jupyter出现Intel MKL FATAL ERROR: Cannot load libmkl_intel_thread.dylib的解决办法
背景
因为conda清华的源老旧，pandas还停留在0.20，当前版本已经到了0.23
将清华的源切换回了默认源。
切换后使用conda update --all更新了全部包
问题
切换后运行jupyter，随意执行一行代码即报错：服务似乎挂掉了,但是会立刻重启的
在命令行中提示：Intel MKL FATAL ERROR: Cannot load libmkl_intel_thread.dylib.
解决
查了不少资料，有的说需要使用
conda update conda
然而使用后无效。
后参考 https://stackoverflow.com/questions/36659453/intel-mkl-fatal-error-cannot-load-libmkl-avx2-so-or-libmkl-def-so
执行
conda install nomkl numpy scipy scikit-learn numexpr
提示
conda install nomkl numpy scipy scikit-learn numexpr
Solving environment: done
## Package Plan ##
environment location: /Users/wangyu/anaconda3
added / updated specs:
- nomkl
- numexpr
- numpy
- scikit-learn
- scipy
The following packages will be downloaded:
package | build
---------------------------|-----------------
mkl_fft-1.0.1 | py36h917ab60_0 125 KB defaults
scikit-learn-0.20.0 | py36hebd9d1a_1 5.4 MB defaults
numpy-base-1.15.3 | py36ha711998_0 4.0 MB defaults
libopenblas-0.3.3 | hdc02c5d_3 8.4 MB defaults
mkl-service-1.1.2 | py36h6b9c3cc_4 10 KB defaults
numexpr-2.6.8 | py36hafae301_0 125 KB defaults
nomkl-3.0 | 0 48 KB defaults
numpy-1.15.3 | py36h926163e_0 35 KB defaults
blas-1.0 | openblas 48 KB defaults
mkl_random-1.0.1 | py36h78cc56f_0 346 KB defaults
scipy-1.1.0 | py36h1a1e112_1 15.4 MB defaults
------------------------------------------------------------
Total: 33.9 MB
The following NEW packages will be INSTALLED:
libopenblas: 0.3.3-hdc02c5d_3 defaults
nomkl: 3.0-0 defaults
The following packages will be UPDATED:
blas: 1.0-mkl defaults --> 1.0-openblas defaults
numexpr: 2.6.8-py36h1dc9127_0 defaults --> 2.6.8-py36hafae301_0 defaults
numpy: 1.15.3-py36h6a91979_0 defaults --> 1.15.3-py36h926163e_0 defaults
numpy-base: 1.15.3-py36h8a80b8c_0 defaults --> 1.15.3-py36ha711998_0 defaults
scikit-learn: 0.20.0-py36h4f467ca_1 defaults --> 0.20.0-py36hebd9d1a_1 defaults
scipy: 1.1.0-py36h28f7352_1 defaults --> 1.1.0-py36h1a1e112_1 defaults
The following packages will be DOWNGRADED:
mkl-service: 1.1.2-py36h6b9c3cc_5 defaults --> 1.1.2-py36h6b9c3cc_4 defaults
mkl_fft: 1.0.6-py36hb8a8100_0 defaults --> 1.0.1-py36h917ab60_0 defaults
mkl_random: 1.0.1-py36h5d10147_1 defaults --> 1.0.1-py36h78cc56f_0 defaults
确认安装后再运行jupyter，执行无误。
考虑问题出在mkl-service上面，回滚后即解决问题。