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Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Current Behavior#
I installed Anaconda on Windows 10 (x64, version 1903) using Anaconda3-2019.10-Windows-x86_64.exe and everything went well. When I create a new environment and try to install any package from a channel different than conda I get the error in the title, followed by a really slow analysis of conflicts:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
Steps to Reproduce
I set up a new environment and installed some basic packages I need
conda create --name am_keras_tf python=3.7
conda activate am_keras_tf
conda install tensorflow-gpu keras matplotlib scipy scikit-learn
Everything was fine at this point. I then tried to install opencv, which is not included in the default channel, with:
conda install -c menpo opencv
That triggers several errors like:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
Examining vc: 2%|███▌ | 2/108 [00:00<?, ?it//
Comparing specs that have this dependency: 34%|█████████████████████████████████████████████████████▊ | 20/58 [01:05<02:05, 3.29s/i-
Comparing specs that have this dependency: 57%|████████████████████████████████████████████████████████████████████████████████████████▊ | 33/58 [01:18<00:59, 2.38s/i| \
Comparing specs that have this dependency: 62%|████████████████████████████████████████████████████████████████████████████████████████████████▊ | 36/58 [01:19<00:48, 2.20s/it]
Finding shortest conflict path for vc=14: 50%|███████████████████████████████████████████████████████████████████████████████▌ | 2/4 [00:04<00:04, 2.29s/i/ /
Comparing specs that have this dependency: 67%|████████████████████████████████████████████████████████████████████████████████████████████████████████▉ | 39/58 [01:24<00:41, 2.16s/i| -
Examining wincertstore: 6%|█████████▋ | 6/108 [01:52<47:43, 28.08s/i/ -
Comparing specs that have this dependency: 2%|███▍ | 1/46 [00:00<00:17, 2.59it/- /
| mparing specs that have this dependency: 9%|█████████████▋ | 4/46 [00:13<02:22, 3.40s/i| -
Comparing specs that have this dependency: 33%|██████████████████████████████████████████████████▊ | 15/46 [02:20<04:50, 9.36s/i| \
Comparing specs that have this dependency: 41%|████████████████████████████████████████████████████████████████▍ | 19/46 [02:26<03:27, 7.69s/i\ /
Comparing specs that have this dependency: 48%|██████████████████████████████████████████████████████████████████████████▌ | 22/46 [02:33<02:47, 6.99s/i\ |
- mparing specs that have this dependency: 52%|█████████████████████████████████████████████████████████████████████████████████▍ | 24/46 [02:34<02:21, 6.44s/i|
Comparing specs that have this dependency: 61%|██████████████████████████████████████████████████████████████████████████████████████████████▉ | 28/46 [02:47<01:47, 5.99s/i/ |
Comparing specs that have this dependency: 74%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎ | 34/46 [03:45<01:19, 6.63s/i/ /
Examining python: 8%|██████████████▉ | 9/108 [06:19<1:05:28, 39.68s/i/ -
Comparing specs that have this dependency: 4%|██████▊ | 2/46 [00:00<00:04, 10.72it/\ -
Comparing specs that have this dependency: 15%|███████████████████████▉ | 7/46 [00:32<03:00, 4.62s/i- \ inding shortest conflict path for python[version='>=3.6,<3.7.0a0']: 62%|█████████████████████████████████████████████████████████████████████████████████▎ | 5/8 [00:00<00:00, 1002.94it/| |
Comparing specs that have this dependency: 24%|█████████████████████████████████████▎ | 11/46 [00:32<01:44, 3.00s/it]
Finding shortest conflict path for python=3.7: 55%|███████████████████████████████████████████████████████████████████████████████████▍ | 6/11 [00:15<00:08, 1.61s/it]
Expected Behavior
The opencv package should be installed (as it was on Windows 7 and it still is on Ubuntu). The same problem happens if I try to install different packages from conda-forge channel, it is not just opencv from menpo
Environment Information
`conda info`
(am_keras_tf) PS C:\> conda info
active environment : am_keras_tf
active env location : C:\Users\***\.conda\envs\am_keras_tf
shell level : 2
user config file : C:\Users\***\.condarc
populated config files : C:\Users\***\.condarc
conda version : 4.7.12
conda-build version : 3.18.9
python version : 3.7.4.final.0
virtual packages : __cuda=10.1
base environment : C:\ProgramData\Anaconda3 (read only)
channel URLs : https://repo.anaconda.com/pkgs/main/win-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/win-64
https://repo.anaconda.com/pkgs/r/noarch
https://repo.anaconda.com/pkgs/msys2/win-64
https://repo.anaconda.com/pkgs/msys2/noarch
package cache : C:\ProgramData\Anaconda3\pkgs
C:\Users\***\.conda\pkgs
C:\Users\***\AppData\Local\conda\conda\pkgs
envs directories : C:\Users\***\.conda\envs
C:\ProgramData\Anaconda3\envs
C:\Users\***\AppData\Local\conda\conda\envs
platform : win-64
user-agent : conda/4.7.12 requests/2.22.0 CPython/3.7.4 Windows/10 Windows/10.0.18362
administrator : False
netrc file : None
offline mode : False
`conda config --show-sources`
(am_keras_tf) PS C:\> conda config --show-sources
==> C:\Users\***\.condarc <==
channel_priority: strict
channels:
- defaults
`conda list --show-channel-urls`
(am_keras_tf) PS C:\> conda list --show-channel-urls
# packages in environment at C:\Users\***\.conda\envs\am_keras_tf:
#
# Name Version Build Channel
_tflow_select 2.1.0 gpu defaults
absl-py 0.8.0 py37_0 defaults
astor 0.8.0 py37_0 defaults
blas 1.0 mkl defaults
ca-certificates 2019.10.16 0 defaults
certifi 2019.9.11 py37_0 defaults
cudatoolkit 10.0.130 0 defaults
cudnn 7.6.0 cuda10.0_0 defaults
cycler 0.10.0 py37_0 defaults
