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Solving environment: failed with initial frozen solve. Retrying with flexible solve. #9367

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ale152 opened this issue Oct 24, 2019 · 46 comments
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@ale152
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@ale152 ale152 commented Oct 24, 2019

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

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@ale152 ale152 commented Oct 24, 2019

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.
@slonik-az

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@slonik-az slonik-az commented Nov 11, 2019

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.

@candalfigomoro

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@candalfigomoro candalfigomoro commented Nov 11, 2019

Same issue, same as #9415?

@laredo

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@laredo laredo commented Nov 18, 2019

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

@gongliyu

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@gongliyu gongliyu commented Nov 18, 2019

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.

@oliverHHY

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@oliverHHY oliverHHY commented Nov 18, 2019

Same problem here on ubuntu.

@iisharankov

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@iisharankov iisharankov commented Nov 18, 2019

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

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@raymondklutse raymondklutse commented Nov 18, 2019

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

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@andrew-braun andrew-braun commented Nov 18, 2019

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:

  1. Run this code to allow downgrades: conda config --set allow_conda_downgrades true

  2. 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.

  3. 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!

  1. 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.

  2. 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.

@WayneKiely

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@WayneKiely WayneKiely commented Nov 26, 2019

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.
']

@Marcsprk43

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@Marcsprk43 Marcsprk43 commented Nov 26, 2019

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!

@WayneKiely

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@WayneKiely WayneKiely commented Nov 28, 2019

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.

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@KyeMML KyeMML commented Nov 29, 2019

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.

@hmnhn

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@hmnhn hmnhn commented Dec 1, 2019

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!

this solution works for me! thanks Marcsprk43!!

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@PuncocharM PuncocharM commented Dec 2, 2019

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

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@gongliyu gongliyu commented Dec 2, 2019

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.

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@victorca25 victorca25 commented Dec 2, 2019

In my case the problem was also solved by downgrading

@dbrisaro

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@dbrisaro dbrisaro commented Dec 2, 2019

Downgrading works indeed!

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@Fredrik00 Fredrik00 commented Dec 3, 2019

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.

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@gittering gittering commented Dec 6, 2019

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)

@lrq3000

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@lrq3000 lrq3000 commented Dec 12, 2019

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.

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@Crispy13 Crispy13 commented Dec 15, 2019

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.

@xinaodan

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@xinaodan xinaodan commented Dec 18, 2019

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.
@jml17

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@jml17 jml17 commented Dec 19, 2019

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.

@schwinnzyx

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@schwinnzyx schwinnzyx commented Dec 19, 2019

hope this will be fixed soon!

@brandonsimpson21

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@brandonsimpson21 brandonsimpson21 commented Dec 20, 2019

same issue

@lengthmin

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@lengthmin lengthmin commented Dec 22, 2019

downgrade conda to 4.6.14, it works.

conda config --set allow_conda_downgrades true
conda install conda=4.6.14
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@MortezaRamezani MortezaRamezani commented Dec 23, 2019

I had the same problem when creating environment with python 3.8, using python 3.7 with conda 4.8 works fine.

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@alantsangmb alantsangmb commented Dec 24, 2019

I have the same problem too.
Is this going to be solved in the future?

@lrq3000

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@lrq3000 lrq3000 commented Dec 24, 2019

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.

@alantsangmb

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@alantsangmb alantsangmb commented Dec 27, 2019

I solved it by removing the conda and re-install the 4.6.14 version.

@ponggung

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@ponggung ponggung commented Dec 31, 2019

I have the same issue too!
Hope this can be solved soon.

Conda info

I have tried to create new conda env
and downgrade conda to 4.6.14 still not work for me.

conda install -y -q -c conda-forge  -c anaconda --file requirements.txt

requirements.txt

pandas==0.25.3
SQLAlchemy==1.3.1
PyMySQL==0.9.3
requests==2.22.0
psutil==5.6.1
alembic==1.0.11
beautifulsoup4==4.7.1
lxml==4.3.2
html5lib==1.0.1
Flask==1.1.0
Flask-Excel==0.0.7
pyexcel-xlsx==0.5.7
imageio==2.6.1
scikit-learn==0.20.3
matplotlib==3.0.3
networkx==2.3
dash==1.3.1
dash-core-components==1.2.1
dash-html-components==1.0.1
dash-renderer==1.1.0
prefect==0.8.1
python-graphviz==0.13.2
nodejs==13.0.0
dask==2.9.0

