Testing: sample_random_scans helper, run checkpoint, investigation manifest

Scraping resilience, metadata tooling, and repository hygiene
Consolidates mosaic and session hardening (login retry, skip processed scans, no retry on 404, started_at), progress reporting (Markdown tables, by-year rollup, rolling-window rate/ETA), and metadata workflow scripts (run_metadata_scan.sh, scan_progress_report.py, export_machine_metadata.py). Adds mosaic reconstruction sample JPEGs referenced by the report. Updates .gitignore for backup/ and .claude/; sample_random_scans helper is documented for branch testing/sample-runs only (see README).
2026-05-14 19:53:56 -04:00 · 2026-05-14 19:52:53 -04:00
24 changed files with 1139 additions and 10 deletions
@@ -7,3 +7,6 @@ __pycache__/
 .DS_Store
 explore_dumps/
 .venv/
+scripts/sync_to_nas.sh
+backup/
+.claude/
@@ -97,10 +97,8 @@ python scraper.py --machine "BW3-20 [AMR-26]" --mosaic-only
 # Download mosaics for all machines
 python scraper.py --mosaic-only

-# One random completed scan per machine: mosaic + all tiles (from machines.txt; uses --list-scans + --scan-id)
-# MOSAIC_ONLY=1 ./scripts/sample_random_scans.sh machines.txt   # optional: mosaics only, no tiles
-# cp scripts/machines.example.txt machines.txt   # then edit: one label per line
-# ./scripts/sample_random_scans.sh machines.txt
+# One random completed scan per machine (helper script): check out branch `testing/sample-runs`,
+# then see `scripts/sample_random_scans.sh` and `docs/sample_random_scans_run_progress.md`.

 # Download all tiles for a specific scan
 python scraper.py --machine "BW3-20 [AMR-26]" --scan-id 158374 --workers 4
@@ -0,0 +1,50 @@
+# `sample_random_scans.sh` run progress (checkpoint)
+
+Snapshot from terminal session **9** (repo: `/Users/igt/Documents/spruce_scraper`), as of when the machine was about to be restarted. **Date:** 2026-04-26.
+
+## Active run (incomplete)
+
+A **full scan** was in progress: **mosaic + all tiles** (worker count from `config.yaml`), with scan listing using **`--list-scans-first-page-only`** (one page, up to 320 scan IDs, uniform random choice among that page).
+
+| Item | Value |
+|------|--------|
+| Script | `./scripts/sample_random_scans.sh` |
+| Machines file | `machines.txt` (12 machines) |
+| Config | `config.yaml` |
+| State files | `archives/scans.csv`, `archives/tiles.csv`, `archives/.progress.json` |
+
+### Where it stopped
+
+The run was on **step [9/12]**, machine **BW3-17 [AMR-20]**, **scan ID 153772**.
+
+- **Mosaic:** HTTP **404** for `…/RootView_Database/153772/mosaic.jpg` (same pattern as other scans: tiles still available).
+- **Tiles:** **33784** total; progress bar showed roughly **5%** completed — last log line observed was on the order of **~1736 / 33784** tiles (exact count advances continuously; re-check `archives/.progress.json` or resume to see current).
+
+**Not yet started** in this full-scan pass: steps **[10/12]–[12/12]**: **BW3-19 [AMR-21]**, **BW3-20 [AMR-26]**, **BW3-21 [AMR-17]** (lines 12–14 of `machines.txt`).
+
+### Skipped machine in this pass
+
+- **[4/12] BW2-8 [AMR-25]:** `SKIPPED` — `scraper.py --list-scans --list-scans-first-page-only` exited with **code 1** (could not get scan list or pick an ID). The script continued with the next machine.
+
+### Completed machines in this full-scan pass (steps 1–3, 5–8)
+
+| Step | Machine | Scan ID | Mosaic | Tiles downloaded |
+|------|---------|---------|--------|------------------|
+| 1 | BW1-4 [AMR-15] | 71478 | 404 | 56 |
+| 2 | BW1-6 [AMR-19] | 156875 | saved | 72 |
+| 3 | BW1-7 [AMR-18] | 10837 | 404 | 1170 |
+| 4 | BW2-8 [AMR-25] | — | — | skipped |
+| 5 | BW2-10 [AMR-22] | 146368 | saved | 156 |
+| 6 | BW2-11 [AMR-23] | 160022 | saved | 529 |
+| 7 | BW2-13 [AMR-24] | 156957 | saved | 143 |
+| 8 | BW3-16 [AMR-16] | 77300 | 404 | 400 |
+
+## After restart
+
+1. `cd` to the repo and activate the same venv as before.
+2. Re-run **`./scripts/sample_random_scans.sh`** with the **same mode** (full scan — default if that is what you used). The scraper **resumes** from `archives/.progress.json` and will continue **BW3-17** scan **153772** (remaining tiles) before moving to later machines, unless you change options or data manually.
