Openpyxl vs. Xlrd

Attribute	Openpyxl	Xlrd
Reading Excel files	Yes	Yes
Writing Excel files	Yes	No
Support for Excel formats	.xlsx, .xlsm, .xltx, .xltm	.xls
Compatibility with Python versions	Python 2.7, 3.4+	Python 2.6, 2.7, 3.3+
Active development	Yes	No

Introduction

When it comes to working with Excel files in Python, two popular libraries that come to mind are Openpyxl and Xlrd. Both libraries provide functionalities to read, write, and manipulate Excel files, but they have some key differences in terms of features and ease of use. In this article, we will compare the attributes of Openpyxl and Xlrd to help you decide which one is best suited for your needs.

Installation

One of the first things to consider when choosing between Openpyxl and Xlrd is the installation process. Openpyxl can be easily installed using pip, a package manager for Python. You can simply run the commandpip install openpyxl to install Openpyxl. On the other hand, Xlrd requires a bit more effort to install, as it has dependencies that need to be installed separately. You will need to run the commandpip install xlrd as well as install the required dependencies manually.

Reading Excel Files

Both Openpyxl and Xlrd provide functionalities to read data from Excel files, but they have different approaches. Openpyxl is more focused on creating and modifying Excel files, so reading data from existing files can be a bit more complex compared to Xlrd. Xlrd, on the other hand, is specifically designed for reading data from Excel files, making it easier to extract information such as cell values, formulas, and formatting.

Writing Excel Files

When it comes to writing data to Excel files, Openpyxl shines with its easy-to-use API. You can create new Excel files, add worksheets, and populate cells with data using simple commands. Openpyxl also provides functionalities to format cells, add charts, and apply styles to the data. On the other hand, Xlrd is primarily focused on reading data from Excel files, so it lacks the ability to write data to Excel files directly.

Compatibility

Another important factor to consider when choosing between Openpyxl and Xlrd is compatibility with different versions of Excel files. Openpyxl supports both .xlsx and .xlsm file formats, which are the default formats for Excel files created in recent versions of Microsoft Excel. Xlrd, on the other hand, has limited support for .xlsx files and does not support .xlsm files, which can be a drawback if you need to work with files created in newer versions of Excel.

Performance

When it comes to performance, Openpyxl and Xlrd have different strengths and weaknesses. Openpyxl is known for its speed and efficiency when working with large Excel files, making it a good choice for processing complex data sets. On the other hand, Xlrd can be slower when reading data from Excel files, especially when dealing with files that contain a large number of rows and columns. It is important to consider the size of your Excel files and the complexity of the data when choosing between Openpyxl and Xlrd.

Community Support

Community support is another important aspect to consider when choosing between Openpyxl and Xlrd. Openpyxl has a large and active community of developers who contribute to the library, provide support, and regularly release updates and bug fixes. This means that you are more likely to find solutions to any issues you encounter while using Openpyxl. Xlrd, on the other hand, has a smaller community of developers and may not receive updates and support as frequently as Openpyxl.

Conclusion

In conclusion, both Openpyxl and Xlrd have their own strengths and weaknesses when it comes to working with Excel files in Python. Openpyxl is a great choice if you need to create, modify, and format Excel files, while Xlrd is more suitable for reading data from existing Excel files. Consider factors such as installation process, reading and writing capabilities, compatibility, performance, and community support when choosing between Openpyxl and Xlrd to ensure that you select the library that best meets your requirements.