AWS Made Easy with Boto3
If you’re a starting out as a Data Engineer and using AWS, then life gets a whole lot easier with the use of Boto3, the AWS SDK for Python. Boto3 simplifies integration of your Python applications, libraries, or scripts with AWS services like Amazon S3, EC2, DynamoDB and more. Well, that’s what the documentation says. […]
Getting Started with Python Exception Handling
The errors that occur during the execution of a Python program are called exceptions. Examples of exceptions include dividing by zero, combining objects of incompatible types, and many others. Some exceptions have specific names, such as ZeroDivisionError and TypeError. If exceptions are not handled properly, they can halt the entire execution of the program. This […]
Exploring the Ins and Outs of Taming Big Data with Apache Spark and Python: A Review of the Hands-On Udemy Course
I recently completed the course “Taming Big Data with Apache Spark and Python – Hands On!” on Udemy, taught by Frank Kane. I wanted to share my thoughts on the course and provide my opinions on what I enjoyed and what I didn’t like as much. My thoughts If you are already familiar with Spark […]
Why Every Data Engineer Needs Jupyter Notebooks in Their Toolkit
Jupyter Notebooks are an important part of my daily routine, whether for work or personal projects. They have been incredibly useful to me and I can’t imagine being a Data Engineer without them. Best thing is, it’s easy to get started with it. You can use it by downloading JupyterLab or accessing it through your […]
The Key Files for a Smooth-Running Python Project
The three key files in a Python project are the Docker file, the Makefile, and the requirements.txt. Makefile The Makefile is particularly important because it allows you to automate various steps in your project, such as installation, deployment, and linting. Essentially, the Makefile acts like a set of recipes that help you streamline your work […]