Workflow entry point not working on runtime 16.4-LTS

mexcram — Wed, 18 Jun 2025 05:54:55 GMT

Hello all,

I'm developing a python code that it is packaged as a wheel and installed inside a docker image. However, since this program requires numpy >= 2.0 I'm forced to use the runtime 16.4-LTS.

When I try to run it as a workflow on databricks I'm encountering the following issue:

Now, what it is odd, is that this exactly workflow is working on a runtime 15.4-LTS (but I have to remove my numpy code).

Do you know if something has changed on the way we have to configure the workflows on runtime 16.4-LTS ?

PS: just for information the issue with numpy >= 2.0 on runtime 15.4-LTS is this:

Re: Workflow entry point not working on runtime 16.4-LTS

Nishant1994 — Mon, 25 Aug 2025 05:50:24 GMT

Facing same issue .

Re: Workflow entry point not working on runtime 16.4-LTS

mark_ott — Tue, 11 Nov 2025 01:25:55 GMT

Databricks Runtime 16.4-LTS introduced some changes that affect workflow configuration, environment management, and, notably, support for Python third-party libraries like NumPy. The main issue you’re encountering with NumPy >= 2.0 in Databricks workflows stems from compatibility and environment management changes in this latest LTS release.

What's Different in 16.4-LTS Workflows

Databricks Runtime 16.4-LTS ships with NumPy 1.26.4 by default. If your workflow (or a third-party wheel) requires NumPy 2.x and tries to upgrade it, you can end up with a version mismatch between NumPy and other libraries like pandas or PySpark, which do not yet support NumPy 2.x fully in Databricks clusters.
Databricks clusters (including custom Docker images) may not automatically reconcile these dependency conflicts, especially when the workflow installs packages that force NumPy to 2.x, breaking compatibility with Databricks-native library expectations.
Databricks Connect and certain libraries explicitly restrict NumPy versions, usually supporting only NumPy < 2.0 due to upstream compatibility issues in PySpark.
Python package management in 16.4-LTS (and especially Machine Learning runtimes) is done with virtualenv, which isolates installations but can still end up with incompatible versions if dependencies are upgraded within a workflow or notebook.

Known numpy 2.0 Issues

NumPy 2.0 includes breaking changes for both Python and C APIs. Packages not rebuilt against NumPy 2.0 may throw errors like “module 'numpy._core' has no attribute 'multiarray'” or binary incompatibility warnings.
Some Databricks tools—including Databricks Connect and possibly workflow orchestrators—still require NumPy < 2.0 for reliable operation and explicitly block or downgrade the package.

Recommendations

On Databricks Runtime 16.4-LTS, pin NumPy to the version provided by the runtime, unless absolutely necessary. That means in most cases you should stick to numpy==1.26.4.
If you must use NumPy 2.x, ensure all dependencies, including pandas (version >=2.2.2), fully support it, and test workflows in isolated environments.
When building wheels for deployment on Databricks, specify compatible versions in your requirements. Adding explicit constraints (e.g., numpy==1.26.4) avoids most runtime errors on 16.4-LTS.
When using custom Docker images, ensure the pre-installed libraries do not conflict with Databricks-managed base libraries. If you force a newer numpy, check all downstream package versions and compatibility carefully.

Key Table: Databricks Runtime, NumPy Support, and Workflow Guidance

Runtime Version	Default NumPy	Supports NumPy 2.x?	Guidance
15.4-LTS	1.26.x	No	Remove NumPy 2.x code; stay <2.0
16.4-LTS	1.26.4	No*	Pin numpy==1.26.4, avoid 2.x if possible
Custom Image	User choice	Possible, risky	Must align all deps; not guaranteed

*16.4-LTS clusters may allow pip installing NumPy 2.x, but this breaks compatibility with Spark and some Databricks tools.

topic Workflow entry point not working on runtime 16.4-LTS in Get Started Discussions

Workflow entry point not working on runtime 16.4-LTS

Re: Workflow entry point not working on runtime 16.4-LTS

Re: Workflow entry point not working on runtime 16.4-LTS

What's Different in 16.4-LTS Workflows

Known numpy 2.0 Issues

Recommendations

Key Table: Databricks Runtime, NumPy Support, and Workflow Guidance