dash-1-optimize-callback-performance

Sub-skill of dash: 1. Optimize Callback Performance (+3).

5 stars

Best use case

dash-1-optimize-callback-performance is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of dash: 1. Optimize Callback Performance (+3).

Teams using dash-1-optimize-callback-performance 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

$curl -o ~/.claude/skills/1-optimize-callback-performance/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/data/analysis/dash/1-optimize-callback-performance/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/1-optimize-callback-performance/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How dash-1-optimize-callback-performance Compares

Feature / Agentdash-1-optimize-callback-performanceStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Sub-skill of dash: 1. Optimize Callback Performance (+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. Optimize Callback Performance (+3)

## 1. Optimize Callback Performance


```python
# Use prevent_initial_call when appropriate
@callback(
    Output("output", "children"),
    Input("button", "n_clicks"),
    prevent_initial_call=True
)
def handle_click(n_clicks):
    return f"Clicked {n_clicks} times"

# Use State for non-triggering inputs
@callback(
    Output("output", "children"),
    Input("submit-btn", "n_clicks"),
    State("input-field", "value")  # Doesn't trigger callback
)
def submit_form(n_clicks, value):
    return f"Submitted: {value}"
```


## 2. Efficient Data Loading


```python
# Cache expensive computations
from flask_caching import Cache

cache = Cache(app.server, config={"CACHE_TYPE": "simple"})

@cache.memoize(timeout=300)
def load_data():
    return pd.read_parquet("large_file.parquet")
```


## 3. Modular Callbacks


```python
# Separate callbacks into modules
# callbacks/analytics.py
from dash import callback, Output, Input

def register_callbacks(app):
    @callback(
        Output("chart", "figure"),
        Input("dropdown", "value")
    )
    def update_chart(value):
        return create_figure(value)
```


## 4. Error Handling


```python
from dash import callback, Output, Input
from dash.exceptions import PreventUpdate

@callback(
    Output("output", "children"),
    Input("input", "value")
)
def safe_callback(value):
    if value is None:
        raise PreventUpdate

    try:
        result = process(value)
        return result
    except Exception as e:
        return html.Div(f"Error: {str(e)}", className="text-danger")
```

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