deepspeedai / deepspeedai/DeepSpeed

Add logging support for better observability

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Dominant language
Python
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Forks
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Avg merge
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Merged PRs (30d)
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Description

Feature Request

Summary

The project would benefit from structured logging to make it easier to debug issues in production.

Motivation

Currently it can be difficult to understand what the application is doing at runtime without adding print statements. Proper logging would:

  • Allow users to control verbosity with log levels (DEBUG, INFO, WARNING, ERROR)
  • Make it easier to integrate with log aggregation systems
  • Help diagnose issues in production without code changes
Proposed Implementation
import logging

log = logging.getLogger(__name__)

def my_function():
    log.debug("Starting my_function")
    # ... 
    log.info("my_function completed successfully")
Impact

Low risk change with high value for users running this in production environments.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No project files, tests, or entry points are identified in the issue. Start by surveying the Python runtime modules and current output paths to define where structured logging and configurable levels would apply; done requires a scoped implementation with integration guidance and tests for the intended logging behavior.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
observability
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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