{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/13"}],"enrichment":{"capability":"Nominal is a Python SDK for automating workflows involving test data, storage, and compute operations through the Nominal platform.","skillfed_tags":["workflow-automation","data-platform-client"],"use_cases":["Automate test data generation and management workflows within Python applications that integrate with the Nominal platform.","Build data pipelines that combine Nominal storage operations with pandas or polars for local data transformation.","Integrate Nominal compute tasks into CI/CD or testing frameworks to orchestrate remote processing.","Programmatically manage multimedia or complex data types through Nominal's storage layer via the Python SDK."],"what_it_does":"Nominal is a Python client library for the Nominal platform, which appears to be a hosted service for managing test data, storage, and compute workflows. The package provides programmatic access to Nominal's APIs, allowing you to automate and integrate Nominal workflows into Python applications. It bundles a substantial dependency tree including pandas and polars for data manipulation, requests and urllib3 for HTTP communication, and ffmpeg-python for media handling, suggesting the platform handles diverse data types and formats.\n\nThe package is actively maintained (last commit 2026-08-14) and supports current Python versions (3.10\u20133.14). Installation is straightforward via pip. The documentation is hosted at docs.nominal.io, and the project is open-source under Apache-2.0. With no known security vulnerabilities and low install friction, it is positioned as a stable integration point for Nominal workflows, though the exact scope of 'test data' and 'compute' operations is not detailed in the fact sheet.","worth_installing":"Yes, if you use the Nominal platform. The package is actively maintained, has low install friction, carries permissive licensing, and has no known vulnerabilities. The large dependency tree suggests rapid iteration, so verify that the API surface matches your use case before committing to production. If you do not use Nominal, this package has no standalone value."},"id":"nominal","links":{"html":"https://skillfed.io/packages/nominal","md":"https://skillfed.io/packages/nominal.md","pypi":"https://pypi.org/project/nominal/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-13","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"nominal","python_support":"supports_current","summary":"Automate Nominal workflows in Python"},"popularity":{"monthly_downloads":201775,"position":9663,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.160.0"}