Conda: 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
ale152
All 116 comments
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.
slonik-az
on 11 Nov 2019
Same issue, same as https://github.com/conda/conda/issues/9415?
candalfigomoro
on 11 Nov 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
laredo
on 18 Nov 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.
gongliyu
on 18 Nov 2019
Same problem here on ubuntu.
hyhuang00
on 18 Nov 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
iisharankov
on 18 Nov 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
raymondklutse
on 18 Nov 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:
Run this code to allow downgrades:
conda config --set allow_conda_downgrades trueFind 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.
andrew-braun
on 18 Nov 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.']
WayneKiely
on 26 Nov 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!
Marcsprk43
on 27 Nov 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.
WayneKiely
on 29 Nov 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.
KyeMML
on 29 Nov 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!!
hmnhn
on 1 Dec 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
PuncocharM
on 2 Dec 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.
gongliyu
on 2 Dec 2019
In my case the problem was also solved by downgrading
victorca25
on 2 Dec 2019
Downgrading works indeed!
dbrisaro
on 2 Dec 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.
Fredrik00
on 3 Dec 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)
gittering
on 6 Dec 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.
lrq3000
on 12 Dec 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.
Crispy13
on 15 Dec 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.
xinaodan
on 19 Dec 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.
jml17
on 19 Dec 2019
hope this will be fixed soon!
schwinnzyx
on 19 Dec 2019
same issue
brandonsimpson21
on 20 Dec 2019
downgrade conda to 4.6.14, it works.
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
lengthmin
on 22 Dec 2019
I had the same problem when creating environment with python 3.8, using python 3.7 with conda 4.8 works fine.
MortezaRamezani
on 23 Dec 2019
I have the same problem too.
Is this going to be solved in the future?
alantsangmb
on 24 Dec 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.
lrq3000
on 24 Dec 2019
I solved it by removing the conda and re-install the 4.6.14 version.
alantsangmb
on 27 Dec 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.
ponggung
on 31 Dec 2019
use pip install _package_name_ within the anaconda prompt
eg pin install tensorflow
doyuga
on 8 Jan 2020
You could create a new environment, and try again. It's works for me.
conda create --name myenv
conda activate myenv
xpzouying
on 8 Jan 2020
I spent like one hour trying to install it in base. By creating a new env works just fine
waque
on 9 Jan 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.
dros1986
on 9 Jan 2020
OMG!!! Downgrading worked!! Thank you @PuncocharM
saikalyan98
on 10 Jan 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.
will133
on 10 Jan 2020
I've got the error when I'm trying to install menpo/opencv3.
, I've got same message as @Fredrik00 ( https://github.com/conda/conda/issues/9367#issuecomment-561147083 ) and @xinaodan ( https://github.com/conda/conda/issues/9367#issuecomment-567264615 ) 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.
palindrom615
on 22 Jan 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?
BalveerSinghYT
on 22 Jan 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
0790864526
on 31 Jan 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.
romainx
on 3 Feb 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!
samratalamshanto
on 15 Feb 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
Isaac009
on 18 Feb 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...
isaacbshelton
on 18 Feb 2020
Why is anoconda becoming more buggy with latest versions
suryacaprice
on 18 Feb 2020
You could create a new environment, and try again. It's works for me.
conda create --name myenv conda activate myenv
This works fine !!!
Thanks @xpzouying
mandar5335
on 23 Feb 2020
I have consistently faced this issue for last two years. Why is this still an issue?To avoid it I started with a Miniconda, and I still get the frozen fail cr*p! I am trying to do the following:
conda install -c anaconda h5py=2.7.0
nirvana1122
on 24 Feb 2020
I've been getting this error too and have tried multiple fixes suggested in this thread.
