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feat(ci): show per-job wait times in timing report

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Add wait time computation: for each job, wait_s = started_at - max(completed_at
of all jobs that finished before it started). This is a timestamp heuristic
(no workflow YAML dependency parse needed) that's accurate for pipeline-shaped
CI where the critical path is linear at each stage.

Shows up in:
- Job table: new Wait + Δ Wait columns
- Gantt chart: hatched bar segment before the run bar
- Step details: '(wait Xs)' annotation in the summary line
- Markdown summary: Total wait row with delta vs baseline
- Stats: total_wait / bl_total_wait in compute_stats

Also completes the skipped-jobs UI:
- Skipped stat card in stats cards
- Skipped row in markdown summary table

Backward compatible: old cached baselines without wait_s annotate on load.
This commit is contained in:
ethernet 2026-07-13 16:51:26 -04:00
parent 7beca22bc0
commit f0b7cf3836
1 changed files with 80 additions and 3 deletions
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83
scripts/ci/timings_report.py
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@ -198,6 +198,38 @@ def _normalize_job(raw: dict) -> dict:
}
def _annotate_wait_times(jobs: list[dict]) -> None:
"""Annotate each job with ``wait_s`` — how long it sat idle before starting.
Wait time = ``started_at - max(completed_at of all jobs that finished
before this job started)``. Jobs with no predecessor (e.g. ``detect``)
get ``wait_s = 0``. Skipped jobs get ``wait_s = None``.
This is a timestamp heuristic, not a workflow-YAML dependency parse: it
infers dependencies from temporal ordering rather than ``needs:``
declarations. It's accurate for pipeline-shaped CI where the critical
path is linear at each stage (detect → parallel lanes → gate → report).
"""
for j in jobs:
if is_skipped(j):
j["wait_s"] = None
continue
started = parse_ts(j.get("started_at"))
if started is None:
j["wait_s"] = None
continue
latest_dep_end: datetime | None = None
for other in jobs:
if other is j or is_skipped(other):
continue
other_end = parse_ts(other.get("completed_at"))
if other_end is None or other_end > started:
continue
if latest_dep_end is None or other_end > latest_dep_end:
latest_dep_end = other_end
j["wait_s"] = (started - latest_dep_end).total_seconds() if latest_dep_end else 0.0
def collect_timings(token: str, repo: str, run_id: str, head_sha: str) -> dict:
"""Collect job/step timings from the GitHub API.
@ -248,6 +280,7 @@ def collect_timings(token: str, repo: str, run_id: str, head_sha: str) -> dict:
all_jobs = [_normalize_job(j) for j in direct + sub_jobs_raw]
all_jobs = [j for j in all_jobs if j["status"] not in ("in_progress", "queued")]
all_jobs.sort(key=lambda j: j.get("started_at") or "")
_annotate_wait_times(all_jobs)
return {
"run_id": run_id,
@ -363,6 +396,8 @@ def compute_stats(timings: dict, baseline: dict | None = None) -> dict:
skipped = sum(1 for j in jobs_all if is_skipped(j))
bl_skipped = sum(1 for j in bl_jobs_all if is_skipped(j))
total_wait = sum(j.get("wait_s") or 0 for j in jobs)
bl_total_wait = sum(j.get("wait_s") or 0 for j in bl_jobs)
return {
"wall": wall,
@ -375,6 +410,8 @@ def compute_stats(timings: dict, baseline: dict | None = None) -> dict:
"no_baseline": no_baseline,
"skipped": skipped,
"bl_skipped": bl_skipped,
"total_wait": total_wait,
"bl_total_wait": bl_total_wait,
"total_jobs": len(jobs_all),
}
@ -423,6 +460,12 @@ h2 { font-size: 18px; margin: 32px 0 12px; }
}
.gantt-bar:hover { color: #fff; z-index: 10; }
.gantt-bar.current { background: #1f6feb; top: 5px; z-index: 2; }
.gantt-bar.wait {
background: repeating-linear-gradient(
45deg, #30363d, #30363d 3px, transparent 3px, transparent 6px
);
top: 5px; z-index: 1; opacity: 0.6;
}
.gantt-bar.baseline {
background: transparent; border: 1px dashed #8b949e; top: 2px; height: 24px; z-index: 1;
}
@ -533,11 +576,25 @@ def _gantt_bars(timings: dict, baseline: dict | None) -> str:
d_text, d_cls = fmt_delta(dur, bl.get("duration_s"))
delta_info = f' — {d_text}'
# Wait bar: shows idle time before the job started running
wait_bar = ""
wait_s = j.get("wait_s")
if wait_s and wait_s >= 1.0:
wait_left = (s - cur_t0).total_seconds() - wait_s
wait_left_pct = max(wait_left / total_s * 100, 0)
wait_width_pct = max(wait_s / total_s * 100, 0.3)
