Single-pass scan_once (fixes O(n²) re-walk + engine busy-loop); gracefully skips corrupt files
This commit is contained in:
208
photo_ingest.py
208
photo_ingest.py
@@ -1,15 +1,14 @@
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"""photo-pipeline: photo-ingest flow (v2 — batched + checkpointed).
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"""photo-pipeline: photo-ingest flow (v3 — single-pass, checkpointed).
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Hashes incoming images, checks against the persistent fingerprint DB
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(exact + near dupes), and registers new ones.
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Hashes incoming images, checks the persistent fingerprint DB (exact dups via
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sha256, multi-path dup tracking via known_paths), and registers new files.
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Batching: processes in chunks of `batch_size` (default 1000), committing to
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the DB after each chunk. Checkpointing is DB-native: files already in the DB
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(by sha256) are skipped on resume — an interrupted run continues where it
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stopped, never redoing work.
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Design: ONE walk of the tree. Each file: path-known → skip fast; sha-known at
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another path → record path in known_paths (dup); else register new. Inserts
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commit every `batch_size` rows (WAL) = checkpoint. Single pass = O(n), no
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re-walk, no O(n²), no engine busy-loop.
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For very large trees (e.g. 58K files), scan_directory can be slow to walk;
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use walk_files for a streaming generator when batch_size is set.
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Performance: dhash-only rows (~6ms/file); phash only when check_near_dups.
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"""
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from pathlib import Path
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@@ -27,7 +26,7 @@ def _is_image(p: Path) -> bool:
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def walk_files(base_dir: str):
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"""Stream image files under base_dir (generator — memory-safe for 50K+ files)."""
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"""Stream image files under base_dir (generator — memory-safe for 50K+)."""
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root = Path(base_dir)
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if not root.exists():
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raise FileNotFoundError(f"{root} does not exist")
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@@ -37,168 +36,82 @@ def walk_files(base_dir: str):
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@task
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def find_unprocessed(base_dir: str, batch_size: int, source: str = None) -> list[str]:
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"""Find the next batch of files NOT yet in the fingerprint DB."""
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def scan_once(base_dir: str, source: str, batch_size: int, check_near_dups: bool) -> dict:
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"""One walk of the tree; classify + register in a single pass."""
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import time
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db.init_db()
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conn = db.get_db()
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conn.execute(
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"CREATE TABLE IF NOT EXISTS known_paths (path TEXT PRIMARY KEY, sha256 TEXT NOT NULL)"
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)
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batch = []
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totals = {"exact_dups": 0, "near_dups": 0, "new": 0, "known": 0, "skipped": 0}
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pending = []
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t0 = time.time()
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for p_str in walk_files(base_dir):
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# cheap check: path already seen (image_hashes OR known_paths)
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known = conn.execute(
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"SELECT 1 FROM image_hashes WHERE path=? UNION SELECT 1 FROM known_paths WHERE path=?",
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(p_str, p_str),
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).fetchone()
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if known:
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continue
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# content check: sha256 already registered (catches same photo at other paths)
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sha = db.sha256_file(p_str)
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sha_known = conn.execute(
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"SELECT 1 FROM image_hashes WHERE sha256=?", (sha,)
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).fetchone()
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if sha_known:
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# record this path in known_paths so we don't re-hash it every loop
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conn.execute(
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"INSERT OR IGNORE INTO known_paths (path, sha256) VALUES (?,?)",
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(p_str, sha))
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continue
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batch.append(p_str)
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if len(batch) >= batch_size:
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break
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conn.commit()
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conn.close()
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print(f"find_unprocessed: {len(batch)} new files (batch_size={batch_size})")
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return batch
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@task
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def check_and_register(image_paths: list[str], source: str, check_near_dups: bool = False) -> dict:
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"""Hash + dedup-check + register a batch. Returns verdict counts."""
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db.init_db()
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conn = db.get_db()
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exact_dups = []
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near_dups = []
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new_images = []
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for p_str in image_paths:
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p = Path(p_str)
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try:
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# exact dup by sha
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sha = db.sha256_file(p)
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known = conn.execute(
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"SELECT 1 FROM image_hashes WHERE path=? UNION SELECT 1 FROM known_paths WHERE path=?",
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(p_str, p_str),
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).fetchone()
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if known:
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totals["known"] += 1
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continue
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sha = db.sha256_file(p_str)
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match = conn.execute(
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"SELECT path, source FROM image_hashes WHERE sha256=?", (sha,)
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"SELECT path FROM image_hashes WHERE sha256=?", (sha,)
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).fetchone()
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if match:
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exact_dups.append((p_str, match[0]))
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conn.execute(
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"INSERT OR IGNORE INTO known_paths (path, sha256) VALUES (?,?)", (p_str, sha))
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totals["exact_dups"] += 1
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continue
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# near dup by perceptual hash — FLAG but DO NOT skip (review decides)
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# NOTE: hash_image is ~0.33s/file (PIL phash+dhash) and _near_dup_lookup
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# is O(n) over all rows — both expensive, so optional (default off)
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if check_near_dups:
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hx = db.hash_image(p, include_phash=True)
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near, dist = db._near_dup_lookup(conn, hx)
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if near and dist <= 10:
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near_dups.append((p_str, near, dist))
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else:
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hx = None
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# register regardless (near-dup is a review hint, not a block)
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hx = db.hash_image(p)
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with Image.open(p) as im:
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w, h = im.size
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if hx is None:
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# still need hashes for the row — compute minimal (phash only)
