class KaggleService {
  private username: string;
  private key: string;

  constructor() {
    this.username = import.meta.env.VITE_KAGGLE_USERNAME || '';
    this.key = import.meta.env.VITE_KAGGLE_KEY || '';

    if (!this.username || !this.key) {
      console.warn('Kaggle credentials not found. Some features may be limited.');
    }
  }

  async searchDatasets(query: string) {
    try {
      // Simulate Kaggle dataset search using mock data
      // In a real implementation, you would use Kaggle's REST API
      const mockDatasets = [
        {
          title: `Dataset related to: ${query}`,
          description: `This dataset contains comprehensive data about ${query} with various features and analysis opportunities.`,
          owner: 'kaggle-user',
          votes: Math.floor(Math.random() * 1000),
          downloadCount: Math.floor(Math.random() * 10000)
        },
        {
          title: `Advanced ${query} Analysis`,
          description: `Deep dive into ${query} with statistical analysis and machine learning applications.`,
          owner: 'data-scientist',
          votes: Math.floor(Math.random() * 500),
          downloadCount: Math.floor(Math.random() * 5000)
        }
      ];

      return mockDatasets;
    } catch (error) {
      console.error('Error searching datasets:', error);
      return [];
    }
  }

  async getDatasetInfo(owner: string, dataset: string) {
    try {
      // Mock dataset information
      return {
        title: dataset,
        owner: owner,
        description: `Detailed information about ${dataset} dataset`,
        files: ['data.csv', 'metadata.json'],
        size: '10.5 MB',
        lastUpdated: new Date().toISOString()
      };
    } catch (error) {
      console.error('Error getting dataset info:', error);
      return null;
    }
  }

  async searchNotebooks(query: string) {
    try {
      // Simulate Kaggle notebook search using mock data
      const mockNotebooks = [
        {
          title: `${query} Analysis Notebook`,
          description: `Comprehensive analysis of ${query} using Python and machine learning techniques.`,
          owner: 'notebook-author',
          votes: Math.floor(Math.random() * 200),
          language: 'Python'
        },
        {
          title: `Exploring ${query} Patterns`,
          description: `Data visualization and pattern recognition in ${query} datasets.`,
          owner: 'data-explorer',
          votes: Math.floor(Math.random() * 150),
          language: 'R'
        }
      ];

      return mockNotebooks;
    } catch (error) {
      console.error('Error searching notebooks:', error);
      return [];
    }
  }

  async getNotebookInfo(owner: string, notebook: string) {
    try {
      // Mock notebook information
      return {
        title: notebook,
        owner: owner,
        description: `Detailed analysis notebook: ${notebook}`,
        language: 'Python',
        lastUpdated: new Date().toISOString(),
        votes: Math.floor(Math.random() * 100)
      };
    } catch (error) {
      console.error('Error getting notebook info:', error);
      return null;
    }
  }
}

export default KaggleService;