pyexcel vs openpyxl

Side-by-side — pricing, strengths, tradeoffs, and fit.

pyexcel

Unified API for handling CSV and spreadsheet files in Python.

openpyxl

Library for reading and writing Excel files in Python.

At a glance

Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
· Not enough data·From $0

Overview

One-liner

Unified API for handling CSV and spreadsheet files in Python.

One-liner

Library for reading and writing Excel files in Python.

Maturity

Established

Maturity

Not enough data

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Developers working with multiple spreadsheet file types who need a unified API for handling and manipulating data.
Projects requiring conversion between CSV, ODS, XLS, XLSX, and XLSM formats.

✓ Best for

Developers who need to automate tasks involving Excel files without requiring Microsoft Office installed
Data scientists working with datasets stored in Excel format for analysis and reporting
Automation scripts that require reading from or writing to Excel spreadsheets

Not ideal for

✕ Not for

Applications that require real-time collaboration on spreadsheets
Complex data analysis tasks that benefit from specialized libraries

✕ Not for

Projects requiring real-time collaboration features within Excel documents
Users who need advanced Excel functionalities not supported by openpyxl, such as macros execution

Strengths

↑ Strengths

Unified API for multiple file formats
Simplified data manipulation across different spreadsheet types
Extensive support for CSV and various spreadsheet formats

↑ Strengths

Read and write Excel files (.xlsx, .xlsm, .xltx, .xltm)
Support for rich text formatting
Ability to create charts within Excel spreadsheets
Support for named ranges

Weaknesses

↓ Weaknesses

Limited documentation and examples
Performance issues with large datasets
Dependency on external libraries for file formats
Small community and limited support

↓ Weaknesses

Limited documentation and examples
Performance issues with large Excel files
Complex setup for advanced features like charts and formatting
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