NumberCell cell values are now limited to 15 significant figures to match the implementation of floating point numbers in Apple Numbers. Using the deprecated methods image_data and image_filename will issue a DeprecationWarning if used.The legacy methods will be removed in a future version of numbers-parser. To better partition cell styles, background image data which was supported in earlier versions through the methods image_data and image_filename is now part of the new cell_style property. For example for python 3.11: C:\Users\Jon>pip install C:\Users\Jon\Downloads\python_snappy-0.6.1-cp311-cp311-win_amd64.whl You must select the correct python version for your installation. On Windows, you will need to either arrange for snappy to be found for VSC++ or you can install python binary libraries compiled by Christoph Gohlke. The most straightforward way to install the binary dependencies is to use Homebrew and source Python from Homebrew rather than from macOS as described in the python-snappy github:įor Intel Macs: brew install snappy python3ĬPPFLAGS = "-I/usr/local/include -L/usr/local/lib" python3 -m pip install python-snappyįor Apple Silicon Macs: brew install snappy python3ĬPPFLAGS = "-I/opt/homebrew/include -L/opt/homebrew/lib" python3 -m pip install python-snappyįor Linux (your package manager may be different): sudo apt-get -y install libsnappy-dev Installation python3 -m pip install numbers-parserĪ pre-requisite for this package is python-snappy which will be installed by Python automatically, but python-snappy also requires that the binary libraries for snappy compression are present. It is not compatible with earlier versions of Python. It supports and is tested against Python versions from 3.8 onwards. It supports Numbers files generated by Numbers version 10.3, and up with the latest tested version being 13.1 (current as of June 2023). Numbers-parser is a Python module for parsing Apple Numbers.
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