Canva VS python xlrd

• Document Creation
  Writing AI
• Custom Prints
  Over 30 products to pick from
• Presentations
  magic shortcuts, animations, recording
• Websites
  Performance Tracking
• Video Editor
  One-click video background remover, animations
• Social Media Content Creation
  Resizing options, content planner
• Whiteboards
  Flowcharts, planning, and brainstorming
• HEIC to JPG Converter
  Convert HEIC to JPG to easily share images on any platform or device using Canva's HEIC to JPG converter
• PDF to JPG Converter
  Convert PDF to JPG to easily share images on any platform or device using Canva's PDF to JPG Converter

• Simplicity
  xlrd provides a straightforward and easy-to-use API for reading Excel files, making it accessible for beginners and quick implementations.
• Widely Used
  xlrd has been a popular choice for handling Excel files in Python, which means there is a lot of available documentation and community support.
• Efficient Reading
  It is optimized for reading data from Excel files without loading entire data into memory, which is beneficial for handling large files.

Possible disadvantages

• No Write Support
  xlrd is designed solely for reading, and it does not support writing or modifying Excel files.
• Limited to Older Excel Formats
  With version 2.0 and above, xlrd only supports the older .xls Excel file format and does not support .xlsx files.
• Deprecated Features
  Due to changes in dependencies and updates to Excel formats, some features in xlrd have become deprecated or removed, which can limit its functionality.

Canva Review

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• I need to read multiple excel files, extract a column from each and compose a new file

  So to get this out of the way first, xlrd has less features than openpyxl and in addition only works with the old '.xls' format, not the newer '.xlsx' format. Even on the xlrd's Github repo it says: 'Please use openpyxl where you can... '. Source: over 4 years ago

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  There are few alternative libraries for reading and writing excel files: Pandas, Xlrd , openpyxl among others. In the end I settled for openpyxl as I had the most experience Using it and it had support for .xlsx files. - Source: dev.to / over 5 years ago