{"categories":[{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities"}],"enrichment":{"capability":"Provides a uniform slicing interface for tensor-like objects (numpy, pandas, scipy, PyTorch, lists, tuples, dicts) via `__getitem__`, enabling non-integer indexing and nested slicing in a single call.","skillfed_tags":["data-slicing","indexing-wrapper","multi-type-support"],"use_cases":["Slice multiple data structures in parallel with a single index operation","Select DataFrame columns by name using the same syntax as positional array slicing","Extract nested subsets from mixed-type data structures in one call","Build data pipelines with consistent indexing across multiple data types","Use semantic aliases as slicing keys without manual index lookup"],"what_it_does":"Slicer wraps tensor-like objects and provides a single, uniform slicing syntax that works across numpy arrays, pandas DataFrames, scipy sparse matrices, PyTorch tensors, and Python built-ins (lists, tuples, dicts). Instead of learning each library's indexing conventions, you wrap objects with `S()` and slice them all the same way via `__getitem__`. The package handles non-integer indexes (useful for selecting DataFrame columns by name), nested slicing in one call, and simultaneous slicing of multiple objects at once\u2014returning results as named attributes or via `.o` for anonymous access.\n\nWith zero runtime dependencies and support for Python 3.6+, slicer is lightweight and portable. It's designed for workflows where you need to slice multiple heterogeneous data structures in parallel. The package includes an Alias mechanism to use semantic keys as slicing indices, bridging the gap between positional and label-based indexing.","worth_installing":"Yes, if you regularly slice multiple heterogeneous data structures and want a unified interface. The zero-dependency design and permissive license make it safe to add. The alpha status and lack of updates since 2024-03-09 are minor concerns for a stable utility, but verify it handles your specific data types before production use."},"id":"slicer","links":{"html":"https://skillfed.io/packages/slicer","md":"https://skillfed.io/packages/slicer.md","pypi":"https://pypi.org/project/slicer/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-03-09","license_spdx":null,"license_treatment":"permissive","name":"slicer","python_support":"supports_current","summary":"A small package for big slicing."},"popularity":{"monthly_downloads":14860793,"position":1214,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.0.8"}