How To Create a Python Data Engineering Project with a Pipeline Pattern

How To Create a Python Data Engineering Project with a Pipeline Pattern

In this article, we cover how to use pipeline patterns in python data engineering projects. Create a functional pipeline, install fastcore, and other steps.

In this article, we cover how to use pipeline patterns in python data engineering projects. Here are the steps:

  1. Functional pipeline
  2. fastcore
  3. Install fastcore
  4. Creating pipeline using fastcore
  5. Dynamic pipeline using fastcore

Let's get into it!

Functional pipeline

The functional pipeline is a design pattern mostly used in the functional programming paradigm, where data flows through a sequence of stages and the output of the previous stage is the input of the next. Each step can be thought of as a filter operation that transforms the data in some way.

This pattern is most suitable for map, filter and reduces operations. It also provides a clean, readable and more sustainable code in data engineering projects.

For example, let's take an input text which has to go through a series of transformations,

  1. Remove white spaces
  2. Remove special characters
  3. Lowercase all letters
  4. and finally produces output.

These pipeline functions are simplified to demonstrate the use case, In a real-life scenario, it would be a lot more complex.

python nlp data-engineering

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Basic Data Types in Python | Python Web Development For Beginners

In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.

Data Science With Python Training | Python Data Science Course | Intellipaat

🔵 Intellipaat Data Science with Python course: https://intellipaat.com/python-for-data-science-training/In this Data Science With Python Training video, you...

Managing Data as a Data Engineer:  Understanding Data Changes

Understand how data changes in a fast growing company makes working with data challenging. In the last article, we looked at how users view data and the challenges they face while using data.

Managing Data as a Data Engineer — Understanding Users

Understanding how users view data and their pain points when using data. In this article, I would like to share some of the things that I have learnt while managing terabytes of data in a fintech company.

Intro to Data Engineering for Data Scientists

Intro to Data Engineering for Data Scientists: An overview of data infrastructure which is frequently asked during interviews