---
title: "Efficient Selection of Type Annotations for Performance Improvement in Gradual Typing"
url: https://daily.dev/posts/efficient-selection-of-type-annotations-for-performance-improvement-in-gradual-typing-jqxx3x7m9
source_url: https://programming-journal.org/2026/11/3/
type: article
source: "The Programming Journal"
published: 2026-03-05T19:46:36.662Z
updated: 2026-03-05T19:46:53.787Z
tags: ["python", "performance"]
reading_time: 2
upvotes: 0
comments: 0
language: en
---

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# Efficient Selection of Type Annotations for Performance Improvement in Gradual Typing

**[The Programming Journal](https://daily.dev/sources/programming-journal)** · 2 min read · 0 upvotes · 0 comments

## Summary

Gradual typing allows mixing static and dynamic typing in a single language, but partially typed programs can suffer unexpected performance degradation when type annotations are added naively. This research presents a technique to selectively choose a subset of type annotations—derived via type inference—to improve execution performance in gradually typed programs. The approach uses a lightweight, amortized method that selects annotations along data flows to minimize expensive runtime casts at typed/untyped boundaries. Evaluated on Reticulated Python, the technique outperforms using all inferred annotations and achieves comparable execution speed to existing approaches while maintaining more stable compilation times.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://programming-journal.org/2026/11/3/>

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Tags: [#python](https://daily.dev/tags/python), [#performance](https://daily.dev/tags/performance)

[View this post on daily.dev](https://daily.dev/posts/efficient-selection-of-type-annotations-for-performance-improvement-in-gradual-typing-jqxx3x7m9)