freetype 2.9.1 ha9979f8_1 defaults
gast 0.3.2 py_0 defaults
grpcio 1.16.1 py37h351948d_1 defaults
h5py 2.9.0 py37h5e291fa_0 defaults
hdf5 1.10.4 h7ebc959_0 defaults
icc_rt 2019.0.0 h0cc432a_1 defaults
icu 58.2 ha66f8fd_1 defaults
intel-openmp 2019.4 245 defaults
joblib 0.13.2 py37_0 defaults
jpeg 9b hb83a4c4_2 defaults
keras 2.2.4 0 defaults
keras-applications 1.0.8 py_0 defaults
keras-base 2.2.4 py37_0 defaults
keras-preprocessing 1.1.0 py_1 defaults
kiwisolver 1.1.0 py37ha925a31_0 defaults
libpng 1.6.37 h2a8f88b_0 defaults
libprotobuf 3.9.2 h7bd577a_0 defaults
markdown 3.1.1 py37_0 defaults
matplotlib 3.1.1 py37hc8f65d3_0 defaults
mkl 2019.4 245 defaults
mkl-service 2.3.0 py37hb782905_0 defaults
mkl_fft 1.0.14 py37h14836fe_0 defaults
mkl_random 1.1.0 py37h675688f_0 defaults
numpy 1.16.5 py37h19fb1c0_0 defaults
numpy-base 1.16.5 py37hc3f5095_0 defaults
openssl 1.1.1d he774522_3 defaults
pip 19.3.1 py37_0 defaults
protobuf 3.9.2 py37h33f27b4_0 defaults
pyparsing 2.4.2 py_0 defaults
pyqt 5.9.2 py37h6538335_2 defaults
pyreadline 2.1 py37_1 defaults
python 3.7.4 h5263a28_0 defaults
python-dateutil 2.8.0 py37_0 defaults
pytz 2019.3 py_0 defaults
pyyaml 5.1.2 py37he774522_0 defaults
qt 5.9.7 vc14h73c81de_0 defaults
scikit-learn 0.21.3 py37h6288b17_0 defaults
scipy 1.3.1 py37h29ff71c_0 defaults
setuptools 41.4.0 py37_0 defaults
sip 4.19.8 py37h6538335_0 defaults
six 1.12.0 py37_0 defaults
sqlite 3.30.0 he774522_0 defaults
tensorboard 1.14.0 py37he3c9ec2_0 defaults
tensorflow 1.14.0 gpu_py37h5512b17_0 defaults
tensorflow-base 1.14.0 gpu_py37h55fc52a_0 defaults
tensorflow-estimator 1.14.0 py_0 defaults
tensorflow-gpu 1.14.0 h0d30ee6_0 defaults
termcolor 1.1.0 py37_1 defaults
tornado 6.0.3 py37he774522_0 defaults
vc 14.1 h0510ff6_4 defaults
vs2015_runtime 14.16.27012 hf0eaf9b_0 defaults
werkzeug 0.16.0 py_0 defaults
wheel 0.33.6 py37_0 defaults
wincertstore 0.2 py37_0 defaults
wrapt 1.11.2 py37he774522_0 defaults
yaml 0.1.7 hc54c509_2 defaults
zlib 1.2.11 h62dcd97_3 defaults
Here is another way to get the same error, using different channels:
(base) PS C:\> conda create --name tf_gpu tensorflow-gpu
(base) PS C:\> conda activate tf_gpu
(tf_gpu) PS C:\> conda install -c conda-forge opencv
And here is the full error:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
Examining clang: 4%|██████▎ | 4/114 [00:00<00:00, 300.16it/s]|failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Package astor conflicts for:
tensorflow -> astor[version='>=0.6.0']
tensorflow-estimator -> astor[version='>=0.6.0']
tensorflow-base -> astor[version='>=0.6.0']
Package six conflicts for:
protobuf -> six
keras-preprocessing -> six[version='>=1.9.0']
grpcio -> six[version='>=1.5.2']
absl-py -> six
keras-base -> six[version='>=1.9.0']
h5py -> six
tensorboard -> six[version='>=1.10.0']
tensorflow-estimator -> six[version='>=1.10.0']
mkl-service -> six
keras -> six[version='>=1.9.0']
tensorflow-base -> six[version='>=1.10.0']
tensorflow -> six[version='>=1.10.0']
Package blas conflicts for:
mkl-service -> blas==1.0=mkl
numpy -> blas[version='*|1.0|1.1',build='openblas|mkl|mkl']
mkl_fft -> blas==1.0=mkl
mkl_random -> blas==1.0=mkl
numpy-base -> blas[version='*|1.0',build=mkl]
scipy -> blas[version='*|1.0',build=mkl]
Package pyyaml conflicts for:
keras-base -> pyyaml
keras -> pyyaml
Package vs2008_runtime conflicts for:
vc -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0']
Package vc conflicts for:
mkl_random -> vc[version='14.*|>=14,<15.0a0']
libprotobuf -> vc[version='14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
opencv -> vc[version='14.*|>=14,<15.0a0']
tensorboard -> vc[version='14.*|>=14.1,<15.0a0']
pyyaml -> vc[version='14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
yaml -> vc[version='10.*|14.*|9.*']
openssl -> vc[version='10.*|14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
numpy -> vc[version='14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
h5py -> vc[version='14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
zlib -> vc[version='10.*|14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0|>=9,<10.0a0']
mkl-service -> vc[version='14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
grpcio -> vc[version='14.*|>=14,<15.0a0|>=14.1,<15.0a0']
hdf5 -> vc[version='10|10.*|14.*|9.*|14|9|>=14,<15.0a0|>=14.1,<15.0a0']
numpy-base -> vc[version='14.*|9.*|>=14.1,<15.0a0']
mkl_fft -> vc[version='14.*|9.*|>=14,<15.0a0']
sqlite -> vc[version='10|10.*|14.*|9.*|14|9|>=14,<15.0a0|>=14.1,<15.0a0']
wrapt -> vc[version='14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
tensorflow-base -> vc[version='14.*|>=14.1,<15.0a0']
python=3.7 -> vc[version='14.*|>=14,<15.0a0|>=14.1,<15.0a0']
protobuf -> vc[version='10.*|14.*|9.*|>=14,<15.0a0|>=14.1,<15.0a0']
Package gast conflicts for:
tensorflow-base -> gast[version='>=0.2.0']
tensorflow -> gast[version='>=0.2.0']
tensorflow-estimator -> gast[version='>=0.2.0']
Package setuptools conflicts for:
pip -> setuptools
wheel -> setuptools
markdown -> setuptools[version='>=36']
protobuf -> setuptools
grpcio -> setuptools
keras -> setuptools
Package icc_rt conflicts for:
numpy -> icc_rt[version='>=13.1.6|>=16.0.4|>=2019.0.0']
scipy -> icc_rt[version='>=13.1.6|>=16.0.4|>=2019.0.0']
hdf5 -> icc_rt[version='>=13.1.6|>=16.0.4|>=2019.0.0']
numpy-base -> icc_rt[version='>=13.1.6|>=16.0.4|>=2019.0.0']
Package termcolor conflicts for:
tensorflow-estimator -> termcolor[version='>=1.1.0']
tensorflow -> termcolor[version='>=1.1.0']
tensorflow-base -> termcolor[version='>=1.1.0']
Package lockfile conflicts for:
pip -> lockfile
Package progress conflicts for:
pip -> progress
Package absl-py conflicts for:
