171 lines
5 KiB
Python
171 lines
5 KiB
Python
import os
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import time
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import logging
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import re
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import psycopg2
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import psycopg2.extras
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import spacy
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from bs4 import BeautifulSoup
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logging.basicConfig(level=logging.INFO, format='[%(asctime)s] %(levelname)s: %(message)s')
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DB = dict(
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host=os.environ.get("DB_HOST", "localhost"),
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port=int(os.environ.get("DB_PORT", 5432)),
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dbname=os.environ.get("DB_NAME", "rss"),
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user=os.environ.get("DB_USER", "rss"),
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password=os.environ.get("DB_PASS", "x"),
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)
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NER_LANG = os.environ.get("NER_LANG", "es").strip().lower()
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BATCH = int(os.environ.get("NER_BATCH", 64))
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ENT_LABELS = {
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"PERSON": "persona",
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"ORG": "organizacion",
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"GPE": "lugar",
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"LOC": "lugar",
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}
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_ws_re = re.compile(r"\s+")
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HTML_TRASH_PATTERNS = [
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r"<[^>]+>",
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r"&[a-z]+;",
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r'width="\d+"',
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r'height="\d+"',
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]
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GENERIC_BAD_TAGS = {
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"república",
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"estado",
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"centro",
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"gobierno",
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"report",
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"sp",
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"unión",
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}
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def clean_tag_text(text):
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if not text:
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return None
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text = BeautifulSoup(text, "html.parser").get_text()
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for pat in HTML_TRASH_PATTERNS:
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text = re.sub(pat, "", text)
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text = _ws_re.sub(" ", text).strip()
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if len(text) < 3:
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return None
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if re.search(r"[<>/\\]", text):
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return None
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lower = text.lower()
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if lower.startswith("href="):
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return None
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if lower.startswith("http"):
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return None
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if lower in GENERIC_BAD_TAGS:
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return None
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replacements = {
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"ee.uu.": "Estados Unidos",
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"los estados unidos": "Estados Unidos",
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"eu": "Unión Europea",
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"ue": "Unión Europea",
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"kosova": "Kosovo",
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}
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if lower in replacements:
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text = replacements[lower]
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return text
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def get_conn():
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return psycopg2.connect(**DB)
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def main():
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nlp = spacy.load("es_core_news_md", disable=["parser", "lemmatizer", "textcat"])
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logging.info("spaCy cargado: es_core_news_md")
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while True:
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try:
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with get_conn() as conn, conn.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur:
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cur.execute(
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"""
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WITH pend AS (
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SELECT t.id, t.titulo_trad, t.resumen_trad
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FROM traducciones t
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LEFT JOIN tags_noticia tn ON tn.traduccion_id = t.id
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WHERE t.status = 'done'
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AND t.lang_to = %s
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GROUP BY t.id, t.titulo_trad, t.resumen_trad
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HAVING COUNT(tn.tag_id) = 0
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ORDER BY t.id DESC
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LIMIT %s
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)
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SELECT * FROM pend;
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""",
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(NER_LANG, BATCH),
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)
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rows = cur.fetchall()
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if not rows:
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time.sleep(5)
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continue
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logging.info(f"Procesando {len(rows)} traducciones para NER...")
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new_links = 0
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for r in rows:
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text = f"{r['titulo_trad'] or ''}\n{r['resumen_trad'] or ''}".strip()
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if not text:
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continue
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doc = nlp(text)
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ents = []
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for ent in doc.ents:
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tipo = ENT_LABELS.get(ent.label_)
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if not tipo:
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continue
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val = clean_tag_text(ent.text)
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if not val:
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continue
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ents.append((val, tipo))
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if not ents:
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continue
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for valor, tipo in set(ents):
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try:
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cur.execute(
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"""
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INSERT INTO tags (valor, tipo)
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VALUES (%s, %s)
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ON CONFLICT (valor, tipo)
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DO UPDATE SET valor = EXCLUDED.valor
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RETURNING id
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""",
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(valor, tipo),
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)
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tag_id = cur.fetchone()[0]
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cur.execute(
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"""
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INSERT INTO tags_noticia (traduccion_id, tag_id)
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VALUES (%s, %s)
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ON CONFLICT DO NOTHING
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""",
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(r["id"], tag_id),
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)
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if cur.rowcount > 0:
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new_links += 1
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except Exception:
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logging.exception("Fallo insertando tag/relación")
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conn.commit()
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logging.info(f"NER lote OK. Nuevos enlaces: {new_links}.")
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except Exception as e:
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logging.exception(f"Error en NER loop: {e}")
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time.sleep(5)
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if __name__ == "__main__":
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main()
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