Convert NUMBERS to ODS in Python Excel Library
High-speed Python excel library for converting NUMBERS to ODS. This is a professional software solution to import and export NUMBERS, ODS, and many other formats using Python.
Convert NUMBERS to ODS Using Python Excel Library
How do I convert NUMBERS to ODS? With Aspose.Cells for Python library, you can easily convert NUMBERS to ODS programmatically with a few lines of code. Aspose.Cells for Python is capable of building cross-platform applications with the ability to generate, modify, convert, render and print all Excel files. Python Excel API not only convert between spreadsheet formats, it can also render Excel files as images, PDF, HTML, ODS, CSV, SVG, JSON, WORD, PPT and more, thus making it a perfect choice to exchange documents in industry-standard formats.Save NUMBERS to ODS in Python Excel Library
The following example demonstrates how to convert NUMBERS to ODS in Python excel library.
Follow the easy steps to convert NUMBERS to ODS. Upload your NUMBERS file, then simply save it as ODS file. For both NUMBERS reading and ODS writing you can use fully qualified filenames. The output ODS content and formatting will be identical to the original NUMBERS document.
import jpype
import asposecells
jpype.startJVM()
from asposecells.api import Workbook
workbook = Workbook("Input.xlsx")
workbook.save("Output.pdf")
jpype.shutdownJVM()
How to Convert NUMBERS to ODS via Python
Need to convert NUMBERS files to ODS programmatically? Python developers can easily load & convert NUMBERS to ODS in just a few lines of code.
- Install ‘Aspose.Cells for Python via Java’.
- Add a library reference (import the library) to your Python project.
- Load NUMBERS file with an instance of Workbook.
- Convert NUMBERS to ODS by calling Workbook.save method.
- Get the conversion result of NUMBERS to ODS.
Python Excel Library to Convert NUMBERS to ODS
There are three options to install “Aspose.Cells for Python via Java” onto your system. Please choose one that resembles your needs and follow the step-by-step instructions:
- Install Aspose.Cells for Python via Java in Windows. See Documentation
- Install Aspose.Cells for Python via Java in Linux. See Documentation
- Install Aspose.Cells for Python via Java in macOS. See Documentation
System Requirements
Aspose.Cells for Python via Java is platform-independent API and can be used on any platform (Windows, Linux and MacOS), just make sure that system have Java 1.8 or higher, Python 3.5 or higher.
- Install Java and add it to PATH environment variable, for example:
PATH=C:\Program Files\Java\jdk1.8.0_131;
. - Install Aspose.Cells for Python from pypi, use command as:
$ pip install aspose-cells
.
NUMBERS What is NUMBERS File Format?
The files with .numbers extension are classified as spreadsheet file type, that's why they are similar to the .xlsx files; but the Numbers files are created by using Apple iWork Numbers spreadsheet software. The Apple iWork Numbers is a unit software of the iWork Productivity Suite. The iWork Productivity Suite is equivalent to the Microsoft Office Suite that is used on Windows PCs. Hence, we can say the Numbers which is available for MacOS is also a competitor of Microsoft Excel. Likewise, Microsoft Excel, the NUMBERS file may also contain the tables, charts and formulas.
Read MoreODS What is ODS File Format?
Files with .ods extension stand for OpenDocument Spreadsheet Document format that are editable by user. Data is stored inside ODF file into rows and columns. It is XML-based format and is one of the several subtypes in the Open Document Formats (ODF) family. The format is specified as part of the ODF 1.2 specifications published and maintained by OASIS. A number of applications on Windows as well as other operating systems can open ODS files for editing and manipulation including Microsoft Excel, NeoOffice and LibreOffice. ODS files can also be converted into other spreadsheet formats as well like XLS, XLSX and others by different applications.
Read MoreOther Supported Conversions
You can also convert NUMBERS to many other file formats including few listed below.