tensorflow-base -> absl-py[version='>=0.1.6']
tensorboard -> absl-py[version='>=0.4']
tensorflow-estimator -> absl-py[version='>=0.1.6|>=0.7.0']
tensorflow -> absl-py[version='>=0.1.6']
Package openssl conflicts for:
python=3.7 -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1c,<1.1.2a']
grpcio -> openssl[version='>=1.0.2o,<1.0.3a|>=1.0.2p,<1.0.3a|>=1.1.1a,<1.1.2a']
Package cudnn conflicts for:
tensorflow-base -> cudnn[version='>=7.1.4,<8.0a0|>=7.3.1,<8.0a0']
Package numpy conflicts for:
tensorflow-estimator -> numpy[version='>=1.13.3|>=1.16.1']
tensorflow -> numpy[version='>=1.11.0|>=1.12.1|>=1.13.3']
numpy-base -> numpy[version='1.11.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3',build='py37hd5b3723_7|py37hd5b3723_6|py36hd5b3723_7|py36hd5b3723_6|py27he0c0ee4_6|py37h19fb1c0_0|py37h19fb1c0_0|py36h19fb1c0_0|py37h19fb1c0_0|py36h19fb1c0_0|py37h19fb1c0_0|py27h5fc8d92_0|py36h19fb1c0_1|py36h19fb1c0_0|py37h19fb1c0_0|py36h19fb1c0_1|py37ha559c80_0|py36ha559c80_0|py27hbe4291b_0|py37ha559c80_0|py37ha559c80_0|py36ha559c80_0|py35ha559c80_0|py27hbe4291b_1|py27hbe4291b_0|py37hc27ee41_0|py36hc27ee41_0|py35hc27ee41_0|py37h9fa60d3_0|py36h9fa60d3_0|py35h9fa60d3_0|py27h911edcf_0|py37hc27ee41_4|py36hc27ee41_4|py36ha06f490_5|py27h22e7547_5|py37h9fa60d3_4|py37h9fa60d3_0|py36h9fa60d3_2|py36h9fa60d3_0|py27h911edcf_2|py27h911edcf_1|py27h911edcf_0|py36h9fa60d3_0|py27h911edcf_0|py36h9fa60d3_1|py27h911edcf_1|py37hd5b3723_8|py37hd5b3723_7|py37h35d8231_12|py36hd5b3723_8|py36h6707678_9|py36h0aa5519_11|py35hd5b3723_9|py35hd5b3723_8|py35h6707678_9|py35h53ece5f_10|py27he0c0ee4_9|py27hc2d41ba_9|py27h239e66a_12|py27h239e66a_11|py27hc42714f_10|py27he0c0ee4_7|py27he0c0ee4_8|py36h35d8231_12|py36h53ece5f_10|py36h53ece5f_11|py36hd5b3723_7|py36hd5b3723_9|py37h0aa5519_11|py37h53ece5f_10|py37h53ece5f_11|py37h6707678_9|py37hd5b3723_9|py35h9fa60d3_1|py35h9fa60d3_0|py27h911edcf_3|py27h911edcf_4|py35h9fa60d3_0|py35h9fa60d3_4|py36h9fa60d3_1|py36h9fa60d3_3|py36h9fa60d3_4|py37h9fa60d3_1|py37h9fa60d3_2|py37h9fa60d3_3|py27h22e7547_4|py35hc27ee41_4|py37ha06f490_5|py27hbe4291b_0|py27hbe4291b_0|py36ha559c80_0|py27h5fc8d92_0|py36h19fb1c0_0|py37h19fb1c0_0|py27h5fc8d92_0|py27h5fc8d92_1|py36h19fb1c0_0|py37h19fb1c0_1|py27h5fc8d92_0|py27h5fc8d92_1|py37h19fb1c0_0|py37h19fb1c0_1|py36h19fb1c0_0|py27h5fc8d92_0|py27h5fc8d92_0|py36h19fb1c0_0|py27he0c0ee4_7|py35hd5b3723_7']
keras-preprocessing -> numpy[version='>=1.9.1']
opencv -> numpy[version='1.10.*|1.11.*|1.12.*|1.13.*|>=1.11|>=1.11.3,<2.0a0|>=1.14.6,<2.0a0|>=1.9']
h5py -> numpy[version='1.10.*|1.11.*|1.12.*|1.13.*|>=1.11|>=1.11,<1.14|>=1.11.3,<2.0a0|>=1.14.6,<2.0a0|>=1.8|>=1.8,<1.14|>=1.9|>=1.9,<1.14']
scipy -> numpy[version='>=1.11.3,<2.0a0|>=1.15.1,<2.0a0']
tensorboard -> numpy[version='>=1.12|>=1.12.0']
keras -> numpy[version='>=1.9.1']
mkl-service -> numpy[version='>=1.11.3,<2.0a0']
keras-base -> numpy[version='>=1.9.1']
mkl_random -> numpy[version='>=1.11|>=1.11.3,<2.0a0|>=1.14.6,<2.0a0']
keras-applications -> numpy[version='>=1.9.1']
mkl_fft -> numpy[version='>=1.11|>=1.11.3,<2.0a0']
tensorflow-base -> numpy[version='>=1.13.3|>=1.13.3,<2.0a0|>=1.14.2,<2.0a0|>=1.14.6,<2.0a0|>=1.16.1']
Package liblapacke conflicts for:
opencv -> liblapacke[version='>=3.8.0,<3.9.0a0']
blas -> liblapacke==3.8.0[build='9_mkl|8_openblas|8_mkl|7_mkl|7_h8933c1f_netlib|6_openblas|5_openblas|4_mkl|14_openblas|14_mkl|13_mkl|12_openblas|10_mkl|10_openblas|11_mkl|11_openblas|12_mkl|13_openblas|4_h8933c1f_netlib|4_openblas|5_h8933c1f_netlib|5_mkl|6_h8933c1f_netlib|6_mkl|7_openblas|9_openblas|*netlib']
Package tensorflow-estimator conflicts for:
tensorflow -> tensorflow-estimator[version='>=1.13.0,<1.14.0a0|>=1.14.0,<1.15.0']
tensorflow-base -> tensorflow-estimator[version='>=1.13.0,<1.14.0a0']
Package tensorflow conflicts for:
keras -> tensorflow
tensorflow-gpu -> tensorflow[version='1.10.0|1.11.0|1.12.0|1.13.1|1.14.0|1.9.0']
Package mock conflicts for:
tensorflow -> mock[version='>=2.0.0']
tensorflow-estimator -> mock[version='>=2.0.0']
Package sqlite conflicts for:
python=3.7 -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.27.2,<4.0a0|>=3.28.0,<4.0a0|>=3.29.0,<4.0a0']
Package protobuf conflicts for:
tensorflow-base -> protobuf[version='>=3.4.0|>=3.6.0|>=3.6.1']
tensorflow-estimator -> protobuf[version='>=3.6.1']
grpcio -> protobuf[version='>=3.5.0']
tensorboard -> protobuf[version='>=3.3.0|>=3.4.0|>=3.6.0']
tensorflow -> protobuf[version='3.1.0|>=3.1.0|>=3.2.0|>=3.3.0|>=3.4.0|>=3.6.0|>=3.6.1']
Package html5lib conflicts for:
tensorflow -> html5lib==0.9999999
tensorboard -> html5lib[version='0.9999999|>=0.9999999,<0.10000000.0a0']
pip -> html5lib
Package libwebp conflicts for:
opencv -> libwebp[version='0.5.*|>=0.5.2,<0.6.0a0|>=1.0.0,<1.1.0a0']
Package werkzeug conflicts for:
tensorboard -> werkzeug[version='>=0.11.10|>=0.11.15']
tensorflow -> werkzeug[version='>=0.11.10']
Package libprotobuf conflicts for:
protobuf -> libprotobuf[version='3.10.0.*,>=3.10.0,<3.11.0a0|3.5.1.1|3.5.1|3.5.2.*|3.5.2|3.6.0.*,>=3.6.0,<3.6.1.0a0|3.6.1.*,>=3.6.1,<3.6.2.0a0|3.7.0.*,>=3.7.0,<3.7.1.0a0|3.7.1.*,>=3.7.1,<3.8.0a0|3.8.0.*,>=3.8.0,<3.9.0a0|3.9.0.*,>=3.9.0,<3.10.0a0|3.9.1.*,>=3.9.1,<3.10.0a0|3.9.2.*,>=3.9.2,<3.10.0a0|>=3.4.1,<3.5.0a0|>=3.5.1,<3.6.0a0|>=3.5.2,<3.6.0a0|>=3.6.0,<3.6.1.0a0|>=3.6.1,<3.6.2.0a0|>=3.7.1,<3.8.0a0']
Package keras-preprocessing conflicts for:
tensorflow-base -> keras-preprocessing[version='>=1.0.3|>=1.0.5']
tensorflow -> keras-preprocessing[version='>=1.0.5']
keras-base -> keras-preprocessing[version='1.0.1|1.0.2.*|>=1.0.5']
keras -> keras-preprocessing[version='1.0.2.*|>=1.0.5|>=1.1.0']
Package liblapack conflicts for:
