refactor: use a slice to pass function arguments #42
Conversation
This file contains 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
This should allow use a temporary vec/slice when calling fuctions, which will allow us to release memory for function calls that will not be needed in the result. We are hoping this will lower our overall memory footprint.
tommy
approved these changes
Jun 23, 2024
| max_args!(context, args, 1); | ||
|
|
||
| let arg = &args[0]; | ||
| let arg = args.first().copied().unwrap_or_else(Value::undefined); |
There was a problem hiding this comment.
I wonder if it's worth, for ergonomics, defining something like:
trait ArgsIndex<'a> {
fn get(i: usize) -> &'a Value<'a>;
}
impl ArgsIndex for &[&'a Value<'a>] {
...
}
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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.
This should allow use a temporary vec/slice when calling fuctions, which will allow us to release memory for function calls that will not be needed in the result. We are hoping this will lower our overall memory footprint.