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:
Let's get into it!
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,
These pipeline functions are simplified to demonstrate the use case, In a real-life scenario, it would be a lot more complex.
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.
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