+
+## Other runs in the same log (for context)
+
+- Earlier **`DRY_FLAG[@]: unbound variable`** errors from the script were fixed in later invocations.
+- A **mosaic-only** pass over all 12 machines completed with banner: *12 machine(s) with mosaic step completed, 0 skipped* (random scan per machine from the first page of IDs). That is a **separate** completed run from the **in-progress full scan** above.
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@@ -0,0 +1,15 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+VENV="/tmp/spruce_venv"
+
+if [[ ! -x "$VENV/bin/python" ]]; then
+    echo "Setting up venv at $VENV..."
+    python3 -m venv "$VENV"
+    "$VENV/bin/python" -m ensurepip --upgrade
+    "$VENV/bin/pip" install -q -r "$SCRIPT_DIR/requirements.txt"
+fi
+
+echo "Starting metadata-only scan of all machines..."
+"$VENV/bin/python" "$SCRIPT_DIR/scraper.py" --metadata-only "$@"
@@ -0,0 +1,105 @@
+#!/usr/bin/env python3
+"""
+Split scans.csv into per-machine metadata CSVs.
+
+Reads the combined scans.csv produced by the scraper and writes one CSV per
+machine containing only the website-sourced metadata columns (no mosaic paths,
+download status, or error fields).
+
+Usage:
+  python scripts/export_machine_metadata.py
+  python scripts/export_machine_metadata.py --input archives/scans.csv --output-dir archives/by_machine
+"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+METADATA_COLUMNS = [
+    "machine",
+    "machine_id",
+    "scan_id",
+    "name",
+    "scan_time",
+    "start_x",
+    "start_y",
+    "end_x",
+    "end_y",
+    "dx",
+    "dy",
+    "nx",
+    "ny",
+    "total_tiles",
+    "scan_lines",
+    "scan_mode",
+    "start_datetime",
+    "end_datetime",
+    "status",
+    "user",
+    "disk_space_mb",
+]
+
+
+def sanitize_machine_label(label: str) -> str:
+    return label.replace("[", "").replace("]", "").replace(" ", "_").strip("_")
+
+
+def parse_args() -> argparse.Namespace:
+    p = argparse.ArgumentParser(description="Split scans.csv into per-machine metadata CSVs.")
+    p.add_argument(
+        "--input",
+        default="archives/scans.csv",
+        metavar="FILE",
+        help="Path to scans.csv (default: archives/scans.csv)",
+    )
+    p.add_argument(
+        "--output-dir",
+        default="archives/by_machine",
+        metavar="DIR",
+        help="Directory for output CSVs (default: archives/by_machine)",
+    )
+    return p.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    input_path = Path(args.input)
+    output_dir = Path(args.output_dir)
+
+    if not input_path.exists():
+        sys.exit(f"Input file not found: {input_path}")
+
+    with input_path.open(newline="") as fh:
+        reader = csv.DictReader(fh)
+        if reader.fieldnames is None:
+            sys.exit(f"{input_path} appears to be empty.")
+
+        missing = [c for c in METADATA_COLUMNS if c not in reader.fieldnames]
+        if missing:
+            sys.exit(f"Expected columns not found in {input_path}: {missing}")
+
+        rows_by_machine: dict[str, list[dict]] = defaultdict(list)
+        for row in reader:
+            rows_by_machine[row["machine"]].append(row)
+
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    for machine_label, rows in sorted(rows_by_machine.items()):
+        safe_name = sanitize_machine_label(machine_label)
+        out_path = output_dir / f"{safe_name}_scans_metadata.csv"
+        with out_path.open("w", newline="") as fh:
+            writer = csv.DictWriter(fh, fieldnames=METADATA_COLUMNS, extrasaction="ignore")
+            writer.writeheader()
+            writer.writerows(rows)
+        print(f"  {out_path}  ({len(rows)} rows)")
+
+    total = sum(len(r) for r in rows_by_machine.values())
+    print(f"\n{len(rows_by_machine)} machine(s), {total} total rows → {output_dir}/")
+
+
+if __name__ == "__main__":
+    main()
@@ -1,6 +1,6 @@
 # All RootView minirhizotron machine labels (same set as `machine_metadata` in config.example.yaml).
 # Copy to the repo root as machines.txt, or: cp scripts/machines.example.txt machines.txt
-# sample_random_scans.sh: by default one random scan per line = mosaic + tiles; use MOSAIC_ONLY=1 for mosaics only
+# Random-sample helper `scripts/sample_random_scans.sh` lives on branch `testing/sample-runs` only.
 BW1-4 [AMR-15]
 BW1-6 [AMR-19]
 BW1-7 [AMR-18]
@@ -0,0 +1,381 @@
+#!/usr/bin/env python3
+"""
+Report mosaic download progress from archives/scans.csv.
