"""Shared configuration + client plumbing for the local e2e runner scripts
(``run_modelling_e2e`` and ``run_first_run_e2e``).

Loads ``backend/.env`` and builds the DB engine from the FastAPI-layer ``DB_*``
vars (the ``infrastructure/postgres`` layer reads ``POSTGRES_*``, which the .env
does not carry), plus an S3-backed ``ParquetReader`` for the geospatial
repository. Secrets live in the .env and the ambient ``~/.aws`` profile; this
module never hard-codes them.
"""

from __future__ import annotations

import io
import os
from pathlib import Path
from typing import Any, cast

import boto3
import pandas as pd
from sqlalchemy import Engine, create_engine

from repositories.geospatial.geospatial_s3_repository import ParquetReader

_REPO_ROOT = Path(__file__).resolve().parents[1]
ENV_PATH = _REPO_ROOT / "backend" / ".env"


def load_env(path: Path = ENV_PATH) -> None:
    """Load `KEY=value` lines from `backend/.env` into the environment (without
    overriding anything already set), so the DB creds + API tokens are present."""
    if not path.exists():
        return
    for raw in path.read_text(encoding="utf-8").splitlines():
        line = raw.strip()
        if not line or line.startswith("#") or "=" not in line:
            continue
        key, value = line.split("=", 1)
        os.environ.setdefault(key.strip(), value.strip().strip('"').strip("'"))


def db_url() -> str:
    """The connection string from the FastAPI-layer `DB_*` env vars."""
    env = os.environ
    return (
        f"postgresql+psycopg2://{env['DB_USERNAME']}:{env['DB_PASSWORD']}"
        f"@{env['DB_HOST']}:{env['DB_PORT']}/{env['DB_NAME']}"
    )


def build_engine() -> Engine:
    """A connection-pooled engine to the target DB (DB_* creds)."""
    return create_engine(
        db_url(), pool_pre_ping=True, connect_args={"connect_timeout": 10}
    )


def s3_parquet_reader(bucket: str) -> ParquetReader:
    """A `ParquetReader` (key -> DataFrame) backed by `bucket` in S3, for the
    `GeospatialS3Repository`. AWS creds come from the ambient `~/.aws` profile;
    pyarrow reads the parquet bytes (s3fs is not installed here)."""
    # boto3 ships only partial type stubs, so the client is an untyped boundary.
    client = cast(Any, boto3.client("s3"))  # pyright: ignore[reportUnknownMemberType]

    def read(key: str) -> pd.DataFrame:
        body = cast(bytes, client.get_object(Bucket=bucket, Key=key)["Body"].read())
        return pd.read_parquet(io.BytesIO(body))

    return read