airflow.providers.standard.example_dags.example_measurement_correction_decorator

Tutorial example Dag: measurement correction storyline (TaskFlow).

This Dag is part of the “Examples Refurbish” storyline and is meant to be a short, didactic walkthrough of a typical scientific or industrial data pipeline. It demonstrates the TaskFlow API on a self-contained workflow that:

  1. reads a raw measurement,

  2. validates it,

  3. applies a correction factor,

  4. stores the corrected result.

The Dag has no external dependencies (no connections, no datasets, no hooks), so it parses and runs out of the box. Pair it with example_measurement_correction_operator.py to compare TaskFlow and the classic PythonOperator style on the exact same storyline.

Attributes

DAG_DOC_MD

Functions

measurement_correction_decorator()

Tutorial Dag: read, validate, correct, and store a measurement.

Module Contents

airflow.providers.standard.example_dags.example_measurement_correction_decorator.DAG_DOC_MD = Multiline-String[source]
Show Value
"""
### Measurement correction (TaskFlow)

Tutorial Dag showing a minimal "read, validate, correct, store" measurement
pipeline implemented with the TaskFlow API.

**Storyline**

1. `read_measurement` produces a raw value coming from a fictional sensor.
2. `validate_measurement` rejects negative values.
3. `apply_correction` multiplies the value by a calibration factor.
4. `store_result` logs the corrected value (the real Dag would persist it).

**When to use this example**

- Learning the TaskFlow API on a single, linear pipeline.
- As a reference shape for new "tutorial" example Dags following the
  [example Dag review checklist](
  https://github.com/apache/airflow/blob/main/contributing-docs/28_example_dag_review_checklist.rst).
"""
airflow.providers.standard.example_dags.example_measurement_correction_decorator.measurement_correction_decorator()[source]

Tutorial Dag: read, validate, correct, and store a measurement.

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