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Apache Airflow ETL Pipeline Built with Docker and Open-Meteo

By PulseAugur Editorial · [1 sources] ·

This guide provides a detailed, step-by-step walkthrough for constructing an Extract, Transform, Load (ETL) pipeline using Apache Airflow. It covers setting up the environment with Docker Compose, integrating with the Open-Meteo API for data extraction, transforming the data, and loading it into a PostgreSQL database. The tutorial addresses practical aspects like API hostname resolution, data passing between tasks via XCom, and database verification, aiming to answer common questions that arise when implementing Airflow workflows. AI

IMPACT Provides a practical guide for building data pipelines, a foundational task for many AI/ML workflows.

RANK_REASON The article describes how to build a specific data pipeline using existing tools, rather than announcing a new product or research.

Read on Towards AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Apache Airflow ETL Pipeline Built with Docker and Open-Meteo

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The article describes how to build a specific data pipeline using existing tools, rather than announcing a new product or research.
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COVERAGE [1]

  1. Towards AI TIER_1 English(EN) · Faizulkhan ·

    Building a Complete Apache Airflow ETL Pipeline with Docker, Open-Meteo, and PostgreSQL

    <p>A theory-inclusive, step-by-step guide to workflow orchestration, Airflow Connections, XCom, Docker Compose deployment, PostgreSQL loading, monitoring, troubleshooting, and database verification.</p><p>Apache Airflow is often introduced with a short example: define a DAG, add …

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