This is the original 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 @/linux-64::__glibc==2.17=0: 50%|█████████████████████████▌ fa $
iledUnsatisfiableError:
I made a new environment:
conda create -n ete3
conda activate ete3
Checked my version of conda:
conda info
active environment : ete3 active env location : /home/kaylee.rich/miniconda3/envs/ete3 shell level : 2 user config file : /home/kaylee.rich/.condarcpopulated config files : /home/kaylee.rich/.condarc
conda version : 4.8.2
conda-build version : not installed
python version : 3.7.4.final.0
virtual packages : __glibc=2.17
base environment : /home/kaylee.rich/miniconda3 (writable)
channel URLs : https://conda.anaconda.org/bioconda/linux-64
https://conda.anaconda.org/bioconda/noarch
https://conda.anaconda.org/r/linux-64
https://conda.anaconda.org/r/noarch
https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
https://conda.anaconda.org/conda-forge/linux-64
https://conda.anaconda.org/conda-forge/noarch
package cache : /home/kaylee.rich/miniconda3/pkgs
/home/kaylee.rich/.conda/pkgs
envs directories : /home/kaylee.rich/miniconda3/envs
/home/kaylee.rich/.conda/envs
platform : linux-64
user-agent : conda/4.8.2 requests/2.22.0 CPython/3.7.4 Linux/3.10.0-957.12.2.el7.x86_64 centos/7.6.1810 glibc/2.
17
UID:GID : 23240533:23240533
netrc file : None
offline mode : False
I downgraded conda:
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
conda install -c etetoolkit ete3_external_apps
And still got this:
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 python=3.7: 33%|██████████████████████▋ [165/1901]
Examining @/linux-64::__glibc==2.17=0: 67%|███████████████████████████ $ [164/1901]
Examining @/linux-64::__glibc==2.17=0: 100%|██████████████████████████▒fa $ [163/1901]
iledUnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:Specifications:
- ete3_external_apps -> python[version='2.7.|3.4.']
Your python: python=3.7
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.
So I installed python 2 in that environment and added the channel to my channels:
conda install python=2
conda config --add channels etetoolkit
conda install ete3_external_apps
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. failedUnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
I'm really unsure what to do from here...
kaydrich
on 25 Feb 2020
Setting up a new environment seems like a constant fix. You may also want to do the following before installing any packages in the new environment:
conda install pycryptosat
conda config --set sat_solver pycryptosat
conda config --set channel_priority strict
I also noticed that dropping channel specification in "condo install" seems to help with the problem.
I hope this helps.
nirvana1122
on 25 Feb 2020
I had the same issue with RStudio on Windows 10 (Python Version 3.7.4.final 0, newest Anaconda-Version)
I tried downgrading using the Anaconda Prompt:
conda install conda=4.6.14
I manually created a new Environment with R activated in the Anaconda Navigator, but could not install RStudio with the Anaconda Navigator in this Environment. The command:
conda install -c r rstudio
did not work.
But i got it to run using this command in the Anaconda Prompt:
conda create -n rstudio rstudio python=3.6
this created a new Environment with RStudio already installed.
MayaDeMay
on 25 Feb 2020
Just to add my 10 cents worth ...
I had created an environment, wanted to add a package to it, tried re-running
conda install --yes --file requirements.txt
and got stuck with the same conflicts issue. I had tried to "remove" the environment but that did not work. I finally downgraded to conda 4.6.14 (just as above). All of a sudden I was able to remove the old environment, and run the package install from scratch. THANK YOU for all of the above, much appreciated!
anthonyrollett
on 29 Feb 2020
conda install conda=4.6.14
I had the same issue with RStudio on Windows 10 (Python Version 3.7.4.final 0, newest Anaconda-Version)
I tried downgrading using the Anaconda Prompt:
conda install conda=4.6.14
I manually created a new Environment with R activated in the Anaconda Navigator, but could not install RStudio with the Anaconda Navigator in this Environment. The command:
conda install -c r rstudio
did not work.
I tried downgrading using the Anaconda Prompt:
conda install conda=4.6.14
@MayaDeMay
There is a typo, it should say
conda install conda==4.6.14
agilebean
on 14 Mar 2020
creating a new environment solved issue for me. Did not have to downgrade conda or python. I was trying to install kivy and pytorch.
Amar-Gill
on 16 Mar 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!
