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PROJECT
Build a News ETL Data Pipeline Using Python and SQLite
In this project, we’ll learn how to build an extract, transform, and load (ETL) data pipeline in Python to extract data from News API, transform it, and then load it into an SQLite database. We’ll also learn how to automate the pipeline using Airflow in Python.
You will learn to:
Create an ETL news data pipeline.
Extract data from News API.
Load the data into an SQLite database.
Automate the entire ETL pipeline using Apache Airflow.
Skills
Data Pipeline Engineering
Data Extraction
Data Manipulation
Data Cleaning
Data Engineering
Prerequisites
Intermediate knowledge of Python programming language
Understanding of data wrangling using pandas
Basic knowledge of database management
Basic knowledge of Apache Airflow
Technologies
Pandas
SQLite
Project Description
Extract, transform, and load (ETL) is a process in data warehousing and data integration where data is extracted from different source systems, transformed into a more suitable format, and then loaded into a target database or data warehouse. The ETL process is a fundamental step in data integration and plays a vital role in ensuring that data is accurate, consistent, and ready for analysis.
SQLite is a lightweight, serverless, and self-contained relational database management system (RDBMS). It’s known for its simplicity and ease of use. It’s used as an embedded system in smart TVs and IoT devices. It’s also used to power web browsers like Google Chrome and Mozilla Firefox to manage and store data, such as bookmarks, history, etc.
In this hands-on project, we’ll delve into the world of data engineering by building an ETL pipeline for news data. The primary goal is to extract news data from News API, which is in a semi-structured format (JSON), transform it into a structured format, and load it into an SQLite database. Furthermore, we’ll explore the automation of this pipeline using Apache Airflow.
The final implementation of the project will transform data from an unstructured format to a structured one, as illustrated below.
Project Tasks
1
Get Started
Task 0: Introduction
Task 1: Import Libraries and Connect to News API
Task 2: Retrieve and Print News Articles
2
Data Transformation
Task 3: Clean Author Column
Task 4: Transform News Data
3
Data Loading
Task 5: Load the Data into SQLite Database
4
Automate News ETL with Airflow
Task 6: Initialize the DAG object
Task 7: Transfer Data Using XComs
Task 8: Create DAG Operators
Task 9: Error Handling and Best Practices
Task 10: Congratulations!
Relevant Courses
Use the following content to review prerequisites or explore specific concepts in detail.