{"categories":[{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks/5"}],"enrichment":{"capability":"Integrates Pandera data validation with Dagster's asset orchestration, enabling schema validation checks within data pipeline workflows.","skillfed_tags":["data-validation","orchestration","schema-checking"],"use_cases":["Validate DataFrame outputs from Dagster assets match expected column names, types, and nullable constraints before passing to downstream tasks.","Catch data quality regressions early by running Pandera schema checks as part of asset materialization in a Dagster pipeline.","Enforce schema contracts across team-owned data assets in a shared Dagster instance without duplicating validation logic.","Build reusable schema definitions in Pandera and apply them consistently across multiple Dagster assets in the same project.","Flag data anomalies (missing columns, type mismatches, constraint violations) in production pipelines with Dagster's observability."],"what_it_does":"dagster-pandera is a bridge between two Python data tools: Dagster (a declarative data orchestrator) and Pandera (a schema validation library). It lets you attach Pandera schema checks to Dagster assets, so your data pipeline can validate that outputs match expected column types, constraints, and structure before downstream tasks consume them.\n\nThe package is maintained as part of the Dagster project and provides decorators or asset checks that integrate Pandera's validation rules into Dagster's asset graph. Rather than writing separate validation logic, you define a Pandera schema once and apply it to your Dagster assets, combining orchestration and data quality in a single declarative model. It assumes you are already using both Dagster for pipeline management and Pandera for schema definition.","worth_installing":"Yes, if you are already using both Dagster and Pandera. The integration is actively maintained, has no known vulnerabilities, and low install friction. It is worth installing to avoid writing custom validation wrappers. If you use only Dagster or only Pandera, this package adds no value."},"id":"dagster-pandera","links":{"html":"https://skillfed.io/packages/dagster-pandera","md":"https://skillfed.io/packages/dagster-pandera.md","pypi":"https://pypi.org/project/dagster-pandera/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-14","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"dagster-pandera","python_support":"supports_current","summary":"Integration layer for dagster and pandera."},"popularity":{"monthly_downloads":127140,"position":11753,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.29.18"}