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

Creating custom operators

As seen in the previous recipe, Creating DAGs, it is nearly impossible to create a DAG without instantiating a task or, in other words, defining an operator. Operators are responsible for holding the logic required to process data in the pipeline.

We also know that Airflow already has predefined operators, allowing dozens of ways to ingest and process data. Now, it is time to put into practice how to create custom operators. Custom operators allow us to apply specific logic to a related project or data pipeline.

You will learn how to create a simple customized operator in this recipe. Although it is very basic, you will be able to apply the foundations of this technique to different scenarios.

In this recipe, we will create a custom operator to connect to and retrieve data from the HolidayAPI, the same as we saw previously, in Chapter 2.

Getting ready

Please, refer to the Getting ready section in the Configuring Airflow recipe for this recipe...