"""End-to-end tests for build_dataset.py, annotate.py, analyze.py and plot_figures.py. A small raw run is synthesised in a temporary directory with the collector's own schema so that the build pipeline, label rules, event join and figure rendering can be exercised without network access. Nothing here is written into the repository's dataset directory. """ import csv import json import math import random from datetime import datetime, timedelta, timezone from pathlib import Path import pytest pd = pytest.importorskip("pandas") import annotate # noqa: E402 import build_dataset as bd # noqa: E402 import collect_data as cd # noqa: E402 START = datetime(2026, 9, 6, 22, 0, 0, tzinfo=timezone.utc) # 18:00 local (UTC-4) INTERVAL = 60 ROWS = 3 * 60 * 6 # 18 h of 1-minute samples LOCAL_OFFSET = timedelta(hours=-4) def write_synthetic_run(raw_dir: Path, run_id: str = "testhost_20260906_180000") -> Path: rng = random.Random(7) rows = [] for i in range(ROWS): t = START + timedelta(seconds=i * INTERVAL) if 400 <= i < 405: # simulated gap of five samples (machine asleep) continue s = cd.Sample(run_id=run_id, host_label="testhost", sample_index=i, timestamp_utc=t.strftime("%Y-%m-%dT%H:%M:%SZ"), timestamp_local=(t + LOCAL_OFFSET).strftime("%Y-%m-%dT%H:%M:%S-04:00"), epoch_s=int(t.timestamp()), elapsed_s=float(i * INTERVAL), link_type="wifi", gateway_ip="192.168.1.1", dns_server="192.168.1.1", target="8.8.8.8") base = 14.0 + 4.0 * math.sin((i / 60.0) / 24.0 * 2 * math.pi) rtts = [max(1.0, rng.gauss(base, 1.2)) for _ in range(10)] if i in (700, 701, 702): # simulated outage rtts = [] elif i % 97 == 0: # occasional single lost packet rtts = rtts[:9] elif i == 900: # latency spike rtts = [r + 120 for r in rtts] st = cd.rtt_stats(rtts) s.rtt_min_ms, s.rtt_avg_ms, s.rtt_median_ms = st["min"], st["avg"], st["median"] s.rtt_max_ms, s.rtt_stddev_ms, s.jitter_ms = st["max"], st["stddev"], st["jitter"] s.packets_sent, s.packets_received = 10, len(rtts) s.packet_loss_pct = round(100.0 * (10 - len(rtts)) / 10, 1) g = [max(0.3, rng.gauss(2.0, 0.5)) for _ in range(5)] if i == 1000: g = [r + 60 for r in g] gst = cd.rtt_stats(g) s.gateway_rtt_min_ms, s.gateway_rtt_avg_ms = gst["min"], gst["avg"] s.gateway_rtt_max_ms, s.gateway_jitter_ms = gst["max"], gst["jitter"] s.gateway_packet_loss_pct = 0.0 s.tcp_connect_min_ms = round(base - 0.5, 3) s.tcp_connect_median_ms = round(base, 3) s.dns_resolve_ms = round(rng.gauss(2.5, 0.4), 3) s.dns_recursive_ms = round(rng.gauss(40, 8), 3) s.http_ms, s.http_status = round(rng.gauss(60, 10), 3), 200 s.wifi_signal_pct = 80 + (i % 5) s.wifi_rssi_dbm = cd.rssi_from_quality(s.wifi_signal_pct) s.wifi_rx_mbps, s.wifi_tx_mbps = 866.7, 866.7 s.wifi_channel, s.wifi_band_ghz, s.wifi_phy = 36, 5.0, "802.11ax" if i % 30 == 0: s.download_mbps, s.upload_mbps = round(rng.gauss(450, 30), 2), round(rng.gauss(22, 2), 2) s.speedtest_ping_ms = 1800000.0 if i == 60 else 9.5 # one failed latency probe s.speedtest_server_id, s.speedtest_server = 1234, "Example ISP, Springfield" s.sample_duration_s = 10.4 s.notes = "ping: no replies" if not rtts else "" rows.append(cd.asdict(s)) raw_dir.mkdir(parents=True, exist_ok=True) csv_path = raw_dir / f"localnet_{run_id}.csv" with csv_path.open("w", newline="", encoding="utf-8") as f: w = csv.DictWriter(f, fieldnames=cd.CSV_FIELDS) w.writeheader() w.writerows(rows) meta = {"run_id": run_id, "collector_version": cd.COLLECTOR_VERSION, "status": "completed", "interval_s": float(INTERVAL), "sample_count": len(rows), "environment": {"os": "Windows-11-10.0.22631-SP0", "ping_resolution_ms": 1.0}, "network": {"link_type": "wifi"}} csv_path.with_suffix(".json").write_text(json.dumps(meta), encoding="utf-8") return csv_path @pytest.fixture(scope="module") def built(tmp_path_factory): root = tmp_path_factory.mktemp("ds") raw = root / "raw" write_synthetic_run(raw) # a manual annotation covering the simulated outage annotate.main(["router