big refactor

core/pdf_exporter/depth_rasterizer.py

@@ -1,37 +0,0 @@
-"""
-SA2 Performance Profiling & Vector Edge Debug Export Module.
-Saves input vector edge debug data and cProfile statistics when debug_sa2 is enabled.
-"""
-from typing import Any
-import numpy as np
-from numpy.typing import NDArray
-
-
-def save_sa2_debug_data(
-    edges: NDArray[np.float64] | None,
-    obj_name: str,
-    filepath: str | Any
-) -> None:
-    """
-    Saves debug edge vector data files in the same folder as the output PDF:
-    - {name}_sa2_debug_edges.txt (Input 2D edge vector coordinates fed to SA2)
-    """
-    if filepath is None:
-        return
-    from pathlib import Path
-    pdf_path = Path(filepath)
-    out_dir = pdf_path.parent
-    out_dir.mkdir(parents=True, exist_ok=True)
-
-    clean_name = pdf_path.stem if pdf_path.suffix.lower() == ".pdf" else str(obj_name)
-    base_prefix = out_dir / f"{clean_name}_sa2_debug"
-
-    # Save input edge coordinates as text file
-    if edges is not None and len(edges) > 0:
-        txt_file = f"{base_prefix}_edges.txt"
-        with open(txt_file, "w") as f:
-            f.write(f"# SA2 Input 2D Edges Debug for {clean_name}\n")
-            f.write(f"# Format: x1 y1 x2 y2\n")
-            for segment in edges:
-                (x1, y1), (x2, y2) = segment[0], segment[1]
-                f.write(f"{x1:.4f} {y1:.4f} {x2:.4f} {y2:.4f}\n")

infra/csv_handling.py

@@ -1,24 +0,0 @@
-from functools import lru_cache
-
-import csv
-import os
-
-@lru_cache(maxsize=128)
-def _load_csv(filename: str, mtime: float, encoding: str | None = None) -> tuple[tuple[str, ...], ...]:
-    with open(filename, 'r', newline='', encoding=encoding) as f:
-        reader = csv.reader(f)
-        return tuple(tuple(row) for row in reader)
-
-def parse_csv_to_tuples(filename: str) -> list[tuple[str, ...]]:
-    current_mtime = os.path.getmtime(filename)
-    data: tuple[tuple[str, ...], ...] = _load_csv(filename, current_mtime)
-    return sorted(data, key=lambda x: x[1])
-
-def parse_csv_to_dict(filename: str) -> dict[str, list[str]]:
-    current_mtime = os.path.getmtime(filename)
-    data: tuple[tuple[str, ...], ...] = _load_csv(filename, current_mtime, encoding='utf-8-sig')
-    result = {}
-    for row in data:
-        if row:
-            result[row[0]] = list(row[1:])
-    return result

infra/json_handling.py

@@ -1,13 +0,0 @@
-import os, json
-
-def dict_from_json(path):
-    with open(path, 'r') as file:
-        return json.load(file)
-
-def dump_dict_to_json(dictionary, path):
-    folder = os.path.dirname(path)
-    if folder and not os.path.exists(folder):
-        os.makedirs(folder, exist_ok=True)
-    
-    with open(path, 'w') as file:
-        json.dump(dictionary, file, indent=2)