data-transformation-engine/README.md

A simple data transformation engine.

# Data Engine Implementation Guide

## Table of Contents

1. [Engine Architecture](#engine-architecture)
2. [Implementation Details](#implementation-details)
3. [Data Flow Steps](#data-flow-steps)
4. [Optimization Techniques](#optimization-techniques)
5. [Error Handling](#error-handling)
6. [Usage Patterns](#usage-patterns)

## Engine Architecture

### High-Level Overview

```mermaid
graph TD
    A[Raw Data Input] --> B[Validation Layer]
    B --> C[Cache Layer]
    C --> D[Transform Layer]
    D --> E[Optimization Layer]
    E --> F[Output Layer]
    
    G[Error Handler] --> B
    G --> C
    G --> D
    G --> E
```

### Core Components

1. **Validation Layer**
   - Input validation
   - Type checking
   - Structure verification
   - Format validation

2. **Cache Layer**
   - Memory cache
   - Cache invalidation
   - Cache hit/miss tracking

3. **Transform Layer**
   - Data normalization
   - Structure optimization
   - Data merging
   - Category processing

4. **Optimization Layer**
   - Memory optimization
   - Performance tuning
   - Data structure optimization

5. **Output Layer**
   - Result formatting
   - Error wrapping
   - Data serialization

## Implementation Details

### 1. Engine Factory

```javascript
const createDataEngine = () => {
  // Private cache storage
  const cache = new Map();
  
  // Private validators
  const validators = {
    isValidTerm: (term) => typeof term === 'string' && term.length > 0,
    isValidStream: (stream) => typeof stream === 'string' && stream.length > 0,
    isValidDetailed: (detailed) => Array.isArray(detailed) && detailed.length > 0,
    isValidMonth: (month) => /^\d{4}-\d{2}$/.test(month),
    isValidValue: (value) => !isNaN(value),
    isValidStructure: (data) => {
      return data && 
             Array.isArray(data) && 
             data.every(item => 
               item.term && 
               Array.isArray(item.interval) &&
               Array.isArray(item.info)
             );
    }
  };

  // Private transformers
  const transformers = {
    // Merge detailed data
    mergeDetailed: (existing, incoming) => {
      const uniqueMap = new Map();
      
      // Process existing data
      existing.forEach(item => {
        const key = `${item.month}-${item.branch}`;
        uniqueMap.set(key, item);
      });
      
      // Merge incoming data
      incoming.forEach(item => {
        const key = `${item.month}-${item.branch}`;
        if (!uniqueMap.has(key) || new Date(item.month) > new Date(uniqueMap.get(key).month)) {
          uniqueMap.set(key, item);
        }
      });
      
      return Array.from(uniqueMap.values());
    },

    // Calculate aggregates
    calculateAggregates: (detailed) => {
      return detailed.reduce((acc, curr) => {
        const value = Number(curr.value);
        return {
          total: acc.total + value,
          branches: new Set([...acc.branches, curr.branch]),
          months: new Set([...acc.months, curr.month])
        };
      }, { total: 0, branches: new Set(), months: new Set() });
    },

    // Normalize data structure
    normalizeData: (data) => {
      return data.map(item => ({
        ...item,
        value: item.value ? Number(item.value) : 0,
        month: item.month.trim(),
        branch: item.branch.trim()
      }));
    }
  };

  // Cache management
  const cacheManager = {
    get: (key) => cache.get(key),
    set: (key, value) => cache.set(key, value),
    has: (key) => cache.has(key),
    delete: (key) => cache.delete(key),
    clear: () => cache.clear(),
    generateKey: (data) => JSON.stringify(data)
  };

  // Error handling
  const errorHandler = {
    wrap: (fn, errorMessage) => {
      try {
        return fn();
      } catch (error) {
        console.error(`${errorMessage}:`, error);
        throw error;
      }
    },
    validate: (data, validator, errorMessage) => {
      if (!validator(data)) {
        throw new Error(errorMessage);
      }
    }
  };

  // Main processing pipeline
  const processRawData = (data) => {
    return errorHandler.wrap(() => {
      // 1. Input Validation
      errorHandler.validate(
        data,
        validators.isValidStructure,
        'Invalid data structure'
      );

      // 2. Cache Check
      const cacheKey = cacheManager.generateKey(data);
      if (cacheManager.has(cacheKey)) {
        return cacheManager.get(cacheKey);
      }

      // 3. Data Processing
      const termMap = new Map();
      
      data.forEach(item => {
        // Validate term
        errorHandler.validate(
          item.term,
          validators.isValidTerm,
          `Invalid term: ${item.term}`
        );

        // Initialize or get term data
        if (!termMap.has(item.term)) {
          termMap.set(item.term, {
            id: crypto.randomUUID(),
            term: item.term,
            info: new Map()
          });
        }

        const termData = termMap.get(item.term);
        
        // Process info items
        item.info.forEach(info => {
          // Validate stream
          errorHandler.validate(
            info.stream,
            validators.isValidStream,
            `Invalid stream: ${info.stream}`
          );

          // Validate detailed data
          errorHandler.validate(
            info.detailed,
            validators.isValidDetailed,
            `Invalid detailed data for stream: ${info.stream}`
          );

          // Process existing or new info
          const existingInfo = termData.info.get(info.stream);
          if (existingInfo) {
            // Merge with existing data
            existingInfo.detailed = transformers.mergeDetailed(
              existingInfo.detailed,
              info.detailed
            );
            
            // Update aggregates
            const aggregates = transformers.calculateAggregates(existingInfo.detailed);
            existingInfo.value = aggregates.total;
            existingInfo.uniqueBranches = aggregates.branches.size;
            existingInfo.monthRange = {
              start: Math.min(...aggregates.months),
              end: Math.max(...aggregates.months)
            };
          } else {
            // Create new info entry
            const normalizedDetailed = transformers.normalizeData(info.detailed);
            const aggregates = transformers.calculateAggregates(normalizedDetailed);
            
            termData.info.set(info.stream, {
              ...info,
              detailed: normalizedDetailed,
              uniqueBranches: aggregates.branches.size,
              monthRange: {
                start: Math.min(...aggregates.months),
                end: Math.max(...aggregates.months)
              }
            });
          }
        });
      });

      // 4. Transform to final structure
      const processed = Array.from(termMap.values()).map(item => ({
        ...item,
        info: Array.from(item.info.values()).map(info => ({
          ...info,
          detailed: info.detailed.sort((a, b) => b.month.localeCompare(a.month))
        }))
      }));

      // 5. Cache result
      cacheManager.set(cacheKey, processed);

      return processed;
    }, 'Error processing raw data');
  };

  // Public API
  return {
    processRawData,
    clearCache: cacheManager.clear,
    validators,
    transformers
  };
};
```

