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Vergleich von Python-Excel-Bibliotheken (kostenlose & kostenpflichtige Tools)

The installation of Python packages is quite effective and efficient for handling file formats like Office Open XML. Developers can read and modify XLSX or XLS files programmatically, which is very handy in terms of working with data analysis, report generation, or any other Excel file manipulation task such as writing data. The popular libraries supporting that kind of work feature unique features, including writing formulas or formatting cells, as well as handling large datasets. These libraries are rather easy to use and integrate nicely into applications using Python, so they bring efficiency and productivity to the workflow. In this article, we are going to see some of the Python XLSX Excel libraries.

openpyxl

openpyxl is a Python package that allows the handling of existing Excel files in the current default format for Microsoft Excel, which since 2007 has simply been .XLSX. An Excel file can be programmatically built by making, reading, modifying, and writing new files. With openpyxl, most types of work with Excel files can be automated: formatting cells, adding formulas, working with charts, handling multiple sheets in one workbook, and so on.

Thus, the library provides data validation, conditional formatting, writing data over, and handling of huge datasets or large files, making it an indispensable tool for the automation of Excel file manipulation and integration of spreadsheet functionality into Python applications.

XlsxWriter

The XlsxWriter library for Python is the standard module for writing files and producing Excel files in the XLSX file format. The module has many features for data writing, cell formatting, and advanced features of Excel spreadsheets such as charts, conditional formatting, and images. This utility is perfect for report generation, automating Excel tasks, and highly-formatted production of an Excel file.

One of its significant advantages is the efficient writing of large datasets. It creates only new files in Excel, not opening the ones already existing for reading or modification. So, it will be useful where you need to create new Excel files from scratch.

pylightxl

pylightxl is a module of Python for handling spreadsheets in .XLSX format excellently. Lightweight and minimalist to read Excel files or write an Excel spreadsheet, it cuts down on the complexity usually involved with feature-rich libraries. This module offers core functionalities in handling data in Excel like access to cells and rows of columns.

pylightxl would be best for a user who requires support for the basic operations of Excel on their files but has no need for extensive formatting or charting capabilities. Indeed, its lightweight nature will ensure swift installation as well as integration into your Python applications; it is therefore ideal for situations where simplicity and speed predominate. With pylightxl, developers can handle their Excel data efficiently yet sidestep the overhead of more complex solutions.

pyxlsb

The pyxlsb package reads Microsoft Excel files in .XLSB format. Because this assignment was based on the function of doing that, it is not standardized to nearly the same extent as the very similar file format .XLSX since it is a binary structure used in the storage of data. Then, applications coded in Python can open the .XLSB files without proprietary applications like Microsoft Excel so it can deal with hundreds of datasets or intricate spreadsheets.

The best approach for scenarios where one needs to extract .XLSB files for analysis, reporting, or import to other systems would be a library that reads the data directly from the binary Excel file and then works directly with it. More generally, other libraries would be better suited to more widely used formats such as .XLSX, and it's far from the best suited to process binary format files.

IronXL

IronXL is a full-featured Python/.NET library for opening and writing Excel files in both .XLSX as well as .XLS format. The library will provide the utmost features as possible in creating, reading, and manipulating spreadsheets, so developers can build their automation on top of all things that can be done with Excel without installing Microsoft Excel. Any operation—from data input, and formula calculations to charting, and finally formatting—can be done easily with IronXL. It also helps us in handling Excel files in multiple ways.

Python Excel Library Comparison (Free & Paid Tools): Figure 5 - IronXL

Data validation, conditional formatting, and big datasets are all supported in the library, thus making it apt for both simple and complex spreadsheet-related work. Since IronXL supports compatibility with Python/.NET, direct integration into a .NET application to a Python one is possible and gives a strong solution for the automated management of Excel files. Cross-platform capabilities and rich features make it a versatile choice for developers if they may need to incorporate the functionalities of Excel into other versions of their software solutions.

Below is the sample code to create a new Excel file using IronXL.

from ironxl import WorkBook  # Import the WorkBook module from IronXL

# Create a new Excel WorkBook object
workbook = WorkBook.Create()

# Create a blank WorkSheet named "new_sheet"
worksheet = workbook.CreateWorkSheet("new_sheet")

# Write data into the Excel file
worksheet["A1"].Value = "Hello World"

# Save the Excel file as an XLSX file
workbook.SaveAs("Demo.xlsx")
from ironxl import WorkBook  # Import the WorkBook module from IronXL

# Create a new Excel WorkBook object
workbook = WorkBook.Create()

# Create a blank WorkSheet named "new_sheet"
worksheet = workbook.CreateWorkSheet("new_sheet")

# Write data into the Excel file
worksheet["A1"].Value = "Hello World"

# Save the Excel file as an XLSX file
workbook.SaveAs("Demo.xlsx")
PYTHON

This code creates a new Excel workbook along with a worksheet named "new_sheet" using IronXL. The code then adds the text "Hello World" into cell A1 and saves the workbook under the name "Demo.xlsx" in the .XLSX file format. It also supports other file formats for saving.

