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requirements.txt
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# This file was autogenerated by uv via the following command:
# uv pip compile pyproject.toml -o requirements.txt
absl-py==2.1.0
# via
# tensorboard
# tensorflow
# tensorflow-probability
aioitertools==0.11.0
# via maggma
annotated-types==0.6.0
# via pydantic
anyio==4.3.0
# via
# httpx
# starlette
astunparse==1.6.3
# via tensorflow
atomate2==0.0.14
attrs==23.2.0
# via
# jsonschema
# referencing
bcrypt==4.1.2
# via paramiko
blinker==1.7.0
# via flask
boto3==1.34.93
# via maggma
botocore==1.34.93
# via
# boto3
# s3transfer
cachetools==5.3.3
# via google-auth
certifi==2024.2.2
# via
# httpcore
# httpx
# requests
cffi==1.16.0
# via
# cryptography
# pynacl
charset-normalizer==3.3.2
# via requests
click==8.1.7
# via
# atomate2
# flask
# mongogrant
# optimade
# uvicorn
cloudpickle==3.0.0
# via tensorflow-probability
contourpy==1.2.1
# via matplotlib
cryptography==42.0.5
# via paramiko
custodian==2024.4.18
# via atomate2
cycler==0.12.1
# via matplotlib
decorator==5.1.1
# via tensorflow-probability
dm-tree==0.1.8
# via tensorflow-probability
dnspython==2.6.1
# via
# email-validator
# maggma
# pymongo
email-validator==2.1.1
# via pydantic
emmet-core==0.82.2
# via
# atomate2
# mp-api
exceptiongroup==1.2.1
# via anyio
fastapi==0.110.2
# via maggma
flask==3.0.3
# via mongogrant
flatbuffers==24.3.25
# via tensorflow
fonttools==4.51.0
# via matplotlib
future==1.0.0
# via uncertainties
gast==0.4.0
# via
# tensorflow
# tensorflow-probability
google-auth==2.29.0
# via
# google-auth-oauthlib
# tensorboard
google-auth-oauthlib==0.4.6
# via tensorboard
google-pasta==0.2.0
# via tensorflow
grpcio==1.62.2
# via
# tensorboard
# tensorflow
h11==0.14.0
# via
# httpcore
# uvicorn
h5py==3.11.0
# via tensorflow
httpcore==1.0.5
# via httpx
httpx==0.27.0
# via optimade
idna==3.7
# via
# anyio
# email-validator
# httpx
# requests
itsdangerous==2.2.0
# via flask
jinja2==3.1.3
# via flask
jmespath==1.0.1
# via
# boto3
# botocore
jobflow==0.1.17
# via atomate2
joblib==1.4.0
# via
# pymatgen
# scikit-learn
jsonschema==4.21.1
# via maggma
jsonschema-specifications==2023.12.1
# via jsonschema
keras==2.11.0
# via tensorflow
kiwisolver==1.4.5
# via matplotlib
lark==1.1.9
# via optimade
latexcodec==3.0.0
# via pybtex
libclang==18.1.1
# via tensorflow
maggma==0.65.0
# via
# jobflow
# mp-api
markdown==3.6
# via tensorboard
markdown-it-py==3.0.0
# via rich
markupsafe==2.1.5
# via
# jinja2
# werkzeug
matminer==0.9.2
# via modnet
matplotlib==3.8.4
# via pymatgen
mdurl==0.1.2
# via markdown-it-py
modnet==0.4.3
mongogrant==0.3.3
# via maggma
mongomock==4.1.2
# via maggma
monty==2024.4.17
# via
# atomate2
# custodian
# emmet-core
# jobflow
# maggma
# matminer
# mp-api
# pymatgen
mp-api==0.41.2
mpmath==1.3.0
# via sympy
msgpack==1.0.8
# via
# maggma
# mp-api
networkx==3.3
# via
# jobflow
# pymatgen
numpy==1.26.4
# via
# atomate2
# contourpy
# h5py
# maggma
# matminer
# matplotlib
# modnet
# opt-einsum
# pandas
# pymatgen
# scikit-learn
# scipy
# spglib
# tensorboard
# tensorflow
# tensorflow-probability
oauthlib==3.2.2
