"""Parse an Elmhurst *recommendation* Summary PDF into an EpcPropertyData.

The Modelling cascade pins use Elmhurst's own before/after measure
re-lodgements as deterministic test vectors: each measure folder under
`sap worksheets/Recommendations Elmhurst Files/` holds a `before` Summary
(the baseline cert) and an `after` Summary (the same cert re-lodged with the
measure applied). Applying the matching Recommendation Generator's overlay to
the parsed `before` must reproduce the calculator's score on the parsed
`after` at delta 0 — proving the overlay is the exact field change Elmhurst
made.

This routes the Summary PDF through the same extractor + mapper chain the
worksheet e2e fixtures use (`_elmhurst_worksheet_001431.build_epc`), NOT the
Textract `parse_site_notes_pdf` path — that path has an unrelated window
extraction bug on cert 001431. The before/after Summaries are mirrored into
`tests/domain/modelling/fixtures/` so the pins do not depend on the unstaged
workspace.
"""

from __future__ import annotations

import re
import subprocess
from pathlib import Path
from typing import Final

from backend.documents_parser.elmhurst_extractor import ElmhurstSiteNotesExtractor
from datatypes.epc.domain.epc_property_data import EpcPropertyData
from datatypes.epc.domain.mapper import EpcPropertyDataMapper

_FIXTURES_DIR: Final[Path] = Path(__file__).resolve().parent / "fixtures"


def _summary_pdf_to_textract_style_pages(pdf_path: Path) -> list[str]:
    """Convert a Summary PDF into the per-page text format the
    `ElmhurstSiteNotesExtractor` expects (label\\nvalue sequences).

    Mirror of the helper in `_elmhurst_worksheet_001431.py`: `pdftotext
    -layout` preserves the spatial label/value pairing on each line; we split
    on 2+ spaces to surface the tokens, then rejoin newline-delimited.
    """
    info: str = subprocess.run(
        ["pdfinfo", str(pdf_path)], capture_output=True, text=True, check=True,
    ).stdout
    match = re.search(r"Pages:\s+(\d+)", info)
    if match is None:
        raise RuntimeError(f"Could not parse page count from {pdf_path}")
    page_count = int(match.group(1))

    pages: list[str] = []
    for i in range(1, page_count + 1):
        layout: str = subprocess.run(
            [
                "pdftotext", "-layout", "-f", str(i), "-l", str(i),
                str(pdf_path), "-",
            ],
            capture_output=True, text=True, check=True,
        ).stdout
        tokens: list[str] = []
        for line in layout.splitlines():
            if not line.strip():
                tokens.append("")
                continue
            parts = [p for p in re.split(r"\s{2,}", line.strip()) if p]
            tokens.extend(parts)
        pages.append("\n".join(tokens))
    return pages


def parse_recommendation_summary(fixture_name: str) -> EpcPropertyData:
    """Parse a before/after recommendation Summary fixture (by file name in
    `tests/domain/modelling/fixtures/`) into an EpcPropertyData."""
    pdf_path: Path = _FIXTURES_DIR / fixture_name
    pages: list[str] = _summary_pdf_to_textract_style_pages(pdf_path)
    site_notes = ElmhurstSiteNotesExtractor(pages).extract()
    return EpcPropertyDataMapper.from_elmhurst_site_notes(site_notes)