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Add integration examples, tests, and update .gitignore
This commit adds comprehensive examples and tests for the app_meshed platform: ## Integration Examples (examples/) - ju_schema_example.py: Demonstrates JSON Schema generation from function signatures * Shows how i2 + ju enable automatic form generation * Examples of various parameter types and their schemas * API usage patterns for RJSF integration - dol_browser_example.py: Demonstrates source-keyed data access with dol * Unified Mapping interface across all stores * Examples of storing/retrieving DAGs, configs * Bulk operations and store statistics * HTTP API mapping - stream_slicing_example.py: Demonstrates creek-inspired [bt:tt] time-based slicing * Single stream time-based access * Multi-channel synchronized slicing * Sample data generation for audio and sensors * Different slicing patterns and use cases ## Tests (tests/) - test_function_registry.py: 11 tests for function registration and metadata * Registration, retrieval, override, unregister * Metadata extraction with i2 * Error handling for edge cases - test_schema_service.py: 9 tests for schema generation * Function to schema conversion * Object to schema conversion * Type mapping validation * Default values and docstrings - test_dag_service.py: 6 tests for DAG operations * Simple and chained DAG execution * Validation of configurations * Error handling ## Configuration - Updated .gitignore to exclude app_meshed runtime data: * data/ directory (dol stores) * *.npy (numpy stream data) * *.pkl (pickled functions) * Audio files (*.wav, *.mp3) All examples are runnable and demonstrate the three-phase architecture: Phase I (dol), Phase II (meshed), and Phase III (creek).
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‎.gitignore‎

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@@ -2,6 +2,13 @@ wads_configs.json
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data/wads_configs.json
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wads/data/wads_configs.json
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# app_meshed specific
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data/
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*.npy
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*.pkl
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*.wav
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*.mp3
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]

‎examples/dol_browser_example.py‎

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"""Example demonstrating dol-based store browsing.
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This example shows how the unified root store provides a flat,
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key-value interface to different types of data storage.
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"""
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import json
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import tempfile
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from pathlib import Path
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from app_meshed.stores.root_store import create_default_root_store
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def main():
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"""Run the dol browser example."""
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print("=" * 70)
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print("DOL Store Browser Example")
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print("=" * 70)
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print()
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# Create a temporary directory for this example
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with tempfile.TemporaryDirectory() as tmpdir:
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print(f"Using temporary directory: {tmpdir}")
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print()
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# Create the root store
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root = create_default_root_store(base_path=tmpdir)
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# Example 1: Storing and retrieving DAG configurations
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print("Example 1: DAG Configuration Storage (meshes store)")
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print("-" * 70)
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print()
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dag_config = {
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"name": "example_dag",
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"nodes": [
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{"id": "node1", "function": "add"},
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{"id": "node2", "function": "multiply"},
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],
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"edges": [
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{
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"source": "node1",
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"target": "node2",
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"sourceOutput": "node1",
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"targetInput": "a",
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}
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],
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}
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# Store the DAG (automatic JSON serialization)
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root.meshes["my_first_dag"] = dag_config
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print("✓ Stored DAG configuration: 'my_first_dag'")
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print()
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# Retrieve it
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retrieved = root.meshes["my_first_dag"]
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print("Retrieved DAG:")
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print(json.dumps(retrieved, indent=2))
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print()
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# List all meshes
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print(f"All meshes in store: {list(root.meshes.keys())}")
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print()
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# Example 2: Application configurations
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print("=" * 70)
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print("Example 2: Application Configuration (configs store)")
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print("-" * 70)
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print()
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app_config = {
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"server": {"host": "0.0.0.0", "port": 8000},
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"data_path": "/data",
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"features": {
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"enable_streaming": True,
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"max_upload_size": 104857600, # 100MB
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},
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}
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root.configs["app_settings"] = app_config
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print("✓ Stored configuration: 'app_settings'")
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print()
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# Retrieve and display
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settings = root.configs["app_settings"]
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print("Retrieved settings:")
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print(json.dumps(settings, indent=2))
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print()
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# Example 3: Working with multiple items
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print("=" * 70)
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print("Example 3: Bulk Operations")
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print("-" * 70)
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print()
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# Store multiple DAGs
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dags = {
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"simple_add": {
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"name": "simple_add",
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"nodes": [{"id": "add", "function": "add"}],
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"edges": [],
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},
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"simple_multiply": {
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"name": "simple_multiply",
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"nodes": [{"id": "mul", "function": "multiply"}],
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"edges": [],
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},
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"chained": {
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"name": "chained",
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"nodes": [
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{"id": "step1", "function": "add"},
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{"id": "step2", "function": "multiply"},
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],
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"edges": [
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{
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"source": "step1",
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"target": "step2",
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"sourceOutput": "step1",
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"targetInput": "a",
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}
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],
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},
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}
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for name, config in dags.items():
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root.meshes[name] = config
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print(f"✓ Stored DAG: '{name}'")
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print()
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print(f"Total DAGs in store: {len(list(root.meshes.keys()))}")
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print(f"DAG names: {list(root.meshes.keys())}")
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print()
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# Example 4: Store statistics
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print("=" * 70)
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print("Example 4: Store Statistics")
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print("-" * 70)
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print()
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all_keys = root.list_all_keys()
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print("Items in each store:")
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for store_name, keys in all_keys.items():
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print(f" {store_name}: {len(keys)} items")
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if keys:
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print(f" Keys: {keys}")
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print()
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# Example 5: Source-keyed architecture in action
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print("=" * 70)
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print("Example 5: Source-Keyed Architecture")
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print("-" * 70)
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print()
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print("Key insight: All stores use the same dict-like interface!")
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print()
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print("Code examples:")
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print(" root.meshes['my_dag'] = {...} # Store a DAG")
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print(" root.configs['settings'] = {...} # Store config")
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print(" dag = root.meshes['my_dag'] # Retrieve DAG")
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print(" 'my_dag' in root.meshes # Check existence")
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print(" del root.meshes['my_dag'] # Delete DAG")
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print(" list(root.meshes.keys()) # List all keys")
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print()
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# Demonstrate the interface
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print("Live demonstration:")
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print(f" 'simple_add' in root.meshes -> {('simple_add' in root.meshes)}")
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print(f" 'nonexistent' in root.meshes -> {('nonexistent' in root.meshes)}")
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print()
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# Example 6: How this maps to HTTP API
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print("=" * 70)
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print("Example 6: HTTP API Mapping")
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print("-" * 70)
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print()
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print("Python code -> HTTP API:")
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print()
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print(" root.meshes['my_dag'] = config")
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print(" ↓")
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print(" PUT /store/meshes/my_dag")
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print(" Body: config (JSON)")
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print()
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print(" dag = root.meshes['my_dag']")
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print(" ↓")
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print(" GET /store/meshes/my_dag")
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print()
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print(" list(root.meshes.keys())")
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print(" ↓")
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print(" GET /store/meshes/keys")
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print()
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print(" del root.meshes['my_dag']")
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print(" ↓")
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print(" DELETE /store/meshes/my_dag")
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print()
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print("=" * 70)
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print("DOL Browser Example Complete!")
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print("=" * 70)
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print()
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print("Key Benefits of dol:")
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print(" ✓ Uniform interface: Everything is a Mapping")
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print(" ✓ Automatic serialization: JSON, pickle, etc.")
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print(" ✓ Backend agnostic: Files, S3, databases, etc.")
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print(" ✓ Easy to extend: Add new stores as needed")
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print(" ✓ API-ready: Direct mapping to HTTP endpoints")
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print()
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if __name__ == "__main__":
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main()

