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# Pokemon Table Implementation
This document describes the high-performance Pokemon data table implementation for the Pokemon Battle Simulator.
## Overview
The Pokemon Table is a high-performance data structure that provides O(1) lookup access to all Pokemon species data. It loads Pokemon data from JSON files and stores them in memory for fast runtime access.
## Features
- **O(1) ID-based lookup**: Access any Pokemon by its ID in constant time
- **O(1) Name-based lookup**: Access any Pokemon by its name using a hash map
- **Automatic data loading**: Loads all Pokemon data from JSON files at startup
- **Memory efficient**: Uses contiguous memory storage for optimal cache performance
- **Type safety**: Strongly typed with comprehensive error handling
- **Validation**: Built-in data validation to ensure integrity
## Architecture
### Core Classes
#### `PokemonTable`
The main class that manages the Pokemon data table.
**Key Methods:**
- `loadFromDataDirectory()`: Loads Pokemon data from the standard data directory
- `loadFromFiles()`: Loads Pokemon data from specific JSON files
- `getPokemon(uint16_t id)`: O(1) lookup by Pokemon ID
- `getPokemonByName(std::string_view name)`: O(1) lookup by Pokemon name
- `hasPokemon(uint16_t id)`: Check if a Pokemon ID exists
- `size()`: Get the total number of loaded Pokemon
- `validate()`: Validate the integrity of loaded data
#### `PokemonSpecies`
Struct containing all the data for a single Pokemon species.
**Fields:**
- `id`: Pokemon ID (1-based)
- `name`: Pokemon name
- `base_stats`: Base stats (HP, Attack, Defense, SpAttack, SpDefense, Speed)
- `types`: Primary and secondary types
### Global Access
The implementation provides a global Pokemon table instance for convenient access:
```cpp
#include "core/pokemon_table.h"
// Initialize the global table (call once at startup)
bool success = PokEng::initializePokemonTable();
// Use the global table
const auto* bulbasaur = PokEng::g_pokemonTable->getPokemon(1);
const auto* charizard = PokEng::g_pokemonTable->getPokemonByName("charizard");
// Clean up (call at shutdown)
PokEng::shutdownPokemonTable();
```
## Performance
### Benchmarks
Based on the example program, the Pokemon table demonstrates excellent performance:
- **Initialization**: ~89ms to load 1025 Pokemon species
- **ID Lookups**: ~33,333 lookups per millisecond (100,000 lookups in 3ms)
- **Memory Usage**: Minimal memory footprint with contiguous storage
### Storage Strategy
The table uses a hybrid storage approach for optimal performance:
1. **Vector storage**: Pokemon species are stored in a `std::vector<PokemonSpecies>` indexed by ID
2. **Hash map**: Name-to-ID mapping using `std::unordered_map` for fast name lookups
3. **Index 0 unused**: Vector index 0 is unused, so Pokemon with ID 1 is at index 1
This approach provides:
- O(1) ID lookups via direct vector indexing
- O(1) average case name lookups via hash table
- Excellent cache locality for ID-based access patterns
## Usage Examples
### Basic Usage
```cpp
#include "core/pokemon_table.h"
int main() {
// Initialize the Pokemon table
if (!PokEng::initializePokemonTable()) {
std::cerr << "Failed to load Pokemon data!" << std::endl;
return 1;
}
// Look up Pokemon by ID
const auto* pikachu = PokEng::g_pokemonTable->getPokemon(25);
if (pikachu) {
std::cout << "Pikachu's speed: " << pikachu->base_stats.speed << std::endl;
std::cout << "Pikachu's type: " << PokEng::TypeUtils::typeToString(pikachu->types.getPrimary()) << std::endl;
}
// Look up Pokemon by name
const auto* charizard = PokEng::g_pokemonTable->getPokemonByName("charizard");
if (charizard) {
std::cout << "Charizard ID: " << charizard->id << std::endl;
}
// Clean up
PokEng::shutdownPokemonTable();
return 0;
}
```
### Advanced Usage
```cpp
// Check if Pokemon exists
if (PokEng::g_pokemonTable->hasPokemon(150)) {
const auto* mewtwo = PokEng::g_pokemonTable->getPokemon(150);
// Use mewtwo data...
}
// Iterate through all Pokemon
for (uint16_t id = 1; id <= PokEng::g_pokemonTable->getMaxId(); ++id) {
const auto* pokemon = PokEng::g_pokemonTable->getPokemon(id);
if (pokemon) {
// Process pokemon...
}
}
// Get all Pokemon at once (for bulk operations)
const auto& allPokemon = PokEng::g_pokemonTable->getAllPokemon();
for (const auto& pokemon : allPokemon) {
if (pokemon.id != 0) { // Skip empty entries
// Process pokemon...
}
}
```
## Data Loading
The Pokemon table automatically loads data from JSON files in the `data/pokemon/` directory:
- `generation-i.json` through `generation-ix.json`
- Each file contains Pokemon from a specific generation
- Data is validated during loading
### JSON Format
Each Pokemon entry in the JSON files has the following structure:
```json
{
"id": 1,
"name": "bulbasaur",
"height": 7,
"weight": 69,
"base_experience": 64,
"types": ["grass", "poison"],
"stats": {
"hp": 45,
"attack": 49,
"defense": 49,
"special-attack": 65,
"special-defense": 65,
"speed": 45
},
"abilities": [...],
"species": {...}
}
```
## Error Handling
The implementation includes comprehensive error handling:
- **File loading errors**: Graceful handling of missing or corrupted JSON files
- **JSON parsing errors**: Detailed error messages for malformed JSON
- **Data validation**: Built-in validation to ensure data integrity
- **Memory safety**: Proper resource management with RAII
## Testing
The implementation includes comprehensive unit tests covering:
- Data loading and initialization
- ID-based and name-based lookups
- Error handling for invalid inputs
- Performance validation
- Data integrity validation
Run tests with:
```bash
cd build
make test
```
## Integration
The Pokemon table is designed to integrate seamlessly with other components:
- **Pokemon creation**: Use table data to create Pokemon instances
- **Battle calculations**: Fast access to base stats and types
- **Type effectiveness**: Integration with type system for damage calculations
- **Stat calculations**: Base stats for battle stat computations
## Future Enhancements
Potential improvements for the Pokemon table:
1. **Lazy loading**: Load Pokemon data on-demand to reduce startup time
2. **Compressed storage**: Use compression to reduce memory footprint
3. **Multi-threading**: Parallel loading of Pokemon data
4. **Caching**: Implement LRU cache for frequently accessed Pokemon
5. **Serialization**: Save/load compiled Pokemon data for faster startup