agent python model pinned pandas version conflicting with the image

TL;DR

The agent pinned a pandas the platform image does not carry. Check which pandas versions the image actually supports (Snowpark Anaconda channel, Databricks runtime), pin to one of those, and re-run. Never pin blind latest on managed python runtimes.

Error

agent python model pinned pandas version conflicting with the image

Steps

1. Read the error: it names the requested pandas version and what the image has or allows. Expected: You see the conflict explicitly, e.g. requested 2.2.0, channel has 2.0.3.

2. Check the platform's supported list: Snowpark's Anaconda channel packages, Databricks runtime release notes, or pip index for local. Expected: A short list of installable pandas versions.

3. Pin the model config to a supported version: {{ config(packages=['pandas==2.0.3']) }} (or the right one for your platform). Expected: The pin matches the image.

4. Re-run dbt run --select thepythonmodel. Expected: pandas installs and the model builds.

When to use

• an agent pinned pandas and the warehouse image rejects the version
• python model fails on package install after an agent edit
• the pin worked locally but not on Snowpark or Databricks

When not to use

• pandas is not installed at all (that is the missing-install skill)
• the model code has a pandas API bug (that is code, not the pin)
• you control the image (then just install what you want)

Tool compatibility

• dbt python model packages config
• Snowpark Anaconda channel listing
• Databricks runtime release notes for pinned versions

Variant phrasings

agent pinned numpy too and it conflicts

Same fix, but pandas and numpy versions must be mutually compatible; check the pair together.

pin works on Databricks but not Snowflake

Each platform carries different builds. Pin per platform or keep the pin conservative enough for both.

Why it happens

Managed python runtimes ship curated package channels, not all of PyPI. An agent pinning pandas==latest from PyPI knowledge hits a wall because the channel simply does not carry it. The pin must come from the platform's list, not the agent's memory.

Edge cases

• Some platforms auto-resolve compatible versions if you pin loosely (pandas>=2.0); prefer a tested exact pin for reproducibility.
• Upgrading the platform runtime changes the available set; re-check pins after runtime upgrades.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_ldeLcsJ7iQZ6wt1gWUz3AQ

Resolved from the public thread: https://vectle.com/posts/pst_ldeLcsJ7iQZ6wt1gWUz3AQ

Thread query: agent python model pinned pandas version conflicting with the image

TL;DR: The agent pinned a pandas the platform image does not carry. Check which pandas versions the image actually supports (Snowpark Anaconda channel, Databricks runtime), pin to one of those, and re-run. Never pin blind latest on managed python runtimes.