458 lines
15 KiB
Python
458 lines
15 KiB
Python
"""
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==============================================================================
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Skript: enrich_fulltext_v1.1.py
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Verze: 1.1
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Datum: 2026-06-03
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Autor: vladimir.buzalka
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Popis: Vytahne PLNY TEXT z dokumentu odkazovanych v MongoDB (db: soubory)
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a ulozi ho do PostgreSQL (db: MongoSoubory) s GIN tsvector indexem.
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Zmeny proti v1.0:
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- PG odmita NUL (0x00) bajty v TEXT -> v _truncate se vsechny NULy odstrani
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(i jine controly krome \\n \\r \\t)
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- DOCX fallback: pokud python-docx selze (typicky "no tr above topmost tr
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in w:tbl" u rozbitych tabulek), pokusi se primy raw extract z word/document.xml
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pres regex - prijde o strukturu tabulek, ale zachrani text
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- drobnost: posunul jsem extractor_version na "1.1" -> stare radky se preparsuji
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Cilove ulozeni:
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- MongoDB 192.168.1.76 db=soubory kolekce=42847922MDD3003, 77242113UCO3001
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- PostgreSQL 192.168.1.76 db=MongoSoubory tabulka=documents
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Podporovane pripony: pdf, docx, xlsx, xlsm, pptx, eml, msg, txt, csv
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==============================================================================
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"""
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from __future__ import annotations
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import email
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import email.policy
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import re
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import sys
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import time
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import traceback
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import zipfile
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from datetime import datetime, timezone
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from pathlib import Path
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import psycopg
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from pymongo import MongoClient
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# --- konfigurace ------------------------------------------------------------
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MONGO_URI = "mongodb://192.168.1.76:27017"
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MONGO_DB = "soubory"
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MONGO_COLLECTIONS = ["42847922MDD3003", "77242113UCO3001"]
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PG_DSN = ("host=192.168.1.76 port=5432 dbname=MongoSoubory "
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"user=vladimir.buzalka password=Vlado7309208104++")
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EXTRACTOR_VERSION = "1.1"
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MAX_TEXT_BYTES = 5 * 1024 * 1024
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MAX_PDF_BYTES = 500 * 1024 * 1024
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MAX_XLSX_BYTES = 200 * 1024 * 1024
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MAX_GENERIC_BYTES = 300 * 1024 * 1024
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SUPPORTED = ("pdf", "docx", "xlsx", "xlsm", "pptx", "eml", "msg", "txt", "csv")
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# --- SCHEMA -----------------------------------------------------------------
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SCHEMA_SQL = """
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CREATE EXTENSION IF NOT EXISTS unaccent;
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CREATE EXTENSION IF NOT EXISTS pg_trgm;
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DO $$
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BEGIN
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IF NOT EXISTS (SELECT 1 FROM pg_ts_config WHERE cfgname = 'soubory') THEN
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CREATE TEXT SEARCH CONFIGURATION soubory ( COPY = simple );
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ALTER TEXT SEARCH CONFIGURATION soubory
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ALTER MAPPING FOR hword, hword_part, word
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WITH unaccent, simple;
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END IF;
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END$$;
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CREATE TABLE IF NOT EXISTS documents (
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id BIGSERIAL PRIMARY KEY,
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mongo_id TEXT NOT NULL,
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study TEXT NOT NULL,
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path TEXT NOT NULL,
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rel_path TEXT,
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name TEXT,
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ext TEXT,
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sha256 TEXT NOT NULL,
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size_bytes BIGINT,
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mtime TIMESTAMPTZ,
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body TEXT,
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body_length INT,
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tsv tsvector GENERATED ALWAYS AS (
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to_tsvector('soubory'::regconfig, coalesce(body, ''))
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) STORED,
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extracted_at TIMESTAMPTZ DEFAULT now(),
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extractor_version TEXT,
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ok BOOLEAN,
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error TEXT,
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UNIQUE (study, path)
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);
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CREATE INDEX IF NOT EXISTS documents_tsv_gin ON documents USING gin(tsv);
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CREATE INDEX IF NOT EXISTS documents_name_trgm ON documents USING gin(name gin_trgm_ops);
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CREATE INDEX IF NOT EXISTS documents_sha256_idx ON documents(sha256);
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CREATE INDEX IF NOT EXISTS documents_study_ext_idx ON documents(study, ext);
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"""
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# --- HELPERY ----------------------------------------------------------------
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# odstrani 0x00 a ostatni controly krome whitespace
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_CTRL_RX = re.compile(r"[\x00-\x08\x0b\x0c\x0e-\x1f]")
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def _clean_for_pg(s: str) -> str:
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if not s:
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return ""
