Fall back to un-optimized filter chain for unknown filters#1284
Open
Fall back to un-optimized filter chain for unknown filters#1284
Conversation
When AstFilterChain optimization is enabled and a filter chain contains an unknown filter (e.g. local_dt), fall back to the standard nested AstMethod evaluation at parse time instead of failing with an "Unknown filter" error and returning null. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Fall back to un-optimized filter chain for unknown filters
Summary
Why
The optimized AstFilterChain handles unknown filters differently from the standard EL evaluation path. For example, module | local_dt|unixtimestamp | pprint | md5 would produce no output with the optimization enabled, but works (with a
warning) in the un-optimized path. The optimization should be transparent — falling back when it can't handle a filter ensures parity.