feat: Implement DataFrame management and batch deletion endpoints #461
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- Marked tasks 2, 2.1, 2.2, and 2.3 as complete in the DataFrame web interface specification. - Added API endpoints for uploading DataFrames, loading from URLs, and batch deletion of DataFrames. - Enhanced error handling for DataFrame deletion with confirmation requirements and detailed responses. - Implemented cleanup functionality for expired DataFrames with dry run options and memory reporting. - Introduced support for multiple file formats during upload and URL loading, including CSV, JSON, Excel, and Parquet. This update significantly improves the DataFrame management capabilities, providing users with robust options for data handling and cleanup.
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Summary
This PR implements comprehensive DataFrame management capabilities and batch deletion endpoints as part of the DataFrame web interface specification. The changes significantly enhance data handling and cleanup functionality.
Changes Made
📋 Task Completion
.kiro/specs/dataframe-web-interface/tasks.md🚀 API Enhancements
🔧 Key Features
Files Modified
.kiro/specs/dataframe-web-interface/tasks.md(17 lines changed)server/api/__init__.py(2 lines changed)server/api/dataframes.py(668 lines added, significant expansion)Testing Performed
Breaking Changes
None - all changes are additive and maintain backward compatibility.
Related Issues
This PR addresses the DataFrame web interface specification requirements and enhances the overall data management capabilities of the MCP server.
Additional Context
The implementation follows existing patterns in the codebase and maintains consistency with the current API design. The batch deletion functionality includes safety measures to prevent accidental data loss.