## Data Flow Steps

### 1. Input Validation Layer

```javascript
// Step 1: Structure Validation
errorHandler.validate(
  data,
  validators.isValidStructure,
  'Invalid data structure'
);

// Step 2: Term Validation
errorHandler.validate(
  item.term,
  validators.isValidTerm,
  `Invalid term: ${item.term}`
);

// Step 3: Stream Validation
errorHandler.validate(
  info.stream,
  validators.isValidStream,
  `Invalid stream: ${info.stream}`
);

// Step 4: Detailed Data Validation
errorHandler.validate(
  info.detailed,
  validators.isValidDetailed,
  `Invalid detailed data for stream: ${info.stream}`
);
```

### 2. Cache Management Layer

```javascript
// Step 1: Generate Cache Key
const cacheKey = cacheManager.generateKey(data);

// Step 2: Check Cache
if (cacheManager.has(cacheKey)) {
  return cacheManager.get(cacheKey);
}

// Step 3: Process Data
const processed = processData(data);

// Step 4: Store in Cache
cacheManager.set(cacheKey, processed);
```

### 3. Data Transformation Layer

```javascript
// Step 1: Initialize Data Structure
const termMap = new Map();

// Step 2: Process Terms
termMap.set(item.term, {
  id: crypto.randomUUID(),
  term: item.term,
  info: new Map()
});

// Step 3: Process Info Items
const existingInfo = termData.info.get(info.stream);
if (existingInfo) {
  // Merge with existing data
  mergeData(existingInfo, info);
} else {
  // Create new entry
  createNewEntry(info);
}

// Step 4: Calculate Aggregates
const aggregates = transformers.calculateAggregates(detailed);

// Step 5: Normalize and Sort
const normalized = transformers.normalizeData(detailed);
const sorted = normalized.sort((a, b) => b.month.localeCompare(a.month));
```