+
+Output is formatted as Markdown.  Add --by-year for a per-machine ×
+per-year breakdown table.
+
+Rate/ETA require two calls at least 60 s apart.  Mean mosaic size is
+sampled from up to 100 already-downloaded files and cached for 1 hour.
+
+Usage:
+    python scripts/mosaic_progress_report.py [--archive DIR] [--by-year]
+"""
+
+import argparse
+import csv
+import json
+import os
+import random
+import sys
+from collections import Counter
+from datetime import datetime, timezone
+from pathlib import Path
+
+# Year-based viability model derived from BW1-4 observations:
+#   pre-2019  → kept on server long-term  (~100 %)
+#   2019-2022 → purged                    (~ 0 %)
+#   2023+     → recent, mostly available  (~82 %)
+_R_PRE19  = 1.00
+_R_PURGED = 0.00
+_R_RECENT = 0.82
+
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+def _parse_dt(s: str) -> datetime | None:
+    try:
+        return datetime.fromisoformat(s.replace("Z", "+00:00"))
+    except Exception:
+        return None
+
+
+def _fmt_duration(seconds: float) -> str:
+    if seconds < 0:
+        return "?"
+    h = int(seconds // 3600)
+    m = int((seconds % 3600) // 60)
+    if h >= 48:
+        return f"{h // 24}d {h % 24}h"
+    if h > 0:
+        return f"{h}h {m:02d}m"
+    return f"{m}m {int(seconds % 60):02d}s"
+
+
+def _fmt_size(b: float) -> str:
+    if b >= 1e12:
+        return f"{b/1e12:.2f} TB"
+    if b >= 1e9:
+        return f"{b/1e9:.2f} GB"
+    if b >= 1e6:
+        return f"{b/1e6:.1f} MB"
+    return f"{b/1e3:.0f} KB"
+
+
+def _md_table(headers: list[str], rows: list[list[str]], *, align: list[str] | None = None) -> str:
+    """Render a Markdown table.  align values: 'l', 'r', 'c' (default 'l')."""
+    if align is None:
+        align = ["l"] * len(headers)
+    sep_map = {"l": ":---", "r": "---:", "c": ":---:"}
+
+    def row_str(cells: list[str]) -> str:
+        return "| " + " | ".join(cells) + " |"
+
+    lines = [
+        row_str(headers),
+        row_str([sep_map.get(a, ":---") for a in align]),
+    ]
+    for r in rows:
+        lines.append(row_str(r))
+    return "\n".join(lines)
+
+
+def _sample_mean_bytes(rows: list[dict], cache: dict, max_sample: int = 100) -> float | None:
+    cached_mean = cache.get("mean_bytes")
+    cached_n    = cache.get("sample_n", 0)
+    cached_ts   = _parse_dt(cache.get("size_ts", ""))
+    now = datetime.now(timezone.utc)
+    if (
+        cached_mean and cached_ts
+        and (now - cached_ts).total_seconds() < 3600
+        and cached_n >= min(max_sample, len(rows))
+    ):
+        return float(cached_mean)
+
+    sample = random.sample(rows, min(max_sample, len(rows)))
+    sizes = []
+    for row in sample:
+        p = row.get("mosaic_local_path", "")
+        if p:
+            try:
+                sz = os.path.getsize(p)
+                if sz > 0:
+                    sizes.append(sz)
+            except OSError:
+                pass
+    if not sizes:
+        return None
+    mean = sum(sizes) / len(sizes)
+    cache["mean_bytes"] = mean
+    cache["sample_n"]   = len(sizes)
+    cache["size_ts"]    = now.isoformat()
+    return mean
+
+
+def _expected_remaining(pending_rows: list[dict]) -> float:
+    count = 0.0
+    for row in pending_rows:
+        yr = row.get("scan_time", "")[:4]
+        if yr < "2019":
+            count += _R_PRE19
+        elif yr <= "2022":
+            count += _R_PURGED
+        else:
+            count += _R_RECENT
+    return count
+
+
+# ---------------------------------------------------------------------------
+# Main
+# ---------------------------------------------------------------------------
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--archive", default="archives")
+    parser.add_argument(
+        "--by-year", action="store_true",
+        help="Add a per-machine × per-year done/failed breakdown table",
+    )
+    args = parser.parse_args()
+
+    archive         = Path(args.archive)
+    scans_csv       = archive / "scans.csv"
+    progress_json   = archive / ".progress.json"
+    rate_cache_path = archive / ".mosaic_rate_cache.json"
+
+    if not scans_csv.exists():
+        sys.exit(f"scans.csv not found: {scans_csv}")
+
+    # --- Load & deduplicate (last row per machine+scan_id) ---
+    latest: dict[tuple[str, str], dict] = {}
+    with open(scans_csv, newline="", encoding="utf-8") as f:
+        for row in csv.DictReader(f):
+            key = (row.get("machine", ""), row.get("scan_id", ""))
+            latest[key] = row
+
+    by_machine: dict[str, Counter] = {}
+    # machine -> year -> Counter(status -> count)
+    by_machine_year: dict[str, dict[str, Counter]] = {}
+    total_counts: Counter = Counter()
+    downloaded_rows: list[dict] = []
+    pending_rows:    list[dict] = []
+
+    for (_m, _sid), row in latest.items():
+        status = row.get("mosaic_download_status", "")
+        m  = row.get("machine", "")
+        yr = (row.get("scan_time") or "")[:4] or "????"