blas -> liblapack==3.8.0[build='9_mkl|8_openblas|8_mkl|7_mkl|7_h8933c1f_netlib|6_openblas|5_openblas|4_mkl|14_openblas|14_mkl|13_mkl|12_openblas|10_mkl|10_openblas|11_mkl|11_openblas|12_mkl|13_openblas|4_h8933c1f_netlib|4_openblas|5_h8933c1f_netlib|5_mkl|6_h8933c1f_netlib|6_mkl|7_openblas|9_openblas|*netlib']
numpy -> liblapack[version='>=3.8.0,<3.9.0a0']
Package libcblas conflicts for:
numpy -> libcblas[version='>=3.8.0,<4.0a0']
blas -> libcblas==3.8.0[build='9_mkl|8_openblas|8_mkl|7_openblas|7_mkl|7_blis|6_openblas|6_blis|5_openblas|4_h8933c1f_netlib|14_openblas|14_mkl|13_blis|12_openblas|12_blis|11_openblas|11_blis|10_openblas|10_mkl|10_blis|11_mkl|12_mkl|13_mkl|13_openblas|14_blis|4_blis|4_mkl|4_openblas|5_blis|5_h8933c1f_netlib|5_mkl|6_h8933c1f_netlib|6_mkl|7_h8933c1f_netlib|8_blis|9_blis|9_openblas']
Package grpcio conflicts for:
tensorflow-estimator -> grpcio[version='>=1.8.6']
tensorflow -> grpcio[version='>=1.8.6']
tensorflow-base -> grpcio[version='>=1.8.6']
tensorboard -> grpcio[version='>=1.6.3']
Package futures conflicts for:
tensorboard -> futures[version='>=3.1.1']
Package yaml conflicts for:
pyyaml -> yaml[version='>=0.1.7,<0.2.0a0']
Package zlib conflicts for:
protobuf -> zlib[version='1.2.*|1.2.11|1.2.8|>=1.2.11,<1.3.0a0']
grpcio -> zlib[version='>=1.2.11,<1.3.0a0']
hdf5 -> zlib[version='1.2.*,>=1.2.11,<1.3.0a0|1.2.*|1.2.11|1.2.8|>=1.2.11,<1.3.0a0']
tensorflow-base -> zlib[version='>=1.2.11,<1.3.0a0']
libprotobuf -> zlib[version='1.2.11|>=1.2.11,<1.3.0a0']
opencv -> zlib[version='1.2.*|1.2.11|>=1.2.11,<1.3.0a0']
Package jpeg conflicts for:
opencv -> jpeg[version='9.*|>=9c,<10a']
Package ca-certificates conflicts for:
openssl -> ca-certificates
Package vs2015_runtime conflicts for:
openssl -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
mkl-service -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
protobuf -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
sqlite -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
vc -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012']
libprotobuf -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
numpy-base -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
numpy -> vs2015_runtime[version='>=14.16.27012,<15.0a0']
Package markdown conflicts for:
tensorboard -> markdown[version='>=2.6.8']
tensorflow -> markdown[version='>=2.6.8']
Package hdf5 conflicts for:
h5py -> hdf5[version='1.10.1|1.10.1.*|1.8.15.*|1.8.17.*|1.8.17|1.8.17.*|1.8.18|1.8.18.*|>=1.10.1,<1.10.2.0a0|>=1.10.2,<1.10.3.0a0|>=1.10.3,<1.10.4.0a0|>=1.10.4,<1.10.5.0a0|>=1.10.5,<1.10.6.0a0|>=1.8.18,<1.8.19.0a0|>=1.8.18,<1.9.0a0|>=1.8.20,<1.9.0a0']
Package py-opencv conflicts for:
opencv -> py-opencv[version='3.4.7|4.1.1|4.1.1|4.1.2',build='py37h5ca1d4c_0|py37h5ca1d4c_3|py37h5ca1d4c_4|py37h5ca1d4c_5|py37h5ca1d4c_4']
Package mkl-service conflicts for:
scipy -> mkl-service[version='>=2,<3.0a0']
numpy-base -> mkl-service[version='>=2,<3.0a0']
numpy -> mkl-service[version='>=2,<3.0a0']
mkl_fft -> mkl-service[version='>=2,<3.0a0']
mkl_random -> mkl-service[version='>=2,<3.0a0']
Package m2w64-gcc-libs conflicts for:
blas -> m2w64-gcc-libs
grpcio -> m2w64-gcc-libs
Package bleach conflicts for:
tensorboard -> bleach[version='1.5.0|>=1.5.0,<1.5.1.0a0']
tensorflow -> bleach==1.5.0
Package keras-applications conflicts for:
tensorflow-base -> keras-applications[version='>=1.0.5|>=1.0.6']
keras -> keras-applications[version='1.0.4.*|>=1.0.6|>=1.0.8']
tensorflow -> keras-applications[version='>=1.0.6']
keras-base -> keras-applications[version='1.0.2|1.0.4.*|>=1.0.6']
Package mkl conflicts for:
numpy -> mkl[version='>=2018.0.0,<2019.0a0|>=2018.0.1,<2019.0a0|>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2020.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0']
mkl_fft -> mkl[version='>=2019.1,<2020.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0']
mkl-service -> mkl[version='>=2019.3,<2020.0a0|>=2019.4,<2020.0a0']
numpy-base -> mkl[version='>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2020.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0']
scipy -> mkl[version='>=2018.0.0,<2019.0a0|>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2020.0a0|>=2019.4,<2020.0a0']
mkl_random -> mkl[version='>=2019.1,<2020.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0']
blas -> mkl
Package distlib conflicts for:
pip -> distlib
Package openblas conflicts for:
numpy -> openblas[version='0.2.20|0.2.20.*|>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0']
blas -> openblas
Package colorama conflicts for:
pip -> colorama
Package backports.weakref conflicts for:
tensorflow -> backports.weakref[version='1.0rc1|>=1.0rc1']
Package cachecontrol conflicts for:
pip -> cachecontrol
Package tensorboard conflicts for:
tensorflow-base -> tensorboard[version='>=1.13.0,<1.14.0a0']
tensorflow -> tensorboard[version='1.10.*|1.9.*|>=0.4.0rc1,<0.5.0|>=1.10.0,<1.11.0|>=1.11.0,<1.12.0|>=1.12.0,<1.13.0|>=1.13.0,<1.14.0|>=1.13.0,<1.14.0a0|>=1.14.0,<1.15.0|>=1.5.0,<1.6.0|>=1.6.0,<1.7.0|>=1.7.0,<1.8.0|>=1.8.0,<1.9.0|>=1.9.0,<1.10.0']
tensorflow-gpu -> tensorboard[version='>=1.8.0,<1.9.0']
Package keras conflicts for:
keras-applications -> keras[version='>=2.1.6']
keras-base -> keras[version='2.2.0|2.2.2|2.2.4']
keras-preprocessing -> keras[version='>=2.1.6']
Package _tflow_select conflicts for:
tensorflow-gpu -> _tflow_select==2.1.0=gpu
tensorflow -> _tflow_select[version='==2.1.0|==2.2.0|==2.3.0',build='gpu|eigen|mkl']
Package intel-openmp conflicts for:
mkl -> intel-openmp
Package libtiff conflicts for:
opencv -> libtiff[version='4.0.*|>=4.0.10,<5.0a0|>=4.0.3,<4.0.8|>=4.0.8,<4.0.10|>=4.0.9,<5.0a0']
Package wrapt conflicts for:
tensorflow-estimator -> wrapt[version='>=1.11.1']
tensorflow-base -> wrapt[version='>=1.11|>=1.11.1']
Package theano conflicts for:
keras -> theano
Package wheel conflicts for:
pip -> wheel
Package numpy-base conflicts for:
numpy -> numpy-base[version='1.11.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|>=1.9.3,<2.0a0',build='py37h5c71026_7|py37h5c71026_6|py36h5c71026_7|py35h5c71026_7|py27h0bb1d87_6|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py37hc3f5095_0|py37h8128ebf_0|py27hb1d0314_0|py36h8128ebf_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py37h8128ebf_0|py37h4a99626_0|py27hfef472a_0|py37hc3f5095_5|py37h8128ebf_4|py36hc3f5095_5|py36h8128ebf_4|py27hb1d0314_5|py27h2753ae9_4|py37h5c71026_4|py37h5c71026_3|py37h5c71026_2|py37h5c71026_1|py36h5c71026_4|py36h5c71026_3|py36h5c71026_0|py35h4a99626_4|py27h0bb1d87_1|py27h0bb1d87_0|py27h0bb1d87_0|py35h555522e_1|py27h917549b_1|py37hc3f5095_12|py37h5c71026_8|py37h5c71026_7|py37h2a9b21d_11|py36hc3f5095_12|py36h8128ebf_9|py36h5c71026_8|py36h5c71026_7|py36h2a9b21d_11|py35h8128ebf_9|py35h4a99626_8|py27hb1d0314_11|py27h2753ae9_10|py27h0bb1d87_7|py27h0bb1d87_8|py27h2753ae9_9|py27hb1d0314_12|py27hfef472a_9|py35h4a99626_9|py35h8128ebf_10|py36h4a99626_9|py36h8128ebf_10|py36h8128ebf_11|py37h4a99626_9|py37h8128ebf_10|py37h8128ebf_11|py37h8128ebf_9|py36h555522e_1|py35h5c71026_0|py36h5c71026_0|py27h0bb1d87_2|py27h0bb1d87_3|py27h0bb1d87_4|py35h5c71026_0|py36h5c71026_1|py36h5c71026_2|py37h5c71026_0|py35h8128ebf_4|py35h4a99626_0|py36h4a99626_0|py27h2753ae9_0|py35h8128ebf_0|py36h8128ebf_0|py35h8128ebf_0|py36h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py36h8128ebf_0|py36hc3f5095_0|py27hb1d0314_0|py27hb1d0314_1|py37hc3f5095_1|py27hb1d0314_0|py27hb1d0314_1|py36hc3f5095_0|py36hc3f5095_1|py37hc3f5095_1|py36hc3f5095_0|py37hc3f5095_0|py27hb1d0314_0|py36hc3f5095_0|py37hc3f5095_0|py27hb1d0314_0|py36hc3f5095_0|py27h0bb1d87_7|py36h5c71026_6']
Package h5py conflicts for:
keras-applications -> h5py
keras-base -> h5py
keras -> h5py
Package qt conflicts for:
opencv -> qt[version='5.6.*|>=5.12.1,<5.13.0a0|>=5.6.2,<5.7.0a0|>=5.9.7,<5.10.0a0']
Package mkl_fft conflicts for:
numpy -> mkl_fft[version='>=1.0.4|>=1.0.6,<2.0a0']
Package cudatoolkit conflicts for:
cudnn -> cudatoolkit[version='10.0.*|8.0.*|9.0.*|>=10.0,<10.1|>=10.1,<10.2|>=9.0,<9.1']
tensorflow-base -> cudatoolkit[version='9.0.*|>=10.0.130,<10.1.0a0|>=9.0,<9.1.0a0']
Package enum34 conflicts for:
absl-py -> enum34
Package keras-base conflicts for:
keras -> keras-base[version='2.2.0.*|2.2.2.*|2.2.4.*']
Package unittest2 conflicts for:
h5py -> unittest2
Package webencodings conflicts for:
pip -> webencodings
Package pip conflicts for:
python=3.7 -> pip
Package libblas conflicts for:
blas -> libblas==3.8.0[build='9_mkl|8_openblas|8_mkl|7_openblas|7_mkl|7_blis|6_openblas|6_blis|5_openblas|4_h8933c1f_netlib|14_openblas|14_mkl|13_blis|12_openblas|12_blis|11_openblas|11_blis|10_openblas|10_mkl|10_blis|11_mkl|12_mkl|13_mkl|13_openblas|14_blis|4_blis|4_mkl|4_openblas|5_blis|5_h8933c1f_netlib|5_mkl|6_h8933c1f_netlib|6_mkl|7_h8933c1f_netlib|8_blis|9_blis|9_openblas']
numpy -> libblas[version='>=3.8.0,<4.0a0']
Package libmklml conflicts for:
tensorflow-base -> libmklml[version='>=2018.0.3|>=2019.0.3|>=2019.0.5']
Package packaging conflicts for:
pip -> packaging
Package mkl_random conflicts for:
numpy -> mkl_random[version='>=1.0.2,<2.0a0']
Package tensorflow-base conflicts for:
tensorflow -> tensorflow-base[version='1.13.1|1.13.1|1.13.1|1.13.1|1.13.1|==1.10.0|==1.11.0|==1.11.0|==1.11.0|==1.12.0|==1.12.0|==1.12.0|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|==1.13.1|1.13.2|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|==1.14.0|1.7.0|1.7.1|1.8.0|==1.9.0|==1.9.0|==1.9.0|==1.9.0',build='mkl_py37ha978198_0|gpu_py36h55fc52a_0|eigen_py36hdbc3f0e_0|py37_7|gpu_py37h0fff12a_0|gpu_py36h871c8ca_0|gpu_py36h0fff12a_0|eigen_py37hf8af7b3_0|eigen_py36hf8af7b3_0|mkl_py36h81393da_0|eigen_py36h45df0d8_0|mkl_py36h81393da_0|mkl_py35h81393da_0|eigen_py35h45df0d8_0|eigen_py36h45df0d8_0|gpu_py35h6e53903_0|gpu_py36h6e53903_0|mkl_py36h81393da_0|eigen_py36h45df0d8_0|gpu_py36h6e53903_0|gpu_py36h6e53903_0|gpu_py37h871c8ca_0|mkl_py36hcaf7020_0|mkl_py37hcaf7020_0|py36_4|py36_5|py36_6|py36_8|py36_0|eigen_py37hdbc3f0e_0|gpu_py36h9ee611f_0|gpu_py37h55fc52a_0|gpu_py37h9ee611f_0|mkl_py36ha978198_0|eigen_py35h45df0d8_0|eigen_py36h45df0d8_0|gpu_py35h6e53903_0|gpu_py36h6e53903_0']
Package scipy conflicts for:
keras-base -> scipy[version='>=0.14']
keras -> scipy[version='>=0.14']
keras-preprocessing -> scipy[version='>=0.14']
Package wincertstore conflicts for:
setuptools -> wincertstore[version='>=0.2']
Package cython conflicts for:
pyyaml -> cython
Package libopencv conflicts for:
opencv -> libopencv[version='3.4.7|4.1.1|4.1.1|4.1.2',build='h7e61296_0|he03da11_4|h7e61296_5|h7e61296_4|he03da11_3']
Package * conflicts for:
numpy -> *[track_features=blas_openblas]
Package libpng conflicts for:
opencv -> libpng[version='1.6.*|>=1.6.21,<1.7|>=1.6.22,<1.6.31|>=1.6.23,<1.7|>=1.6.28,<1.7|>=1.6.32,<1.6.35|>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0|>=1.6.37,<1.7.0a0']
Package tensorflow-gpu-base conflicts for:
tensorflow-gpu -> tensorflow-gpu-base==1.8.0
Package libflang conflicts for:
numpy -> libflang[version='>=5.0.0']
Package freetype conflicts for:
opencv -> freetype[version='>=2.9.1,<3.0a0']
Package requests conflicts for:
pip -> requests
Package pyreadline conflicts for:
h5py -> pyreadline
Package certifi conflicts for:
setuptools -> certifi[version='>=2016.09']
Note that strict channel priority may have removed packages required for satisfiability.