## Optimization Techniques

### 1. Memory Optimization

```javascript
// Use Map for O(1) lookups
const termMap = new Map();

// Use Set for unique values
const uniqueBranches = new Set();

// Efficient data merging
const mergeDetailed = (existing, incoming) => {
  const uniqueMap = new Map();
  // ... merging logic
};
```

### 2. Performance Optimization

```javascript
// Cache expensive operations
const cacheKey = JSON.stringify(data);
if (cache.has(cacheKey)) return cache.get(cacheKey);

// Efficient data structure
const termData = {
  id: crypto.randomUUID(),
  term: item.term,
  info: new Map()  // O(1) lookup
};

// Optimize sorting
detailed.sort((a, b) => b.month.localeCompare(a.month));
```

### 3. Memory Management

```javascript
// Clear cache when needed
const clearCache = () => cache.clear();

// Remove unused data
const cleanup = () => {
  cache.forEach((value, key) => {
    if (isStale(value)) cache.delete(key);
  });
};
```

## Error Handling

### 1. Validation Errors

```javascript
const validators = {
  isValidTerm: (term) => {
    if (!term || typeof term !== 'string') {
      throw new Error('Invalid term type');
    }
    if (term.length === 0) {
      throw new Error('Term cannot be empty');
    }
    return true;
  }
};
```

### 2. Processing Errors

```javascript
const processWithErrorHandling = (data) => {
  try {
    return processRawData(data);
  } catch (error) {
    console.error('Processing error:', error);
    return {
      error: true,
      message: error.message,
      data: null
    };
  }
};
```

### 3. Cache Errors

```javascript
const safeCacheAccess = (key) => {
  try {
    return cache.get(key);
  } catch (error) {
    console.error('Cache access error:', error);
    cache.delete(key);  // Clean up potentially corrupted cache
    return null;
  }
};
```

## Usage Patterns

### 1. Basic Usage

```javascript
const engine = createDataEngine();
const processed = engine.processRawData(rawData);
```

### 2. With Error Handling

```javascript
const engine = createDataEngine();
try {
  const processed = engine.processRawData(rawData);
  // Use processed data
} catch (error) {
  console.error('Engine error:', error);
  // Handle error case
}
```

### 3. With Cache Management

```javascript
const engine = createDataEngine();

// Process data
const result1 = engine.processRawData(data);

// Same data will use cache
const result2 = engine.processRawData(data);

// Clear cache if needed
engine.clearCache();
```

### 4. Custom Validation

```javascript
const engine = createDataEngine();
const customValidator = (data) => {
  return engine.validators.isValidStructure(data) &&
         engine.validators.isValidTerm(data.term);
};

if (customValidator(data)) {
  const processed = engine.processRawData(data);
}
```

## Performance Considerations

1. **Memory Usage**
   - Use Map and Set for efficient data structures
   - Implement cache size limits
   - Clean up unused data

2. **Processing Speed**
   - Optimize loops and iterations
   - Use efficient sorting algorithms
   - Implement lazy loading where possible

3. **Cache Efficiency**
   - Implement cache invalidation strategy
   - Monitor cache hit/miss ratio
   - Optimize cache key generation

## Best Practices

1. **Data Validation**
   - Always validate input data
   - Use type checking
   - Validate data structure
   - Handle edge cases

2. **Error Handling**
   - Implement comprehensive error handling
   - Provide meaningful error messages
   - Log errors appropriately
   - Recover gracefully from errors

3. **Code Organization**
   - Keep code modular
   - Use consistent naming
   - Document complex logic
   - Follow SOLID principles

4. **Testing**
   - Unit test all components
   - Test edge cases
   - Performance testing
   - Memory leak testing

## Contributing Guidelines

1. Follow the established code style
2. Add tests for new functionality
3. Update documentation
4. Consider performance implications
5. Test edge cases thoroughly

## License

MIT License - See LICENSE file for details