from __future__ import annotations import io import html import re import struct import tempfile import zipfile from dataclasses import dataclass from pathlib import Path from xml.etree import ElementTree as ET import numpy as np class KmlToTabError(RuntimeError): """Raised when a KML file cannot be converted to MapInfo TAB.""" @dataclass(frozen=True) class TabLayerSummary: name: str geometry_type: str feature_count: int @dataclass(frozen=True) class TabConversionResult: zip_bytes: bytes layers: list[TabLayerSummary] files: list[str] _WKB_GEOMETRY_TYPES = { 1: "Point", 2: "LineString", 3: "Polygon", 4: "MultiPoint", 5: "MultiLineString", 6: "MultiPolygon", 7: "GeometryCollection", } def convert_kml_to_tab_zip(kml_bytes: bytes, source_name: str) -> TabConversionResult: """Convert one KML file to native MapInfo TAB tables packed into a ZIP.""" if not kml_bytes: raise KmlToTabError("Le fichier KML est vide.") pyogrio = _import_pyogrio() base_name = _safe_stem(source_name) with tempfile.TemporaryDirectory(prefix="kml_to_tab_") as tmp_dir_name: tmp_dir = Path(tmp_dir_name) input_path = tmp_dir / f"{base_name}.kml" output_dir = tmp_dir / "tab_output" output_dir.mkdir() input_path.write_bytes(kml_bytes) try: metadata, _fids, geometry, field_data = pyogrio.raw.read( input_path, force_2d=True, ) except Exception as exc: # pragma: no cover - exact GDAL errors vary raise KmlToTabError(f"Lecture du KML impossible: {exc}") from exc if geometry is None or len(geometry) == 0: raise KmlToTabError("Aucune geometrie exploitable trouvee dans le KML.") fields, field_data = _append_kml_fields( metadata.get("fields"), field_data, kml_bytes, len(geometry), ) crs = metadata.get("crs") or "EPSG:4326" geometry_groups = _group_geometry_indexes(geometry) layers: list[TabLayerSummary] = [] for geometry_type, indexes in geometry_groups.items(): layer_name = _layer_name(base_name, geometry_type, len(geometry_groups)) output_path = output_dir / f"{layer_name}.tab" layer_geometry = geometry[indexes] layer_field_data = [column[indexes] for column in field_data] try: pyogrio.raw.write( output_path, layer_geometry, layer_field_data, fields, driver="MapInfo File", geometry_type=geometry_type, crs=crs, encoding=metadata.get("encoding") or "UTF-8", ) except Exception as exc: # pragma: no cover - exact GDAL errors vary raise KmlToTabError( f"Ecriture du TAB impossible pour la couche {layer_name}: {exc}" ) from exc layers.append( TabLayerSummary( name=layer_name, geometry_type=geometry_type, feature_count=len(indexes), ) ) files = sorted(path.name for path in output_dir.iterdir() if path.is_file()) return TabConversionResult( zip_bytes=_zip_directory(output_dir), layers=layers, files=files, ) def _import_pyogrio(): try: import pyogrio except ImportError as exc: # pragma: no cover - depends on environment raise KmlToTabError( "La conversion TAB requiert pyogrio/GDAL. " "Installe les dependances avec `pip install -r requirements.txt`." ) from exc return pyogrio def _safe_stem(filename: str) -> str: stem = Path(filename or "converted").stem stem = re.sub(r"[^A-Za-z0-9_-]+", "_", stem).strip("_") return (stem or "converted")[:60] def _layer_name(base_name: str, geometry_type: str, group_count: int) -> str: if group_count == 1: return base_name suffix = re.sub(r"(? dict[str, list[int]]: groups: dict[str, list[int]] = {} for index, wkb in enumerate(geometry): geometry_type = _wkb_geometry_type(wkb) groups.setdefault(geometry_type, []).append(index) unsupported = sorted( geometry_type for geometry_type in groups if geometry_type == "GeometryCollection" ) if unsupported: raise KmlToTabError( "Les GeometryCollection ne sont pas supportees pour l'export TAB." ) return groups def _append_kml_fields(fields, field_data, kml_bytes: bytes, feature_count: int): records = _extract_kml_records(kml_bytes) if len(records) != feature_count: return fields, field_data field_pairs = _output_field_pairs(records, fields) if not field_pairs: return fields, field_data extra_values = { output_name: _record_column(records, source_name) for source_name, output_name in field_pairs } return ( np.array( [*fields, *[output_name for _source, output_name in field_pairs]], dtype=object, ), [ *field_data, *[extra_values[output_name] for _source, output_name in field_pairs], ], ) def _extract_kml_records(kml_bytes: