pypi-streamlit

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# Streamlit
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A powerful Python framework that transforms Python scripts into interactive web applications in minutes. Streamlit enables developers and data scientists to create dashboards, reports, and chat applications without requiring web development expertise.
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## Package Information
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- **Package Name**: streamlit
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- **Language**: Python
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- **Installation**: `pip install streamlit`
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- **CLI Command**: `streamlit run app.py`
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## Core Imports
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```python
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import streamlit as st
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```
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## Basic Usage
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```python
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import streamlit as st
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import pandas as pd
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import numpy as np
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# Set page configuration
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st.set_page_config(
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    page_title="My App",
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    page_icon="🎯",
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    layout="wide"
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)
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# Display title and text
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st.title("My Data Dashboard")
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st.markdown("Welcome to my **Streamlit** app!")
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# Create some sample data
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data = pd.DataFrame({
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    'x': np.random.randn(100),
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    'y': np.random.randn(100)
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})
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# Display interactive widgets
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name = st.text_input("Enter your name:")
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age = st.slider("Select your age:", 0, 100, 25)
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show_data = st.checkbox("Show raw data")
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# Display charts and data
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st.line_chart(data)
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if show_data:
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    st.dataframe(data)
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# Display metrics
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col1, col2 = st.columns(2)
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with col1:
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    st.metric("Mean X", f"{data['x'].mean():.2f}")
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with col2:
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    st.metric("Mean Y", f"{data['y'].mean():.2f}")
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# Create form for user input
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with st.form("feedback_form"):
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    feedback = st.text_area("Provide feedback:")
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    rating = st.selectbox("Rating:", [1, 2, 3, 4, 5])
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    submitted = st.form_submit_button("Submit")
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    if submitted:
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        st.success(f"Thank you {name}! Rating: {rating}/5")
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```
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## Architecture
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Streamlit follows a reactive programming model built on several key concepts:
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- **Script Re-execution**: The entire script re-runs when user interactions change widget values
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- **Session State**: Persistent state management across script re-runs via `st.session_state`
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- **Caching**: Performance optimization through `@st.cache_data` and `@st.cache_resource` decorators
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- **Delta Generator**: Core abstraction that manages the display tree and updates efficiently
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- **Widget State**: Automatic state tracking for all input widgets with optional callbacks
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This design enables rapid development by treating web apps as simple Python scripts while providing powerful interactive capabilities through automatic state management and efficient UI updates.
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## Capabilities
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### Display Elements
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Core functions for displaying text, data, charts, and media content. Includes everything from simple text and markdown to interactive dataframes and complex visualizations.
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```python { .api }
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def title(body, anchor=None, *, help=None): ...
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def header(body, anchor=None, *, help=None, divider=False): ...
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def markdown(body, *, unsafe_allow_html=False, help=None): ...
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def dataframe(data, width=None, height=None, *, use_container_width=False, hide_index=None, column_order=None, column_config=None): ...
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def line_chart(data, *, x=None, y=None, color=None, width=None, height=None, use_container_width=False, help=None): ...
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def image(image, caption=None, width=None, *, use_column_width=None, clamp=False, channels="RGB", output_format="auto", help=None): ...
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```
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[Display Elements](./display-elements.md)
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### Input Widgets
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Interactive widgets for user input including buttons, text inputs, selection widgets, file uploads, and form controls.
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```python { .api }
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def button(label, key=None, help=None, on_click=None, args=None, kwargs=None, *, type="secondary", disabled=False, use_container_width=False, icon=None): ...
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def 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"): ...
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def selectbox(label, options, index=0, format_func=str, key=None, help=None, on_change=None, args=None, kwargs=None, *, placeholder="Choose an option", disabled=False, label_visibility="visible"): ...
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def 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"): ...
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def 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"): ...
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```
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[Input Widgets](./input-widgets.md)
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### Layout and Containers
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Functions for organizing app layout including columns, containers, sidebars, tabs, and expandable sections.
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```python { .api }
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def columns(spec, *, gap="small"): ...
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def container(*, height=None, border=None): ...
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def expander(label, *, expanded=False, icon=None): ...
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def tabs(tab_list): ...
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def form(key, *, clear_on_submit=False, border=True): ...
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```
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[Layout and Containers](./layout-containers.md)
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### State Management
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Session state, query parameters, and context management for maintaining application state across interactions.
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```python { .api }
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session_state: SessionStateProxy
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query_params: QueryParamsProxy
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context: ContextProxy
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```
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[State Management](./state-management.md)
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### Caching and Performance
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Caching decorators and performance optimization tools for efficient data processing and resource management.
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```python { .api }
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def cache_data(func=None, *, ttl=None, max_entries=None, show_spinner=True, persist=None, experimental_allow_widgets=False, hash_funcs=None, validate=None): ...
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def cache_resource(func=None, *, ttl=None, max_entries=None, show_spinner=True, validate=None, hash_funcs=None): ...
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```
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[Caching and Performance](./caching-performance.md)
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### Navigation and Pages
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Multi-page application support, navigation controls, and execution flow management.
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```python { .api }
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def set_page_config(page_title=None, page_icon=None, layout="centered", initial_sidebar_state="auto", menu_items=None): ...
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def navigation(pages, *, position="sidebar", expanded=True): ...
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class Page: ...
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def switch_page(page): ...
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def rerun(): ...
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def stop(): ...
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```
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[Navigation and Pages](./navigation-pages.md)
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### User and Authentication
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User authentication, login/logout functionality, and user information access.
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```python { .api }
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user: UserInfoProxy
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def login(provider, *, oauth2=None): ...
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def logout(): ...
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```
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[User and Authentication](./user-auth.md)
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### Advanced Features
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Chat interfaces, app fragments, modal dialogs, and database connections for sophisticated applications.
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```python { .api }
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def chat_message(name, *, avatar=None): ...
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def chat_input(placeholder=None, key=None, max_chars=None, on_submit=None, args=None, kwargs=None, *, disabled=False): ...
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def fragment(func): ...
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def dialog(title, *, width="small"): ...
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def connection(name, type=None, **kwargs): ...
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```
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[Advanced Features](./advanced-features.md)
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### Components and Configuration
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Custom component framework and column configuration for data editors and dataframes.
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```python { .api }
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# Custom components
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components.v1.html(html, *, width=None, height=None, scrolling=False): ...
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components.v1.declare_component(name, path=None, url=None): ...
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# Column configuration
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column_config.TextColumn(label=None, width=None, help=None, disabled=None, required=None, default=None, max_chars=None, validate=None): ...
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column_config.NumberColumn(label=None, width=None, help=None, disabled=None, required=None, default=None, min_value=None, max_value=None, step=None, format=None): ...
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```
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[Components and Configuration](./components-config.md)
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## Global Objects and Utilities
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```python { .api }
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# Sidebar access
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sidebar: DeltaGenerator
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# Secrets management
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secrets: SecretsProxy
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# Version information
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__version__: str
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# Configuration
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def get_option(key): ...
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def set_option(key, value): ...
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# Utility functions
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def help(obj): ...
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def write(*args, unsafe_allow_html=False): ...
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def write_stream(stream, *, help=None): ...
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def echo(code_location="above"): ...
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```