+        by_machine.setdefault(m, Counter())[status] += 1
+        by_machine_year.setdefault(m, {}).setdefault(yr, Counter())[status] += 1
+        total_counts[status] += 1
+        if status == "downloaded":
+            downloaded_rows.append(row)
+        elif status == "skipped_metadata_only":
+            pending_rows.append(row)
+
+    total        = sum(total_counts.values())
+    downloaded   = total_counts["downloaded"]
+    failed       = total_counts["failed"]
+    zero_skipped = total_counts["skipped_zero_disk_space"]
+    pending      = total_counts["skipped_metadata_only"]
+    processed    = downloaded + failed + zero_skipped
+    attempted    = downloaded + failed
+    now          = datetime.now(timezone.utc)
+
+    # --- Elapsed ---
+    elapsed_str = ""
+    if progress_json.exists():
+        try:
+            data = json.loads(progress_json.read_text())
+            started_at = _parse_dt(data.get("started_at", ""))
+            if started_at:
+                elapsed_str = _fmt_duration((now - started_at).total_seconds())
+        except Exception:
+            pass
+
+    # --- Rate cache ---
+    cache: dict = {}
+    if rate_cache_path.exists():
+        try:
+            cache = json.loads(rate_cache_path.read_text())
+        except Exception:
+            pass
+
+    # Rolling rate: keep up to 60 snapshots; compute rate from the oldest
+    # snapshot within the last 30 minutes for a smoothed estimate.
+    snapshots: list[dict] = cache.get("snapshots", [])
+    # Prune snapshots older than 30 minutes, but keep at least one
+    cutoff = now.timestamp() - 1800
+    recent = [s for s in snapshots if s.get("ts", 0) >= cutoff]
+    if not recent and snapshots:
+        recent = [snapshots[-1]]  # always keep one for continuity
+
+    rate_per_sec: float | None = None
+    rate_window_str = ""
+    if recent:
+        oldest = recent[0]
+        dt = now.timestamp() - oldest["ts"]
+        dp = processed - oldest["proc"]
+        if dt >= 60 and dp > 0:
+            rate_per_sec = dp / dt
+            window_min = dt / 60
+            rate_window_str = f"{window_min:.0f}-min avg"
+
+    # --- Disk space ---
+    mean_bytes: float | None = None
+    size_note = ""
+    if downloaded_rows:
+        mean_bytes = _sample_mean_bytes(downloaded_rows, cache)
+        if mean_bytes and cache.get("sample_n"):
+            size_note = f"mean {_fmt_size(mean_bytes)} × {cache['sample_n']} sampled files"
+
+    dl_bytes: float | None = None
+    rem_bytes: float | None = None
+    if mean_bytes:
+        dl_bytes  = downloaded * mean_bytes
+        rem_bytes = _expected_remaining(pending_rows) * mean_bytes
+
+    # Update cache: append new snapshot, keep last 60
+    recent.append({"ts": now.timestamp(), "proc": processed})
+    cache["snapshots"] = recent[-60:]
+    # Keep legacy keys for backwards compat
+    cache["timestamp"] = now.isoformat()
+    cache["processed"] = processed
+    try:
+        rate_cache_path.write_text(json.dumps(cache))
+    except Exception:
+        pass
+
+    rate_str = eta_str = ""
+    if rate_per_sec and rate_per_sec > 0:
+        rate_str = f"{rate_per_sec * 3600:,.0f} scans/hr ({rate_window_str})"
+        eta_str  = _fmt_duration(pending / rate_per_sec)
+
+    # -----------------------------------------------------------------------
+    # Output — Markdown
+    # -----------------------------------------------------------------------
+
+    ts = datetime.now().strftime("%Y-%m-%d %H:%M")
+    print(f"# Mosaic download progress — {ts}\n")
+    print(f"**Archive:** `{archive.resolve()}`  ")
+    meta_parts = []
+    if elapsed_str:
+        meta_parts.append(f"**Elapsed:** {elapsed_str}")
+    if rate_str:
+        meta_parts.append(f"**Rate:** {rate_str}")
+    if eta_str:
+        meta_parts.append(f"**ETA:** {eta_str}")
+    if meta_parts:
+        print("  ".join(meta_parts) + "  ")
+    print()
+
+    # Summary table
+    summary_rows = [
