Building ETL Pipelines with Python: Create and deploy enterprise-ready ETL pipelines by employing modern methods

Develop production-ready ETL pipelines by leveraging Python libraries and deploying them for suitable use cases

Key Features:

• Understand how to set up a Python virtual environment with PyCharm
• Learn functional and object-oriented approaches to create ETL pipelines
• Create robust CI/CD processes for ETL pipelines
• Purchase of the print or Kindle book includes a free PDF eBook

Book 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 Learn:

• Explore the available libraries and tools to create ETL pipelines using Python
• Write clean and resilient ETL code in Python that can be extended and easily scaled
• Understand the best practices and design principles for creating ETL pipelines
• Orchestrate the ETL process and scale the ETL pipeline effectively
• Discover tools and services available in AWS for ETL pipelines
• Understand different testing strategies and implement them with the ETL process

Who 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.

利用Python函式庫開發可用於適當使用案例的生產就緒ETL流程

主要特點:
- 了解如何使用PyCharm建立Python虛擬環境
- 學習使用函數式和物件導向方法來創建ETL流程
- 建立強大的CI/CD流程用於ETL流程
- 購買印刷版或Kindle電子書將包含免費的PDF電子書

書籍描述:
現代的數據工程ETL流程傾向於使用Python語言，因為它具有廣泛的用途和大量的工具、應用程序和開源組件。由於其簡單性和廣泛的庫支持，Python已成為數據處理的無可爭議的選擇。

在本書中，您將逐步了解ETL數據流程開發的全過程，從數據流程的基礎知識入門，建立Python開發環境以創建流程開始。一旦您瞭解了ETL流程設計原則和ET開發過程，您將能夠設計自定義的ETL流程。接下來，您將瞭解ETL流程中的步驟，包括提取有價值的數據；進行轉換，通過清理、操作和確保數據完整性；最終將處理後的數據加載到存儲系統中。您還將回顧Python中的幾個ETL模塊，比較它們在構建數據流程和利用AWS等雲工具時的優缺點。最後，您將學習ETL流程的測試驅動開發概念，以確保安全部署。

通過閱讀本書，您將通過幾個實例來創建高性能的ETL流程，以使用Python開發堅固、可擴展和可靠的環境。

您將學到什麼:
- 探索可用的庫和工具，使用Python創建ETL流程
- 編寫乾淨且堅固的Python ETL代碼，可擴展且易於擴展
- 瞭解創建ETL流程的最佳實踐和設計原則
- 編排ETL流程並有效擴展ETL流程
- 探索AWS中可用的用於ETL流程的工具和服務
- 瞭解不同的測試策略並在ETL流程中實施

本書適合對使用Python創建企業級ETL流程的數據工程師或軟件專業人士。需要具備Python的基礎知識。