ExStruct FAQs

Question 1

What is ExStruct and what is its primary purpose?

Accepted Answer

ExStruct is a powerful Python library and CLI tool designed to transform complex Excel workbooks into highly structured JSON, YAML, or TOON formats. Its primary purpose is to enable seamless integration of Excel data into Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) pipelines, enhancing data usability for AI.

Question 2

What are the output formats supported by ExStruct, and can it render files?

Accepted Answer

ExStruct supports output in JSON (compact or pretty), YAML, and TOON formats. Additionally, when Excel is available, it can optionally render Excel sheets to PDF documents and per-sheet PNG images, providing visual representations alongside structured data.

Question 3

What types of data can ExStruct extract from an Excel workbook?

Accepted Answer

ExStruct can extract a comprehensive range of elements including cells, table candidates, shapes, charts, SmartArt, merged cell ranges, print areas, auto page-break areas, hyperlinks, and formula maps. It offers 'light', 'standard', and 'verbose' output modes for varying levels of detail.

Question 4

Does ExStruct require Microsoft Excel to be installed?

Accepted Answer

Full extraction of elements like shapes and charts requires Windows with Microsoft Excel (COM via xlwings). However, ExStruct gracefully falls back to basic extraction (cells + table candidates) using openpyxl if Excel COM is unavailable, allowing it to function in non-COM environments.

Question 5

Can ExStruct help with optimizing table detection in Excel files?

Accepted Answer

Yes, ExStruct provides tunable table detection heuristics, allowing users to adjust parameters like score threshold, density, and coverage. This enables optimization of accuracy for diverse datasets, ensuring that true tables are correctly identified while reducing false positives.

ExStruct

ExStruct

Key Features

Use Cases

Key Features

Use Cases