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RuntimeError with numpy==1.13 and pandas==0.21.1

See original GitHub issue

Wasn’t super sure as to whether to post this here or on the downstream pandas repository since I’m not sure where the issue originates, but I think it might be here. Basically, I updated all my packages and found that pandas was spitting out errors (but continues). After a bunch of installing / uninstalling and binary searching through my requirements files, I found that removing bottleneck removes the issue. Perhaps this is a compatibility problem - has numpy changed a critical API?

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
RuntimeError: module compiled against API version 0xc but this version of numpy is 0xb
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
RuntimeError: module compiled against API version 0xc but this version of numpy is 0xb
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
RuntimeError: module compiled against API version 0xc but this version of numpy is 0xb
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
RuntimeError: module compiled against API version 0xc but this version of numpy is 0xb

Steps:

python3 -mvenv env
. env/bin/activate
pip install "numpy==1.13 pandas==0.21.1
Import pandas and see that it works
pip install bottleneck
Import pandas and see above errors.

Issue Analytics

State:
Created 6 years ago
Comments:14

Top GitHub Comments

1reaction

kwgoodmancommented, Jan 11, 2018

Installation is impenetrable magic to me. Hopefully the PR fairy will come along with a magical solution.

0reactions

qwhelancommented, Nov 13, 2019

Closing as I believe this is fixed by the 1.3.0 release. Please feel to reopen if that is not the case.

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