streamlit-1-use-caching-appropriately
Sub-skill of streamlit: 1. Use Caching Appropriately (+3).
Best use case
streamlit-1-use-caching-appropriately is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of streamlit: 1. Use Caching Appropriately (+3).
Teams using streamlit-1-use-caching-appropriately 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/1-use-caching-appropriately/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How streamlit-1-use-caching-appropriately Compares
| Feature / Agent | streamlit-1-use-caching-appropriately | 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: 1. Use Caching Appropriately (+3).
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
# 1. Use Caching Appropriately (+3)
## 1. Use Caching Appropriately
```python
# GOOD: Cache data loading
@st.cache_data
def load_data():
return pd.read_csv("data.csv")
# GOOD: Cache resources (DB connections, models)
@st.cache_resource
def get_model():
return load_model("model.pkl")
# AVOID: Caching with unhashable arguments
# Use _arg prefix to skip hashing
@st.cache_data
def process_data(_db_connection, query):
return _db_connection.execute(query)
```
## 2. Organize Large Apps
```python
# utils/data.py
def load_data():
pass
# utils/charts.py
def create_chart(df):
pass
# app.py
from utils.data import load_data
from utils.charts import create_chart
```
## 3. Handle State Carefully
```python
# GOOD: Initialize state at the top
if "data" not in st.session_state:
st.session_state.data = None
# GOOD: Use callbacks for complex updates
def on_filter_change():
st.session_state.filtered_data = apply_filter(st.session_state.data)
st.selectbox("Filter", options, on_change=on_filter_change)
```
## 4. Optimize Performance
```python
# Use containers for layout stability
placeholder = st.empty()
# Batch widget updates in forms
with st.form("filters"):
# Multiple widgets
st.form_submit_button()
# Use columns for responsive layout
cols = st.columns([1, 2, 1])
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