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return _CTRL_RX.sub("", s)
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def _truncate(s: str) -> str:
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s = _clean_for_pg(s or "")
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if not s:
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return ""
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b = s.encode("utf-8", errors="replace")
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if len(b) <= MAX_TEXT_BYTES:
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return s
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return b[:MAX_TEXT_BYTES].decode("utf-8", errors="ignore")
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# --- EXTRAKTORY -------------------------------------------------------------
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def extract_pdf(path: Path) -> str:
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from pypdf import PdfReader
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reader = PdfReader(str(path))
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if reader.is_encrypted:
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try:
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reader.decrypt("")
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except Exception:
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return ""
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parts = []
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total = 0
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for page in reader.pages:
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try:
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t = page.extract_text() or ""
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except Exception:
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continue
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parts.append(t)
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total += len(t)
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if total > MAX_TEXT_BYTES:
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break
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return _truncate("\n".join(parts))
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# regex pro DOCX fallback - vytahne <w:t>...</w:t>
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_DOCX_WT_RX = re.compile(r"<w:t[^>]*>([^<]*)</w:t>", re.DOTALL)
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_DOCX_WP_END_RX = re.compile(r"</w:p>")
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def _docx_raw_text(path: Path) -> str:
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"""Fallback - cte primo word/document.xml ze ZIPu."""
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with zipfile.ZipFile(str(path)) as z:
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try:
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xml = z.read("word/document.xml").decode("utf-8", errors="replace")
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except KeyError:
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return ""
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xml = _DOCX_WP_END_RX.sub("\n", xml)
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return "\n".join(m.group(1) for m in _DOCX_WT_RX.finditer(xml))
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def extract_docx(path: Path) -> str:
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from docx import Document
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try:
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doc = Document(str(path))
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parts = [p.text for p in doc.paragraphs if p.text]
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for tbl in doc.tables:
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for row in tbl.rows:
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parts.append(" | ".join(c.text for c in row.cells))
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return _truncate("\n".join(parts))
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except Exception:
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# fallback - raw XML extract
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return _truncate(_docx_raw_text(path))
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def extract_xlsx(path: Path) -> str:
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from openpyxl import load_workbook
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wb = load_workbook(str(path), read_only=True, data_only=True)
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parts = []
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total = 0
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for ws in wb.worksheets:
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parts.append(f"# {ws.title}")
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for row in ws.iter_rows(values_only=True):
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line = "\t".join("" if v is None else str(v) for v in row)
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if line.strip():
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parts.append(line)
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total += len(line)
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if total > MAX_TEXT_BYTES:
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break
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if total > MAX_TEXT_BYTES:
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break
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wb.close()
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return _truncate("\n".join(parts))
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def extract_pptx(path: Path) -> str:
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from pptx import Presentation
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prs = Presentation(str(path))
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parts = []
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for i, slide in enumerate(prs.slides, 1):
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parts.append(f"# slide {i}")
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for shape in slide.shapes:
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if shape.has_text_frame:
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for para in shape.text_frame.paragraphs:
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line = "".join(run.text for run in para.runs)
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if line.strip():
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parts.append(line)
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if slide.has_notes_slide:
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notes = slide.notes_slide.notes_text_frame.text
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if notes:
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parts.append(f"[notes] {notes}")
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return _truncate("\n".join(parts))
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def extract_eml(path: Path) -> str:
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with path.open("rb") as f:
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msg = email.message_from_binary_file(f, policy=email.policy.default)
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head = []
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for k in ("From", "To", "Cc", "Subject", "Date"):
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v = msg.get(k)
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if v:
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head.append(f"{k}: {v}")
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parts = ["\n".join(head)]
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if msg.is_multipart():
