I use macOS. I have to use LibRecommender in my code.
Python Version: 3.8.13
According to this link, the 2.10 is a suitable tensorflow version.
This is what's in my requirements.txt file I install within a conda environment.
absl-py==2.1.0
aiohttp==3.9.5
aiosignal==1.2.0
annotated-types==0.7.0
anyio==4.4.0
appnope==0.1.4
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
arrow==1.3.0
asttokens==2.4.1
astunparse==1.6.3
async-lru==2.0.4
async-timeout==4.0.3
attrs==23.1.0
Babel==2.15.0
backcall==0.2.0
beautifulsoup4==4.12.3
bleach==6.1.0
blinker==1.6.2
Brotli==1.0.9
cachetools==5.3.3
certifi==2024.6.2
cffi==1.16.0
charset-normalizer==2.0.4
click==8.1.7
comm==0.2.2
cryptography==41.0.3
db-dtypes==1.3.0
debugpy==1.8.2
decorator==5.1.1
defusedxml==0.7.1
dnspython==2.6.1
email_validator==2.2.0
exceptiongroup==1.2.1
executing==2.0.1
fastapi==0.111.0
fastapi-cli==0.0.4
fastjsonschema==2.20.0
filelock==3.15.4
flatbuffers==2.0
fqdn==1.5.1
frozenlist==1.4.0
fsspec==2024.6.1
gast==0.4.0
gensim==4.3.2
google-api-core==2.19.2
google-auth==2.29.0
google-auth-oauthlib==0.4.4
google-cloud-bigquery==3.25.0
google-cloud-bigquery-storage==2.33.1
google-cloud-core==2.4.3
google-cloud-storage==3.4.1
google-crc32c==1.5.0
google-pasta==0.2.0
google-resumable-media==2.7.2
googleapis-common-protos==1.65.0
grpcio==1.66.1
grpcio-status==1.66.1
h11==0.14.0
h5py==3.11.0
httpcore==1.0.5
httptools==0.6.1
httpx==0.27.0
idna==3.7
importlib-metadata==7.0.1
importlib_resources==6.4.0
ipykernel==6.29.5
ipython==8.12.3
ipywidgets==8.1.3
isoduration==20.11.0
jedi==0.19.1
Jinja2==3.1.4
joblib==1.4.2
json5==0.9.25
jsonpointer==3.0.0
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
jupyter==1.0.0
jupyter-console==6.6.3
jupyter_client==8.6.2
jupyter_core==5.7.2
jupyter-events==0.10.0
jupyter-lsp==2.2.5
jupyter_server==2.14.1
jupyter_server_terminals==0.5.3
jupyterlab==4.2.3
jupyterlab_pygments==0.3.0
jupyterlab_server==2.27.2
jupyterlab_widgets==3.0.11
keras==2.10.0
Keras-Preprocessing==1.1.2
LibRecommender==1.5.1
Markdown==3.4.1
markdown-it-py==3.0.0
MarkupSafe==2.1.3
matplotlib-inline==0.1.7
mdurl==0.1.2
mistune==3.0.2
mpmath==1.3.0
multidict==6.0.4
nbclient==0.10.0
nbconvert==7.16.4
nbformat==5.10.4
nest-asyncio==1.6.0
networkx==3.1
notebook==7.2.1
notebook_shim==0.2.4
numpy==1.24.3
oauthlib==3.2.2
opt-einsum==3.3.0
orjson==3.10.6
overrides==7.7.0
packaging==23.2
pandas==2.0.3
pandocfilters==1.5.1
parso==0.8.4
pexpect==4.9.0
pickleshare==0.7.5
pillow==10.4.0
pip==24.0
pkgutil_resolve_name==1.3.10
platformdirs==3.10.0
pooch==1.7.0
prometheus_client==0.20.0
prompt_toolkit==3.0.47
proto-plus==1.24.0
protobuf==5.28.0
psutil==6.0.0
ptyprocess==0.7.0
pure-eval==0.2.2
pyarrow==17.0.0
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser==2.21
pydantic==2.8.0
pydantic_core==2.20.0
Pygments==2.18.0
PyJWT==2.8.0
pyOpenSSL==23.2.0
PySocks==1.7.1
python-dateutil==2.9.0.post0
python-dotenv==1.0.1
python-json-logger==2.0.7
python-multipart==0.0.9
pytz==2024.1
PyYAML==6.0.1
pyzmq==26.0.3
qtconsole==5.5.2
QtPy==2.4.1
redis==5.0.7
referencing==0.35.1
requests==2.32.2
requests-oauthlib==1.3.0
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
rich==13.7.1
rpds-py==0.18.1
rsa==4.7.2
scikit-learn==1.3.2
scipy==1.10.1
Send2Trash==1.8.3
setuptools==69.5.1
shellingham==1.5.4
six==1.16.0
smart-open==7.0.4
sniffio==1.3.1
soupsieve==2.5
stack-data==0.6.3
starlette==0.37.2
sympy==1.12.1
tensorboard==2.10.0
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow==2.10.0
tensorflow-estimator==2.10.0
termcolor==2.1.0
terminado==0.18.1
threadpoolctl==3.5.0
tinycss2==1.3.0
tomli==2.0.1
torch==2.3.1
torchvision==0.18.1
tornado==6.4.1
tqdm==4.66.4
traitlets==5.14.3
typer==0.12.3
types-python-dateutil==2.9.0.20240316
typing_extensions==4.11.0
tzdata==2024.1
ujson==5.10.0
uri-template==1.3.0
urllib3==2.2.2
uvicorn==0.30.1
uvloop==0.19.0
watchfiles==0.22.0
wcwidth==0.2.13
webcolors==24.6.0
webencodings==0.5.1
websocket-client==1.8.0
websockets==12.0
Werkzeug==3.0.3
wheel==0.35.1
widgetsnbextension==4.0.11
wrapt==1.14.1
yarl==1.9.3
zipp==3.17.0
My colleague uses the exact same libraries (verified via pip list). Some how it works for my colleague. However, I get this error during the installation:
ERROR: Ignored the following versions that require a different python version: 0.0.1 Requires-Python >=3.9,<4.0; 0.10.2 Requires-Python >=3.9.0; 0.11.0 Requires-Python >=3.9; 0.12.0 Requires-Python >=3.9; 0.21.0 Requires-Python >=3.9; 0.22.0 Requires-Python >=3.9; 0.22.1
...
ERROR: Could not find a version that satisfies the requirement tensorflow==2.10.0 (from versions: 2.13.0rc0, 2.13.0rc1, 2.13.0rc2, 2.13.0, 2.13.1)
ERROR: No matching distribution found for tensorflow==2.10.0
What am I missing out on?
requirements.txtfile that is too specific and pinning the exact versions of every sub-dependency. The best solution is to create a minimalrequirements.txtfile listing only your direct, top-level packages (likeLibRecommender,pandas,tensorflow-macos). This allows pip to automatically resolve and install a compatible set of underlying dependencies, likeprotobuf, and eliminate the conflict. Thanks!