pdf2docx Documentation

⚠️ Note: pdf2docx is no longer actively maintained by Artifex.

The project has been relicensed under the MIT License, allowing the community to use, fork, and maintain it. While community pull requests are welcome, Artifex no longer provides active development.

If you require a full-featured PDF processing library, the maintainers suggest considering PyMuPDF or MuPDF.NET.

To remove pdf2docx from your environment, use pip uninstall.

pip uninstall pdf2docx

Navigate to the docs directory and use sphinx-build to generate HTML files. The output will be placed in the build/html directory.

If you have updated CSS or assets in the _static folder, use the -a flag to ensure all assets are included in the build.

To install the latest version directly from the master branch on GitHub (which may be newer than the version available on PyPI), use the following command:

pip install git+git://github.com/ArtifexSoftware/pdf2docx.git@master --upgrade

For a simpler one-line conversion of all pages, use the parse method from pdf2docx.

from pdf2docx import parse

pdf_file = '/path/to/sample.pdf'
docx_file = 'path/to/sample.docx'

# convert pdf to docx
parse(pdf_file, docx_file)

To speed up conversion, you can enable multi-processing using the --multi_processing flag. You can also control the number of CPU cores used with the --cpu_count flag.

• --multi_processing: Set to True to enable multi-processing. If no count is specified, it defaults to the total number of available CPUs.
• --cpu_count: Specifies the exact number of CPUs to use for the operation.

You can convert a PDF to DOCX using either the Converter class or the high-level parse function. Both methods convert all pages by default.

from pdf2docx import Converter

pdf_file = '/path/to/sample.pdf'
docx_file = 'path/to/sample.docx'

# Using Converter class
cv = Converter(pdf_file)
cv.convert(docx_file)      # all pages by default
cv.close()

To extract tables from a PDF file, use the Converter class from pdf2docx. Initialize the Converter with the path to your PDF, call extract_tables() specifying the range of tables to extract via start and end parameters, and ensure you call close() to release resources. The extracted tables are returned as a list of lists, where each inner list represents a row in the table.

from pdf2docx import Converter

pdf_file = '/path/to/sample.pdf'

cv = Converter(pdf_file)
tables = cv.extract_tables(start=0, end=1)
cv.close()

for table in tables:
    print(table)

The pdf2docx command line interface supports three primary commands:

• convert: Converts a PDF file to a DOCX file.
• debug: Converts a single PDF page and plots layout information for debugging purposes.
• table: Extracts table content from PDF pages.

$ pdf2docx --help