ERROR: pip‘s dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
conda–repo–cli 1.0.75 requires requests_mock, which is not installed.
tables 3.8.0 requires blosc2~=2.0.0, which is not installed.
tables 3.8.0 requires cython>=0.29.21, which is not installed.
gensim 4.3.0 requires FuzzyTM>=0.4.0, which is not installed.
datasets 2.12.0 requires dill<0.3.7,>=0.3.0, but you have dill 0.3.7 which is incompatible.
conda–repo–cli 1.0.75 requires clyent==1.2.1, but you have clyent 1.2.2 which is incompatible.
aiobotocore 2.5.0 requires botocore<1.29.77,>=1.29.76, but you have botocore 1.31.81 which is incompatible.
numba 0.57.1 requires numpy<1.25,>=1.21, but you have numpy 1.26.1 which is incompatible.
# Install missing dependencies using pip or conda
pip install requests_mock
pip install blosc2~=2.0.0
pip install cython>=0.29.21
pip install "FuzzyTM>=0.4.0"
# Or using conda, if the packages are available in conda repositories
conda install requests_mock
conda install blosc2=2.0.0 -c conda-forge # specifying the channel if necessary
conda install cython>=0.29.21
conda install "FuzzyTM>=0.4.0" -c conda-forge # as an example
# Resolve version conflicts by downgrading/adjusting versions
pip install "dill<0.3.7,>=0.3.0"
pip install clyent==1.2.1
pip install "botocore<1.29.77,>=1.29.76"
pip install "numpy<1.25,>=1.21"
# If using conda, you can also use it to force-reinstall to specific versions
conda install dill=0.3.6
conda install clyent=1.2.1
conda install botocore=1.29.76
conda install numpy=1.21
# Note: If you're running into issues where pip and conda are conflicting,
# you might want to stick to one package manager. In a conda environment,
# it's generally recommended to use conda when possible.
原文地址:https://blog.csdn.net/weixin_53704902/article/details/134305416
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