‎examples/ju_schema_example.py‎

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"""Example demonstrating ju-based JSON Schema generation.
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This example shows how function signatures are automatically converted
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to JSON Schemas suitable for React JSON Schema Form (RJSF).
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"""
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import json
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from app_meshed.services.schema_service import func_to_schema, object_to_schema
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def process_audio(
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audio_data: str,
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sample_rate: int = 44100,
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gain: float = 1.0,
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normalize: bool = True,
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) -> dict:
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"""Process audio data with configurable parameters.
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Args:
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audio_data: Path to audio file
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sample_rate: Sample rate in Hz
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gain: Gain multiplier
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normalize: Whether to normalize the output
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Returns:
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Processed audio metadata
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"""
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return {
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"processed": True,
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"sample_rate": sample_rate,
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"gain": gain,
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"normalized": normalize,
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}
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def main():
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"""Run the ju schema generation example."""
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print("=" * 70)
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print("JSON Schema Generation Example (ju + i2)")
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print("=" * 70)
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print()
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# Example 1: Generate schema from function signature
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print("Example 1: Function to JSON Schema")
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print("-" * 70)
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print()
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schema = func_to_schema(process_audio, title="Audio Processing")
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print("Function signature:")
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print(f" {process_audio.__name__}{process_audio.__code__.co_varnames[:process_audio.__code__.co_argcount]}")
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print()
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print("Generated JSON Schema (for RJSF):")
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print(json.dumps(schema, indent=2))
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print()
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# Example 2: Schema from a configuration object
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print("=" * 70)
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print("Example 2: Object to JSON Schema")
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print("-" * 70)
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print()
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config = {
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"server": {
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"host": "localhost",
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"port": 8000,
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"debug": True,
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},
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"data_path": "/path/to/data",
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"max_connections": 100,
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}
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object_schema = object_to_schema(config, title="Server Configuration")
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print("Configuration object:")
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print(json.dumps(config, indent=2))
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print()
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print("Generated JSON Schema:")
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print(json.dumps(object_schema, indent=2))
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print()
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# Example 3: Different parameter types
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print("=" * 70)
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print("Example 3: Various Parameter Types")
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print("-" * 70)
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print()
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def complex_function(
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name: str,
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age: int,
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height: float,
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active: bool,
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tags: list,
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metadata: dict,
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optional_note: str = "default note",
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) -> dict:
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"""Function with various parameter types."""
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return {}
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complex_schema = func_to_schema(complex_function, title="Complex Parameters")
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print("Function with various types:")
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print(json.dumps(complex_schema, indent=2))
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print()
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# Example 4: How this is used in the API
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print("=" * 70)
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print("Example 4: API Usage Pattern")
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print("-" * 70)
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print()
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print("In the app_meshed API:")
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print(" 1. Frontend requests: GET /schema/function/process_audio")
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print(" 2. Backend generates schema using func_to_schema()")
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print(" 3. Frontend receives JSON Schema")
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print(" 4. RJSF renders a form based on the schema")
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print(" 5. User fills form and submits")
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print(" 6. Frontend sends validated data to DAG execution endpoint")
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print()
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print("API Response Example:")
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api_response = {
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"endpoint": "/schema/function/process_audio",
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"method": "GET",
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"response": schema,
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}
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print(json.dumps(api_response, indent=2))
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print()
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print("=" * 70)
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print("Schema Generation Complete!")
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print("=" * 70)
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print()
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print("Key Benefits:")
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print(" ✓ No manual form definitions needed")
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print(" ✓ Type-safe: schemas match actual function signatures")
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print(" ✓ Self-documenting: docstrings included in schemas")
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print(" ✓ Automatic validation in the frontend")
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print()
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if __name__ == "__main__":
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main()

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