├── .DS_Store ├── Building Data Engineering Pipelines in Python ├── .DS_Store ├── Exercises │ ├── .ipynb_checkpoints │ │ └── Chapter 1 - Ingesting Data-checkpoint.ipynb │ ├── Chapter 1 - Ingesting Data.ipynb │ └── data │ │ └── chapter_1 │ │ ├── database_config.json │ │ └── ingest │ │ ├── data_lake.conf │ │ └── marketing_tap │ │ ├── setup.py │ │ ├── tap_marketing_api.egg-info │ │ ├── PKG-INFO │ │ ├── SOURCES.txt │ │ ├── dependency_links.txt │ │ ├── entry_points.txt │ │ ├── requires.txt │ │ └── top_level.txt │ │ └── tap_marketing_api.py └── Slides │ ├── Chapter 1 - Ingesting Data.pdf │ ├── Chapter 2 - Creating a data transformation pipeline with PySpark.pdf │ ├── Chapter 3 - Testing your data.pdf │ └── Chapter 4 - Managing and orchestrating a workflow.pdf ├── Data Engineering for Everyone ├── .DS_Store ├── Exercises │ ├── .DS_Store │ ├── Chapter 1 - What is data engineering?.md │ ├── Chapter 2 - Storing data.md │ ├── Chapter 3 - Moving and processing data.md │ └── images │ │ └── img1.png └── Slides │ ├── Chapter 1 - What is data engineering?.pdf │ ├── Chapter 2 - Storing data.pdf │ └── Chapter 3 - Moving and processing data.pdf ├── Data Processing in Shell ├── .DS_Store └── Exercises │ ├── Chapter 1 - Downloading Data on the Command Line.pdf │ ├── Chapter 2 - Data Cleaning and Munging on the Command Line.pdf │ ├── Chapter 3 - Database Operations on the Command Line.pdf │ └── Chapter 4 - Data Pipeline on the Command Line.pdf ├── Introduction to Airflow in Python ├── .DS_Store └── Slides │ ├── Chapter 1 - Intro to Airflow.pdf │ ├── Chapter 2 - Implementing Airflow DAGs.pdf │ ├── Chapter 3 - Maintaining and monitoring Airflow workflows.pdf │ └── Chapter 4 - Building production pipelines in Airflow.pdf ├── Introduction to Bash Scripting ├── .DS_Store └── Slides │ ├── Chapter 1 - From Command-Line to Bash Script.pdf │ ├── Chapter 2 - Variables in Bash Scripting.pdf │ ├── Chapter 3 - Control Statements in Bash Scripting.pdf │ └── Chapter 4 - Functions and Automation.pdf ├── Introduction to Data Engineering ├── .DS_Store └── Slides │ ├── Chapter 1 - Introduction to Data Engineering.pdf │ ├── Chapter 2 - Data engineering toolbox.pdf │ ├── Chapter 3 - Extract, Transform and Load.pdf │ └── Chapter 4 - Case Study_DataCamp.pdf ├── LICENSE ├── Object-Oriented Programming in Python ├── Chapter 1 - OOP Fundamentals.pdf ├── Chapter 2 - Inheritance and Polymorphism.pdf ├── Chapter 3 - Integrating with Standard Python.pdf └── Chapter 4 - Best Practices of Class Design.pdf ├── README.md ├── Streamlined Data Ingestion with pandas ├── .DS_Store └── Slides │ ├── Chapter 1 - Importing Data From Flat Files.pdf │ ├── Chapter 2 - Importing Data From Excel Files.pdf │ ├── Chapter 3 - Importing Data From Databases.pdf │ └── Chapter 4 - Importing JSON Data and Working with APIs.pdf ├── Unit Testing for Data Science in Python ├── .DS_Store └── Slides │ ├── Chapter 1 - Unit testing basics.pdf │ ├── Chapter 2 - Intermediate unit testing.pdf │ ├── Chapter 3 - Test Organization and Execution.pdf │ └── Chapter 4 - Test Models, Plots and Much More.pdf ├── Writing Efficient Python Code ├── .DS_Store └── Slides │ ├── Chapter 1 - Foundations for efficiencies.pdf │ ├── Chapter 3 - Gaining efficiencies.pdf │ ├── Chapter 4 - Basic pandas optimizations.pdf │ └── Chpater 2 - Timing and profiling code.pdf └── Writing Functions in Python ├── .DS_Store └── Slides ├── Chapter 1 - Best Practices.pdf ├── Chapter 2 - Context Managers.pdf ├── Chapter 3 - Decorators.pdf └── Chapter 4 - More on Decorators.pdf /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Wathon/data_engineering_with_python-track-datacamp/HEAD/.DS_Store -------------------------------------------------------------------------------- /Building Data Engineering Pipelines in Python/.DS_Store: -------------------------------------------------------------------------------- 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