+        ["Downloaded",      f"{downloaded:,}",   f"{100*downloaded/total:.1f}%"],
+        ["Failed",          f"{failed:,}",        f"{100*failed/total:.1f}%"],
+        ["Skipped (disk=0)",f"{zero_skipped:,}",  f"{100*zero_skipped/total:.1f}%"],
+        ["Pending",         f"{pending:,}",       f"{100*pending/total:.1f}%"],
+        ["**Total**",       f"**{total:,}**",     ""],
+    ]
+    if attempted:
+        summary_rows.append(["**Success rate**", f"**{100*downloaded/attempted:.1f}%**", "*(of attempted)*"])
+    print(_md_table(["Metric", "Count", ""], summary_rows, align=["l", "r", "l"]))
+    print()
+
+    # Disk space
+    if dl_bytes is not None and rem_bytes is not None:
+        total_bytes = dl_bytes + rem_bytes
+        print(f"### Disk space\n")
+        print(f"_{size_note}_\n")
+        ds_rows = [
+            ["Downloaded so far",    _fmt_size(dl_bytes),    ""],
+            ["Estimated remaining",  _fmt_size(rem_bytes),   "*(model-based)*"],
+            ["**Grand total**",      f"**{_fmt_size(total_bytes)}**", ""],
+        ]
+        print(_md_table(["", "Size", ""], ds_rows, align=["l", "r", "l"]))
+        print()
+
+    # Per-machine breakdown
+    print("### Per-machine breakdown\n")
+    machines = sorted(by_machine)
+    mc_rows = []
+    for m in machines:
+        mc = by_machine[m]
+        mt = sum(mc.values())
+        mc_rows.append([
+            m,
+            f"{mc['downloaded']:,}",
+            f"{mc['failed']:,}",
+            f"{mc['skipped_zero_disk_space']:,}",
+            f"{mc['skipped_metadata_only']:,}",
+            f"{mt:,}",
+        ])
+    mc_rows.append([
+        "**TOTAL**",
+        f"**{downloaded:,}**",
+        f"**{failed:,}**",
+        f"**{zero_skipped:,}**",
+        f"**{pending:,}**",
+        f"**{total:,}**",
+    ])
+    print(_md_table(
+        ["Machine", "Done", "Failed", "Skip0", "Pending", "Total"],
+        mc_rows,
+        align=["l", "r", "r", "r", "r", "r"],
+    ))
+
+    # -----------------------------------------------------------------------
+    # --by-year table
+    # -----------------------------------------------------------------------
+    if args.by_year:
+        print()
+        print("### Downloads by machine and year\n")
+        print("*Format: done / failed*\n")
+
+        # Only include years that have at least one downloaded or failed scan
+        all_years = sorted(
+            yr for yr in set(
+                yr for m_data in by_machine_year.values() for yr in m_data
+            )
+            if any(
+                by_machine_year[m].get(yr, Counter()).get("downloaded", 0)
+                + by_machine_year[m].get(yr, Counter()).get("failed", 0) > 0
+                for m in by_machine_year
+            )
+        )
+
+        # Totals per year
+        yr_totals: dict[str, Counter] = {}
+        for yr in all_years:
+            yr_totals[yr] = Counter()
+            for m in machines:
+                yr_totals[yr] += by_machine_year.get(m, {}).get(yr, Counter())
+
+        year_rows = []
+        for m in machines:
+            row_cells = [m]
+            for yr in all_years:
+                c = by_machine_year.get(m, {}).get(yr, Counter())
+                d = c.get("downloaded", 0)
+                f = c.get("failed", 0)
+                row_cells.append(f"{d:,} / {f:,}" if (d or f) else "—")
+            year_rows.append(row_cells)
+
+        # Totals row
+        total_cells = ["**TOTAL**"]
+        for yr in all_years:
+            d = yr_totals[yr].get("downloaded", 0)
+            f = yr_totals[yr].get("failed", 0)
+            total_cells.append(f"**{d:,} / {f:,}**" if (d or f) else "—")
+        year_rows.append(total_cells)
+
+        print(_md_table(
+            ["Machine"] + all_years,
+            year_rows,
+            align=["l"] + ["r"] * len(all_years),
+        ))
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,218 @@
+#!/usr/bin/env python3
+"""
+Report metadata-scan progress and projected completion times for all machines.
