LSP: Publishing Diagnostics For All Open Files

Nov 27, 2025 by Alex Johnson 47 views

In Language Server Protocol (LSP), the PublishDiagnostics notification is crucial for providing real-time feedback on code quality. However, some LSP implementations, like the one in astral-sh for ty, might only publish diagnostics for the file that has been changed, overlooking related files that might also be affected by the change. This article delves into the issue, proposes a solution, and discusses the trade-offs involved.

The Problem: Limited Diagnostic Scope

The core issue arises when a change in one file affects other files within the same project. Consider a scenario where you have two Python files, lib.py and main.py:

# lib.py
class Foo:
 name: str

# main.py
from lib import Foo

foo = Foo()

print(foo.name)

If you rename Foo.name to Foo.name2 in lib.py, an LSP implementation that only publishes diagnostics for the changed file (i.e., lib.py) will not immediately show any errors in main.py. The diagnostic for main.py will only appear once you start making changes to it. This behavior can lead to a delayed discovery of errors, potentially increasing debugging time and effort.

This limitation stems from the LSP server's strategy of only analyzing the currently modified file. While this approach optimizes performance by reducing the workload on each change, it sacrifices the ability to provide a holistic view of the project's health. In scenarios where cross-file dependencies are prevalent, such as in large codebases or projects with extensive module interconnections, this limitation can become a significant hindrance to developer productivity.

The impact is particularly pronounced in dynamically typed languages like Python, where errors related to attribute access or function calls across files might not be immediately apparent. The developer might continue working under the assumption that the code is correct, only to encounter runtime errors or unexpected behavior later on. This delayed feedback loop can disrupt the development workflow and increase the cognitive load on the developer.

Furthermore, this issue can lead to inconsistencies in the reported diagnostics. The developer might see errors in one file while the related errors in another file remain hidden, creating a fragmented view of the project's overall state. This inconsistency can be confusing and make it more difficult to understand the root cause of the problem.

Proposed Solution: Publish Diagnostics for All Open Documents

A more comprehensive approach is to send the PublishDiagnostics notification for all open documents whenever a change occurs. This ensures that diagnostics are always up-to-date across the entire project, providing a more accurate and immediate view of the code's health. By expanding the scope of the diagnostics, developers can quickly identify and address issues that might otherwise go unnoticed. This proactive approach not only enhances the debugging experience but also promotes a more robust and reliable development process.

By implementing this broader scope, the LSP server effectively acts as a vigilant guardian, continuously monitoring the intricate web of dependencies within the project. This constant surveillance ensures that any ripple effects from a change in one file are immediately reflected in the diagnostics of all affected files. The result is a more seamless and intuitive development experience, where developers can confidently navigate their codebase, knowing that they have a reliable safety net in place.

This approach is particularly beneficial in collaborative environments, where multiple developers are working on different parts of the same project. By ensuring that diagnostics are consistently updated across all open files, the LSP server can help prevent integration issues and conflicts that might arise from outdated or incomplete information. The shared understanding of the project's state fostered by this comprehensive diagnostic approach promotes better communication and collaboration among team members.

Balancing Performance: The `didSave` Approach

However, sending PublishDiagnostics on every didChange notification might be overly aggressive and potentially expensive in terms of performance. Frequent updates can strain system resources and negatively impact the responsiveness of the editor, leading to a frustrating user experience. The key is to strike a balance between providing timely feedback and maintaining optimal performance.

An alternative, and perhaps more pragmatic, approach is to trigger the PublishDiagnostics notification for all open documents only on didSave events. This strategy, employed by Pyre, offers a reasonable compromise. By deferring the diagnostic update until the file is saved, the LSP server can avoid unnecessary computations and reduce the frequency of notifications. This approach still provides comprehensive diagnostics but does so in a more controlled and resource-efficient manner.

This didSave approach also aligns well with the typical development workflow. Developers often make a series of changes before saving their work, and the didSave event serves as a natural checkpoint for triggering a diagnostic update. By waiting until the save point, the LSP server can analyze the cumulative impact of the changes and provide a more accurate and relevant set of diagnostics. This not only reduces the computational burden but also minimizes the chances of displaying transient or misleading error messages.

Furthermore, the didSave approach allows the LSP server to leverage the saved file's content as a stable basis for analysis. This is particularly important in scenarios where the code is undergoing rapid changes, as it ensures that the diagnostics are based on a consistent and reliable state. By avoiding the analysis of partially completed or unstable code fragments, the LSP server can provide more meaningful and actionable feedback to the developer.

Conclusion

The issue of limited diagnostic scope in LSP implementations can hinder developer productivity. Publishing diagnostics for all open files offers a solution, but the didSave approach provides a balanced strategy that prioritizes both accuracy and performance. By adopting this approach, LSP servers can provide a more comprehensive and efficient diagnostic experience, ultimately leading to better code quality and a smoother development workflow.

For more information on Language Server Protocol and its capabilities, visit the official Language Server Protocol Specification.

By addressing the limitations of diagnostic scope and implementing strategies that balance performance and accuracy, LSP implementations can truly empower developers to write better code, faster.

By considering the broader context of the project and providing timely and relevant feedback, LSP servers can play a crucial role in fostering a more efficient and enjoyable development experience.

This improved diagnostic coverage not only helps developers identify and fix errors more quickly but also encourages them to adopt best practices and write more maintainable code. The ability to see the impact of their changes across the entire project empowers developers to make more informed decisions and avoid potential pitfalls.

Ultimately, the goal of LSP is to provide a seamless and intuitive development experience. By continuously improving its diagnostic capabilities and addressing the challenges of cross-file dependencies, LSP can help developers focus on what they do best: building great software.