I am using python 3.6, the following is the library version in my environment
ABSL-PY 0.15.0
Astunparse 1.6.3
Cached-property 1.5.2
Cachetools 4.2.4
Certified 2021.5.30
Charset-Normalizer 2.0.12
CLANG 5.0
Cycler 0.11.0
Dataclasses 0.8
Decorator 4.4.2
DNSPYthon 2.2.1
FastAPI 0.83.0
Flatbuffers 1.12
Future 1.0.0
Gast 0.4.0
Google-Auth 2.22.0
google-auth-oauthlib 0.4.6
Google-Pasta 0.2.0
Grupcio 1.48.2
H5Py 3.1.0
IDNA 3.10
Importlib-Metadata 4.8.3
Joblib 1.1.1
Keras 2.6.0
Keras-Preprocessing 1.1.2
Kiwisolver 1.3.1
Markdown 3.3.7
Matplotlib 3.3.4
Megnet 1.2.0
Monty 2023.9.25
MPMath 1.3.0
NetworkX 2.5.1
Numpy 1.19.5
Oauthlib 3.2.2
Opt-Einsum 3.3.0
Packaging 21.3
Palettable 3.3.2
Pandas 1.1.5
Pillow 8.4.0
PIP 21.2.2
Plottly 5.18.0
Protobuf 3.19.6
Pyasn1 0.5.1
Pyasn1-modules 0.3.0
PyDispatcher 2.0.7
Pymatgen 2021.2.8
PyNaCl 1.5.0
Pyparsing 3.1.4
Python-dateutil 2.9.0 post0
Pytz 2024.2
PyYAML 6.0.1
Requests 2.27.1
Request-oauthlib 2.0.0
RSA 4.9
Ruamel.yaml 0.17.32
Ruamel.yaml.clib 0.2.7
Scikit-learn 0.24.2
Scipy 1.5.4
SetupTools 58.0.4
Six 1.15.0
SPGLIB 2.0.2
SSHTunnel 0.4.0
Sympy 1.9
Tabulate 0.8.10
Tenacity 8.2.2
Tensorboard 2.10.1
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
TensorFlow 2.6.0
tensorflow-estimator 2.8.0
TermColor 1.1.0
Threadpoolctl 3.1.0
Typing-extensions 3.7.4.3
Uncertainties 3.1.7
Urllib3 1.26.20
Werkzeug 2.0.3
Wheel 0.37.1
WincertStore 0.2
Wrapt 1.12.1
Zipp 3.6.0
When I try to use the new api given by the website in the error message, ERROR: Could not find a version that satisfies the requirement mp-api (from versions: none), ERROR: No matching distribution found for mp-api
Tip I can’t install mp-api, does that mean my python can’t be used, but my hardware can’t support higher tensorflow versions for megnet network operations, please give me some help, thank you very much
python has discontinued support for 3.6 a long time ago and we generally track their cycle for support in our libraries. Is there a specific need why you need to run tensorflow and mp-api in the same python environment? You could use a separate environment for mp-api to retrieve the data you need from MP, save it to disk, and read the resulting file as input to your code using tensorflow. See #4 at https://docs.materialsproject.org/downloading-data/using-the-api/tips-for-large-downloads HTH
Thank you very much for your reply, my original intention was to reproduce the code of the megnet project on GitHub, because I just came into contact with megnet, [GitHub - davidtangGT/MEGNET] (GitHub - davidtangGT/MEGNET), his code appears #from pymatgen import MPRester
#mpr = MPRester (), as my original question, he can’t use our new api, so your current suggestion is that I create a separate environment to store data locally, and then use tf to train, is that right? Thanks again for your reply.
Yes, that’s correct. I’d also suggest reaching out to the MEGNET maintainers for how to use their code with MP’s new API client.
Thank you very much for your suggestion, I will try again according to your suggestion.