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| 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; |