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for part in msg.walk():
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if part.get_content_type() == "text/plain" and not part.get_filename():
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try:
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parts.append(part.get_content())
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except Exception:
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pass
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else:
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try:
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parts.append(msg.get_content())
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except Exception:
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pass
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return _truncate("\n\n".join(parts))
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def extract_msg(path: Path) -> str:
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import extract_msg
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with extract_msg.openMsg(str(path)) as m:
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head = []
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if m.subject: head.append(f"Subject: {m.subject}")
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if m.sender: head.append(f"From: {m.sender}")
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if m.to: head.append(f"To: {m.to}")
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if m.cc: head.append(f"Cc: {m.cc}")
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if m.date: head.append(f"Date: {m.date}")
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return _truncate("\n".join(head) + "\n\n" + (m.body or ""))
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def extract_text(path: Path) -> str:
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data = path.read_bytes()[:MAX_TEXT_BYTES]
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for enc in ("utf-8-sig", "cp1250", "latin-1"):
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try:
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return _truncate(data.decode(enc))
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except UnicodeDecodeError:
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continue
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return _truncate(data.decode("utf-8", errors="replace"))
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EXTRACTORS = {
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"pdf": (extract_pdf, MAX_PDF_BYTES),
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"docx": (extract_docx, MAX_GENERIC_BYTES),
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"xlsx": (extract_xlsx, MAX_XLSX_BYTES),
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"xlsm": (extract_xlsx, MAX_XLSX_BYTES),
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"pptx": (extract_pptx, MAX_GENERIC_BYTES),
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"eml": (extract_eml, MAX_GENERIC_BYTES),
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"msg": (extract_msg, MAX_GENERIC_BYTES),
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"txt": (extract_text, MAX_GENERIC_BYTES),
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"csv": (extract_text, MAX_GENERIC_BYTES),
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}
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def _short(s, n=40):
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if not s:
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return ""
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s = str(s).replace("\n", " ").replace("\r", " ").strip()
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return s if len(s) <= n else s[:n] + "..."
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def _now() -> datetime:
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return datetime.now(tz=timezone.utc)
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# --- HLAVNI SMYCKA ----------------------------------------------------------
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def process_collection(pg: psycopg.Connection, mongo_coll, study: str) -> dict:
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with pg.cursor() as cur:
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cur.execute(
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"SELECT path, sha256, extractor_version, ok FROM documents WHERE study = %s",
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(study,),
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)
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existing = {row[0]: (row[1], row[2], row[3]) for row in cur.fetchall()}
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cursor = mongo_coll.find(
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{"ext": {"$in": list(EXTRACTORS.keys())}, "deleted_at": {"$exists": False}},
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{"_id": 1, "path": 1, "rel_path": 1, "name": 1, "ext": 1,
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"sha256": 1, "size_bytes": 1, "mtime": 1},
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no_cursor_timeout=True,
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)
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processed = ok = errors = skipped = too_big = 0
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queue: list[dict] = []
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total_pending = mongo_coll.count_documents(
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{"ext": {"$in": list(EXTRACTORS.keys())}, "deleted_at": {"$exists": False}}
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)
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print(f"[{study}] kandidatu v Mongo: {total_pending}")
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n = 0
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try:
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for doc in cursor:
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n += 1
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prev = existing.get(doc["path"])
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if prev and prev[0] == doc.get("sha256") and prev[1] == EXTRACTOR_VERSION and prev[2]:
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skipped += 1
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continue
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ext = doc["ext"]
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extractor, max_bytes = EXTRACTORS[ext]
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path = Path(doc["path"])
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row = {
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"mongo_id": str(doc["_id"]),
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"study": study,
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"path": doc["path"],
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"rel_path": doc.get("rel_path"),
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"name": doc.get("name"),
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"ext": ext,
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"sha256": doc.get("sha256"),
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"size_bytes": doc.get("size_bytes"),
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"mtime": doc.get("mtime"),
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"body": None,
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"body_length": 0,
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"extracted_at": _now(),
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"extractor_version": EXTRACTOR_VERSION,
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"ok": False,
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"error": None,
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}
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status = "OK "