bytes) -> list[dict[str, object]]: try: root = ET.fromstring(kml_bytes) except ET.ParseError: return [] records: list[dict[str, object]] = [] for element in root.iter(): tag = _local_name(element) if tag != "Placemark" or not _placemark_has_geometry(element): continue description = _child_text(element, "description") record = _parse_structured_description(description) value = float("nan") if record else _parse_measurement_value(description) if not record and np.isfinite(value): record["value"] = value records.append(record) return records def _output_field_pairs( records: list[dict[str, object]], existing_fields, ) -> list[tuple[str, str]]: used = {str(field).lower() for field in existing_fields} pairs: list[tuple[str, str]] = [] for source_name in _record_field_names(records): output_name = source_name if output_name.lower() in used: output_name = _unique_field_name(f"description_{source_name}", used) else: used.add(output_name.lower()) pairs.append((source_name, output_name)) return pairs def _unique_field_name(name: str, used: set[str]) -> str: base = _safe_column_name(name)[:31] candidate = base suffix = 2 while candidate.lower() in used: suffix_text = f"_{suffix}" candidate = f"{base[: 31 - len(suffix_text)]}{suffix_text}" suffix += 1 used.add(candidate.lower()) return candidate def _record_field_names(records: list[dict[str, object]]) -> list[str]: names: list[str] = [] if any("value" in record for record in records): names.append("value") for record in records: for name in record: if name != "value" and name not in names: names.append(name) return names def _record_column(records: list[dict[str, object]], name: str): values = [record.get(name, "") for record in records] if name == "value": return np.array( [value if value != "" else float("nan") for value in values], dtype=float, ) return np.array([_stringify_field_value(value) for value in values], dtype=object) def _stringify_field_value(value: object) -> str: if value is None: return "" if isinstance(value, float) and not np.isfinite(value): return "" return str(value) def _placemark_has_geometry(placemark) -> bool: geometry_tags = { "Point", "LineString", "LinearRing", "Polygon", "MultiGeometry", "Model", "Track", "MultiTrack", } return any(_local_name(child) in geometry_tags for child in placemark.iter()) def _child_text(element, child_name: str) -> str: child = _first_child(element, child_name) if child is None: return "" return " ".join("".join(child.itertext()).split()) def _first_child(element, child_name: str): for child in element: if _local_name(child) == child_name: return child return None def _local_name(element) -> str: return str(element.tag).rsplit("}", maxsplit=1)[-1] def _parse_measurement_value(description: str) -> float: match = re.match( r"(?s)^.*?\s+(-?\d+(?:\.\d+)?(?:[eE][+-]?\d+)?)\s*$", description, ) if not match: return float("nan") return float(match.group(1)) def _parse_structured_description(description: str) -> dict[str, str]: text = html.unescape(description or "") text = re.sub(r"(?i)", "\n", text) text = re.sub(r"(?i)", "", text) text = re.sub(r"<[^>]+>", "", text) record: dict[str, str] = {} for line in text.splitlines(): if ":" not in line: continue key, value = line.split(":", maxsplit=1) column = _safe_column_name(key) value = value.strip() if not column or not value: continue record[column] = value return record def _safe_column_name(name: str) -> str: column = html.unescape(name or "").strip() column = re.sub(r"\s+", "_", column) column = re.sub(r"[^A-Za-z0-9_]+", "_", column).strip("_") if not column: return "" if column[0].isdigit(): column = f"field_{column}" return column[:31] def _wkb_geometry_type(wkb: bytes) -> str: if not wkb or len(wkb) < 5: raise KmlToTabError("Geometrie WKB invalide dans le KML.") endian = "<" if wkb[0] == 1 else ">" raw_code = struct.unpack(f"{endian}I", wkb[1:5])[0] base_code = raw_code & 0xFF geometry_type = _WKB_GEOMETRY_TYPES.get(base_code) if geometry_type is None: raise KmlToTabError(f"Type de geometrie non supporte: WKB {raw_code}.") return geometry_type def _zip_directory(directory: Path) -> bytes: zip_buffer = io.BytesIO() with zipfile.ZipFile(zip_buffer, mode="w", compression=zipfile.ZIP_DEFLATED) as zf: for path in sorted(directory.iterdir()): if path.is_file(): zf.write(path, arcname=path.name) return zip_buffer.getvalue()