| #!/usr/bin/env bash |
| set -euo pipefail |
|
|
| cd "$(dirname "$0")" |
| PYTHON_BIN="${PYTHON_BIN:-python3}" |
| "$PYTHON_BIN" - <<'__SKILL_EVOL_SOLVE_PY_0__' |
| from __future__ import annotations |
|
|
| import os |
| from pathlib import Path |
| from textwrap import dedent |
|
|
| PROJECT_ROOT = Path(os.environ.get("PROJECT_ROOT", "/root/task")).resolve() |
|
|
| FILES = { |
| "schema_casefold.py": dedent( |
| """ |
| from __future__ import annotations |
| |
| |
| def resolve_metric_column(columns, desired: str = "amount") -> str: |
| normalized = {str(column).strip().lower(): column for column in columns} |
| actual = normalized.get(desired.lower()) |
| if actual is None: |
| raise KeyError(f"missing metric column: {desired}") |
| return actual |
| """ |
| ), |
| "process_amounts.py": dedent( |
| """ |
| from __future__ import annotations |
| |
| import json |
| import os |
| from pathlib import Path |
| |
| import pandas as pd |
| |
| from schema_casefold import resolve_metric_column |
| |
| DEFAULT_SOURCE = Path("sales_data.csv") |
| OUTPUT_PATH = Path("output.json") |
| |
| |
| def run(source: Path | None = None, output_path: Path = OUTPUT_PATH) -> dict: |
| csv_path = Path(os.environ.get("SALES_SOURCE", source or DEFAULT_SOURCE)) |
| df = pd.read_csv(csv_path) |
| metric_column = resolve_metric_column(df.columns, "amount") |
| total = round(float(pd.to_numeric(df[metric_column], errors="raise").sum()), 2) |
| payload = { |
| "metric_column": str(metric_column).strip().lower(), |
| "total_amount": total, |
| "row_count": int(len(df)), |
| } |
| output_path.write_text(json.dumps(payload, indent=2), encoding="utf-8") |
| return payload |
| |
| |
| if __name__ == "__main__": |
| run() |
| """ |
| ), |
| } |
|
|
| for relative_path, content in FILES.items(): |
| target = PROJECT_ROOT / relative_path |
| target.write_text(content, encoding="utf-8") |
| print(f"wrote {target}") |
| __SKILL_EVOL_SOLVE_PY_0__ |
|
|