# via requests-oauthlib
opt-einsum==3.3.0
# via tensorflow
optimade==1.0.4
orjson==3.10.1
# via maggma
packaging==24.0
# via
# matplotlib
# mongomock
# plotly
# tensorflow
palettable==3.3.3
# via pymatgen
pandas==1.5.3
# via
# matminer
# modnet
# pymatgen
paramiko==3.4.0
# via sshtunnel
pillow==10.3.0
# via matplotlib
plotly==5.21.0
# via pymatgen
protobuf==3.19.6
# via
# tensorboard
# tensorflow
psutil==5.9.8
# via custodian
pyasn1==0.6.0
# via
# pyasn1-modules
# rsa
pyasn1-modules==0.4.0
# via google-auth
pybtex==0.24.0
# via
# emmet-core
# pymatgen
pycparser==2.22
# via cffi
pydantic==2.7.1
# via
# atomate2
# emmet-core
# fastapi
# jobflow
# maggma
# optimade
# pydantic-settings
pydantic-core==2.18.2
# via pydantic
pydantic-settings==2.2.1
# via
# atomate2
# emmet-core
# jobflow
# maggma
# optimade
pydash==8.0.1
# via
# jobflow
# maggma
pygments==2.17.2
# via rich
pymatgen==2024.3.1
# via
# atomate2
# emmet-core
# matminer
# modnet
# mp-api
pymongo==4.7.0
# via
# maggma
# matminer
# mongogrant
pynacl==1.5.0
# via paramiko
pyparsing==3.1.2
# via matplotlib
python-dateutil==2.9.0.post0
# via
# botocore
# maggma
# matplotlib
# pandas
python-dotenv==1.0.1
# via pydantic-settings
pytz==2024.1
# via pandas
pyyaml==6.0.1
# via
# atomate2
# jobflow
# pybtex
pyzmq==26.0.2
# via maggma
referencing==0.35.0
# via
# jsonschema
# jsonschema-specifications
requests==2.31.0
# via
# matminer
# mongogrant
# mp-api
# optimade
# pymatgen
# requests-oauthlib
# tensorboard
requests-oauthlib==2.0.0
# via google-auth-oauthlib
rich==13.7.1
# via optimade
rpds-py==0.18.0
# via
# jsonschema
# referencing
rsa==4.9
# via google-auth
ruamel-yaml==0.18.6
# via
# custodian
# maggma
# pymatgen
ruamel-yaml-clib==0.2.8
# via ruamel-yaml
s3transfer==0.10.1
# via boto3
scikit-learn==1.4.2
# via
# matminer
# modnet
scipy==1.13.0
# via
# pymatgen
# scikit-learn
sentinels==1.0.0
# via mongomock
setuptools==69.5.1
# via
# maggma
# mp-api
# tensorboard
# tensorflow
six==1.16.0
# via
# astunparse
# google-pasta
# pybtex
# python-dateutil
# tensorflow
# tensorflow-probability
smart-open==7.0.4
# via mp-api
sniffio==1.3.1
# via
# anyio
# httpx
spglib==2.4.0
# via pymatgen
sshtunnel==0.4.0
# via maggma
starlette==0.37.2
# via fastapi
sympy==1.12
# via
# matminer
# pymatgen
tabulate==0.9.0
# via pymatgen
tenacity==8.2.3
# via plotly
tensorboard==2.11.2
# via tensorflow
tensorboard-data-server==0.6.1
# via tensorboard
tensorboard-plugin-wit==1.8.1
# via tensorboard
tensorflow==2.11.1
# via modnet
tensorflow-estimator==2.11.0
# via tensorflow
tensorflow-io-gcs-filesystem==0.36.0
# via tensorflow
tensorflow-probability==0.18.0
termcolor==2.4.0
# via tensorflow
threadpoolctl==3.4.0
# via scikit-learn
tqdm==4.66.2
# via
# maggma
# matminer
# pymatgen
typing-extensions==4.11.0
# via
# anyio
# emmet-core
# fastapi
# mp-api
# pydantic
# pydantic-core
# pydash
# tensorflow
# uvicorn
uncertainties==3.1.7
# via pymatgen
urllib3==2.2.1
# via
# botocore
# requests
uvicorn==0.29.0
# via maggma
werkzeug==3.0.2
# via
# flask
# tensorboard
wheel==0.43.0
# via
# astunparse
# tensorboard
wrapt==1.16.0
# via
# smart-open
# tensorflow