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

Scheduling daily ingestions

Data constantly changes in our dynamic world, with new information being added every day and even every second. Therefore, it is crucial to regularly update our data lake to reflect the latest scenarios and information.

Managing multiple projects or pipelines concurrently and manually triggering them while integrating new data from various sources can be daunting. To alleviate this issue, we can rely on schedulers, and Airflow provides a straightforward solution for this purpose.

In this recipe, we will create a simple Directed Acyclic Graph (DAG) in Airflow and explore how to use its parameters to schedule a pipeline to run daily.

Getting ready

Please refer to the Technical requirements section for this recipe since we will handle it with the same technology mentioned here.

In this exercise, we will create a simple DAG. The structure of your Airflow folder should look like the following:

Figure 11.3 – daily_ingestion_dag DAG folder structure

Figure 11.3 – daily_ingestion_dag...