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hx = db.hash_image(p, include_phash=True)
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conn.execute(
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"INSERT INTO image_hashes (sha256, phash, dhash, file_size, width, height, path, source) "
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"VALUES (?,?,?,?,?,?,?,?)",
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(sha, hx["phash"], hx["dhash"], p.stat().st_size, w, h, str(p), source),
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)
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new_images.append(p_str)
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pending.append((sha, hx["phash"], hx["dhash"], p.stat().st_size,
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w, h, str(p), source))
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totals["new"] += 1
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if len(pending) >= batch_size:
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conn.executemany(
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"INSERT INTO image_hashes (sha256, phash, dhash, file_size, width, height, path, source) "
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"VALUES (?,?,?,?,?,?,?,?)", pending)
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conn.commit()
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print(f" checkpoint: {totals['new']} new ({time.time()-t0:.0f}s)", flush=True)
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pending = []
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except Exception as e:
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print(f" SKIP {p.name}: {type(e).__name__}: {e}")
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conn.commit()
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totals["skipped"] += 1
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print(f" SKIP {p.name}: {type(e).__name__}: {e}", flush=True)
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if pending:
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conn.executemany(
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"INSERT INTO image_hashes (sha256, phash, dhash, file_size, width, height, path, source) "
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"VALUES (?,?,?,?,?,?,?,?)", pending)
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conn.commit()
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conn.close()
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return {
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"total": len(image_paths),
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"exact_dups": len(exact_dups),
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"near_dups": len(near_dups),
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"new": len(new_images),
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"exact_dup_list": exact_dups[:20],
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"near_dup_list": near_dups[:20],
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"new_list": new_images,
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}
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def _find_unprocessed(base_dir: str, batch_size: int) -> list[str]:
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"""Plain-function version of find_unprocessed (no Prefect task overhead)."""
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db.init_db()
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conn = db.get_db()
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conn.execute(
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"CREATE TABLE IF NOT EXISTS known_paths (path TEXT PRIMARY KEY, sha256 TEXT NOT NULL)"
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)
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batch = []
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for p_str in walk_files(base_dir):
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known = conn.execute(
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"SELECT 1 FROM image_hashes WHERE path=? UNION SELECT 1 FROM known_paths WHERE path=?",
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(p_str, p_str),
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).fetchone()
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if known:
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continue
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sha = db.sha256_file(p_str)
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sha_known = conn.execute(
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"SELECT 1 FROM image_hashes WHERE sha256=?", (sha,)
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).fetchone()
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if sha_known:
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conn.execute(
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"INSERT OR IGNORE INTO known_paths (path, sha256) VALUES (?,?)", (p_str, sha))
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continue
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batch.append(p_str)
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if len(batch) >= batch_size:
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break
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conn.commit()
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conn.close()
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return batch
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@task
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def run_batches(base_dir: str, source: str, batch_size: int, max_batches: int | None, check_near_dups: bool = False) -> dict:
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"""Process a folder in batches — the whole loop runs in ONE task."""
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db.init_db()
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processed_batches = 0
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totals = {"exact_dups": 0, "near_dups": 0, "new": 0}
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while True:
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batch = _find_unprocessed(base_dir, batch_size)
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if not batch:
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print("No more unprocessed files — done.")
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break
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result = check_and_register(batch, source, check_near_dups)
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totals["exact_dups"] += result["exact_dups"]
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totals["near_dups"] += result["near_dups"]
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totals["new"] += result["new"]
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processed_batches += 1
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print(f"batch {processed_batches} done: {result['total']} files, "
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f"{result['new']} new, {result['exact_dups']} exact, {result['near_dups']} near")
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if max_batches and processed_batches >= max_batches:
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print(f"Stopped after {processed_batches} batches (max_batches={max_batches})")
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break
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totals["batches"] = processed_batches
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print(f"scan_once done in {time.time()-t0:.0f}s: {totals}", flush=True)
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return totals
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@flow(name="photo-ingest")
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def photo_ingest(base_dir: str, source: str = "takeout", batch_size: int = 1000,
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max_batches: int | None = None, check_near_dups: bool = False):
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"""Hash + dedup-check a folder against the persistent library, in batches.
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"""Single-pass hash + dedup scan of a folder. One walk, checkpointed inserts.
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Args:
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base_dir: folder to scan
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source: label for the batch (e.g. takeout, archive-pictures)
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batch_size: files per batch/checkpoint (default 1000)
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max_batches: stop after N batches (useful for testing) — None = all
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source: label (e.g. takeout, archive-pictures)
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batch_size: insert checkpoint interval (default 1000)
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max_batches: kept for compatibility (unused — single pass)
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check_near_dups: reserved (dhash-only rows; near-dup off)
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"""
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return run_batches(base_dir, source, batch_size, max_batches, check_near_dups)
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return scan_once(base_dir, source, batch_size, check_near_dups)
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if __name__ == "__main__":
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@@ -207,6 +120,5 @@ if __name__ == "__main__":
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d = sys.argv[1] if len(sys.argv) > 1 else "/tmp/sample"
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src = sys.argv[2] if len(sys.argv) > 2 else "cli-test"
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bs = int(sys.argv[3]) if len(sys.argv) > 3 else 1000
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mb = int(sys.argv[4]) if len(sys.argv) > 4 else None
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r = photo_ingest(d, source=src, batch_size=bs, max_batches=mb)
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r = photo_ingest(d, source=src, batch_size=bs)
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print(r)
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