streamlit-8-advanced-features
Sub-skill of streamlit: 8. Advanced Features.
Best use case
streamlit-8-advanced-features is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of streamlit: 8. Advanced Features.
Teams using streamlit-8-advanced-features should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/8-advanced-features/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How streamlit-8-advanced-features Compares
| Feature / Agent | streamlit-8-advanced-features | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of streamlit: 8. Advanced Features.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 8. Advanced Features
## 8. Advanced Features
**Status and Progress:**
```python
import streamlit as st
import time
# Progress bar
progress = st.progress(0, text="Processing...")
for i in range(100):
time.sleep(0.01)
progress.progress(i + 1, text=f"Processing... {i+1}%")
# Spinner
with st.spinner("Loading data..."):
time.sleep(2)
st.success("Done!")
# Status messages
st.success("Operation successful!")
st.info("This is informational")
st.warning("Warning: Check your inputs")
st.error("An error occurred")
st.exception(ValueError("Example exception"))
# Toast notifications
st.toast("Data saved!", icon="✅")
# Balloons and snow
st.balloons()
st.snow()
```
**Chat Interface:**
```python
import streamlit as st
import time
st.title("Chat Demo")
# Initialize chat history
if "messages" not in st.session_state:
st.session_state.messages = []
# Display chat history
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Chat input
if prompt := st.chat_input("What's on your mind?"):
# Add user message
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
# Generate response
with st.chat_message("assistant"):
response = f"You said: {prompt}"
st.markdown(response)
st.session_state.messages.append({"role": "assistant", "content": response})
```
**Data Editor:**
```python
import streamlit as st
import pandas as pd
# Editable dataframe
df = pd.DataFrame({
"Name": ["Alice", "Bob", "Charlie"],
"Age": [25, 30, 35],
"Active": [True, False, True]
})
edited_df = st.data_editor(
df,
num_rows="dynamic", # Allow adding/deleting rows
column_config={
"Name": st.column_config.TextColumn("Name", required=True),
"Age": st.column_config.NumberColumn("Age", min_value=0, max_value=120),
"Active": st.column_config.CheckboxColumn("Active")
}
)
if st.button("Save changes"):
st.write("Saved:", edited_df)
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