Use Tablib to Handle Simple Tabular Data in Python
Author:Murphy | View: 26853 | Time: 2025-03-22 19:29:40
Overview
- Introduction – What is Tablib?
- Working with Datasets
- Importing Data
- Exporting Data
- Dynamic Columns
- Formatters
- Wrapping Up
Introduction – What is Tablib?
For many years I have been working with tools like Pandas and PySpark in Python for Data Ingestion, data processing, and data exporting. These tools are great for complex data transformations and big data sizes (Pandas when the data fits in memory). However, often I have used these tools when the following conditions apply:
- The data size is relatively small. Think well below 100,000 rows of data.
- Performance is not an issue at all. Think of a one-off job or a job that repeats at midnight every night, but I don't care if it takes 20 seconds or 5 minutes.
- There are no complex transformations needed. Think of simply importing 20 JSON files with the same format, stacking them on top of each other, and then exporting this as a CSV file.
In these cases, tools like Pandas and (especially) PySpark are like shooting a fly with a canon. In these cases, the library Tablib is perfect
