VLLM dependency Issues with DBR 17.0

[nish7]

I am trying to install vllm and its appropriate dependencies on DataBricks Cluster DBR 17.0.

I have the vllm wheel and its dependent wheels within the databricks catalog in a Volumes folder.

I am running the following command below to install all the wheel files.

%pip install /Volumes/workspace/libs/artifacts/vllm-v0.10.1.1/*.whl

I keep finding myself running into this issue below

The conflict is caused by:
    The user requested numba 0.61.2 (from /Volumes/workspace/libs/artifacts/vllm-v0.10.1.1/numba-0.61.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl)
    vllm 0.10.1.1+cu118 depends on numba==0.61.2; python_version > "3.9"
    ydata-profiling 4.16.1 depends on numba<=0.61 and >=0.56.0

Downgrading numba<=0.61 causes vllm to fail as it depends on numba==0.61.2 but ydata-profiling throws an error when numba is not <0.61

I do not have a wheel for ydata-profiling being installed within the volumes folder

Here are all the wheels files located within the volumes that are being installed for vllm 

aiohappyeyeballs                  2.6.1
aiohttp                           3.12.15
aiosignal                         1.4.0
annotated-types                   0.7.0
anyio                             4.10.0
astor                             0.8.1
attrs                             25.3.0
blake3                            1.0.5
cachetools                        6.2.0
cbor2                             5.7.0
certifi                           2025.8.3
cffi                              2.0.0
charset-normalizer                3.4.3
click                             8.2.1
cloudpickle                       3.1.1
compressed-tensors                0.10.2
cupy-cuda12x                      13.6.0
depyf                             0.19.0
dill                              0.4.0
diskcache                         5.6.3
distro                            1.9.0
dnspython                         2.8.0
einops                            0.8.1
email-validator                   2.3.0
fastapi                           0.116.1
fastapi-cli                       0.0.11
fastapi-cloud-cli                 0.1.5
fastrlock                         0.8.3
filelock                          3.19.1
frozenlist                        1.7.0
fsspec                            2025.9.0
gguf                              0.17.1
h11                               0.16.0
hf-xet                            1.1.9
httpcore                          1.0.9
httptools                         0.6.4
httpx                             0.28.1
huggingface-hub                   0.34.4
idna                              3.10
interegular                       0.3.3
Jinja2                            3.1.6
jiter                             0.10.0
jsonschema                        4.25.1
jsonschema-specifications         2025.9.1
lark                              1.2.2
llguidance                        0.7.30
llvmlite                          0.44.0
lm-format-enforcer                0.10.12
markdown-it-py                    4.0.0
MarkupSafe                        3.0.2
mdurl                             0.1.2
mistral_common                    1.8.4
mpmath                            1.3.0
msgpack                           1.1.1
msgspec                           0.19.0
multidict                         6.6.4
networkx                          3.5
ninja                             1.13.0
numba                             0.61.2
numpy                             2.2.6
nvidia-cublas-cu12                12.6.4.1
nvidia-cuda-cupti-cu12            12.6.80
nvidia-cuda-nvrtc-cu12            12.6.77
nvidia-cuda-runtime-cu12          12.6.77
nvidia-cudnn-cu12                 9.5.1.17
nvidia-cufft-cu12                 11.3.0.4
nvidia-cufile-cu12                1.11.1.6
nvidia-curand-cu12                10.3.7.77
nvidia-cusolver-cu12              11.7.1.2
nvidia-cusparse-cu12              12.5.4.2
nvidia-cusparselt-cu12            0.6.3
nvidia-nccl-cu12                  2.26.2
nvidia-nvjitlink-cu12             12.6.85
nvidia-nvtx-cu12                  12.6.77
openai                            1.107.0
openai-harmony                    0.0.4
opencv-python-headless            4.12.0.88
outlines_core                     0.2.10
packaging                         25.0
partial-json-parser               0.2.1.1.post6
pillow                            11.3.0
pip                               25.2
prometheus_client                 0.22.1
prometheus-fastapi-instrumentator 7.1.0
propcache                         0.3.2
protobuf                          6.32.0
psutil                            7.0.0
py-cpuinfo                        9.0.0
pybase64                          1.4.2
pycountry                         24.6.1
pycparser                         2.23
pydantic                          2.11.7
pydantic_core                     2.33.2
pydantic-extra-types              2.10.5
Pygments                          2.19.2
python-dotenv                     1.1.1
python-json-logger                3.3.0
python-multipart                  0.0.20
PyYAML                            6.0.2
pyzmq                             27.1.0
ray                               2.49.1
referencing                       0.36.2
regex                             2025.9.1
requests                          2.32.5
rich                              14.1.0
rich-toolkit                      0.15.1
rignore                           0.6.4
rpds-py                           0.27.1
safetensors                       0.6.2
scipy                             1.16.1
sentencepiece                     0.2.1
sentry-sdk                        2.37.1
setproctitle                      1.3.7
setuptools                        79.0.1
shellingham                       1.5.4
six                               1.17.0
sniffio                           1.3.1
soundfile                         0.13.1
soxr                              1.0.0
starlette                         0.47.3
sympy                             1.14.0
tiktoken                          0.11.0
tokenizers                        0.22.0
torch                             2.7.1
torchaudio                        2.7.1
torchvision                       0.22.1
tqdm                              4.67.1
transformers                      4.56.1
triton                            3.3.1
typer                             0.17.4
typing_extensions                 4.15.0
typing-inspection                 0.4.1
urllib3                           2.5.0
uvicorn                           0.35.0
uvloop                            0.21.0
vllm                              0.10.1.1
watchfiles                        1.1.0
websockets                        15.0.1
wget                              3.2
xformers                          0.0.31
xgrammar                          0.1.21
yarl                              1.20.1

What is causing the compatibility issues between numba & ydata-profiling which is not allowing vllm to be installed on databricks 17.0 cluster.

Thanks

[Louis_Frolio · Accepted solution]

Hi @nish7  here are some helpful suggestions,

I did some digging and confirmed that the issue you’re encountering stems from conflicting dependencies. Specifically, there’s a hard version clash around the numba library:

=> vLLM 0.10.1.1 requires exactly numba==0.61.2

=> ydata-profiling 4.16.1 requires numba <0.61, but at least 0.56.0

Because Databricks Runtime 17.0 clusters run Python versions above 3.9, vLLM enforces numba==0.61.2. This version falls outside the range supported by ydata-profiling, which does not accept numba 0.61.2. As a result, the two packages cannot be installed together in the same environment.

Two possible mitigations are:

=> Remove ydata-profiling: If feasible, uninstall or prevent ydata-profiling (and its dependents) from being installed before adding vLLM. If you feel that you don’t need ydata-profiling, you can remove it directly at the notebook level with:

%pip uninstall ydata-profiling --yes

=> Custom Build: Currently, no version of ydata-profiling supports numba 0.61.2, and vLLM requires this version for compatibility with Python 3.12+. Neither package can be safely downgraded in this Databricks Runtime without breaking the other, so a custom build or fork would be required to reconcile the dependencies. Heads up, this is a going to be difficult.

Hope this helps. 

Cheers, Louis.