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[perf-scan] 2026-10-09 -- performance opportunities found

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
70/100
Issue type
Refactor
Clarity
Clearly specified
Activity status
Active
Tech stack
git, python
Domain
cli, performance

Research direction

Start with the top-level imports in src/apm_cli/commands/update.py (lines 62-68) and src/apm_cli/commands/view.py (line 17). Each imported name is used once inside a function body (update.py lines 141 and 178, view.py line 601), so move those imports into the functions. Before editing, check the test suite for patches that target these module-level names. Done when the imports are local, the affected tests pass with any updated patch targets, and apm update and apm view still work.

Written by the indexing model from the issue text.

Description

type/automation type/performance

Performance Scan - 2026-10-09

Automated scan of src/apm_cli/ for algorithmic performance anti-patterns.
1 finding(s) identified.

Findings
[E] Heavy top-level imports on CLI command modules -- src/apm_cli/commands/update.py:62-68 and src/apm_cli/commands/view.py:17
  • Current: importing these command modules eagerly loads git (GitPython), requests, and the whole deps.github_downloader module graph at CLI startup, even when running unrelated sub-commands. update.py uses GitHubPackageDownloader once (line 141) and GitCommandError once (line 178); view.py uses GitHubPackageDownloader once (line 601).
  • Proposed: O(1) startup cost for unrelated commands; the cost is paid only when update / view run.
  • Fix: Move from ..deps.github_downloader import GitHubPackageDownloader and from git.exc import GitCommandError into the function bodies that use them (low priority: startup latency only; note tests may patch the module-level names, so adjust patch targets).
Scan coverage
  • src/apm_cli/ (488 files scanned)
  • Patterns checked: A (quadratic loops), B (linear scan in loop),
    C (unconditional expensive ops), D (redundant config parsing),
    E (heavy top-level imports), F (sequential independent I/O)

Patterns A, B, C, D, F: sampled candidates (e.g. policy _union, SARIF detail filtering) already use sets or are on small bounded collections; no confirmed findings.

Generated by Daily Performance Scanner · copilot · auto · 19.3 AIC · ⌖ 0.552 AIC · ⊞ 11.1K · ◷

  • expires on Oct 16, 2026, 1:44 AM UTC
Dominant language
Python
Stars
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Forks
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Avg merge
4d 6h
Merged PRs (30d)
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