Yes, I work for me to But when i import cv2 in jupyter notebook. it give me error : No module named 'cv2'. NEED YOUR HELP!!!!!!!!
What i can do solve this error???
My conda version is 4.7.12 and python version is 3.7.4.
muhammadazeem-collab
on 19 Mar 2020
No solution up to now on this?
Creating new environment does not work.
Installed a module and used it on a project and the module just disappeared. I have uninstalled the module and created new environment but still get this error message when I try to install the module:
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.
failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
skmaingi
on 24 Mar 2020
Hi guys, there is a solution that could probably solve your problems.
It seems that you are trying to install packages that are not from conda default channel. Take @ale152 's case for example. He is trying to install opencv from the channel menpo, then I would suggest running these commands first to add these channels to ~/.condarc:
(ordering may matter)
conda config --add channels defaults
conda config --add channels conda-forge
conda config --add channels menpo
I solved my similar issue by doing this today. Hope it works for you.
SilentGene
on 25 Mar 2020
Hi guys, there is a solution that could probably solve your problems.
It seems that you are trying to install packages that are not from conda default channel. Take @ale152 's case for example. He is trying to installopencvfrom the channelmenpo, then I would suggest running these commands first to add these channels to~/.condarc:
(ordering may matter)conda config --add channels defaults conda config --add channels conda-forge conda config --add channels menpoI solved my similar issue by doing this today. Hope it works for you.
Worked for me! I had the same issue when trying to install Scanpy, at the channel bioconda
I'm sort of a beginner with conda, but I think the proposed solution could in some cases have the effect of altering the priority order of the channels
I don't know what the preferred order is supposed to be, but I manually modified the .condarc file and left 'defaults' first, 'conda-forge' second, and 'bioconda' third, and I was able to install Scanpy without problems (at least so far)
josueibarra95
on 1 Apr 2020
The Marcsprk43's solution works !
som-ould
on 15 Apr 2020
I had the same issue when installing opencv (plus other packages) Downgrading to 4.6 worked for me.
Escalion
on 18 Apr 2020
downgrade conda to 4.6.14, it works.
conda config --set allow_conda_downgrades true conda install conda=4.6.14
THANKSSSSSSSSS for lengthmin's comments! it WORKSSSSSSSSSSSSS
Mirthgrief
on 27 Apr 2020
downgrade conda to 4.6.14, it works.
conda config --set allow_conda_downgrades true conda install conda=4.6.14THANKSSSSSSSSS for lengthmin's comments! it WORKSSSSSSSSSSSSS
Yep second that. It works. I was finally able to install imutils
antonywu
on 29 Apr 2020
Here is what worked for me.
I had faced the same error while installing argcomplete. I had conda-forge configured with priority. Even changing the order of the channels have not helped. I ended up removing condarc. After this, the environment was not stuck and able to proceed. Probably I will try adding conda-forge later.
mv ~/.condarc ~/.condarc_backup
This was the content of my condarc,
ssl_verify: true
channels:
- defaults
- conda-forge
channel_priority: strict
allow_conda_downgrades: true
gurusudhan
on 2 May 2020
So I've downgraded conda to 4.6.14, but I'm still having a similar issue.
This time, instead of saying
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
it just says
Solving environment: failed
but the result of it being unable to install a package from a channel that has it still holds.
I'm trying to run
conda install psi4 -c psi4
if anyone can see anything wrong with that.
Dripto
on 4 May 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 didn't get it here, the problem at the top of the page was "when trying to install a package on a newly created env from other channel than conda it crashes into the long Solving environment problem"
The solution is creating a new env? I created a new env and still couldn't install the orange3 package from conda-forge, it crashes into the Solving Environment loop in any env created.
I'm still stuck in this problem and didn't understand this aswer and how it worked.
