feat: Add poblacion_apta service to docker-compose, enhance API gateway for new service integration, and update README with service details. Introduce new database tables for poblacion_apta_jobs and poblacion_apta_rows, and implement functionality for handling cop/mod calculations in the cleaning service.

services/poblacion_apta/domain/csv_io.py

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+"""Carga robusta de CSV desde bytes (uploads)."""
+from __future__ import annotations
+
+import csv as _csv
+import os
+import tempfile
+from collections import Counter
+from typing import Optional
+
+import pandas as pd
+
+_CANDIDATE_DELIMITERS = ["|", ";", "\t", ",", ":"]
+
+
+def _detect_delimiter_from_sample(sample: str) -> str:
+  if not sample:
+    return ","
+  try:
+    dialect = _csv.Sniffer().sniff(sample, delimiters="".join(_CANDIDATE_DELIMITERS))
+    sniffed = dialect.delimiter
+  except _csv.Error:
+    sniffed = None
+
+  lines = [ln for ln in sample.splitlines() if ln.strip()]
+  if not lines:
+    return sniffed or ","
+
+  scores: dict[str, tuple[int, int]] = {}
+  for delim in _CANDIDATE_DELIMITERS:
+    counts = [ln.count(delim) for ln in lines[:50]]
+    if not counts or max(counts) == 0:
+      continue
+    mode_count, mode_freq = Counter(counts).most_common(1)[0]
+    if mode_count == 0:
+      continue
+    scores[delim] = (mode_count, mode_freq)
+
+  if scores:
+    best = max(scores.items(), key=lambda kv: (kv[1][0], kv[1][1]))
+    if sniffed and sniffed in scores:
+      sniffed_score = scores[sniffed]
+      if sniffed_score[0] >= best[1][0] - 1:
+        return sniffed
+    return best[0]
+  return sniffed or ","
+
+
+def load_csv_bytes(content: bytes, filename: str = "upload.csv") -> tuple[pd.DataFrame, str]:
+  """Carga un CSV desde bytes. Devuelve `(df, delimiter)`."""
+  if not content:
+    raise RuntimeError(f"El archivo {filename} está vacío")
+
+  sample = ""
+  for enc in ("utf-8-sig", "utf-8", "latin-1", "cp1252"):
+    try:
+      sample = content[:65536].decode(enc, errors="replace")
+      break
+    except Exception:
+      continue
+  delimiter = _detect_delimiter_from_sample(sample)
+
+  suffix = os.path.splitext(filename)[1] or ".csv"
+  with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
+    tmp.write(content)
+    tmp_path = tmp.name
+
+  last_error: Optional[Exception] = None
+  try:
+    for enc in ("utf-8-sig", "utf-8", "latin-1", "cp1252"):
+      try:
+        df = pd.read_csv(
+          tmp_path,
+          delimiter=delimiter,
+          dtype=str,
+          encoding=enc,
+          engine="python",
+          on_bad_lines="skip",
+          keep_default_na=False,
+        )
+        df.columns = [str(c).strip() for c in df.columns]
+        return df, delimiter
+      except Exception as exc:  # noqa: BLE001
+        last_error = exc
+    raise RuntimeError(f"No se pudo leer el CSV {filename}: {last_error}")
+  finally:
+    try:
+      os.unlink(tmp_path)
+    except OSError:
+      pass