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

Inserting logs

As mentioned in the introduction of this chapter, adding logging functionality to your applications is essential for debugging or making improvements later on. However, creating several log messages without necessity may generate confusion or even cause us to miss crucial alerts. In any case, knowing which kind of message to show is indispensable.

This recipe will cover how to create helpful log messages using Python and when to insert them.

Getting ready

We will use only Python code. Make sure you have Python version 3.7 or above. You can use the following command to check it on your command-line interface (CLI):

$ python3 –-version
Python 3.8.10

The following code execution can be done on a Python shell or a Jupyter notebook.

How to do it…

To perform this exercise, we will make a function that reads and returns the first line of a CSV file using the best logging practices. Here is how we do it:

  1. First, let’s import the...