Boicote13
on 5 May 2020
Found somwhere that sometimes _conda install anaconda_ helps so now i'm trying this
conda seems to try to fix the issue by herself (for 1,5 of hours now):
C:\Windows\system32>conda install anaconda
Collecting package metadata (current_repodata.json): done
Solving environment: /
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- defaults/win-64::anaconda==2020.02=py37_0
- defaults/noarch::numpydoc==0.9.2=py_0
- defaults/noarch::sphinx==2.4.0=py_0
- defaults/win-64::spyder==4.0.1=py37_0
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: |
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- defaults/win-64::anaconda==2020.02=py37_0
- defaults/noarch::numpydoc==0.9.2=py_0
- defaults/noarch::sphinx==2.4.0=py_0
- defaults/win-64::spyder==4.0.1=py37_0
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 win_unicode_console: 5%|██▎ | 14/305 [00:14<02:07, 2.28it/s]|Examining xlwings: 13%|████████▏ | 40/305 [00:51<14:43, 3.33s/it]\Examining hdf5: 14%|█████████▍ | 44/305 [00:52<10:42, 2.46s/it]\Examining zipp: 19%|████████████▌ | 59/305 [01:46<04:46, 1.17s/it]-Examining libarchive: 20%|███████████▊ | 61/305 [01:46<03:27, 1.18it/s]|Examining conda[version='>=4.8.3']: 36%|████████████████ | 111/305 [02:03<00:39, 4.97it/s]\Examining pytorch: 37%|██████████████████████▌ | 113/305 [02:04<00:42, 4.49it/s]\Examining intel-openmp: 46%|█████████████████████████▋ | 140/305 [02:25<01:06, 2.48it/s]|Examining importlib_metadata: 47%|███████████████████████▍ | 143/305 [02:25<00:50, 3.21it/s]-Examining spyder: 50%|██████████████████████████████▋ | 151/305 [02:29<00:27, 5.58it/s]\Examining distributed: 50%|████████████████████████████▊ | 154/305 [02:48<14:35, 5.80s/it]|Examining soupsieve: 55%|████████████████████████████████▎ | 167/305 [03:15<04:39, 2.02s/it]\Examining flask: 59%|█████████████████████████████████████▍ | 181/305 [03:52<02:50, 1.37s/it]/Examining kiwisolver: 62%|███████████████████████████████████▉ | 189/305 [03:55<04:29, 2.33s/it]|Examining navigator-updater: 68%|██████████████████████████████████▌ | 207/305 [04:12<01:28, 1.11it/s]\Examining autopep8: 73%|████████████████████████████████████████████ | 224/305 [04:21<00:55, 1.45it/s]/Examining tqdm: 80%|██████████████████████████████████████████████████▉ | 243/305 [04:28<00:13, 4.43it/s]-Examining libiconv: 80%|████████████████████████████████████████████████▏ | 245/305 [04:29<00:57, 1.05it/s]/Examining fastcache: 85%|█████████████████████████████████████████████████▉ | 258/305 [04:39<00:38, 1.21it/s]-Examining werkzeug: 87%|███████████████████████████████████████████████████▉ | 264/305 [04:48<00:33, 1.21it/s]|Examining pluggy: 97%|████████████████████████████████████████████████████████████▏ | 296/305 [05:17<00:05, 1.60it/s]-Examining xlrd: 97%|██████████████████████████████████████████████████████████████▎ | 297/305 [05:17<00:17, 2.15s/it]|Examining libspatialindex: 100%|█████████████████████████████████████████████████████| 305/305 [05:20<00:00, 1.05it/s]-
Examining conflict for libcurl bokeh curl imageio anaconda krb5 pillow tk scikit-image anaconda-navigator torchvision: -
Examining conflict for libcurl paramiko cryptography sortedcontainers soupsieve cython sortedcollections pycparser alab|
Examining conflict for paramiko cryptography matplotlib-base notebook anaconda-project pytest-openfiles matplotlib test/
Examining conflict for nbconvert bleach jupyterlab pygments nbformat pyflakes soupsieve cython numba wheel matplotlib-b\
Examining conflict for bleach jupyterlab pygments pyflakes numba cython wheel matplotlib-base jupyter_client pywinpty/
frikazoid11
on 7 May 2020
Same issue here on Ubuntu 20.04. I want to install some libraries, but I got the same error message:
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.
