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Export and integrate MULLER datasets with other formats - Arrow, Parquet, JSON, NumPy, MindRecord. Use when user wants to export data, convert formats, or integrate with other frameworks.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Advanced query operations for MULLER datasets - indexing, vector search, aggregation, and complex filtering. Use when user wants to create indexes, perform vector similarity search, or run aggregation queries.
Create, query, and manage MULLER datasets (multimodal data lake with version control). Use when user wants to work with datasets, create tensors, append data, query samples, or inspect dataset information.
Git-like version control for MULLER datasets - commit, branch, merge, diff, and conflict resolution. Use when user wants to version datasets, create branches, merge changes, or view history.
Basado en la clasificación ocupacional SOC
| name | muller-export |
| description | Export and integrate MULLER datasets with other formats - Arrow, Parquet, JSON, NumPy, MindRecord. Use when user wants to export data, convert formats, or integrate with other frameworks. |
| compatibility | Requires Python 3.11+, muller package installed |
DO NOT create new Python files. Always use the existing script:
scripts/export.py for all export and integration operationsExecute the script directly with python3 command. Never write new scripts to the project root.
When executing operations:
Use this skill when the user wants to:
Handles export and format conversion operations.
Operations:
to-arrow - Export to Apache Arrow formatto-parquet - Export to Parquet filesto-json - Export to JSON formatto-numpy - Convert tensors to NumPy arraysto-mindrecord - Export to MindRecord formatget-info - Get export informationUsage:
# Export to Arrow
python3 .claude/skills/muller-export/scripts/export.py to-arrow \
--path ./my_dataset --output ./output.arrow
# Export to Parquet
python3 .claude/skills/muller-export/scripts/export.py to-parquet \
--path ./my_dataset --output ./output_dir
# Export to JSON
python3 .claude/skills/muller-export/scripts/export.py to-json \
--path ./my_dataset --output ./output.json
# Convert tensor to NumPy
python3 .claude/skills/muller-export/scripts/export.py to-numpy \
--path ./my_dataset --tensor embeddings --output ./embeddings.npy
# Export to MindRecord
python3 .claude/skills/muller-export/scripts/export.py to-mindrecord \
--path ./my_dataset --output ./output.mindrecord
Export formats: Arrow (columnar exchange), Parquet (storage/analytics), JSON (web APIs), NumPy (ML frameworks), MindRecord (MindSpore).
For detailed workflows, check references/ directory.