mlflow / mlflow-export-import

Apache License 2.0
139 stars 87 forks source link

Databricks Wheel Error #135

Closed zwag20 closed 1 year ago

zwag20 commented 1 year ago

I created a wheel file using Databricks ML 13.2 using the code in the readme.

I export the wheel and install it on my prod cluster (the prod cluster has no access to the internet), but it errors with the following message:

WARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))': /simple/pandas/
WARNING: Retrying (Retry(total=3, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))': /simple/pandas/
WARNING: Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))': /simple/pandas/
WARNING: Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))': /simple/pandas/
WARNING: Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))': /simple/pandas/
ERROR: Could not find a version that satisfies the requirement pandas>=1.5.2 (from mlflow-export-import) (from versions: none)
ERROR: No matching distribution found for pandas>=1.5.2

Is it the lack of internet access that is preventing this? Do I need to make a new pandas wheel?

amesar commented 1 year ago

This is general Python question. Yes, you need access to the internet. Look in the wheel and you see it does not contain 3rd party packages. You will need to create an "uber wheel". See https://pypi.org/project/pyassembly/ or https://pypi.org/project/fat-wheel/ or google for others.