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Resolving dependency with pipenv

Open lmidatascience opened this issue 4 years ago • 1 comments

Resolving dependency failure with pipenv for both 0.9.0 and 0.10.0 releases.

[pipenv.exceptions.ResolutionFailure]: Warning: Your dependencies could not be resolved. You likely have a mismatch in your sub-dependencies.
  First try clearing your dependency cache with $ pipenv lock --clear, then try the original command again.
 Alternatively, you can use $ pipenv install --skip-lock to bypass this mechanism, then run $ pipenv graph to inspect the situation.
  Hint: try $ pipenv lock --pre if it is a pre-release dependency.
ERROR: Could not find a version that matches numpy<1.19.0,>=0.16.0,>=1.13.3,>=1.15,>=1.16,>=1.16.5,>=1.9.1,~=1.19.2 (from causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
Tried: 1.3.0, 1.4.1, 1.5.0, 1.5.1, 1.6.0, 1.6.0, 1.6.1, 1.6.1, 1.6.2, 1.6.2, 1.7.0, 1.7.0, 1.7.1, 1.7.1, 1.7.2, 1.7.2, 1.8.0, 1.8.0, 1.8.1, 1.8.1, 1.8.2, 1.8.2, 1.9.0, 1.9.0, 1.9.1, 1.9.1, 1.9.2, 1.9.2, 1.9.3, 1.9.3, 1.10.0.post2, 1.10.0.post2, 1.10.1, 1.10.1, 1.10.2, 1.10.2, 1.10.4, 1.10.4, 1.11.0, 1.11.0, 1.11.1, 1.11.1, 1.11.2, 1.11.2, 1.11.3, 1.12.0, 1.12.1, 1.13.0, 1.13.1, 1.13.3, 1.14.0, 1.14.1, 1.14.2, 1.14.3, 1.14.4, 1.14.5, 1.14.5, 1.14.6, 1.14.6, 1.15.0, 1.15.0, 1.15.1, 1.15.1, 1.15.2, 1.15.2, 1.15.3, 1.15.3, 1.15.4, 1.15.4, 1.16.0, 1.16.0, 1.16.1, 1.16.1, 1.16.2, 1.16.2, 1.16.3, 1.16.3, 1.16.4, 1.16.4, 1.16.5, 1.16.5, 1.16.6, 1.16.6, 1.17.0, 1.17.0, 1.17.1, 1.17.1, 1.17.2, 1.17.2, 1.17.3, 1.17.3, 1.17.4, 1.17.4, 1.17.5, 1.17.5, 1.18.0, 1.18.0, 1.18.1, 1.18.1, 1.18.2, 1.18.2, 1.18.3, 1.18.3, 1.18.4, 1.18.4, 1.18.5, 1.18.5, 1.19.0, 1.19.0, 1.19.0, 1.19.1, 1.19.1, 1.19.1, 1.19.2, 1.19.2, 1.19.2, 1.19.3, 1.19.3, 1.19.3, 1.19.4, 1.19.4, 1.19.4, 1.19.5, 1.19.5, 1.19.5, 1.20.0, 1.20.0, 1.20.0, 1.20.1, 1.20.1, 1.20.1, 1.20.2, 1.20.2, 1.20.2
Skipped pre-versions: 1.13.0rc1, 1.13.0rc2, 1.14.0rc1, 1.15.0rc1, 1.15.0rc2, 1.15.0rc2, 1.16.0rc1, 1.16.0rc1, 1.16.0rc2, 1.16.0rc2, 1.17.0rc1, 1.17.0rc1, 1.17.0rc2, 1.17.0rc2, 1.18.0rc1, 1.18.0rc1, 1.19.0rc1, 1.19.0rc1, 1.19.0rc1, 1.19.0rc2, 1.19.0rc2, 1.19.0rc2, 1.20.0rc1, 1.20.0rc1, 1.20.0rc1, 1.20.0rc2, 1.20.0rc2, 1.20.0rc2
There are incompatible versions in the resolved dependencies:
  numpy (from lightgbm==3.2.1->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy (from pygam==0.8.0->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy (from shap==0.39.0->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy (from xgboost==1.4.1->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy<1.19.0,>=0.16.0 (from causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.13.3 (from scikit-learn==0.24.2->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.13.3 (from scipy==1.4.1->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.15 (from seaborn==0.11.1->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.15 (from statsmodels==0.12.2->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.16 (from matplotlib==3.4.1->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.16.5 (from pandas==1.2.4->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy>=1.9.1 (from keras==2.4.3->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))
  numpy~=1.19.2 (from tensorflow==2.4.1->causalml==0.9.0->-r /tmp/pipenvdfwhb_w4requirements/pipenv-m7zmxz89-constraints.txt (line 2))

lmidatascience avatar Apr 29 '21 00:04 lmidatascience

Unfortunately there are conflicts in version requirements across many dependencies, and it's hard to resolve.

To create working environments, we recommend using the conda environments files provided in the envs/ folder.

jeongyoonlee avatar Apr 29 '21 16:04 jeongyoonlee

Close for now. Feel free to re-open if needed.

vincewu51 avatar Aug 19 '23 01:08 vincewu51