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Best python xlrd Alternatives ranked by AI · updated Aug 2026

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xlrd is a Python library for reading legacy Microsoft Excel .xls files. It is aimed at developers importing spreadsheet data without requiring Excel, with support for workbook structures, formulas, dates, and formatting metadata.

Developer: Python-Excel Price: Free 🎯 github.com/python-excel/xlrd

Top 6 python xlrd alternatives

1

openpyxl

openpyxl contributors

πŸ’‘ Pick it for modern .xlsx files or when you need to edit Excel workbooks.

openpyxl is a Python library for reading and writing modern Excel .xlsx and .xlsm workbooks. It is designed for developers who need...

Pros

  • Much stronger .xlsx and .xlsm support than xlrd
  • Can create and modify workbooks, not just read them
  • Handles styles, charts, comments, merged cells, and defined names

Cons

  • Does not support legacy binary .xls files
  • Uses more memory than xlrd for large workbooks
  • Slower than table-oriented tools for bulk data analysis
2

πŸ’‘ Pick it when spreadsheet data must flow directly into analysis, cleaning, or machine-learning workflows.

Pandas is a fast, powerful, flexible, and easy-to-use open-source data analysis and manipulation tool built on top of the Python programming language....

Pros

  • Efficient data manipulation and analysis
  • Support for handling missing data
  • Integration with data visualization libraries

Cons

  • Performance can be an issue with very large datasets
  • Complex operations may require advanced knowledge
3

python-calamine

Dima Stassiuk

πŸ’‘ Pick it when you need fast, read-only support for several Excel and OpenDocument formats.

python-calamine provides Python bindings to the Rust calamine library for reading Excel and OpenDocument spreadsheets. It targets developers who need one fast...

Pros

  • Supports more spreadsheet formats than current xlrd
  • Rust-based parsing can be fast for read-heavy workloads
  • Single engine covers .xls, .xlsx, .xlsm, .xlsb, and .ods

Cons

  • Read-only and less feature-rich for workbook manipulation
  • Smaller ecosystem than pandas or openpyxl
  • Does not provide the same detailed editing model as openpyxl
4

pyxlsb

Will Trnr

πŸ’‘ Pick it specifically for lightweight, read-only imports from binary .xlsb workbooks.

pyxlsb is a Python library for reading binary Excel .xlsb workbooks. It is aimed at developers importing data from large binary spreadsheets...

Pros

  • Reads .xlsb files, which xlrd and openpyxl do not support
  • Stream-oriented access can reduce memory pressure
  • Simple API for iterating through sheets and rows

Cons

  • Supports only .xlsb rather than the broader Excel format range
  • Read-only with limited workbook metadata and formatting support
  • Less actively developed than pandas or openpyxl
5

pyexcel

pyexcel contributors

πŸ’‘ Pick it when you want one simple API for exchanging tabular data across multiple spreadsheet formats.

pyexcel is a Python interface for reading and writing spreadsheet-like data through a common API. It is for developers who want format-independent...

Pros

  • Offers a consistent API across multiple spreadsheet formats
  • Supports both reading and writing through a plugin architecture
  • Simpler for basic tabular exchange than cell-level workbook libraries

Cons

  • Excel format support depends on separately installed plugins
  • Less capable than openpyxl for styles, charts, and workbook structure
  • Smaller community and ecosystem than pandas
6

tablib

Tablib contributors

πŸ’‘ Pick it for straightforward table serialization in applications, not for preserving complex Excel workbooks.

Tablib is a Python library for exporting and importing tabular datasets in formats including XLSX, CSV, JSON, and YAML. It is aimed...

Pros

  • Very simple dataset-oriented API
  • Supports multiple import and export formats through one interface
  • Useful for web applications and APIs handling tabular records

Cons

  • Does not provide the detailed cell and workbook access available in xlrd
  • Limited support for complex Excel formatting and formulas
  • Less suitable for large or heavily structured workbooks

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