{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/14"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/8"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/17"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"}],"enrichment":{"capability":"tfx_bsl provides shared libraries and utilities used internally by TensorFlow eXtended (TFX) components and standalone TFX libraries like TFDV, TFMA, and TFT.","skillfed_tags":["tensorflow-ecosystem","data-pipeline-infrastructure"],"use_cases":["Building TFX pipelines that use TFDV, TFMA, or TFT, where tfx_bsl is installed as a transitive dependency","Developing custom TFX components that need access to shared utilities from the tfx_bsl/public API","Working with TensorFlow data validation and transformation workflows that rely on tfx_bsl's internal infrastructure","Ensuring version compatibility across multiple TFX libraries by pinning tfx_bsl to match minor versions (e.g., 0.14.* for tensorflow_data_validation 0.14.*)"],"what_it_does":"tfx_bsl is a foundational library that packages shared code used across the TensorFlow eXtended ecosystem. It provides utilities, data structures, and helper functions that multiple TFX components\u2014such as TensorFlow Data Validation (TFDV), TensorFlow Model Analysis (TFMA), and TensorFlow Transform (TFT)\u2014rely on to avoid duplication and maintain consistency.\n\nThe package is designed primarily as an internal dependency rather than a direct user-facing library. Its public API (exported from tfx_bsl/public submodules) is intended for TFX pipeline authors and component developers, while other internal APIs carry no backward-compatibility guarantee. It depends on a substantial stack including apache-beam for distributed processing, tensorflow for computation, tensorflow-metadata for schema handling, and pyarrow for columnar data, making it a heavyweight but essential component of the TFX infrastructure.","worth_installing":"Yes, but typically as an indirect dependency. Install directly only if you are building custom TFX components or need specific utilities from tfx_bsl/public. The package is actively maintained, has no known vulnerabilities, and uses a permissive license. Medium install friction is acceptable given its role in the TFX ecosystem. If you are using any TFX library, it will be installed automatically."},"id":"tfx-bsl","links":{"html":"https://skillfed.io/packages/tfx-bsl","md":"https://skillfed.io/packages/tfx-bsl.md","pypi":"https://pypi.org/project/tfx-bsl/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-10","license_spdx":null,"license_treatment":"permissive","name":"tfx-bsl","python_support":"supports_current","summary":"tfx_bsl (TFX Basic Shared Libraries) contains libraries shared by many TFX (TensorFlow eXtended) libraries and components."},"popularity":{"monthly_downloads":159408,"position":10696,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.21.0"}