Book Image

Data Ingestion with Python Cookbook

By : Gláucia Esppenchutz
Book Image

Data Ingestion with Python Cookbook

By: Gláucia Esppenchutz

Overview of this book

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges. You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation. By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process.
Table of Contents (17 chapters)
1
Part 1: Fundamentals of Data Ingestion
9
Part 2: Structuring the Ingestion Pipeline

Configuring logs in airflow.cfg

We had our first contact with the airflow.cfg file in the Storing log files in a remote location recipe. At a glance, we saw how powerful and handy this configuration file is. There are many ways to customize and improve Airflow just by editing it.

This exercise will teach how you to enhance your logs by setting applicable configurations in the airflow.cfg file.

Getting ready

Refer to the Technical requirements section for this recipe, since we will handle it with the same technology.

Airflow DAG code

To avoid redundancy and focus on the goal of this recipe, which is to configure remote logging in Airflow, we will use the same DAG as the Creating basic logs in Airflow recipe. However, feel free to create another DAG with a different name but the same code.

How to do it…

Since we will use the same DAG code from Creating basic logs in Airflow, let’s jump right to the required configuration to format our logs...