as st
2import plotly.express as px
3
4# Plotly charts
5df = px.data.gapminder().query("year == 2007")
6fig = px.scatter(df, x="gdpPercap", y="lifeExp", 
7                 color="continent", size="pop",
8                 hover_name="country", log_x=True)
9
10st.plotly_chart(fig, use_container_width=True)

1import streamlit as st
2import matplotlib.pyplot as plt
3import seaborn as sns
4
5# Matplotlib
6fig, ax = plt.subplots()
7ax.plot([1, 2, 3, 4], [1, 4, 2, 3])
8ax.set_title("Simple Plot")
9st.pyplot(fig)
10
11# Seaborn
12tips = sns.load_dataset("tips")
13fig, ax = plt.subplots()
14sns.histplot(tips["total_bill"], ax=ax)
15st.pyplot(fig)

1import streamlit as st
2
3# Equal columns
4col1, col2, col3 = st.columns(3)
5
6with col1:
7    st.header("Column 1")
8    st.write("Content here")
9
10with col2:
11    st.header("Column 2")
12    st.image("https://picsum.photos/200")
13
14with col3:
15    st.header("Column 3")
16    st.button("Click")
17
18# Custom widths
19col1, col2 = st.columns([2, 1])  # 2:1 ratio

1tab1, tab2, tab3 = st.tabs(["📈 Chart", "🗃 Data", "📝 About"])
2
3with tab1:
4    st.header("Charts")
5    st.line_chart([1, 2, 3, 4])
6
7with tab2:
8    st.header("Data")
9    st.dataframe(df)
10
11with tab3:
12    st.header("About")
13    st.write("This is the about section")

1# Expander
2with st.expander("Click to expand"):
3    st.write("Hidden content here")
4    st.image("https://picsum.photos/300")
5
6# Container
7with st.container():
8    st.write("This is inside a container")
9    
10# Empty placeholder
11placeholder = st.empty()
12placeholder.text("This will be replaced")
13placeholder.write("New content!")

1# Sidebar
2st.sidebar.title("Settings")
3option = st.sidebar.selectbox("Select option", ["A", "B", "C"])
4value = st.sidebar.slider("Value", 0, 100, 50)
5
6# With form
7with st.sidebar.form("my_form"):
8    name = st.text_input("Name")
9    submitted = st.form_submit_button("Submit")
10    if submitted:
11        st.write(f"Hello {name}")

1import streamlit as st
2
3# Session state
4if 'count' not in st.session_state:
5    st.session_state.count = 0
6
7# Increment button
8if st.button('Increment'):
9    st.session_state.count += 1
10
11st.write(f"Count: {st.session_state.count}")
12
13# Reset button
14if st.button('Reset'):
15    st.session_state.count = 0

1import streamlit as st
2import pandas as pd
3
4# Cache data (không chạy lại khi có input khác thay đổi)
5@st.cache_data
6def load_data(url):
7    """Load data - chỉ chạy 1 lần"""
8    return pd.read_csv(url)
9
10# Cache resource (database connections, ML models)
11@st.cache_resource
12def load_model():
13    """Load ML model - chỉ chạy 1 lần"""
14    import pickle
15    with open("model.pkl", "rb") as f:
16        return pickle.load(f)
17
18# Sử dụng
19df = load_data("data.csv")  # Cached!
20model = load_model()        # Cached!

1# dashboard.py
2import streamlit as st
3import pandas as pd
4import plotly.express as px
5
6# Page config
7st.set_page_config(
8    page_title="Sales Dashboard",
9    page_icon="📊",
10    layout="wide"
11)
12
13# Title
14st.title("📊 Sales Dashboard")
15st.markdown("---")
16
17# Load data
18@st.cache_data
19def load_data():
20    # Sample data
21    return pd.DataFrame({
22        'Date': pd.date_range('2024-01-01', periods=100),
23        'Sales': np.random.randint(100, 1000, 100),
24        'Region': np.random.choice(['North', 'South', 'East', 'West'], 100),
25        'Product': np.random.choice(['A', 'B', 'C'], 100)
26    })
27
28df = load_data()
29
30# Sidebar filters
31st.sidebar.header("Filters")
32regions = st.sidebar.multiselect(
33    "Select Region",
34    options=df['Region'].unique(),
35    default=df['Region'].unique()
36)
37products = st.sidebar.multiselect(
38    "Select Product",
39    options=df['Product'].unique(),
40    default=df['Product'].unique()
41)
42
43# Filter data
44df_filtered = df[
45    (df['Region'].isin(regions)) & 
46    (df['Product'].isin(products))
47]
48
49# KPIs
50col1, col2, col3, col4 = st.columns(4)
51col1.metric("Total Sales", f"${df_filtered['Sales'].sum():,.0f}")
52col2.metric("Avg Sales", f"${df_filtered['Sales'].mean():,.0f}")
53col3.metric("Max Sales", f"${df_filtered['Sales'].max():,.0f}")
54col4.metric("Transactions", f"{len(df_filtered):,}")
55
56st.markdown("---")
57
58# Charts
59col1, col2 = st.columns(2)
60
61with col1:
62    st.subheader("Sales by Region")
63    fig = px.pie(df_filtered, values='Sales', names='Region', hole=0.4)
64    st.plotly_chart(fig, use_container_width=True)
65
66with col2:
67    st.subheader("Sales Trend")
68    daily_sales = df_filtered.groupby('Date')['Sales'].sum().reset_index()
69    fig = px.line(daily_sales, x='Date', y='Sales')
70    st.plotly_chart(fig, use_container_width=True)
71
72# Data table
73st.subheader("Raw Data")
74st.dataframe(df_filtered, use_container_width=True)
75
76# Download
77csv = df_filtered.to_csv(index=False)
78st.download_button("Download CSV", csv, "sales_data.csv", "text/csv")

1my_app/
2├── app.py           # Main app
3├── requirements.txt # Dependencies
4└── .streamlit/
5    └── config.toml  # Config (optional)

1streamlit
2pandas
3plotly
4numpy

1# 1. Use page config
2st.set_page_config(page_title="My App", layout="wide")
3
4# 2. Cache expensive operations
5@st.cache_data
6def load_data():
7    return pd.read_csv("large_file.csv")
8
9# 3. Use session state for persistence
10if 'initialized' not in st.session_state:
11    st.session_state.initialized = True
12
13# 4. Organize with containers
14with st.container():
15    st.header("Section 1")
16
17# 5. Use forms for multiple inputs
18with st.form("my_form"):
19    name = st.text_input("Name")
20    age = st.number_input("Age")
21    submitted = st.form_submit_button("Submit")
22
23# 6. Progress bars for long operations
24with st.spinner("Loading..."):
25    time.sleep(2)
26
27progress = st.progress(0)
28for i in range(100):
29    progress.progress(i + 1)