dagster-pandera
Integration layer for dagster and pandera.
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to 3.14); dagster and pandera must be installed as runtime dependencies.
- Low friction install with a pure Python wheel.
- Active maintenance with a recent release and strong upstream project health (15996 GitHub stars, last commit 2026-08-14).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and open-source projects without copyleft obligations.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 15,996 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 127,140 downloads/mo, #11,753 on PyPI
Alternatives
Verify before relying
pip install dagster-pandera
import dagster as dg
from dagster_pandera import pandera_asset_check
import pandera as pa
# Use pandera_asset_check decorator to validate asset outputs against a schema- Specific validation patterns and decorators available in this integration version
- Whether asset checks run inline or as separate observability steps
- Performance overhead of schema validation at orchestration time
- Support for custom Pandera validators and error handling strategies
What it is and 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.
The 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.
Use it for
- 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.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
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.
Install
dagster-pandera on PyPI
Before you install
Low friction install with a pure Python wheel. Active maintenance with a recent release and strong upstream project health (15996 GitHub stars, last commit 2026-08-14).
Requires Python 3.10 or later (supports up to 3.14); dagster and pandera must be installed as runtime dependencies.
License in practice
Apache-2.0 permissive license allows use in commercial and open-source projects without copyleft obligations.
Quickstart
pip install dagster-pandera
import dagster as dg
from dagster_pandera import pandera_asset_check
import pandera as pa
# Use pandera_asset_check decorator to validate asset outputs against a schemaVerify before relying
- Specific validation patterns and decorators available in this integration version
- Whether asset checks run inline or as separate observability steps
- Performance overhead of schema validation at orchestration time
- Support for custom Pandera validators and error handling strategies
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesdagsterpandaspandera |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 127,140 / month, #11,753 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dagster_pandera-0.29.18-py3-none-any.whl
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See also dagster · pandera · dagster-pyspark · dagster-dg-core · dagster-webserver · dagster-dbt · dagster-rest-resources · dagster-cloud-cli · dagster-aws · dagster-spark