Develop FiftyOne Plugins

Key Directives

ALWAYS follow these rules:

1. Understand before coding

Ask clarifying questions. Never assume what the plugin should do.

2. Plan before implementing

Present file structure and design. Get user approval before generating code.

3. Search existing plugins for patterns

# Clone official plugins for reference
git clone https://github.com/voxel51/fiftyone-plugins.git /tmp/fiftyone-plugins 2>/dev/null || true

# Search for similar patterns
grep -r "keyword" /tmp/fiftyone-plugins/plugins/ --include="*.py" -l

list_plugins(enabled=True)
list_operators(builtin_only=False)
get_operator_schema(operator_uri="@voxel51/brain/compute_similarity")

4. Test locally before done

# Get plugins directory
PLUGINS_DIR=$(python -c "import fiftyone as fo; print(fo.config.plugins_dir)")

# Develop plugin in plugins directory
cd $PLUGINS_DIR/my-plugin

Write tests:

• Python: pytest for operators/panels
• JavaScript: vitest for React components

Verify in FiftyOne App before done.

5. Iterate on feedback

Run server separately to see logs:

# Terminal 1: Python logs
python -m fiftyone.server.main

# Terminal 2: Browser at localhost:5151 (JS logs in DevTools console)

fiftyone app debug          # logs printed to shell; use with a dataset:
fiftyone app debug <dataset-name>

For automated iteration, use Playwright e2e tests:

npx playwright test

Refine until the plugin works as expected.

Critical Patterns

Operator Execution

# Chain operators (non-delegated operators only, in execute() only, fire-and-forget)
ctx.trigger("@plugin/other_operator", params={...})

# UI operations
ctx.ops.notify("Done!")
ctx.ops.set_progress(0.5)

View Selection

# Use ctx.target_view() to respect user's current selection and filters
view = ctx.target_view()

# ctx.dataset - Full dataset (use when explicitly exporting all)
# ctx.view - Filtered view (use for read-only operations)
# ctx.target_view() - Filtered + selected samples (use for exports/processing)

Store Keys (Avoid Collisions)

# Use namespaced keys to avoid cross-dataset conflicts
def _get_store_key(self, ctx):
    plugin_name = self.config.name.split("/")[-1]
    return f"{plugin_name}_store_{ctx.dataset._doc.id}_{self.version}"

store = ctx.store(self._get_store_key(ctx))

Panel State vs Execution Store

# ctx.panel.state - Transient (resets when panel reloads)
# ctx.store() - Persistent (survives across sessions)

def on_load(self, ctx):
    ctx.panel.state.selected_tab = "overview"  # Transient
    store = ctx.store(self._get_store_key(ctx))
    ctx.panel.state.config = store.get("user_config") or {}  # Persistent

Delegated Execution

Use for operations that: process >100 samples or take >1 second.

@property
def config(self):
    return foo.OperatorConfig(
        name="heavy_operator",
        allow_delegated_execution=True,
        default_choice_to_delegated=True,
    )

Progress Reporting

@property
def config(self):
    return foo.OperatorConfig(
        name="progress_operator",
        execute_as_generator=True,
    )

def execute(self, ctx):
    total = len(ctx.target_view())
    for i, sample in enumerate(ctx.target_view()):
        # Process sample...
        yield ctx.trigger("set_progress", {"progress": (i+1)/total})
    yield {"status": "complete"}

Custom Runs (Auditability)

Use Custom Runs for operations needing reproducibility and history tracking:

# Create run key (must be valid Python identifier - use underscores, not slashes)
run_key = f"my_plugin_{self.config.name}_v1_{timestamp}"

# Initialize and register
run_config = ctx.dataset.init_run(operator=self.config.name, params=ctx.params)
ctx.dataset.register_run(run_key, run_config)

See PYTHON-OPERATOR.md for full Custom Runs pattern. See EXECUTION-STORE.md for advanced caching patterns. See HYBRID-PLUGINS.md for Python + JavaScript communication.

Workflow

Phase 1: Requirements

Understand what the user needs to accomplish:

1. "What problem are you trying to solve?"
2. "What should the user be able to do?" (user's perspective)
3. "What information does the user provide?"
4. "What result does the user expect to see?"
5. "Any external data sources or services involved?"
6. "How will this fit into the user's workflow?"

Phase 2: Design

1. Search existing plugins for similar patterns
2. For panels, default to hybrid (Python + JavaScript). See HYBRID-PLUGINS.md.
3. Create plan with:
   • Plugin name (@org/plugin-name)
   • File structure
   • Operator/panel specs
   • Input/output definitions
4. Get user approval before coding

See PLUGIN-STRUCTURE.md for file formats.

