从pyxdameraulevenshtein导入会出现以下错误
pyxdameraulevenshtein==1.5.3
pandas==1.1.4
scikit-learn==0.20.2.
Numpy是1.16.1。
在Python 3.6中工作良好,在Python 3.7中问题。
有人在使用Python 3.7(3.7.9)时遇到过类似的问题吗?
from pyxdameraulevenshtein import normalized_damerau_levenshtein_distance as norm_dl_dist
__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
这对我很有用(当这一页上的任何东西都不起作用时):
# Create environment with conda or venv.
# Do *not* install any other packages here.
pip install numpy==1.21.5
# Install all other packages here.
# This works as a package may build against the currently installed version of numpy.
这解决了一个特别残酷的问题,截至2022-04-11,本页上的所有其他答案都无法解决:
其他答案试图在问题发生后解决问题,这种方法在问题发生前解决问题。
此外,可以尝试不同版本的Python,例如3.8、3.9、3.10。
@FZeiser的回答很好,解释了为什么这种方法有效。
不升级numpy的解决方案
虽然升级numpy版本通常可以解决这个问题,但并不总是可行的。一个很好的例子是,当你使用tensorflow==2.6.0时,它与最新的numpy版本不兼容(它需要~=1.19.2)。
正如在FZeiser的回答中已经提到的,在1.20.0版本中numpys C API发生了变化。有一些包在构建时依赖于这个C API,例如pyxdameraulevenshtein。鉴于pips依赖解析器不保证安装包的任何顺序,可能会发生以下情况:
pip figures out that it needs to install numpy and it chooses the latest version, 1.21.2 as of the time writing this answer.
It then builds a package that depends on numpy and its C API, e.g. pyxdameraulevenshtein. This package is now compatible with numpy 1.21.2 C API.
At a later point pip needs to install a package that has a requirement for an older version of numpy, e.g. tensorflow==2.6.0 which would try to install numpy==1.19.5. As a result, numpy==1.21.2 is uninstalled and the older version is installed.
When running code that uses pyxdameraulevenshtein, its current installation relies on the updated numpy C API, yet the numpy version was downgraded which would result in the error.
解决方案
您应该使用过时的numpy C API重新构建包,以确保它与当前安装的numpy版本兼容。例如,对于pyxdameraulevenshtein:
pip uninstall pyxdameraulevenshtein
pip install pyxdameraulevenshtein --no-binary pyxdameraulevenshtein