I am experience very similar problem with conda 4.7.12.
Trying to update rpy2 to a new version on conda-forge I am seeing the same failure:
$ conda install --strict-channel-priority -c defaults -c conda-forge rpy2=3.1.0
results in the following error:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Busy indicator kept spinning for about 15 minutes after that I killed the job. The conda version is 4.7.12.
I don't think is the same issue as #9415 - I have a similar problem with the same conda 4.7.12 trying to upgrade to matplotlib 3.1.2 only available in conda-forge -
At the end for the sake of progress I just downloaded and updated the package manually
I experience the same problem, both on windows and Ubuntu Linux. I started with a new installation of OS and anaconda, but always went to this problem.
Same issue with the ...failed with initial frozen solve. Retrying with flexible solve. when trying to update my base anaconda from python 3.6.9 to 3.7 or 3.8. Easily ran for over half an hour both times with CPU throttling the whole time.
Also tried a new OS (from Ubuntu to Manjaro) and with a fresh install, when I installed anaconda it was still at Python 3.6, tried to update to 3.8 and same issue.
Today I tried downgrading to conda install conda=4.6.141 (first run conda config --set allow_conda_downgrades true) and was able to get Python 3.7 with normal behavior during the installation process. I feel this is an issue with the new conda version
I experienced the same problem and decided to create a virtual environment with python 3.7 before installing my package( Spacy using conda-forge).This seems to have worked but I don't know if it cuts across all packages. I am sure the issue is with some incompatibility with the python version
I've had this issue for the past few days as well; came up when I was trying to install the Selenium package from conda-forge into conda 4.7.12. Tried a bunch of different things, but the only thing that seemed to work was downgrading manually, following the suggestion here since I couldn't install anything via conda. Here's how I did it:
-
Run this code to allow downgrades:
conda config --set allow_conda_downgrades true -
Find and download the standalone conda executable you want here: https://repo.anaconda.com/pkgs/misc/conda-execs/. I went with 4.7.5 and it's been fine so far.
-
Run this to install the downloaded executable into your existing directory:
<executable path> install -p <path to broken installation> conda=<version number>
<executable path> is the path to the downloaded .exe. <path to broken installation> is just your main Anaconda folder. <version number> is whatever executable number you've decided to go with. That worked for me, anyway!
-
Once that goes through, run
conda config --set auto_update_conda false. Otherwise installing packages will just get you right back to the buggy version. -
Install your packages and wait until a confirmed fix for this is rolled out before upgrading your conda again :D
Not sure how universal of a fix this will be, but it worked for me. Installed Selenium, at least, and it's working in Spyder right now.
I too have experienced this error on a fresh Anaconda install (V 1.9.7) downloaded 2019-11-24 on Windows 10 Pro (x64, version 1809 build 17763.864). The problem arose when trying to install OpenCV. After allowing the analysis of the problem to continue for many hours the following list of incompatibilities was displayed. I hope this helps someone.
(base) C:\Users\wayne>conda install -c conda-forge opencv
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment:
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
Examining llvmdev: 23%|██████████████ | 89/379 [00:00<00:00, 2960.43it/|
Comparing specs that have this dependency: 19%|███████▌ | 6/32 [03:04<13:20, 30.80s/i
Comparing specs that have this dependency: 38%|██████████████▋ | 12/32 [05:17<08:49, 26.48s/i- /
Comparing specs that have this dependency: 50%|████████████████▌ | 16/32 [8:43:27<8:43:27, 1962.99s/i/ |
Examining llvm-meta: 80%|█████████████████████████████████████████▍ | 302/379 [12:35:46<10:39:29, 498.31s/i-
Comparing specs that have this dependency: 16%|██████▎ | 5/32 [05:22<29:00, 64.46s/i/ -
Comparing specs that have this dependency: 38%|████████████▍ | 12/32 [3:44:51<6:14:45, 1124.28s/i/
failed -
-
UnsatisfiableError: The following specifications were found to be incompatible with each other: /
Package llvm-meta conflicts for: pytest-arraydiff -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pandas -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 seaborn -> numpy[version='>=1.9.3'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] dask -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 bokeh -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pytables -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] nltk -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] bkcharts -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 patsy -> numpy[version='>=1.4.0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] scipy -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] bottleneck -> numpy=1.11 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 scikit-learn -> blas==1.0=mkl -> libblas==3.8.0=8_mkl -> libopenblas==0.3.7=h29e5d5d_0 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] patsy -> numpy[version='>=1.4.0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 bkcharts -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] blas -> openblas -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] imageio -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] nltk -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pytest-astropy -> pytest-arraydiff[version='>=0.1'] -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] mkl-service -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 scikit-image -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] pywavelets -> numpy=1.13 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 seaborn -> numpy[version='>=1.9.3'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 astropy -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] pytest-arraydiff -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] scipy -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pytest-astropy -> pytest-arraydiff[version='>=0.1'] -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pytables -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 numpy-base -> mkl-service[version='>=2,<3.0a0'] -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] distributed -> bokeh[version='>=0.12.3'] -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 distributed -> bokeh[version='>=0.12.3'] -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] mkl_fft -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 mkl_random -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] opencv -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta[version='5.0.0.|8.0.0.'] scikit-learn -> blas==1.0=mkl -> libblas==3.8.0=8_mkl -> libopenblas==0.3.7=h29e5d5d_0 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] h5py -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] pytest-doctestplus -> numpy[version='>=1.10'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] numba -> numpy[version='>=1.11,<1.12.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pywavelets -> numpy=1.13 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] mkl-service -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] bokeh -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] numexpr -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 opencv -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] mkl_fft -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 numexpr -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] statsmodels -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] blas -> openblas -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 numpy-base -> mkl-service[version='>=2,<3.0a0'] -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 matplotlib -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] imageio -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 scikit-image -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 matplotlib -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 h5py -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 mkl_random -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 dask -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] bottleneck -> numpy=1.11 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] pytest-doctestplus -> numpy[version='>=1.10'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 numba -> numpy[version='>=1.11,<1.12.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] statsmodels -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 astropy -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 -> llvm-meta=5.0.0 pandas -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> llvm-meta[version='5.0.0|5.0.0.'] Package llvmdev conflicts for: scipy -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 imageio -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 pytest-astropy -> pytest-arraydiff[version='>=0.1'] -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 mkl_fft -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 blas -> openblas -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 nltk -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 dask -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 bottleneck -> numpy=1.11 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 numpy-base -> mkl-service[version='>=2,<3.0a0'] -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 matplotlib -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 numexpr -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 numba -> numpy[version='>=1.11,<1.12.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 scikit-learn -> blas==1.0=mkl -> libblas==3.8.0=8_mkl -> libopenblas==0.3.7=h29e5d5d_0 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 seaborn -> numpy[version='>=1.9.3'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 bokeh -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 pandas -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 pywavelets -> numpy=1.13 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 mkl_random -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 bkcharts -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 opencv -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 pytables -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 distributed -> bokeh[version='>=0.12.3'] -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 statsmodels -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 h5py -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 pytest-doctestplus -> numpy[version='>=1.10'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 scikit-image -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 pytest-arraydiff -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 astropy -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 patsy -> numpy[version='>=1.4.0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 mkl-service -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] -> llvmdev==5.0.0 Package clangdev conflicts for: numexpr -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] numba -> numpy[version='>=1.11,<1.12.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] numpy-base -> mkl-service[version='>=2,<3.0a0'] -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] bokeh -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] bottleneck -> numpy=1.11 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] h5py -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] pytest-astropy -> pytest-arraydiff[version='>=0.1'] -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] mkl_random -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] blas -> openblas -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] pytest-doctestplus -> numpy[version='>=1.10'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] seaborn -> numpy[version='>=1.9.3'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] statsmodels -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] astropy -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] mkl_fft -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] pytables -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] nltk -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] bkcharts -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] pywavelets -> numpy=1.13 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] pandas -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] distributed -> bokeh[version='>=0.12.3'] -> numpy[version='>=1.7.1'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] mkl-service -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] dask -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] scikit-image -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] scikit-learn -> blas==1.0=mkl -> libblas==3.8.0=8_mkl -> libopenblas==0.3.7=h29e5d5d_0 -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] matplotlib -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] pytest-arraydiff -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] opencv -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] patsy -> numpy[version='>=1.4.0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] imageio -> numpy -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.'] scipy -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] -> openmp==5.0.0 -> clangdev[version='5.0.0|5.0.0.']