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detail = ""
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size_mb = (doc.get("size_bytes") or 0) / 1024 / 1024
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if not path.exists():
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row["error"] = "file_missing"
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status = "ERR"; detail = "file_missing"; errors += 1
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elif (doc.get("size_bytes") or 0) > max_bytes:
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row["error"] = f"too_big_>{max_bytes}"
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status = "BIG"; detail = f"too_big_>{max_bytes//1024//1024}MB"; too_big += 1
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else:
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try:
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body = extractor(path) or ""
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row["body"] = body if body else None
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row["body_length"] = len(body)
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row["ok"] = True
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ok += 1
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detail = f"{len(body)} znaku {_short(body, 60)!r}"
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except Exception as e:
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row["error"] = f"{type(e).__name__}: {e}"[:500]
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status = "ERR"; detail = row["error"][:80]; errors += 1
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queue.append(row)
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processed += 1
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print(f" [{n:>4}/{total_pending}] {status} {ext:<4} {size_mb:6.1f}MB "
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f"{path.name} | {detail}", flush=True)
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if len(queue) >= 50:
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_flush(pg, queue); queue.clear()
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finally:
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cursor.close()
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if queue:
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_flush(pg, queue)
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return {"study": study, "processed": processed, "ok": ok,
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"errors": errors, "skipped": skipped, "too_big": too_big}
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UPSERT_SQL = """
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INSERT INTO documents
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(mongo_id, study, path, rel_path, name, ext, sha256, size_bytes, mtime,
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body, body_length, extracted_at, extractor_version, ok, error)
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VALUES
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(%(mongo_id)s, %(study)s, %(path)s, %(rel_path)s, %(name)s, %(ext)s, %(sha256)s,
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%(size_bytes)s, %(mtime)s, %(body)s, %(body_length)s, %(extracted_at)s,
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%(extractor_version)s, %(ok)s, %(error)s)
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ON CONFLICT (study, path) DO UPDATE SET
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mongo_id = EXCLUDED.mongo_id,
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rel_path = EXCLUDED.rel_path,
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name = EXCLUDED.name,
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ext = EXCLUDED.ext,
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sha256 = EXCLUDED.sha256,
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size_bytes = EXCLUDED.size_bytes,
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mtime = EXCLUDED.mtime,
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body = EXCLUDED.body,
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body_length = EXCLUDED.body_length,
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extracted_at = EXCLUDED.extracted_at,
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extractor_version = EXCLUDED.extractor_version,
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ok = EXCLUDED.ok,
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error = EXCLUDED.error
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"""
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def _flush(pg: psycopg.Connection, rows: list[dict]) -> None:
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# posledni pojistka - jeste jednou strip NUL (kdyby se necim prokrouzil)
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for r in rows:
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if r.get("body"):
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r["body"] = _clean_for_pg(r["body"])
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if r.get("error"):
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r["error"] = _clean_for_pg(r["error"])
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with pg.cursor() as cur:
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cur.executemany(UPSERT_SQL, rows)
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pg.commit()
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def main() -> int:
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t0 = time.time()
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print("Pripojuji se k PostgreSQL...")
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pg = psycopg.connect(PG_DSN, connect_timeout=10)
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with pg.cursor() as cur:
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cur.execute(SCHEMA_SQL)
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pg.commit()
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print("Schema OK.")
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print("Pripojuji se k MongoDB...")
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mongo = MongoClient(MONGO_URI, serverSelectionTimeoutMS=5000)
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mongo.admin.command("ping")
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db = mongo[MONGO_DB]
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print("Mongo OK.")
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results = []
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for name in MONGO_COLLECTIONS:
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results.append(process_collection(pg, db[name], name))
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pg.close()
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print("\n=== SHRNUTI ===")
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for r in results:
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print(f" {r['study']}: processed={r['processed']} ok={r['ok']} "
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f"errors={r['errors']} skipped={r['skipped']} too_big={r['too_big']}")
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print(f"\nCelkem trvalo: {time.time() - t0:.1f} s")
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return 0
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if __name__ == "__main__":
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try:
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raise SystemExit(main())
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except KeyboardInterrupt:
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print("\nPreruseno uzivatelem")
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except Exception:
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traceback.print_exc()
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sys.exit(1)
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