Phase 3: Generate Code

Create these files:

File	Required	Purpose
fiftyone.yml	Yes	Plugin manifest
__init__.py	Yes	Python operators/panels
requirements.txt	If deps	Python dependencies
package.json	JS only	Node.js metadata
src/index.tsx	JS only	React components

Reference docs:

• PYTHON-OPERATOR.md - Python operators
• PYTHON-PANEL.md - Python panels
• JAVASCRIPT-PANEL.md - React/TypeScript panels
• HYBRID-PLUGINS.md - Python + JavaScript communication
• EXECUTION-STORE.md - Persistent storage and caching

For JavaScript panels with rich UI: Invoke the fiftyone-voodo-design skill for VOODO components (buttons, inputs, toasts, design tokens). VOODO is FiftyOne's official React component library.

Phase 4: Validate & Test

4.1 Validate Detection

list_plugins(enabled=True)  # Should show your plugin
list_operators()  # Should show your operators

If not found: Check fiftyone.yml syntax, Python syntax errors, restart App.

4.2 Validate Schema

get_operator_schema(operator_uri="@myorg/my-operator")

Verify inputs/outputs match your expectations.

4.3 Test Execution

set_context(dataset_name="test-dataset")
launch_app()
execute_operator(operator_uri="@myorg/my-operator", params={...})

Common failures:

• "Operator not found" → Check fiftyone.yml operators list
• "Missing parameter" → Check resolve_input() required fields
• "Execution error" → Check execute() implementation

Phase 5: Iterate

1. Get user feedback
2. Fix issues (sync source and plugins directory if separate)
3. Restart App if needed
4. Repeat until working

Quick Reference

Plugin Types

Type	Language	Use Case
Operator	Python	Data processing, computations
Panel	Hybrid (default)	Python backend + React frontend (recommended)
Panel	Python-only	Simple UI without rich interactivity

Operator Config Options

Option	Default	Effect
dynamic	False	Recalculate inputs on change
execute_as_generator	False	Stream progress with yield
allow_immediate_execution	True	Execute in foreground
allow_delegated_execution	False	Background execution
default_choice_to_delegated	False	Default to background
unlisted	False	Hide from operator browser
on_startup	False	Execute when app starts
on_dataset_open	False	Execute when dataset opens

Panel Config Options

Option	Default	Effect
allow_multiple	False	Allow multiple panel instances
surfaces	"grid"	Where panel can display ("grid", "modal", "grid modal")
category	None	Panel category in browser
priority	None	Sort order in UI

Input Types

Type	Method
Text	inputs.str()
Number	inputs.int() / inputs.float()
Boolean	inputs.bool()
Dropdown	inputs.enum()
File	inputs.file()
View	inputs.view_target()

Minimal Example

fiftyone.yml:

name: "@myorg/hello-world"
type: plugin
operators:
  - hello_world

init.py:

import fiftyone.operators as foo
import fiftyone.operators.types as types

class HelloWorld(foo.Operator):
    @property
    def config(self):
        return foo.OperatorConfig(
            name="hello_world",
            label="Hello World"
        )

    def resolve_input(self, ctx):
        inputs = types.Object()
        inputs.str("message", label="Message", default="Hello!")
        return types.Property(inputs)

    def execute(self, ctx):
        print(ctx.params["message"])
        return {"status": "done"}

def register(p):
    p.register(HelloWorld)

Debugging

Where Logs Go

Log Type	Location
Python backend	Terminal running the server
JavaScript frontend	Browser console (F12 → Console)
Network requests	Browser DevTools (F12 → Network)
Operator errors	Operator browser in FiftyOne App

Running in Debug Mode (Recommended for Development)

fiftyone app debug                    # server logs printed to shell
fiftyone app debug <dataset-name>     # with a dataset pre-loaded

Python Debugging

def execute(self, ctx):
    # Use print() for quick debugging (shows in server terminal)
    print(f"Params received: {ctx.params}")
    print(f"Dataset: {ctx.dataset.name}, View size: {len(ctx.view)}")

    # For structured logging
    import logging
    logging.info(f"Processing {len(ctx.target_view())} samples")

    # ... rest of execution

JavaScript/TypeScript Debugging

// Use console.log in React components
console.log("Component state:", state);
console.log("Panel data:", panelData);

// Check browser DevTools:
// - Console: JS errors, syntax errors, plugin load failures
// - Network: API calls, variable values before/after execution

Common Debug Locations

• Operator not executing: Check Network tab for request/response
• Plugin not loading: Check Console for syntax errors
• Variables not updating: Check Network tab for payload data
• Silent failures: Check Operator browser for error messages

Troubleshooting

Plugin not appearing:

• Check fiftyone.yml exists in plugin root
• Verify location: ~/.fiftyone/plugins/
• Check for Python syntax errors
• Restart FiftyOne App

Operator not found:

• Verify operator listed in fiftyone.yml
• Check register() function
• Run list_operators() to debug

Secrets not available:

• Add to fiftyone.yml under secrets:
• Set environment variables before starting FiftyOne

Advanced

Programmatic Operator Execution

# For executing operators outside of FiftyOne App context
import fiftyone.operators as foo
result = foo.execute_operator(operator_uri, ctx, **params)

Resources

• Plugin Development Guide
• Developing Panels
• Developing JS Plugins
• Panel Examples (reference implementations)
• FiftyOne Plugins Repo
• Operator Types API