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ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject

Importing from pyxdameraulevenshtein gives the following error, I have

pyxdameraulevenshtein==1.5.3, 
pandas==1.1.4 and 
scikit-learn==0.20.2. 
Numpy is 1.16.1. 
Works well in Python3.6, Issue in Python3.7.

Has anyone been facing similar issues with Python3.7 (3.7.9), docker image - python:3.7-buster

__init__.pxd:242: in init pyxdameraulevenshtein
    ???
E   ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject
over 4 years ago · Santiago Trujillo
3 Respostas
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0

I'm in Python 3.8.5. It sounds too simple to be real, but I had this same issue and all I did was reinstall numpy. Gone.

pip install --upgrade numpy

or

pip uninstall numpy
pip install numpy
over 4 years ago · Santiago Trujillo Relatório

0

try with numpy==1.20.0 this worked here, even though other circumstances are different (python3.8 on alpine 3.12).

over 4 years ago · Santiago Trujillo Relatório

0

Indeed, (building and) installing with numpy>=1.20.0 should work, as pointed out e.g. by this answer below. However, I thought some background might be interesting -- and provide also alternative solutions.

There was a change in the C API in numpy 1.20.0. In some cases, pip seems to download the latest version of numpy for the build stage, but then the program is run with the installed version of numpy. If the build version used in <1.20, but the installed version is =>1.20, this will lead to an error.

(The other way around it should not matter, because of backwards compatibility. But if one uses an installed version numpy<1.20, they did not anticipate the upcoming change.)

This leads to several possible ways to solve the problem:

  • upgrade (the build version) to numpy>=1.20.0
  • use minmum supported numpy version in pyproject.toml (oldest-supported-numpy)
  • install with --no-binary
  • install with --no-build-isolation

For a more detailed discussion of potential solutions, see https://github.com/scikit-learn-contrib/hdbscan/issues/457#issuecomment-773671043.

over 4 years ago · Santiago Trujillo Relatório
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