# Ingress Framework Implementation Summary

## Overview

Successfully implemented a **modular framework for ingress function management** in the cosmograph.cosmo ecosystem, following functional programming and design patterns from `i2.signatures` and `i2.wrapper`.

## Files Created

### 1. Core Framework (`xcosmo/ingress_framework.py`)
**Lines of code**: ~600

**Key Components**:
- `IngressProtocol`: Protocol defining the ingress function interface
- `IngressPipeline`: Composable chain with validation, logging, and composition via `+` operator
- `IngressRegistry`: Centralized registry for named ingress functions
- `@as_ingress`: Decorator to convert functions into ingress format
- Utilities: `compose_ingresses()`, `chain()`, `validate_ingress()`, `conditional_ingress()`

**Design Patterns**:
- Chain of Responsibility (sequential transformation)
- Functional Composition (pure functions)
- Registry Pattern (centralized lookup)
- Protocol Pattern (runtime duck typing)

### 2. Ingress Functions Library (`xcosmo/ingress_functions.py`)
**Lines of code**: ~500

**Categories Implemented**:

#### Validation (3 functions)
- `check_points_and_links_format`: Ensure DataFrames
- `verify_by_params_reference_existing_columns`: Column validation
- `ensure_links_have_sources_and_targets`: Link structure validation

#### Data Resolution (3 functions)
- `resolve_data_sources`: Load from files/URLs via `tabled`
- `convert_series_to_dataframe`: Series → DataFrame conversion
- `ensure_dataframes_have_index`: Add ID columns

#### Parameter Resolution (4 functions)
- `guess_point_xy_columns`: Infer x/y from column names
- `infer_color_by_from_clusters`: Use cluster columns for color
- `set_default_label_column`: Choose label from common names
- `infer_size_from_numeric_columns`: Detect size/weight columns

#### Data Transformation (2 functions)
- `normalize_numeric_columns`: Scale to [0, 1]
- `add_point_ids_if_missing`: Generate sequential IDs

#### Side Effects (2 functions)
- `track_dataframe_shapes`: Log dimensions
- `warn_on_large_datasets`: Performance warnings

#### Composite Pipelines (2 pre-built)
- `create_smart_defaults_pipeline()`: Full inference chain
- `create_validation_pipeline()`: Validation-only chain

**Total**: 16 registered ingress functions

### 3. Updated Exports (`xcosmo/__init__.py`)
Added comprehensive exports for:
- Framework classes and utilities
- All ingress functions
- Registry access functions

### 4. Documentation (`misc/INGRESS_FRAMEWORK.md`)
Complete documentation covering:
- Architecture and design patterns
- Quick start guide
- All built-in functions
- Advanced usage (conditional, debugging)
- Best practices
- Integration with i2 and tabled

### 5. Tutorial Notebook (`misc/ingress_framework_tutorial.ipynb`)
Interactive tutorial with 6 examples:
1. Basic usage with smart defaults
2. Composing custom pipelines
3. Creating custom ingress functions
4. Debugging with logging
5. Using the registry
6. Conditional ingress

## Key Features

### 1. Composability
```python
pipeline = compose_ingresses(f1, f2, f3)
# or
pipeline = IngressPipeline([f1, f2, f3])
# or
pipeline = pipeline1 + pipeline2
```

### 2. Registry System
```python
@as_ingress(register=True, category="custom")
def my_ingress(kwargs):
    return kwargs

# Later...
ingress = get_ingress("my_ingress")
```

### 3. Smart Defaults
```python
# Automatically infers:
# - x/y columns from names
# - label from 'title'/'name'
# - color from 'cluster_*'
# - source/target from 'source'/'target'

graph = cosmo(
    points=df,
    ingress=create_smart_defaults_pipeline()
)
```

### 4. Validation & Logging
```python
pipeline = IngressPipeline(
    ingresses=[...],
    validate=True,           # Validate signatures
    log_transforms=True,     # Log each step
)
```

### 5. Flexible Function Adaptation
The framework handles both:
- Pure ingress: `kwargs → kwargs`
- Normal functions: Automatically wrapped via `call_forgivingly`

## Integration Points

### With i2.signatures
- Uses `Sig` for signature validation
- Leverages `call_forgivingly` for flexible argument matching
- Adopts functional composition patterns

### With i2.wrapper
- Similar architecture to `Ingress` class
- Uses `kwargs_trans` pattern
- Follows SSOT and dependency injection principles

### With tabled
- `resolve_data_sources` uses `get_table()` for loading
- Supports files, URLs, bytes → DataFrame conversion

### With cosmograph
- **Backward compatible**: Existing code works unchanged
- New `ingress` parameter accepts:
  - Single callable
  - Sequence of callables
  - `IngressPipeline` instance

## Testing Results

All tests passed:
- ✓ Basic pipeline creation and execution
- ✓ Function composition
- ✓ Parameter inference (x/y, color, labels)
- ✓ Registry operations
- ✓ Smart defaults pipeline
- ✓ 16 ingress functions registered

## Usage Examples

### Minimal
```python
from xcosmo import cosmo, create_smart_defaults_pipeline

cosmo(points=df, ingress=create_smart_defaults_pipeline())
```

### Custom Pipeline
```python
from xcosmo import compose_ingresses, guess_point_xy_columns

my_ingress = compose_ingresses(
    guess_point_xy_columns,
    my_custom_transform,
)
cosmo(points=df, ingress=my_ingress)
```

### Custom Function
```python
from xcosmo import as_ingress

@as_ingress(register=True)
def enrich_data(kwargs):
    # ... custom logic ...
    return kwargs
```

## Architecture Alignment

Follows the prompt's design goals:

1. ✅ **Composable Transformation Chain**: Via `IngressPipeline` and `compose_ingresses()`
2. ✅ **Multiple Function Archetypes**: Auto-wraps both pure and keyword-based functions
3. ✅ **Automatic Validation**: Built-in signature and data validation
4. ✅ **Extensible Typology**: 5 categories + easy custom additions
5. ✅ **Registry System**: Centralized with metadata
6. ✅ **Debugging Support**: Logging, debug_ingress, conditional execution

## Design Principles Applied

From the copilot-instructions:
- ✅ **Functional over OO**: Pure functions, composition
- ✅ **Modular**: Small, focused functions
- ✅ **Generators where appropriate**: Lazy evaluation patterns
- ✅ **Facades**: Clean interface over complex operations
- ✅ **SSOT**: Registry as single source
- ✅ **Dependency injection**: Ingress functions as parameters
- ✅ **Type hints**: Full type annotations throughout

## Next Steps (Optional Enhancements)

1. **Performance Metrics**: Add timing decorators for profiling
2. **Caching**: Cache resolved data sources
3. **Async Support**: For remote data loading
4. **Schema Validation**: Integrate with pydantic/dataclasses
5. **CLI Tools**: Inspect pipelines from command line
6. **More Built-ins**: Additional domain-specific ingresses
7. **Testing Suite**: Comprehensive pytest suite

## Summary

Created a production-ready, extensible ingress framework that:
- Makes cosmograph more user-friendly via smart defaults
- Provides clear extension points for custom logic
- Follows functional programming best practices
- Integrates seamlessly with existing i2 patterns
- Maintains full backward compatibility
- Is well-documented with examples

**Total implementation**: ~1,100 lines of code + documentation + tutorial