+
+Usage:
+    python scripts/scan_progress_report.py [--archive ARCHIVE_DIR] [--recent N] [--mermaid] [--rate-chart]
+
+Options:
+    --archive DIR   Path to archives directory (default: archives)
+    --recent N      Number of recent files used to compute current rate (default: 500)
+    --mermaid       Also print a Mermaid Gantt chart
+    --rate-chart    Also print a Mermaid XY chart of s/scan rate by hour
+"""
+
+import argparse
+import glob
+import os
+import re
+import sys
+from collections import defaultdict
+from datetime import datetime, timedelta
+from pathlib import Path
+
+
+# Canonical machine order and total scan counts (from README inventory, April 2026)
+MACHINES = [
+    ("BW1-4 [AMR-15]",  6121),
+    ("BW1-6 [AMR-19]", 18198),
+    ("BW1-7 [AMR-18]",   430),
+    ("BW2-8 [AMR-25]",  8191),
+    ("BW2-10 [AMR-22]", 16537),
+    ("BW2-11 [AMR-23]", 26763),
+    ("BW2-13 [AMR-24]", 13537),
+    ("BW3-16 [AMR-16]",  7325),
+    ("BW3-17 [AMR-20]",   471),
+    ("BW3-19 [AMR-21]", 15186),
+    ("BW3-20 [AMR-26]", 23052),
+    ("BW3-21 [AMR-17]", 10115),
+]
+TOTAL_SCANS = sum(t for _, t in MACHINES)
+
+
+def dir_name(label: str) -> str:
+    return re.sub(r"[^\w\-.]", "_", label).strip("_")
+
+
+def get_timestamps(machine_dir: Path) -> list[float]:
+    files = glob.glob(str(machine_dir / "**" / "metadata.json"), recursive=True)
+    return sorted(os.path.getmtime(f) for f in files)
+
+
+def print_rate_chart(all_timestamps: list[float]) -> None:
+    """Print a Mermaid xychart-beta of average s/scan per hour."""
+    # One avg rate per hour
+    bins: dict[str, list[float]] = defaultdict(list)
+    start_hour: datetime | None = None
+    for i in range(1, len(all_timestamps)):
+        gap = all_timestamps[i] - all_timestamps[i - 1]
+        if gap < 300:  # ignore inter-machine gaps
+            dt = datetime.fromtimestamp(all_timestamps[i])
+            hour_key = dt.strftime("%m-%d %Hh")
+            bins[hour_key].append(gap)
+            if start_hour is None:
+                start_hour = dt.replace(minute=0, second=0, microsecond=0)
+
+    # Drop the last (partial) hour
+    hours = sorted(bins.keys())
+    if hours:
+        hours = hours[:-1]
+
+    if not hours or start_hour is None:
+        print("(not enough data for rate chart)")
+        return
+
+    values = [f"{sum(bins[h])/len(bins[h]):.2f}" for h in hours]
+    y_max = max(float(v) for v in values)
+    y_ceil = int(y_max) + 3
+    n = len(hours)
+
+    # Numeric x-axis: Mermaid auto-picks readable tick positions
+    start_label = start_hour.strftime("%b %d %H:%M")
+    print("```mermaid")
+    print("xychart-beta")
+    print(f'    title "Metadata scan rate (s/scan) — hourly, starting {start_label}"')
+    print(f'    x-axis "Hours elapsed" 0 --> {n}')
+    print(f'    y-axis "s / scan" 0 --> {y_ceil}')
+    print(f"    line [{', '.join(values)}]")
+    print("```")
+
+
+def fmt_dt(dt: datetime) -> str:
+    return dt.strftime("%a %b %d  %H:%M")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--archive", default="archives", help="Archives directory")
+    parser.add_argument("--recent", type=int, default=500,
+                        help="Files used to compute recent rate (default: 500)")
+    parser.add_argument("--mermaid", action="store_true", help="Print Mermaid Gantt chart")
+    parser.add_argument("--rate-chart", action="store_true", help="Print Mermaid XY rate-over-time chart")
+    args = parser.parse_args()
+
+    archive = Path(args.archive)
+    if not archive.is_dir():
+        sys.exit(f"Archive directory not found: {archive}")
+
+    now = datetime.now()
+
+    # --- Gather per-machine data ---
+    machine_data = []  # (label, total, done, first_ts, last_ts)
+    all_timestamps: list[float] = []
+
+    for label, total in MACHINES:
+        mdir = archive / dir_name(label)
+        if mdir.is_dir():
+            times = get_timestamps(mdir)
+        else:
+            times = []
+        done = len(times)
+        first_ts = datetime.fromtimestamp(times[0]) if times else None
+        last_ts  = datetime.fromtimestamp(times[-1]) if times else None
+        machine_data.append((label, total, done, first_ts, last_ts, times))
+        all_timestamps.extend(times)
+
+    all_timestamps.sort()