Hi there. I had the same problem doing
conda install -c conda-forge opencv
It gave the error:
Solving environment: failed with initial frozen solve. Retrying with flexible solve,
and loaded forever. I managed to fix the problem. First, I created an environment called opencv using
conda create -n opencv
I then activated it:
conda activate opencv
and downloaded an earlier version using a different command:
conda install -c anaconda opencv
This gave me opencv 3, not the most recent 4. I then created a second environment called opencv4. Use above code to create and activate. I finally did the standard download:
conda install -c conda-forge opencv
And it worked! The first environment, opencv3, may have created necessary files - or not. The solution could be just creating the environment. Feel free to try that out!
I can confirm that Marcsprk43's instructions above (the long version at least - I did not try just creating the environment) work without issue. I also found that 'pip install opencv-python' from the Anaconda prompt worked.
I had the same issue installing RStudio. What solved it for me was a silly small mistake. Using anaconda's navigator, make sure the environment has R accepted. So when making a new environment using anaconda navigator, when prompted with what language, ensure to select R.
Hi there. I had the same problem doing
conda install -c conda-forge opencvIt gave the error:Solving environment: failed with initial frozen solve. Retrying with flexible solve, and loaded forever. I managed to fix the problem. First, I created an environment called opencv usingconda create -n opencvI then activated it:conda activate opencvand downloaded an earlier version using a different command:conda install -c anaconda opencvThis gave me opencv 3, not the most recent 4. I then created a second environment called opencv4. Use above code to create and activate. I finally did the standard download:conda install -c conda-forge opencvAnd it worked! The first environment, opencv3, may have created necessary files - or not. The solution could be just creating the environment. Feel free to try that out!
this solution works for me! thanks Marcsprk43!!
I had the same issue with multiple packages after updating conda. I "solved" it by downgrading back to older version of conda.
conda install -n root conda=4.6
It seems the problem two packages are requiring different version of the same dependent package, which cannot be solved by conda. My case is I installed PyTorch 1.3.1 first with cudatoolkit-10.1, then try to install tensorflow-gpu which conflicts with cudatoolkit-10.1. I remember the old conda was trying to downgrade PyTorch. But maybe because there is no such solution now.
For me the issue occurred on conda version 4.7.12 when creating a new environment. It seems when I did not specify a python version it defaulted to 3.8.0 although the supported version should have been 3.7. Specifying python=3.7 solved the issue for me when trying to install pytorch.
I am a newbie and had exactly the same problem. As others pointed out, the key is "conda create -n opencv". As of today (12/05/2019), this worked great for me and everything is uptodate (opencv-4.0.1): (ignore starlines) (use Administrator: Anaconda Prompt (Anaconda3))
C:\Users\george>conda activate base (base) C:\Users\george>conda create -n opencv Collecting package metadata (current_repodata.json): done Solving environment: done
Package Plan
environment location: C:\ProgramData\Anaconda3\envs\opencv
Proceed ([y]/n)? y
Preparing transaction: done Verifying transaction: done Executing transaction: done
To activate this environment, use
$ conda activate opencv
To deactivate an active environment, use
$ conda deactivate
(base) C:\Users\george>conda activate opencv
(opencv) C:\Users\george>conda install -c anaconda opencv Collecting package metadata (current_repodata.json): done Solving environment: done
Package Plan
environment location: C:\ProgramData\Anaconda3\envs\opencv
added / updated specs: - opencv
The following packages will be downloaded:
package | build
---------------------------|-----------------
blas-1.0 | mkl 6 KB anaconda
ca-certificates-2019.11.27 | 0 163 KB anaconda
certifi-2019.11.28 | py38_0 157 KB anaconda
hdf5-1.10.4 | h7ebc959_0 19.2 MB anaconda
icc_rt-2019.0.0 | h0cc432a_1 9.4 MB anaconda
intel-openmp-2019.5 | 281 1.9 MB anaconda
jpeg-9b | vc14h4d7706e_1 313 KB anaconda
libopencv-4.0.1 | hbb9e17c_0 38.1 MB anaconda
libpng-1.6.37 | h2a8f88b_0 598 KB anaconda
libtiff-4.1.0 | h56a325e_0 997 KB anaconda
mkl-2019.5 | 281 158.3 MB anaconda
mkl-service-2.3.0 | py38hb782905_0 59 KB anaconda
mkl_fft-1.0.15 | py38h14836fe_0 139 KB anaconda
mkl_random-1.1.0 | py38hf9181ef_0 285 KB anaconda
numpy-1.17.4 | py38h4320e6b_0 5 KB anaconda
numpy-base-1.17.4 | py38hc3f5095_0 4.8 MB anaconda
opencv-4.0.1 | py38h2a7c758_0 23 KB anaconda
openssl-1.1.1 | he774522_0 5.7 MB anaconda
pip-19.3.1 | py38_0 1.9 MB anaconda
py-opencv-4.0.1 | py38he44ac1e_0 1.9 MB anaconda
python-3.8.0 | hff0d562_2 19.6 MB anaconda
setuptools-42.0.2 | py38_0 675 KB anaconda
six-1.13.0 | py38_0 27 KB anaconda
sqlite-3.30.1 | he774522_0 962 KB anaconda
vc-14.1 | h0510ff6_4 6 KB anaconda
vs2015_runtime-14.16.27012 | hf0eaf9b_0 2.4 MB anaconda
wheel-0.33.6 | py38_0 53 KB anaconda
wincertstore-0.2 | py38_0 15 KB anaconda
xz-5.2.4 | h2fa13f4_4 812 KB anaconda
zlib-1.2.11 | vc14h1cdd9ab_1 117 KB anaconda
zstd-1.3.7 | h508b16e_0 536 KB anaconda
------------------------------------------------------------
Total: 269.1 MB
The following NEW packages will be INSTALLED:
blas anaconda/win-64::blas-1.0-mkl ca-certificates anaconda/win-64::ca-certificates-2019.11.27-0 certifi anaconda/win-64::certifi-2019.11.28-py38_0 hdf5 anaconda/win-64::hdf5-1.10.4-h7ebc959_0 icc_rt anaconda/win-64::icc_rt-2019.0.0-h0cc432a_1 intel-openmp anaconda/win-64::intel-openmp-2019.5-281 jpeg anaconda/win-64::jpeg-9b-vc14h4d7706e_1 libopencv anaconda/win-64::libopencv-4.0.1-hbb9e17c_0 libpng anaconda/win-64::libpng-1.6.37-h2a8f88b_0 libtiff anaconda/win-64::libtiff-4.1.0-h56a325e_0 mkl anaconda/win-64::mkl-2019.5-281 mkl-service anaconda/win-64::mkl-service-2.3.0-py38hb782905_0 mkl_fft anaconda/win-64::mkl_fft-1.0.15-py38h14836fe_0 mkl_random anaconda/win-64::mkl_random-1.1.0-py38hf9181ef_0 numpy anaconda/win-64::numpy-1.17.4-py38h4320e6b_0 numpy-base anaconda/win-64::numpy-base-1.17.4-py38hc3f5095_0 opencv anaconda/win-64::opencv-4.0.1-py38h2a7c758_0 openssl anaconda/win-64::openssl-1.1.1-he774522_0 pip anaconda/win-64::pip-19.3.1-py38_0 py-opencv anaconda/win-64::py-opencv-4.0.1-py38he44ac1e_0 python anaconda/win-64::python-3.8.0-hff0d562_2 setuptools anaconda/win-64::setuptools-42.0.2-py38_0 six anaconda/win-64::six-1.13.0-py38_0 sqlite anaconda/win-64::sqlite-3.30.1-he774522_0 vc anaconda/win-64::vc-14.1-h0510ff6_4 vs2015_runtime anaconda/win-64::vs2015_runtime-14.16.27012-hf0eaf9b_0 wheel anaconda/win-64::wheel-0.33.6-py38_0 wincertstore anaconda/win-64::wincertstore-0.2-py38_0 xz anaconda/win-64::xz-5.2.4-h2fa13f4_4 zlib anaconda/win-64::zlib-1.2.11-vc14h1cdd9ab_1 zstd anaconda/win-64::zstd-1.3.7-h508b16e_0