Error

Collecting package metadata: ...working... done
Solving environment: ...working... failed

UnsatisfiableError: The following specifications were found to be in conflict:
  - matplotlib==3.0.3 -> matplotlib-base==3.0.3=py36h5f35d83_1 -> icu[version='>=58.2,<59.0a0']
  - nodejs==13.0.0
Use "conda search <package> --info" to see the dependencies for each package.
@doyuga

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@doyuga doyuga commented Jan 8, 2020

use pip install package_name within the anaconda prompt
eg pin install tensorflow

@xpzouying

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@xpzouying xpzouying commented Jan 8, 2020

You could create a new environment, and try again. It's works for me.

conda create --name myenv
conda activate myenv
@waque

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@waque waque commented Jan 9, 2020

I spent like one hour trying to install it in base. By creating a new env works just fine

@dros1986

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@dros1986 dros1986 commented Jan 9, 2020

I spent all day trying to solve this problem. At the end, I was able to solve it with:

conda config --set channel_priority false

All conflicts have been solved and now I can install everything without problems.

Hope it helps.

@saikalyan98

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@saikalyan98 saikalyan98 commented Jan 10, 2020

OMG!!! Downgrading worked!! Thank you @PuncocharM

@will133

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@will133 will133 commented Jan 10, 2020

I recently also tried to upgrade to 4.8.0 and experienced this problem as well. I have a conda environment where I tried to upgrade the pycodestyle package to 2.5.0. It's a pretty straightforward package with only python as its dependency. My environment has hundreds of packages, but it's just trying to upgrade one. I waited for the solve for more than 30+ minutes before I hit ctrl-c out.

Trying the channel_priority does not seem to work for me. I downgraded to 4.6.14 and it could resolve fine after a short while with no problem. This is really a showstopper for us so we're staying away with the latest release for now.

@palindrom615

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@palindrom615 palindrom615 commented Jan 22, 2020

I've got the error when I'm trying to install menpo/opencv3.

, I've got same message as @Fredrik00 ( #9367 (comment) ) and @xinaodan ( #9367 (comment) ) mentioned and it seems having trouble with python version 3.7

...
UnsatisfiableError: The following specifications were found                                                                                                                
to be incompatible with the existing python installation in your environment:

Specifications:

  - opencv3 -> python[version='2.7.*|3.5.*|3.6.*']
  - opencv3 -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0']

Your python: python=3.7
...

I solved the issue with creating environment with python 3.6 without downgrading anaconda itself.

@BalveerSinghYT

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@BalveerSinghYT BalveerSinghYT commented Jan 22, 2020

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 installed opencv but how can i add its path to base?

@0790864526

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@0790864526 0790864526 commented Jan 31, 2020

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!

this solution works for me! thanks Marcsprk43!!

i had the same problem. this has really helped me . thank you

@romainx

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@romainx romainx commented Feb 3, 2020

Just to share my experience if it could help. I had the same kind of issue (a package cannot be installed on the conda version 4.7.12.1). To fix it I had to downgrade conda (in fact install an earlier version of miniconda) to version 4.5.12.

So I was wondering is this behavior is related to the implementation of the new channel priority mechanism (see #7729) that can now take 3 values: strict, flexible, and disabled.

@samratalamshanto

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@samratalamshanto samratalamshanto commented Feb 15, 2020

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!

this solution works for me! thanks Marcsprk43!!

i had the same problem. this has really helped me . thank you

It works.Thank you!

@Isaac009

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@Isaac009 Isaac009 commented Feb 18, 2020

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 works for me, thanks

@isaacbshelton

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@isaacbshelton isaacbshelton commented Feb 18, 2020

Had the same problem trying to install pyarrow. Downgrading to 4.6 worked.

Is this a known issue? Surely installing packages is important...and it used to work correctly...

@suryacaprice

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@suryacaprice suryacaprice commented Feb 18, 2020

Why is anoconda becoming more buggy with latest versions

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