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

Connecting to a NoSQL database (MongoDB)

MongoDB is an open source, unstructured, document-oriented database made in C++. It is well known in the data world for its scalability, flexibility, and speed.

As someone who will work with data (or maybe already does), it is essential to know how to explore a MongoDB (or any other unstructured) database. MongoDB has some peculiarities, which we will explore practically here.

In this recipe, you will learn how to create a connection to access MongoDB documents via Studio 3T Free, a MongoDB GUI.

Getting ready

To start our work with this robust database, first, we need to install and create a MongoDB server on our local machine. We already configured a MongoDB Docker container in Chapter 1, so let’s get it up and running. You can do this using Docker Desktop or via the command line using the following command:

my-project/mongo-local$ docker run \
--name mongodb-local \
-p 27017:27017 \
-e MONGO_INITDB_ROOT_USERNAME=<your_username...