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Feature/Add retry to with backoff to policy download #638

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@SafetyQuincyF SafetyQuincyF commented Nov 22, 2024

Description

Adds 3 retries with backoff when trying to download the policy file.

Type of Change

  • Bug fix
  • New feature
  • Documentation update
  • Refactor
  • Other (please describe):

Testing

  • Tests added or updated
  • No tests required

Checklist

  • Code is well-documented
  • Changelog is updated (if needed)
  • No sensitive information (e.g., keys, credentials) is included in the code
  • All PR feedback is addressed

Summary by CodeRabbit

  • New Features

    • Implemented a retry mechanism for downloading policies from the cloud, enhancing reliability.
    • Users receive feedback on retry attempts during the download process.
  • Bug Fixes

    • Improved error handling to allow retries before reporting a failure.
  • Documentation

    • Updated logging messages for clearer user feedback during policy downloads.

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coderabbitai bot commented Nov 22, 2024

Walkthrough

The changes in this pull request significantly modify the print_wait_policy_download function in safety/scan/render.py. The function now includes a retry mechanism for downloading a policy from the cloud, rather than just a single attempt. It introduces constants for managing retries and enhances error handling by allowing multiple attempts before logging a failure. The logging has been improved to provide clearer feedback during the download process, and the function signature has been updated to include a new parameter for error delay.

Changes

File Change Summary
safety/scan/render.py - Updated print_wait_policy_download function to implement a retry mechanism for policy downloads.
- Added constants for maximum retries, backoff time, and multiplier.
- Enhanced error handling to allow retries before logging a failure.
- Improved logging messages for clearer user feedback.
- Updated function signature to include on_error_delay parameter.

Possibly related PRs

  • fix: basic policy file test #622: The changes in this PR enhance the testing of policy files, which may relate to the new retry mechanism in the print_wait_policy_download function, as both involve handling policy files and ensuring their correctness.

Suggested reviewers

  • dylanpulver

Poem

🐰 In the clouds, a policy waits,
With retries now, it opens gates.
Three chances given, logs will say,
"Try again, don't fade away!"
So hop along, dear console friend,
For every download, we shall mend! 🌥️

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📥 Commits

Reviewing files that changed from the base of the PR and between 9c28e27 and dee078d.


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@SafetyQuincyF SafetyQuincyF changed the title feature/add retry to with backoff to policy download Feature/Add retry to with backoff to policy download Nov 22, 2024
@SafetyQuincyF SafetyQuincyF self-assigned this Nov 22, 2024
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Actionable comments posted: 1

🧹 Outside diff range and nitpick comments (1)
safety/scan/render.py (1)

340-344: Consider using the tenacity library for retry logic

To simplify the retry mechanism and improve maintainability, consider using the tenacity library. It provides robust features for retrying operations with exponential backoff and can handle more complex retry strategies.

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  • safety/scan/render.py (1 hunks)

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Actionable comments posted: 1

🧹 Outside diff range and nitpick comments (2)
safety/scan/render.py (2)

340-343: Consider moving retry configuration to a dedicated constants file.

The retry mechanism constants could be moved to a dedicated configuration file or constants module for better maintainability and reusability across the codebase.

-    # can replace with tenacity in the future
-    MAX_RETRIES = 3
-    INITIAL_BACKOFF = 1  # seconds
-    BACKOFF_MULTIPLIER = 2  # Exponential factor for backoff
+    from safety.constants import (
+        POLICY_MAX_RETRIES,
+        POLICY_INITIAL_BACKOFF,
+        POLICY_BACKOFF_MULTIPLIER
+    )

349-363: Enhance error messaging for better debugging.

While the retry logic is well-implemented, the error message could be more informative by including the specific error details.

-                    console.print("Not using cloud policy file.")
+                    console.print(f"Not using cloud policy file. Failed to download after {MAX_RETRIES} attempts. Last error: {str(e)}")
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  • safety/scan/render.py (1 hunks)
🔇 Additional comments (1)
safety/scan/render.py (1)

340-369: Verify integration with error handling system.

The retry mechanism is well-implemented, but we should verify its integration with the overall error handling system.

✅ Verification successful

The retry mechanism aligns well with the existing error handling patterns

The implementation follows the established error handling patterns in the codebase:

  • Uses consistent logging patterns with LOG.exception for detailed error tracking
  • Properly handles exceptions without exposing sensitive information
  • Gracefully degrades by falling back to "Not using cloud policy file" when retries are exhausted
  • Integrates with the existing SafetyException hierarchy used throughout the codebase
🏁 Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Check for consistent error handling patterns across the codebase
rg -A 2 "SafetyException|LOG\.(error|warning|exception)" safety/

Length of output: 9018

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@SafetyQuincyF SafetyQuincyF force-pushed the feature/add-retry-to-policy branch from 9c28e27 to dee078d Compare November 22, 2024 03:04
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Actionable comments posted: 0

🧹 Outside diff range and nitpick comments (1)
safety/scan/render.py (1)

340-343: Consider moving constants to configuration and using tenacity.

The retry configuration constants could be moved to a dedicated configuration file for better maintainability. Also, as noted in the comment, consider using the tenacity library which provides a robust retry mechanism with features like jitter and various backoff strategies.

-    # can replace with tenacity in the future
-    MAX_RETRIES = 3
-    INITIAL_BACKOFF = 1  # seconds
-    BACKOFF_MULTIPLIER = 2  # Exponential factor for backoff
+    from safety.config import POLICY_MAX_RETRIES, POLICY_INITIAL_BACKOFF, POLICY_BACKOFF_MULTIPLIER
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  • safety/scan/render.py (1 hunks)
🔇 Additional comments (2)
safety/scan/render.py (2)

349-363: LGTM! Well-implemented retry mechanism.

The retry implementation follows best practices with:

  • Proper exception handling
  • Clear user feedback
  • Exponential backoff
  • Appropriate logging

365-369: 🛠️ Refactor suggestion

Improve warning message and fix potential race condition.

The warning message could be more specific about the impact of failing to fetch the policy, and there's a potential race condition between the success message and the warning log.

         if policy:
             wait_msg = "Policy fetched from Safety Platform."
         else:
-            LOG.warning("Failed to fetch policy after retries.")
+            LOG.warning("Failed to fetch policy after %d retries. Falling back to default policies.", MAX_RETRIES)
+            wait_msg = "Not using cloud policy file."

Likely invalid or redundant comment.

console.print(f"Retrying in {backoff_time:.1f} seconds...")
time.sleep(backoff_time) # Wait before next attempt
else:
console.print("Not using cloud policy file.")
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My only question here is why is this failing? Is this a retry/timeout issue?

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Not sure on platform side no error was logged in sentry.

@@ -337,22 +337,36 @@ def print_wait_policy_download(console: Console, closure: Tuple[Any, Dict[str, A
Returns:
Optional[PolicyFileModel]: The downloaded policy file model.
"""
# can replace with tenacity in the future
MAX_RETRIES = 3
INITIAL_BACKOFF = 1 # seconds
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Can we start with lower initial retry i.e 0.2 which is 200 ms and bump the retries to 5.

LOG.exception(f"Attempt {attempt} failed: {e}")
if attempt < MAX_RETRIES:
backoff_time = INITIAL_BACKOFF * (BACKOFF_MULTIPLIER ** (attempt - 1))
console.print(f"Retrying in {backoff_time:.1f} seconds...")
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@jakub-safetycli jakub-safetycli Nov 25, 2024

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I don't think we need to notify the user about it, if there is a way to make this a debug log I would prefer that, but not in the normal log output.

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3 participants