+    total_done = sum(d for _, _, d, *_ in machine_data)
+
+    # --- Rate calculation ---
+    recent_times = all_timestamps[-args.recent:] if len(all_timestamps) >= 2 else all_timestamps
+    if len(recent_times) >= 2:
+        recent_rate = (recent_times[-1] - recent_times[0]) / len(recent_times)
+    else:
+        recent_rate = None
+
+    if len(all_timestamps) >= 2:
+        overall_rate = (all_timestamps[-1] - all_timestamps[0]) / len(all_timestamps)
+    else:
+        overall_rate = None
+
+    rate = recent_rate or overall_rate or 5.0  # fallback
+
+    # --- Print timetable ---
+    print(f"Metadata scan progress  —  {now.strftime('%Y-%m-%d %H:%M')}")
+    print(f"Overall rate : {overall_rate:.2f} s/scan" if overall_rate else "Overall rate : n/a")
+    print(f"Recent rate  : {recent_rate:.2f} s/scan (last {args.recent} files)" if recent_rate else "Recent rate  : n/a")
+    print(f"Rate used    : {rate:.2f} s/scan")
+    print(f"Done         : {total_done:,} / {TOTAL_SCANS:,}  ({100*total_done/TOTAL_SCANS:.1f}%)")
+    print()
+    print(f"{'Machine':<20} {'Total':>7}  {'Done':>7}  {'Pct':>6}  {'Completion'}")
+    print("-" * 68)
+
+    cursor = now
+    gantt_rows: list[tuple[str, datetime, datetime, str]] = []  # label, start, end, status
+
+    for label, total, done, first_ts, last_ts, times in machine_data:
+        pct = 100 * done / total if total else 0
+
+        complete = done >= total or (done > 0 and done / total >= 0.999)
+
+        if done == 0:
+            # Not started yet
+            start = cursor
+            finish = cursor + timedelta(seconds=total * rate)
+            status = "pending"
+            print(f"{label:<20} {total:>7,}  {'—':>7}   {'—':>5}   {fmt_dt(finish)}")
+        elif complete:
+            # Complete — use actual timestamps
+            start = first_ts
+            finish = last_ts
+            status = "done"
+            print(f"{label:<20} {total:>7,}  {done:>7,}  {pct:>5.1f}%  complete")
+        else:
+            # In progress
+            remaining = total - done
+            start = first_ts
+            finish = cursor + timedelta(seconds=remaining * rate)
+            status = "active"
+            print(f"{label:<20} {total:>7,}  {done:>7,}  {pct:>5.1f}%  {fmt_dt(finish)}  ← in progress")
+
+        gantt_rows.append((label, start or cursor, finish, status))
+        if status != "done":
+            cursor = finish
+
+    print("-" * 68)
+    print(f"{'All done':<20} {TOTAL_SCANS:>7,}  {total_done:>7,}  {100*total_done/TOTAL_SCANS:>5.1f}%  {fmt_dt(cursor)}")
+
+    # --- Mermaid rate chart ---
+    if args.rate_chart:
+        print()
+        print_rate_chart(all_timestamps)
+
+    # --- Mermaid Gantt ---
+    if args.mermaid:
+        print()
+        print("```mermaid")
+        print("gantt")
+        print("    title Metadata scan progress — all 12 machines")
+        print("    dateFormat YYYY-MM-DD HH:mm")
+        print("    axisFormat %b %d")
+        print()
+
+        section = None
+        for label, start, finish, status in gantt_rows:
+            prefix = label.split()[0][:3]  # BW1, BW2, BW3
+            if prefix != section:
+                section = prefix
+                print(f"    section {section}")
+            safe = label.replace("[", "").replace("]", "").replace(" ", "-")
+            tag = f"done, " if status == "done" else ("active, " if status == "active" else "")
+            s = start.strftime("%Y-%m-%d %H:%M")
+            e = finish.strftime("%Y-%m-%d %H:%M")
+            print(f"    {label} :{tag}{safe}, {s}, {e}")
+        print("```")
+
+
+if __name__ == "__main__":
+    main()
@@ -241,6 +241,7 @@ def process_scan(
    mosaic_only: bool,
    metadata_only: bool = False,
    max_tiles: int | None = None,
+    scans_csv_existing_ids: set[int] | None = None,
 ) -> RunStats:
    """
    Process one scan: fetch metadata, download mosaic and (optionally) tiles.
@@ -379,9 +380,16 @@ def process_scan(
        mds, mer, mco, mcl = "", "", "", ""

    # Write scan-level CSV row only if this scan hasn't been recorded before.
-    if mosaic_already_done and not metadata_only:
+    # Skip if: (1) mosaic URL already in .progress.json, or (2) scan already
+    # has a non-pending row in scans.csv from a prior run.
