{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"Provides shared utilities for the TabPFN tabular foundation model ecosystem, including regression result handling, data serialization between pandas/NumPy/CSV formats, dataset loading, and optional telemetry.","skillfed_tags":["tabular-ml","foundation-models"],"use_cases":["Load and preprocess standard ML datasets (iris, etc.) with proper train/test splits for TabPFN experiments.","Convert regression prediction outputs containing mean, median, mode, and quantiles into serializable formats.","Estimate computational costs and cloud pricing for TabPFN classification or regression tasks before execution.","Serialize pandas DataFrames to CSV-formatted bytes for transmission or storage in TabPFN workflows.","Track anonymous usage patterns across TabPFN ecosystem tools via optional telemetry integration."],"what_it_does":"TabPFN Common Utilities is a support library for the TabPFN tabular foundation model ecosystem. It provides a collection of utilities for handling regression prediction results (mean, median, mode, quantiles), converting data between pandas DataFrames, NumPy arrays, and CSV formats, and loading standard ML datasets with train/test splits. The package also includes cost estimation tools for planning computational resources and cloud pricing, with different models for classification versus regression tasks.\n\nThe package depends on numpy, pandas, scikit-learn, requests, filelock, platformdirs, typing-extensions, and includes optional telemetry via posthog and nvidia-ml-py for GPU monitoring. It supports Python 3.9 through 3.13 and is actively maintained. Telemetry is anonymous and aggregated, and can be disabled via environment variable.","worth_installing":"Yes, if you are working within the TabPFN ecosystem. The package is actively maintained, has low install friction, carries no known vulnerabilities, and is licensed permissively. However, it is very new (first release September 2025) with minimal external adoption signals. Install it as a dependency of TabPFN or related tools, or directly if you need its specific data utilities; do not expect it as a general-purpose ML utility library."},"id":"tabpfn-common-utils","links":{"html":"https://skillfed.io/packages/tabpfn-common-utils","md":"https://skillfed.io/packages/tabpfn-common-utils.md","pypi":"https://pypi.org/project/tabpfn-common-utils/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-22","license_spdx":null,"license_treatment":"permissive","name":"tabpfn-common-utils","python_support":"supports_current","summary":"Utilities shared between TabPFN codebases"},"popularity":{"monthly_downloads":243171,"position":8821,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.2.23"}