⚡ Bolt: [performance improvement] Use walrus operator in optimize.py

[bashandbone]

💡 What: Implemented the walrus operator inside a list comprehension in src/codeweaver/providers/optimize.py's _nvidia_smi_device_ids function.
🎯 Why: To prevent evaluating .strip() twice per iteration over the nvidia-smi output lines (once in the condition, once in the int cast), which causes redundant method execution and memory allocation.
📊 Impact: Minor CPU time and memory allocation savings due to executing the string manipulation once instead of twice.
🔬 Measurement: Run standard pytest over the providers module to ensure it still correctly parses comma-separated ints out of nvidia-smi output logic.

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PR created automatically by Jules for task 3881520017440252450 started by @bashandbone

Summary by Sourcery

Enhancements:

• Simplify and optimize _nvidia_smi_device_ids by reusing stripped line values instead of recomputing them in the list comprehension.

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[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

Refactors the parsing of nvidia-smi output in _nvidia_smi_device_ids to use the walrus operator, eliminating redundant string stripping while preserving behavior.

Flow diagram for _nvidia_smi_device_ids parsing logic

flowchart TD
    A[start__nvidia_smi_device_ids] --> B[call_subprocess_run]
    B --> C{nvidia_smi_available}
    C -->|false| Z[return_empty_list]
    C -->|true| D[split_out_into_lines]
    D --> E[iterate_lines]
    E --> F[compute_stripped_line_with_walrus]
    F --> G{stripped_is_digit}
    G -->|false| E
    G -->|true| H[cast_stripped_to_int]
    H --> I[append_int_to_device_ids]
    I --> E
    E -->|no_more_lines| J[return_device_ids_list]

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File-Level Changes

Change	Details	Files
Optimize nvidia-smi device ID parsing by avoiding repeated string stripping in the list comprehension.	Replace the existing list comprehension with one that uses the walrus operator to assign line.strip() once per iteration. Reuse the assigned stripped value both in the isdigit() predicate and the int() conversion. Add an inline comment documenting the use of the walrus operator and the reason for the change.	src/codeweaver/providers/optimize.py

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[github-actions]

🤖 Hi @bashandbone, I've received your request, and I'm working on it now! You can track my progress in the logs for more details.

[sourcery-ai]

Hey - I've left some high level feedback:

• Using the walrus operator inside the comprehension trades a very small micro-optimization for reduced readability; consider either keeping the original version or extracting the strip() into a small pre-processing loop or generator to keep the intent clear while avoiding duplicate calls.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Using the walrus operator inside the comprehension trades a very small micro-optimization for reduced readability; consider either keeping the original version or extracting the `strip()` into a small pre-processing loop or generator to keep the intent clear while avoiding duplicate calls.

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[github-actions]

🤖 I'm sorry @bashandbone, but I was unable to process your request. Please see the logs for more details.

[Copilot]

Pull request overview

This PR makes a small micro-optimization in the provider runtime-detection path by using the walrus operator in _nvidia_smi_device_ids() so each nvidia-smi output line is stripped only once before validation and conversion.

Changes:

• Replaced a repeated line.strip() pattern with a single walrus-assigned stripped value inside the list comprehension.
• Added an inline comment explaining the intent of the micro-optimization.

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