Refactor diff_targets function for better code organization and session pool handling

[mischadiehm]

Summary

This branch refactors the diff_targets function in src/network_toolkit/api/diff.py to improve code organization, fix parallel execution behavior, and ensure proper handling of session pools vs. fresh connections.

Current Status: Work in Progress

The branch contains initial refactoring work that needs completion and testing.

Changes Made

1. Refactored diff_targets function structure

Before: Used functools.partial with a module-level _perform_device_diff function for parallel execution.

After: Moved _perform_device_diff inside diff_targets as a nested function (closure) to:

• Simplify access to options and other local variables
• Avoid passing multiple parameters through partial
• Improve code locality and readability

2. Improved parallel execution control

Added conditional parallel execution based on session pool availability:

if is_config or is_command:
    if len(devices) > 1 and options.session_pool is None:
        batched = execute_parallel(devices, _perform_device_diff)
        results = [item for batch in batched for item in batch]
    else:
        for dev in devices:
            results.extend(_perform_device_diff(dev))

Rationale: When a session pool is provided, sessions should be reused rather than creating parallel fresh connections. This avoids connection exhaustion and respects the pool's purpose.

3. Separated config vs command handling in device-to-device mode

Refactored the device-to-device comparison (2 devices, no baseline) to have separate code paths for:

• Config diffs (/export compact)
• Command diffs (arbitrary / commands)

This improves clarity and allows for mode-specific label formatting.

4. Added helper functions

• _save_current_artifact(): Closure-based wrapper for artifact saving
• _is_missing_baseline_error(): Centralized error classification for missing baselines

5. Improved result sorting

Changed from sorting by device only to sorting by (device, subject) tuple for more consistent output ordering.

6. Tests for parallel execution

Added tests/api/test_diff_parallel.py with tests for:

• Parallel execution triggering and result sorting
• Device-to-device parallel comparison

TODO / Remaining Work

• Add unit tests for StateDiffer heuristic diffing logic
• Test sequence diff mode with the new structure
• Verify heuristic mode (--heuristic / -H) integration works correctly
• Consider extracting device-to-device diff into separate function for clarity
• Performance testing with large device counts
• Document the session pool vs parallel execution trade-offs

Related Files

• src/network_toolkit/api/diff.py - Main refactoring
• src/network_toolkit/api/execution.py - Parallel execution helper (order-preserving fix from main)
• src/network_toolkit/api/state_diff.py - Heuristic diffing (from main)
• src/network_toolkit/api/state_diff_patterns.py - Regex patterns for heuristic diffing (from main)
• tests/api/test_diff_parallel.py - New parallel execution tests

Design Decisions

Why move _perform_device_diff inside the function?

The original design used functools.partial to bind options and sequence_manager to a module-level function. This had several issues:

1. Required importing partial
2. Made the function signature complex
3. Separated related code

The nested function approach is more Pythonic and keeps related code together.

Why conditionally skip parallel execution with session pools?

Session pools are designed for connection reuse across operations. Running parallel operations with a session pool could:

1. Cause race conditions if the pool isn't thread-safe
2. Defeat the purpose of pooling by overwhelming the pool
3. Lead to connection exhaustion

When no session pool is provided, parallel execution creates independent connections which is safe and efficient.

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