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Supported Features on Document Load
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Aspose.Words strives to support all features for all supported formats. Almost all features of Microsoft Word documents are supported and are faithfully preserved during conversion. Using Aspose.Words you can load and convert a document of any size and can easily handle the conversion of a document consisting of thousands of pages within seconds. The only limitation is the amount of available working memory on the machine.
For more information and a description of the features available for the different formats, see the Supported Features on Document Load section in the Aspose.Words for .NET documentation.
FAQ
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Q: What document formats can be loaded with Aspose.Words for Python via .NET?
A: Aspose.Words can load all formats supported by Microsoft Word, including DOC, DOCX, RTF, HTML, MHTML, ODT, PDF (for import), and many others. The full list is documented in the “Supported Features on Document Load” section of the .NET documentation. -
Q: Is there a size limit for documents that can be loaded?
A: There is no explicit size limit imposed by Aspose.Words; the only constraint is the amount of available RAM on the host machine. Large documents (thousands of pages) can be loaded and converted as long as sufficient memory is available. -
Q: Does loading a document preserve all Word features such as headers, footers, footnotes, and styles?
A: Yes. Aspose.Words strives to preserve virtually all Word features during loading, including headers, footers, footnotes, endnotes, styles, numbering, and custom XML parts. The fidelity of these features is described in the supported‑features documentation. -
Q: Can I load documents on Linux environments using Aspose.Words for Python via .NET?
A: Yes. Aspose.Words for Python via .NET runs on Linux via .NET Core/.NET 5+ runtimes. The same loading capabilities are available on Linux as on Windows, provided the required .NET runtime is installed. -
Q: How does available memory affect document loading performance?
A: Loading performance is directly related to the amount of free memory. When memory is limited, loading very large documents may cause slower processing or OutOfMemory exceptions. It is recommended to allocate sufficient RAM or process documents in chunks when dealing with extremely large files.