I created a fresh environment (from cloning my _base_ environment). Then I changed my _.condarc_ file to its defaults channels setting the channel priority false with conda config --set channel_priority false or manually in the file itself:
auto_activate_base: false
channels:
- defaults
- conda-forge
ssl_verify: true
channel_priority: false
Finally, I did conda update anaconda. However, when I want to install any other package it takes double of time than before with the warning Solving environment: failed with initial frozen solve. Retrying with flexible solve.
lwbaqueros
on 11 May 2020
I believe quite a few of these issues are due to dependencies not available for your python version.
So some of you may solve this issue by creating a new environment with a lower python version (e.g. 3.7 but you could try even 3.6). Assuming your problematic package is called myfavpkg and you want a new environment called my37env with python 3.7:
conda create -n my37env python=3.7
conda install -n my37env myfavpkg
It could also help to use the conda-forge channel, so one could use instead for the second command:
conda install -n my37env myfavpkg -c conda-forge
So another example using python 3.6 and the conda-forge channel would be:
conda create -n my36env python=3.6
conda install -n my36env myfavpkg -c conda-forge
It may solve only the problem for some (like @lrq3000 possibly), but in my situation this was exactly the problem. I got the Solving environment: failed with initial frozen solve. Retrying with flexible solve. error because one of the dependency was not yet available for python 3.8: cf here for the issue relating to the package i wanted to install and there for the issue relating to the dependency which is not yet available for python 3.8).
mick-d
on 13 May 2020
Same problem here. Since I knew when the problem began, I solved it by rolling back each of my environments:
conda list --revisions
and
conda install --revision=NUM
After reading your comments I'll make sure to not update until this is fixed.
flimao
on 21 May 2020
Couldn't install spleeter using Conda last night, I tried all the fixes in this thread to no avail, ended up using pip to install, and that worked fine. Seems like there is a major issue with conda. I uninstalled it for now.
RobVM1
on 27 May 2020
@mick-d
How do you know which package is not compatible with a newer version of Python, before you update Python?
hzfmer
on 2 Jun 2020
@hzfmer In the context of conda, you normally get an error indicating that the version for which a package you were going to install (as a dependency or not) is not available for that python version. The whole issue is that in some cases this error is not propagated correctly and instead you see this uninformative failed with initial frozen solve error instead.
So the way i could diagnose the problem on my end was to test a list of dependencies which may have had an issue and then trying to install each dependency individually in turn. That's how i got the conda message indicating me the specific package (dcmstack in my case) was not available for the python version i wanted (python 3.8):
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- dcmstack -> python[version='2.7.*|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']
Your python: python=3.8
@mick-d
Thank you for your detailed response. However, my situation is a bit different.
I would like to update python from 3.7 to 3.8. conda update python won't make it, neither does conda update --all. I guess some of my packages stop conda from updating python to 3.8 because of incompatibility. However, I don't know which package it is.
Then I tried to update Python by conda install python=3.8.2, which brings endless conflict checking after "failed with initial frozen solve".
I don't really want to reinstall Anaconda from scratch, but somehow I am trapped in python 3.7 now..
hzfmer
on 4 Jun 2020
@hzfmer I would not recommend updating python within a conda environment, but rather create a new environment with the python version you want (and then installing the packages you would like in that environment):
conda create --name py38 python=3.8
Still having this problem with conda. All the solutions above either don't help or are band-aids to the problem. I've set up new environments and the environments work by downloading packages at the beginning but afterwards they still have a problem.
I have luck with some packages. Others, doesn't matter what I do, will never download. This seems to be a problem for almost a year -- what's up conda? This is a pretty serious error and a lot of people are getting it. This should have been resolved long ago.
mizkulg
on 7 Jun 2020
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.
Thank you it worked for me as well
avikay
on 11 Jun 2020
The solution that ended up working for me was downloading an older anaconda version on their website. I chose one from early 2019 that came with 4.6 conda. I use a lot of packages in one environment so this was the most convenient solution.
mizkulg
on 11 Jun 2020
same problem with versions 4.7 and 4.8 . Conda 4.6.14 works without errors.
rustequal
on 12 Jun 2020
Same problem occured in the docker images continuumio/miniconda3 4.7.12 and 4.8.2.