rebooted", "--category", "maintenance", "--start", "2026-09-07T09:39:30Z", "--end", "2026-09-07T09:43:00Z", "--file", str(raw / "events.csv")]) card = root / "DATASET_CARD.md" card.write_text("---\nsize_categories:\n - n<1K\n---\n# card\n\n" f"{bd.CARD_BEGIN}\nold\n{bd.CARD_END}\n", encoding="utf-8") bd.main(["--raw-dir", str(raw), "--out-dir", str(root), "--card", str(card)]) df = pd.read_csv(root / "localnet_dynamics.csv") summary = json.loads((root / "summary.json").read_text(encoding="utf-8")) return root, df, summary, card def test_rows_and_columns(built): root, df, summary, _ = built assert len(df) == ROWS - 5 assert list(df.columns[:11]) == cd.CSV_FIELDS[:11] assert df.columns[-1] == "notes" for col in bd.RUN_COLUMNS + bd.TIME_COLUMNS + bd.LABEL_COLUMNS + bd.EVENT_COLUMNS: assert col in df.columns assert (root / "localnet_dynamics.parquet").exists() assert summary["rows"] == len(df) and summary["runs"][0]["interval_s"] == 60.0 assert summary["runs"][0]["os"].startswith("Windows") assert df["collector_os"].iloc[0] == "Windows" and df["rtt_resolution_ms"].iloc[0] == 1.0 def test_time_features_and_gaps(built): _, df, summary, _ = built first = df.iloc[0] assert first["hour_local"] == 18 and first["date_local"] == "2026-09-06" assert first["weekday_local"] == 6 and first["is_weekend"] == 1 # Sunday gaps = df["gap_before_s"].dropna() assert gaps.max() == 6 * INTERVAL and (gaps == INTERVAL).sum() == len(gaps) - 1 assert 99.0 < summary["coverage_pct"] < 100.0 def test_reference_labels(built): _, df, summary, _ = built outages = df[df["label_outage"] == 1] assert list(outages["sample_index"]) == [700, 701, 702] assert df.loc[df["sample_index"] == 900, "label_high_latency"].item() == 1 assert df.loc[df["sample_index"] == 1000, "label_gateway_degraded"].item() == 1 assert df.loc[df["sample_index"] == 97, "label_packet_loss"].item() == 1 assert df.loc[df["sample_index"] == 97, "label_outage"].item() == 0 assert df["label_high_latency"].sum() <= 5 # rule is not over-sensitive assert (df["label_anomaly"] >= df["label_outage"]).all() thr = summary["runs"][0]["thresholds"]["rtt_avg_ms"] assert thr["threshold"] >= thr["median"] + 10.0 assert summary["labels"]["label_outage"]["rows"] == 3 def test_failed_speedtest_latency_is_missing(built): _, df, summary, _ = built tests = df[df["download_mbps"].notna()] assert len(tests) == 36 assert tests["speedtest_ping_ms"].isna().sum() == 1 assert tests.loc[tests["sample_index"] == 60, "speedtest_ping_ms"].isna().all() assert summary["metrics"]["speedtest_ping_ms"]["max"] == 9.5 def test_event_join(built): _, df, summary, _ = built tagged = df[df["event_category"].fillna("") != ""] assert summary["events"] == 1 assert set(tagged["sample_index"]) == {700, 701, 702, 703} assert (tagged["event_description"] == "router rebooted").all() def test_card_updated(built): _, _, summary, card = built text = card.read_text(encoding="utf-8") assert "old" not in text assert f"| Rows | {summary['rows']:,} |" in text assert "size_categories:\n - 1K= {"log_rtt_avg_ms", "loss_indicator", "http_ms"} def test_figures(built, tmp_path): pytest.importorskip("matplotlib") import plot_figures root, _, _, _ = built out = tmp_path / "figures" plot_figures.main(["--input", str(root / "localnet_dynamics.csv"), "--out-dir", str(out)]) for name in ("overview_timeline", "diurnal_profile", "calendar_heatmaps", "tcp_vs_icmp", "loss_anatomy", "regimes", "autocorrelation", "speedtest", "labels"): assert (out / "png" / f"{name}.png").stat().st_size > 10_000, name assert (out / "pdf" / f"{name}.pdf").stat().st_size > 1_000, name def test_annotate_parses_local_and_utc_times(): assert annotate.parse_time("2026-09-12T16:00:00Z").isoformat() == "2026-09-12T16:00:00+00:00" assert annotate.parse_time("2026-09-12 16:00+02:00").isoformat() == "2026-09-12T14:00:00+00:00" local = annotate.parse_time("2026-09-12 16:00") assert local.tzinfo == timezone.utc