Proceed ([y]/n)? y
Downloading and Extracting Packages py-opencv-4.0.1 | 1.9 MB | ################################################# | 100% jpeg-9b | 313 KB | ################################################# | 100% libopencv-4.0.1 | 38.1 MB | ################################################# | 100% wincertstore-0.2 | 15 KB | ################################################# | 100% libtiff-4.1.0 | 997 KB | ################################################# | 100% zlib-1.2.11 | 117 KB | ################################################# | 100% libpng-1.6.37 | 598 KB | ################################################# | 100% mkl-2019.5 | 158.3 MB | ################################################# | 100% pip-19.3.1 | 1.9 MB | ################################################# | 100% numpy-1.17.4 | 5 KB | ################################################# | 100% blas-1.0 | 6 KB | ################################################# | 100% intel-openmp-2019.5 | 1.9 MB | ################################################# | 100% vc-14.1 | 6 KB | ################################################# | 100% icc_rt-2019.0.0 | 9.4 MB | ################################################# | 100% setuptools-42.0.2 | 675 KB | ################################################# | 100% mkl_random-1.1.0 | 285 KB | ################################################# | 100% wheel-0.33.6 | 53 KB | ################################################# | 100% sqlite-3.30.1 | 962 KB | ################################################# | 100% hdf5-1.10.4 | 19.2 MB | ################################################# | 100% six-1.13.0 | 27 KB | ################################################# | 100% xz-5.2.4 | 812 KB | ################################################# | 100% mkl-service-2.3.0 | 59 KB | ################################################# | 100% python-3.8.0 | 19.6 MB | ################################################# | 100% vs2015_runtime-14.16 | 2.4 MB | ################################################# | 100% numpy-base-1.17.4 | 4.8 MB | ################################################# | 100% openssl-1.1.1 | 5.7 MB | ################################################# | 100% opencv-4.0.1 | 23 KB | ################################################# | 100% certifi-2019.11.28 | 157 KB | ################################################# | 100% mkl_fft-1.0.15 | 139 KB | ################################################# | 100% ca-certificates-2019 | 163 KB | ################################################# | 100% zstd-1.3.7 | 536 KB | ################################################# | 100% Preparing transaction: done Verifying transaction: done Executing transaction: done
(opencv) C:\Users\george>
----------then I went to this folder:------------------ C:\ProgramData\Anaconda3\envs\opencv
find and click python (the application file), got this worked:(ignore the dashlines)
Python 3.8.0 (default, Nov 6 2019, 16:00:02) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32 Type "help", "copyright", "credits" or "license" for more information.
import cv2 print(cv2.version) 4.0.1
(Credit also to https://medium.com/@pranav.keyboard/installing-opencv-for-python-on-windows-using-anaconda-or-winpython-f24dd5c895eb)
Come on, we already had a similar issue this summer during July after Conda stopped integrating the free channel. I tried to update now thinking the issue was resolved, but no! As soon as I try to conda install any package (I'm not even creating a new env), it fails.
PS: downgrading using conda install -n root conda=4.6 just like in July doesn't work either, still "failed with frozen solve".
And for info I'm trying to install "nibabel", but really any package install fails with conda since July. That's awful.
I have a similar issue, and solved it by adding proper channels of the packages which i need.
'-c conda-forge'
conda create -n snubh python tensorflow=2.0.0 keras matplotlib opencv scipy anaconda -c anaconda -c conda-forge
But i don't know why this solved it.
I have the same issue running conda install keras.
Running conda install conda=4.6 results in
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- conda=4.6 -> python[version='2.7.*|3.6.*']
- conda=4.6 -> python[version='<=3.3']
- conda=4.6 -> python[version='>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
Your python: python=3.8
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
The following specifications were found to be incompatible with each other:
Package certifi conflicts for:
python=3.8 -> pip -> setuptools -> certifi[version='>=2016.9.26']
conda=4.6 -> requests[version='>=2.18.4,<3'] -> certifi[version='>=2016.09|>=2016.9.26|>=2017.4.17']
Package wheel conflicts for:
conda=4.6 -> python[version='>=3.7,<3.8.0a0'] -> pip -> wheel
python=3.8 -> pip -> wheel
Package pip conflicts for:
conda=4.6 -> python[version='>=3.7,<3.8.0a0'] -> pip
python=3.8 -> pip
Package setuptools conflicts for:
conda=4.6 -> python[version='>=3.7,<3.8.0a0'] -> pip -> setuptools
python=3.8 -> pip -> setuptools
conda=4.6 -> setuptools[version='>=31.0.1']
Package ca-certificates conflicts for:
conda=4.6 -> python[version='>=3.7,<3.8.0a0'] -> openssl=1.0 -> ca-certificates
python=3.8 -> openssl[version='>=1.1.1a,<1.1.2a'] -> ca-certificates
Note that strict channel priority may have removed packages required for satisfiability.
I encountered the same problem trying to install opencv from conda-forge. Got it to install by rolling conda back to 4.6.14 from 4.8.0. My colleagues and I have experienced this issue with several other non-core packages, on both Linux and Windows machines.
downgrade conda to 4.6.14, it works.
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
I had the same problem when creating environment with python 3.8, using python 3.7 with conda 4.8 works fine.
Update: I could solve it by first deleting all my Anaconda install (including Python 2, which for some reason conflicted with Python 3) and installing an older version: Anaconda3-2019.03-Windows-x86_64.exe , downloadable from:
https://repo.continuum.io/archive/
For the moment, I will avoid updating to the latest conda and Anaconda at all cost. All releases since July have been a mess.