Hope this will be fixed soon...
b-niu
on 16 Jun 2020
That's it - I upgraded conda to v4.7.12 several days ago, and I have encountered so many issues these days, including the 'solving environment' issue.
So, just run:
conda activate base
conda config --set auto_update_conda False
conda install conda=4.6.14
forskamse
on 19 Jun 2020
I removed anaconda, removed all version of python. After that I installed anaconda again and all start to work.
nulay
on 22 Jun 2020
I use conda version 4.8.3. and also experienced this Found conflicts! Looking for incompatible packages. issue. Last time it occurred when I tried to upgrade tensorflow to version 2.0.0.
I tried to downgrade conda to version 4.6.14 (conda install conda=4.6.14) but it failed with lots of error messages like Package ipython conflicts for.
The issue was fixed by moving conda-forge channel to the end of the list in .condarc:
channels:
- defaults
- conda-forge
channel_priority: strict
sash-ko
on 27 Jun 2020
I encounter the same problem when install opencv via anaconda.
Using this command I got "failed with initial frozen solve. Retrying with flexible solve." error
conda install -c conda-forge opencv
I change to use below command and get success
pip install opencv-python==3.4.2.17
pip install opencv-contrib-python==3.4.2.17
Just share to everyone
james3345678
on 1 Jul 2020
Encountered same problem while trying to install RocksDB package
conda install -c activisiongamescience rocksdb
sandeepnmenon
on 2 Jul 2020
I encounter the same problem.
bounlu
on 3 Jul 2020
This is still an ongoing issue!
conda v4.8.2,
conda create r-base
conda activate
conda install -c conda-forge openssh
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.
What is the solution?
howff
on 7 Jul 2020
Current Behavior
I installed Anaconda on Windows 10 (x64, version 1903) using
Anaconda3-2019.10-Windows-x86_64.exeand everything went well. When I create a new environment and try to install any package from a channel different thancondaI 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-learnEverything was fine at this point. I then tried to install opencv, which is not included in the default channel, with:
conda install -c menpo opencvThat 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`
I had faced the same problem. The problem seems to be the python version. TensorFlow is only supported on python 3.6.
I downgraded the python version to 3.6 using this command first.
conda install python=3.6
Then I tried installing Tensorflow again and it worked.
Note: Anaconda automatically downgraded all the python version dependent libraries along with python.
nihith98
on 14 Jul 2020
From what I've experienced the problem is with the python version 3.7
Other envs with different version tend not to crash from what i've observed
Installing some packages changes the python version automaticaly, some attention to the packeges requirements is recommended.
Basically creating a new env with a different python version then 3.7 seems to solve the problem.
Altough I'm not completly sure and haven't tested this properly.
Boicote13
on 14 Jul 2020
Thank You. It really worked for me. I tried every possible way out given on stack overflow and git hub from the last 3 hours, and at the end yours worked perfectly.
shivam-sg07
on 17 Jul 2020
I encounter the same problem when install opencv via anaconda.
In the administration mode
>> (base) C:\WINDOWS\System32> conda install -c conda-forge opencv
Using this command I got "failed with initial frozen solve. Retrying with flexible solve." error
But i solved the issue using
>> (base) C:\WINDOWS\System32> conda update -all
now again try to install
>> (base) C:\WINDOWS\System32> conda install -c conda-forge opencv
It works for me :) , I Hope it helps
hritik5102
on 21 Jul 2020
Got same issues, I can't install anything with _conda_.
So I install _opencv_ with pip install opencv-python
My version of _conda_ is 4.8.3 with _python_ 3.7.6
ichsan2895
on 1 Aug 2020
Try changing the python version to anyone besides 3.7.x, creating another
env maybe
Worked for me
Good luck
Le ven. 31 juil. 2020 à 23:21, ichsan2895 notifications@github.com a
écrit :
Got same issues, I can't install anything with conda included opencv.
