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airflow/performance
github-actions[bot]andJarek Potiuk cfbd70b66d [main] Upgrade important CI environment (#76278)
* [main] CI: Upgrade important CI environment

* Ignore pydantic-ai's generic OpenAI-compatible provider in vendor drift checks

pydantic-ai-slim 2.63.0 adds a provider for any OpenAI-compatible endpoint. It needs a service name at construction and infer_model has no prefix for it, so a common.ai connection can never reach it and it is not a vendor the services page should list.

Generated-by: Claude Opus 5

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Jarek Potiuk <jarek@potiuk.com>
2026-11-02 19:39:05 +01:00
..

Apache Airflow Performance Testing

This package contains performance testing utilities and DAGs for Apache Airflow.

Overview

The performance testing framework generates DAGs for performance testing purposes. The number of DAGs, tasks, and their structure can be controlled through environment variables.

Environment Variables

  • PERF_DAGS_COUNT - number of DAGs to generate
  • PERF_TASKS_COUNT - number of tasks in each DAG
  • PERF_START_DATE - if not provided current time - PERF_START_AGO applies
  • PERF_START_AGO - start time relative to current time used if PERF_START_DATE is not provided. Default 1h
  • SCHEDULE_INTERVAL_ENV - Schedule interval. Default @once
  • PERF_SHAPE - shape of DAG. See DagShape. Default NO_STRUCTURE

Installation

pip install -e .

License

Apache License 2.0