Dependency Issue in Installation

[YanjunLiu2]

Dear contributors,

When I followed the instructions of installing with anaconda:
conda create --name chemml_env python=3.8
source activate chemml_env
conda install -c conda-forge openbabel rdkit nb_conda_kernels python-graphviz
pip install chemml

I got the following dependency error:

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.

sqlalchemy 2.0.27 requires typing-extensions>=4.6.0, but you have typing-extensions 4.5.0 which is incompatible.
Successfully installed MarkupSafe-2.1.5 absl-py-2.1.0 appnope-0.1.4 asttokens-2.4.1 astunparse-1.6.3 backcall-0.2.0 cachetools-5.3.2 charset-normalizer-3.3.2 chemml-1.3 comm-0.2.1 decorator-5.1.1 et-xmlfile-1.1.0 executing-2.0.1 flatbuffers-23.5.26 future-0.18.3 gast-0.4.0 google-auth-2.28.0 google-auth-oauthlib-1.0.0 google-pasta-0.2.0 grpcio-1.60.1 h5py-3.10.0 idna-3.6 ipython-8.12.3 ipywidgets-8.1.2 jedi-0.19.1 joblib-1.3.2 jupyterlab-widgets-3.0.10 keras-2.13.1 libclang-16.0.6 lxml-5.1.0 markdown-3.5.2 matplotlib-inline-0.1.6 numpy-1.24.3 oauthlib-3.2.2 openpyxl-3.1.2 opt-einsum-3.3.0 parso-0.8.3 pexpect-4.9.0 pickleshare-0.7.5 prompt-toolkit-3.0.43 protobuf-4.25.3 ptyprocess-0.7.0 pure-eval-0.2.2 pyasn1-0.5.1 pyasn1-modules-0.3.0 pygments-2.17.2 requests-2.31.0 requests-oauthlib-1.3.1 rsa-4.9 scikit-learn-1.3.2 scipy-1.10.1 seaborn-0.13.2 stack-data-0.6.3 tensorboard-2.13.0 tensorboard-data-server-0.7.2 tensorflow-2.13.1 tensorflow-estimator-2.13.0 tensorflow-io-gcs-filesystem-0.34.0 termcolor-2.4.0 threadpoolctl-3.3.0 typing-extensions-4.5.0 urllib3-2.2.1 wcwidth-0.2.13 werkzeug-3.0.1 wget-3.2 widgetsnbextension-4.0.10 wrapt-1.16.0

And when I tried to run magpie feature module I got:

2024-02-19 01:04:32.630354: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
File "/Users/yanjunliu/Documents/3DSC/magpie_feature.py", line 39, in
print(MAGPIE_features('NaCl'))
File "/Users/yanjunliu/Documents/3DSC/magpie_feature.py", line 20, in MAGPIE_features
features = f.generate_features(entries=all_comps)
File "/Users/yanjunliu/opt/anaconda3/envs/3DSC/lib/python3.8/site-packages/chemml/chem/magpie_python/attributes/generators/composition/ValenceShellAttributeGenerator.py", line 64, in generate_features
n_valence[i] = LookUpData.load_property("N"+s+"Valence")
File "/Users/yanjunliu/opt/anaconda3/envs/3DSC/lib/python3.8/site-packages/chemml/chem/magpie_python/data/materials/util/LookUpData.py", line 161, in load_property
values = np.zeros(len(self.element_ids), dtype=np.float)
File "/Users/yanjunliu/opt/anaconda3/envs/3DSC/lib/python3.8/site-packages/numpy/init.py", line 305, in getattr
raise AttributeError(former_attrs[attr])
AttributeError: module 'numpy' has no attribute 'float'.
np.float was a deprecated alias for the builtin float. To avoid this error in existing code, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

Are these errors related? I just need the related functions in chemml to generate magpie features. Thank you very much!

Best regards,

Yanjun Liu