So I install opencv with pip install opencv-pythonMy version of conda is 4.8.3 with python 3.7.6
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/conda/conda/issues/9367#issuecomment-667453624, or
unsubscribe
https://github.com/notifications/unsubscribe-auth/APBGV7GW2COJFZH6MV6C42LR6N32RANCNFSM4JEQ7OIQ
.
Boicote13
on 1 Aug 2020
I had the same problem when trying to install packages using conda.
Finally, I could solve the problem by downgrading python and then downgrading conda. I used the following codes:
conda install python=3.6
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
After these steps, I could install packages successfully.
Good luck
puyafazlali
on 3 Aug 2020
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.
This worked for me, just open a terminal from Notebook homepage new->Terminal and ran the command 'pip install opencv-python'. Thanks 👍
vi3k6i5
on 12 Aug 2020
Resume: a dependency solver which cannot solve. )))
ivan866
on 19 Aug 2020
Having the same error when trying to install old version of pandas.
conda install pandas==0.25.0
So I used pip,
pip install pandas==0.25.0 and it works well.
Good luck
com3dian
on 20 Aug 2020
I am still facing the issue. tried everything.
(myenv) C:\Users\Naman>conda install xgboost
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- xgboost
Current channels:
- 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
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
Please help if anyone know how to resolve
deadpool2997
on 27 Aug 2020
I observed this issue with conda 4.8.2 and 4.8.5 when trying to download gcc from conda-forge, with environments using 3.6, 3.7, and 3.8. @lengthmin and other's suggestion of downgrading to 4.6.14 worked. Thank you!
https://github.com/conda/conda/issues/9367#issuecomment-568234961
brendanreardon
on 25 Sep 2020
I met the similar error when use _conda install opencv-python_ in anaconda prompt.
Then I try to use _python -m pip install opencv-python_ in CMD prompt, it is installed successfully.
ljw0032
on 10 Oct 2020
Have been through the same error installing a couple of different packages.
For now, it seems that updating all in the env should get things working again.
conda update --all
vitor1klein
on 24 Oct 2020
I had the same issue when trying to install pytorch in a python3.9 environment. Created a new python3.7 environment, which solved the problem for me.
vincentmaye
on 14 Nov 2020
This software's design just makes no sense. It fails to resolve the conflicts and it will just repeat the same attempt to resolve things again and again without offering any solution - what's the point of this all? What's a user to do with a dump of 100s of conflicts the resolver reports? It should not just quit doing nothing but help the user, e.g. something like:
Couldn't install requested packages because the environment has conflicts, Do you want to:
- remove all the conflicting packages and try to to reinstall them selectively [Y/n]
- or save the current list of installed packages and rebuild the environment from scratch? [Y/n]
Bottom line, until conda starts to do something useful in this situation - the solution is to use conda only for binary packages you can't install in any other way. That is:
- Create a new environment
- Install binary packages you can't install via pip
- From that moment on use
pipfor all other installs
If you need to install another binary package via conda down the road, try to do it and if it fails go to step 1.
stas00
on 22 Nov 2020
if you have same problem see below codes and run them in promp:
Fix ‘Solving environment: failed with initial frozen solve. Retrying with flexible solve.’
🤚✋
🤚✋
🤚✋
conda create --name deep python=3.7
conda activate deep
conda install tensorflow-gpu keras matplotlib scipy scikit-learn
conda install -c menpo opencv
conda install -c anaconda opencv
conda update --all
conda update -n base conda
conda install conda = 4.6.11
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
conda config --set channel_priority true
==or
conda config --set channel_priority false
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
conda install -c conda requests-kerberos
conda update --prefix C:\apps\anaconda3 anaconda
see this link:
C:\ProgramData\Anaconda3\envsopencv
added / updated specs:
- opencv
conda activate deep
conda config --set auto_update_conda False
conda install conda=4.6.14
conda install --strict-channel-priority -c defaults -c conda-forge rpy2=3.1.0
🤚✋
🤚✋
🤚✋
Hamed-Aghapanah
on 23 Nov 2020
I had the same problem when trying to install packages using conda.