Conclusion

In summary, openpyxl and XlsxWriter stand out from other traditional libraries for handling Excel files due to their Python foundation, which sets them apart from IronXL. openpyxl and XlsxWriter can create, write, and read Excel files; openpyxl is more suitable when trying to read and manipulate existing files, while XlsxWriter is more targeted at feature-rich file creation.

In that regard, IronXL is noteworthy since it supports importing all types of Excel files and allows formula calculations, and complex formatting possibilities akin to Excel. Your choices depend on your necessities. For example, if you require native Python-based solutions, then openpyxl and XlsxWriter would be ideal. In contrast, if your application needs to merge with .NET and use extensive Excel features and functionalities, then IronXL would be the best choice.

You're definitely well-versed in the fact that IronXL is based on Python, so you can do pretty much anything you'd want to do in Excel. Users can start using IronXL for free with its trial, and when ready to commit, licensing options start at $599. For more about the Iron Software products, check the Iron Suite page.

Hinweis:openpyxl, XlsxWriter, pylightxl, and pyxlsb are registered trademarks of their respective owners. This site is not affiliated with, endorsed by, or sponsored by openpyxl, XlsxWriter, pylightxl, or pyxlsb. All product names, logos, and brands are property of their respective owners. Comparisons are for informational purposes only and reflect publicly available information at the time of writing.

Häufig gestellte Fragen

Wie kann ich vorhandene Excel-Dateien in Python ändern?

Sie können die `openpyxl`-Bibliothek verwenden, um bestehende .XLSX-Dateien zu lesen und zu modifizieren. Sie ermöglicht Aufgaben wie das Formatieren von Zellen, das Hinzufügen von Formeln und die Automatisierung von Excel-Dateimanipulationen.

Welche Bibliothek sollte ich verwenden, um neue Excel-Dateien mit erweitertem Format zu erstellen?

Die `XlsxWriter`-Bibliothek ist ideal für die Erstellung neuer Excel-Dateien von Grund auf geeignet, da sie erweitertes Formatieren und Diagrammfunktionen unterstützt.

Welche Python-Bibliothek wird für die Arbeit mit .XLSB-Dateien empfohlen?

Die `pyxlsb`-Bibliothek ist speziell dafür ausgelegt, Excel-Dateien im .XLSB-Format zu lesen, sodass Sie Daten aus binären Excel-Dateien extrahieren können, ohne Microsoft Excel zu benötigen.

Welche Python-Bibliothek ist am besten für leichte Excel-Operationen?

Die `pylightxl`-Bibliothek ist ideal für grundlegende Excel-Operationen und bietet eine minimalistische und schnelle Lösung für Benutzer, die keine umfangreichen Formatierungs- oder Diagrammfunktionen benötigen.

Welche Vorteile bietet IronXL für Python/.NET-Anwendungen?

IronXL unterstützt sowohl .XLSX- als auch .XLS-Formate und bietet Funktionen wie Dateneingabe, Formelberechnungen und komplexe Formatierungen. Es integriert sich gut in Python/.NET-Anwendungen und bietet eine vielseitige Lösung für automatisiertes Excel-Dateimanagement.

Kann ich IronXL kostenlos verwenden?

Ja, IronXL bietet eine kostenlose Testversion an. Für umfassende Nutzung sind Lizenzoptionen ab 599 $ verfügbar.

Was sollten Entwickler bei der Auswahl einer Python-Excel-Bibliothek beachten?

Wenn eine native Python-Lösung erforderlich ist, sind Bibliotheken wie `openpyxl` und `XlsxWriter` ideal. Für Anwendungen, die .NET-Integration und erweiterte Excel-Funktionen benötigen, ist IronXL die bessere Wahl.

Gibt es eine Bibliothek, die sowohl das Lesen als auch das Schreiben von Excel-Dateien unterstützt?

Ja, IronXL ermöglicht es Ihnen, sowohl .XLSX- als auch .XLS-Dateien zu lesen und zu schreiben. Es bietet umfassende Funktionen für das Erstellen, Lesen und Manipulieren von Tabellenkalkulationen.

Curtis Chau
Technischer Autor

Curtis Chau hat einen Bachelor-Abschluss in Informatik von der Carleton University und ist spezialisiert auf Frontend-Entwicklung mit Expertise in Node.js, TypeScript, JavaScript und React. Leidenschaftlich widmet er sich der Erstellung intuitiver und ästhetisch ansprechender Benutzerschnittstellen und arbeitet gerne mit modernen Frameworks sowie der Erstellung gut strukturierter, optisch ansprechender ...

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