#!/usr/bin/env python3
"""Build a strategic APLD dashboard from research artifacts."""
from __future__ import annotations
import csv
import html
import subprocess
import sys
from pathlib import Path
BASE = Path(__file__).resolve().parent
OUT = BASE / "strategic_apld_dashboard.html"
def read_csv(name: str) -> list[dict[str, str]]:
with (BASE / name).open(newline="", encoding="utf-8") as f:
return list(csv.DictReader(f))
def table(rows: list[dict[str, str]], cols: list[str]) -> str:
head = "".join(f"| {html.escape(c)} | " for c in cols)
body = "".join(
"" + "".join(f"| {html.escape(row.get(c, ''))} | " for c in cols) + "
"
for row in rows
)
return f""
def main() -> None:
subprocess.run([sys.executable, "score_apld_thesis.py"], cwd=BASE, check=True)
summary = read_csv("strategic_loop_summary.csv")
thesis = read_csv("apld_thesis_scores.csv")
financial = read_csv("apld_financial_conversion_rows.csv")
status = read_csv("apld_status_table.csv")
read = (BASE / "apld_research_read.md").read_text(encoding="utf-8")
page = f"""
Strategic APLD Forecast-vs-Actual Dashboard
Strategic APLD Forecast-vs-Actual Dashboard
Strategic Loop Summary
{table(summary, ["iteration","chose_20_words","did_20_words","score_1_10","score_reason_20_words","next_20_words"])}
Thesis Scores
{table(thesis, ["hypothesis_id","hypothesis","score_1_10","score_reason","status"])}
Capacity Status
{table(status, ["project","forecast","actual_or_status","status"])}
Financial Conversion Rows
{table(financial, ["period_reported","metric","normalized_value","unit","forecast_or_actual","caveat"])}
"""
OUT.write_text(page, encoding="utf-8")
print(f"wrote {OUT.name}")
if __name__ == "__main__":
main()