Finally, I could solve the problem by downgrading python and then downgrading conda. I used the following codes:
conda install python=3.6
conda config --set allow_conda_downgrades true
conda install conda=4.6.14After these steps, I could install packages successfully.
Good luck
Fixed it for me! Thanks @puyafazlali
But it's only a workaround... I'm not satisfied to be forced to use an old conda version... 👎
Djedouas
on 27 Nov 2020
So many similar problems. I came across the same problem trying to install humann2 package. Any solutions??
YikeShen
on 1 Dec 2020
So many similar problems. I came across the same problem trying to install humann2 package. Any solutions??
please check this path in your anaconda: C:\ProgramData\Microsoft\Windows\Start Menu\Programs\Anaconda3 (64-bit) or you can find Anaconda3 in your system,
Then change Properties from read-only to another one
Hamed-Aghapanah
on 1 Dec 2020
I had the same problem when trying to install packages using conda.
Finally, I could solve the problem by downgrading python and then downgrading conda. I used the following codes:
conda install python=3.6
conda config --set allow_conda_downgrades true
conda install conda=4.6.14
After these steps, I could install packages successfully.
Good luckFixed it for me! Thanks @puyafazlali
But it's only a workaround... I'm not satisfied to be forced to use an old conda version... 👎
This behavior was finally caused by a lack of RAM for me.
I upgraded from 4Go to 8Go and I was able to install my package without issue with the latest conda version.
Djedouas
on 2 Dec 2020
My workaround is to use "conda" only to create an environment. Then I install all packages only through "pip".
rustequal
on 2 Dec 2020
I had same problem and this is what solved it for me.
pip install opencv-python
nuelxelence
on 7 Dec 2020
So many similar problems. I came across the same problem trying to install humann2 package. Any solutions??
Thank you all for the answers!! I solved the problem by creating a new environment and uninstall/reinstall anaconda3.
TL;DR
Reasons are
1) I did not creat a new environment, so there are conflicts in packages.
2) Because I was running many pipelines before and I did not create a new environment for each task, my anacodna3 had a lot of conflicts in packages resulting in disk quota exceed as well. I used conda clean -all to clean up unused packages, I was able to install, but the solving environment still failed but anaconda still reported error.
3)I finally decide to uninstall my anaconda3 and reinstall the latest version of anaconda3. Every problem solved.
Long comment short, it is a good reminder to create a new environment every time we run a pipeline to prevent conflicts packages!
YikeShen
on 7 Dec 2020
After encountering the same problem and waiting for a while, turns out conda found some dependency issues.
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.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Managed to fix by updating all packages:
conda update --all --yes
paleboot
on 23 Dec 2020
For linux;
python3 --version
My version is 3.7
conda install python=3.7 anaconda=custom
sudo apt install python3-pip
When the package is installed, the pip3 tool can be used.
pip3 install "package to be installed"
Solved for me
barlikburak
on 29 Dec 2020
Same problem here
celestialized
on 2 Jan 2021
@Marcsprk43 's black magic worked for me
filippocastelli
on 2 Jan 2021
Current Behavior
I installed Anaconda on Windows 10 (x64, version 1903) using
Anaconda3-2019.10-Windows-x86_64.exeand everything went well. When I create a new environment and try to install any package from a channel different thancondaI 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-learnEverything was fine at this point. I then tried to install opencv, which is not included in the default channel, with:
conda install -c menpo opencvThat 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`
Please download python 3.7 to your computer. (Example: go to microsoft store -> dowload python 3.7), Then run the code again. (conda create --name am_keras_tf python = 3.7 run from anaconda prompt)
ugurcansoruc
on 2 Jan 2021
I had the same problem when creating R kernel environment in Anaconda with python 3.7 and conda 4.9, then it was solved by downgrading conda to 4.6.
WinnieC18
on 8 Jan 2021
Related issues
mjspeck
·
59Comments
maien85
·
60Comments
asmeurer
·
73Comments
cgivre
·
49Comments
TomLav
·
54Comments
Most helpful comment
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 using
conda 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!