wait_bar = (
f'<div class="gantt-bar wait" '
f'style="left:{wait_left_pct:.2f}%;width:{wait_width_pct:.2f}%" '
f'title="{escape(j["name"])} — waited: {fmt_dur(wait_s)}"></div>'
)
rows.append(
f'<div class="gantt-row">'
f'<div class="gantt-label" title="{escape(j["name"])}">{name_display}</div>'
f'<div class="gantt-track">'
f'{bl_bar}'
f'{wait_bar}'
f'<div class="gantt-bar current" '
f'style="left:{left:.2f}%;width:{width:.2f}%" '
f'title="{escape(j["name"])}: {fmt_dur(dur)}{delta_info}"></div>'
@ -555,6 +612,7 @@ def _gantt_bars(timings: dict, baseline: dict | None) -> str:
legend = (
'<div class="legend">'
'<span><span class="legend-swatch" style="background:#1f6feb"></span>Current</span>'
'<span><span class="legend-swatch" style="background:repeating-linear-gradient(45deg,#30363d,#30363d 3px,transparent 3px,transparent 6px);opacity:0.6"></span>Wait</span>'
)
if baseline:
legend += '<span><span class="legend-swatch" style="border:1px dashed #8b949e"></span>Baseline (main)</span>'
@ -587,6 +645,8 @@ def _stats_cards(stats: dict) -> str:
f'<div class="stat-value slower">{stats["slower"]}</div></div>',
f'<div class="stat-card"><span class="stat-label">Unchanged</span>'
f'<div class="stat-value neutral">{stats["unchanged"]}</div></div>',
f'<div class="stat-card"><span class="stat-label">Skipped</span>'
f'<div class="stat-value neutral">{stats["skipped"]}</div></div>',
f'<div class="stat-card"><span class="stat-label">No Baseline</span>'
f'<div class="stat-value neutral">{stats["no_baseline"]}</div></div>',
]
@ -612,30 +672,37 @@ def _job_table(timings: dict, baseline: dict | None) -> str:
f'<td class="num neutral">skipped</td>'
f'<td class="num neutral">—</td>'
f'<td class="num neutral">—</td>'
f'<td class="num neutral">—</td>'
f'<td class="{concl_cls}" style="text-align:center">{concl_icon}</td>'
f'</tr>'
)
continue
dur = j.get("duration_s")
wait = j.get("wait_s")
bl = bl_map.get(j["name"])
bl_dur = bl.get("duration_s") if bl and not is_skipped(bl) else None
bl_wait = bl.get("wait_s") if bl and not is_skipped(bl) else None
delta_text, delta_cls = fmt_delta(dur, bl_dur)
wait_delta_text, wait_delta_cls = fmt_delta(wait, bl_wait)
rows.append(
f'<tr>'
f'<td class="job-name">{name}</td>'
f'<td class="num">{fmt_dur(dur)}</td>'
f'<td class="num">{fmt_dur(wait)}</td>'
f'<td class="num">{fmt_dur(bl_dur)}</td>'
f'<td class="num {delta_cls}">{delta_text}</td>'
f'<td class="num {wait_delta_cls}">{wait_delta_text}</td>'
f'<td class="{concl_cls}" style="text-align:center">{concl_icon}</td>'
f'</tr>'
)
return (
'<table><thead><tr>'
'<th>Job</th><th class="num">Current</th><th class="num">Baseline</th>'
'<th class="num">Delta</th><th>Status</th>'
'<th>Job</th><th class="num">Run</th><th class="num">Wait</th>'
'<th class="num">Baseline</th><th class="num">Δ Run</th>'
'<th class="num">Δ Wait</th><th>Status</th>'
'</tr></thead><tbody>' + "".join(rows) + '</tbody></table>'
)
@ -652,10 +719,13 @@ def _step_details(timings: dict, baseline: dict | None) -> str:
bl_steps = {s["name"]: s for s in bl.get("steps", [])}
dur = j.get("duration_s") or 0
bl_dur = bl.get("duration_s") if bl else None
wait = j.get("wait_s")
bl_dur = bl.get("duration_s") if bl and not is_skipped(bl) else None
delta_text, delta_cls = fmt_delta(dur, bl_dur)
summary_text = f'{escape(j["name"])} — {fmt_dur(dur)}'
if wait is not None and wait >= 1.0:
summary_text += f' <span class="neutral">(wait {fmt_dur(wait)})</span>'
if bl_dur is not None:
summary_text += f' <span class="{delta_cls}">({delta_text})</span>'
@ -811,9 +881,16 @@ def generate_summary(timings: dict, baseline: dict | None = None) -> str:
compute_d = d
lines.append(f"| Total compute | {fmt_dur(stats['compute'])} | {fmt_dur(stats['bl_compute'])} | {compute_d} |")
wait_d = ""
if stats["bl_total_wait"] is not None:
d, _ = fmt_delta(stats["total_wait"], stats["bl_total_wait"])
wait_d = d
lines.append(f"| Total wait | {fmt_dur(stats['total_wait'])} | {fmt_dur(stats['bl_total_wait'])} | {wait_d} |")
lines.append(f"| Jobs faster | {stats['faster']} | — | — |")
lines.append(f"| Jobs slower | {stats['slower']} | — | — |")
lines.append(f"| Jobs unchanged | {stats['unchanged']} | — | — |")
lines.append(f"| Jobs skipped | {stats['skipped']} | {stats['bl_skipped']} | — |")
lines.append(f"| Jobs without baseline | {stats['no_baseline']} | — | — |")
lines.append("")