Key FeaturesUnderstand how to set up a Python virtual environment with PyCharmLearn functional and object-oriented approaches to create ETL pipelinesCreate robust CI/CD processes for ETL pipelinesPurchase of the print or Kindle book includes a free PDF eBookBook Description
Modern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing.
In this book, you'll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You'll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you'll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments.
By the end of this book, you'll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.
What you will learnExplore the available libraries and tools to create ETL pipelines using PythonWrite clean and resilient ETL code in Python that can be extended and easily scaledUnderstand the best practices and design principles for creating ETL pipelinesOrchestrate the ETL process and scale the ETL pipeline effectivelyDiscover tools and services available in AWS for ETL pipelinesUnderstand different testing strategies and implement them with the ETL processWho this book is for
If you are a data engineer or software professional looking to create enterprise-level ETL pipelines using Python, this book is for you. Fundamental knowledge of Python is a prerequisite.
Table of ContentsA Primer on Python and the Development EnvironmentUnderstanding the ETL Process and Data PipelinesDesign Principles for Creating Scalable and Resilient PipelinesSourcing Insightful Data and Data Extraction StrategiesData Cleansing and Transformationloading Transformed DataTutorial - Building an End-to End ETL Pipeline in PythonPowerful ETL Libraries and Tools in PythonA Primer on AWS tools for ETL ProcessesTutorial - Creating an ETL Pipeline in AWSBuilding Robust Deployment Pipelines in AWSOrchestration and Scaling in ETL PipelinesTesting Strategies for ETL pipelinesBest Practices for ETL PipelinesUse Cases and Further Reading