Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

fix: trying librabbitmq for celery backend! #77

Merged
merged 3 commits into from
Jun 26, 2024
Merged

Conversation

amindadgar
Copy link
Member

@amindadgar amindadgar commented Jun 26, 2024

Summary by CodeRabbit

  • New Features

    • Improved performance and reliability by switching the Celery broker to librabbitmq.
  • Bug Fixes

    • Reduced memory usage by releasing task results after invocation.

Copy link
Contributor

coderabbitai bot commented Jun 26, 2024

Walkthrough

The primary changes involve switching the Celery broker from pyamqp to librabbitmq for better performance and memory management enhancements. Additionally, task handling was improved by assigning the result of the asynchronous task to a variable and calling result.forget() to release resources.

Changes

File Changes Summary
celery_app/server.py Updated Celery broker from pyamqp to librabbitmq.
worker.py Modified task invocation to store result in a variable and added result.forget() to release memory.

Sequence Diagram(s)

Loading
sequenceDiagram
    participant Client
    participant Worker
    participant RabbitMQ as RabbitMQ Server

    Note over Client, Worker: Updated Workflow
    Client->>Worker: ask_question_auto_search.delay(...)
    Worker->>RabbitMQ: Send task to queue (librabbitmq)
    RabbitMQ-->>Worker: Task fetch by worker
    Worker->>Worker: Execute task
    Worker->>Worker: result.forget()

    Note over Client, Worker: Task result is forgotten to free resources

Poem

🌟 In the realm of tasks and queues,
Our broker's swapped its shoes, 🐇
From pyamqp to rabbitmq swift,
A memory-efficient shift.
Tasks complete and then they part,
Freed from memory, a work of art. 🌸


Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

Share
Tips

Chat

There are 3 ways to chat with CodeRabbit:

  • Review comments: Directly reply to a review comment made by CodeRabbit. Example:
    • I pushed a fix in commit <commit_id>.
    • Generate unit testing code for this file.
    • Open a follow-up GitHub issue for this discussion.
  • Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
    • @coderabbitai generate unit testing code for this file.
    • @coderabbitai modularize this function.
  • PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
    • @coderabbitai generate interesting stats about this repository and render them as a table.
    • @coderabbitai show all the console.log statements in this repository.
    • @coderabbitai read src/utils.ts and generate unit testing code.
    • @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.
    • @coderabbitai help me debug CodeRabbit configuration file.

Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

CodeRabbit Commands (invoked as PR comments)

  • @coderabbitai pause to pause the reviews on a PR.
  • @coderabbitai resume to resume the paused reviews.
  • @coderabbitai review to trigger an incremental review. This is useful when automatic reviews are disabled for the repository.
  • @coderabbitai full review to do a full review from scratch and review all the files again.
  • @coderabbitai summary to regenerate the summary of the PR.
  • @coderabbitai resolve resolve all the CodeRabbit review comments.
  • @coderabbitai configuration to show the current CodeRabbit configuration for the repository.
  • @coderabbitai help to get help.

Additionally, you can add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.

CodeRabbit Configration File (.coderabbit.yaml)

  • You can programmatically configure CodeRabbit by adding a .coderabbit.yaml file to the root of your repository.
  • Please see the configuration documentation for more information.
  • If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: # yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json

Documentation and Community

  • Visit our Documentation for detailed information on how to use CodeRabbit.
  • Join our Discord Community to get help, request features, and share feedback.
  • Follow us on X/Twitter for updates and announcements.

@amindadgar amindadgar requested a review from cyri113 June 26, 2024 14:47
@cyri113 cyri113 merged commit 34c557b into main Jun 26, 2024
16 checks passed
Copy link
Contributor

@coderabbitai coderabbitai bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Actionable comments posted: 0

Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 83ff554 and d5e4a4a.

Files selected for processing (2)
  • celery_app/server.py (1 hunks)
  • worker.py (1 hunks)
Additional comments not posted (2)
celery_app/server.py (1)

10-12: Ensure compatibility and stability with librabbitmq.

Switching the broker from pyamqp to librabbitmq could offer performance improvements, but it's crucial to verify that all existing functionalities are compatible with librabbitmq. This includes testing in the intended deployment environment.

worker.py (1)

35-41: Good practice to release memory, but ensure it's necessary.

Assigning the task result to result and subsequently calling result.forget() is a good practice to manage memory in long-running applications. However, it's important to confirm that this memory management step is necessary in this context. If the task results are not large or if they are not causing memory issues, this step might be unnecessary.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

2 participants