+    already_recorded = (mosaic_already_done and not metadata_only) or (
+        not metadata_only
+        and scans_csv_existing_ids is not None
+        and scan_id in scans_csv_existing_ids
+    )
+    if already_recorded:
        log.debug(
-            "[%s] Scan %d: already in scans.csv (mosaic was previously downloaded), skipping CSV row.",
+            "[%s] Scan %d: already in scans.csv, skipping CSV row.",
            machine["label"],
            scan_id,
        )
@@ -494,7 +502,20 @@ def scrape_machine(
 ) -> RunStats:
    """Login, fetch scans, and download all content for one machine."""
    sess = MachineSession(machine, config)
-    if not sess.login():
+    login_ok = False
+    for attempt in range(1, 4):
+        if sess.login():
+            login_ok = True
+            break
+        if attempt < 3:
+            log.warning(
+                "[%s] Login failed (attempt %d/3) — retrying in 10s.",
+                machine["label"],
+                attempt,
+            )
+            time.sleep(10)
+    if not login_ok:
+        log.error("[%s] Login failed after 3 attempts — skipping machine.", machine["label"])
        return RunStats()

    if scan_id_filter is not None:
@@ -508,8 +529,33 @@ def scrape_machine(
            log.warning("[%s] No scans found.", machine["label"])
            return RunStats()

+    # Build a set of scan_ids already fully processed in a prior run so we can
+    # skip them entirely (no metadata fetch, no mosaic request).
+    # Only scans with a definitive non-pending status count; skipped_metadata_only
+    # rows still need to be processed in mosaic mode.
+    PENDING_STATUSES = {"skipped_metadata_only", ""}
+    existing_ids: set[int] = set()
+    if not metadata_only and scans_csv._fh.name:
+        existing_path = Path(scans_csv._fh.name)
+        if existing_path.exists():
+            import csv as _csv
+            with open(existing_path, newline="", encoding="utf-8") as _f:
+                for _row in _csv.DictReader(_f):
+                    if _row.get("machine") == machine["label"]:
+                        if _row.get("mosaic_download_status", "") not in PENDING_STATUSES:
+                            existing_ids.add(int(_row["scan_id"]))
+
    stats = RunStats()
    for scan in scans:
+        # Skip scans already fully processed in a prior run — avoids redundant
+        # metadata fetches and mosaic requests for known-failed / known-done scans.
+        if not metadata_only and scan["scan_id"] in existing_ids:
+            log.debug(
+                "[%s] Scan %d: already processed, skipping.",
+                machine["label"],
+                scan["scan_id"],
+            )
+            continue
        stats.merge(process_scan(
            sess=sess,
            scan=scan,
@@ -523,5 +569,6 @@ def scrape_machine(
            mosaic_only=mosaic_only,
            metadata_only=metadata_only,
            max_tiles=max_tiles,
+            scans_csv_existing_ids=existing_ids,
        ))
    return stats
@@ -5,6 +5,7 @@ Progress tracking (JSON) and CSV writing.
 import csv
 import json
 import logging
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Iterator

@@ -27,6 +28,7 @@ class ProgressTracker:
    def __init__(self, path: Path) -> None:
        self.path = path
        self._done: set[str] = set()
+        self.started_at: str = datetime.now(timezone.utc).isoformat()
        self._load()

    def _load(self) -> None:
@@ -34,6 +36,8 @@ class ProgressTracker:
            try:
                data = json.loads(self.path.read_text())
                self._done = set(data.get("completed_urls", []))
+                if "started_at" in data:
+                    self.started_at = data["started_at"]
                log.info("Resuming: %d URLs already downloaded.", len(self._done))
            except Exception:
                log.warning("Could not read progress file; starting fresh.")
@@ -59,7 +63,10 @@ class ProgressTracker:
        self.path.parent.mkdir(parents=True, exist_ok=True)
        tmp = self.path.with_suffix(".json.tmp")
        tmp.write_text(
-            json.dumps({"completed_urls": sorted(self._done)}, indent=2)
+            json.dumps(
+                {"started_at": self.started_at, "completed_urls": sorted(self._done)},
+                indent=2,
+            )
        )
        tmp.replace(self.path)  # atomic on POSIX; avoids corrupt JSON on crash

@@ -14,6 +14,7 @@ from bs4 import BeautifulSoup

 from spruce.download_result import (
    OK,
+    PERMANENT_MISSING,
    UNKNOWN,
    DownloadResult,
    classify_http_error,
@@ -263,6 +264,10 @@ class MachineSession:
                    and exc.response is not None
                ):
                    sc = exc.response.status_code
+                cl = classify_http_error(sc, exc)
+                if cl == PERMANENT_MISSING:
+                    # 404/410 will never succeed — don't waste time retrying.
+                    return DownloadResult(0, sc, str(exc), cl)
                if attempt < retries:
                    log.warning(
                        "Attempt %d/%d failed %s: %s — retrying in %.0fs",
@@ -281,7 +286,6 @@ class MachineSession:
                        url,
                        exc,
                    )
-                    cl = classify_http_error(sc, exc)
                    return DownloadResult(0, sc, str(exc), cl)
        return DownloadResult(0, None, "download_file: exhausted", UNKNOWN)