"""Declarative management of the Hugging Face Jobs that run this recipe.

Scheduling lives on Hugging Face rather than in an external CI system: the data,
the recipe revision, and the compute that produces them stay in one place, and a
job is not bound by an external runner's disk or wall-clock limits.

The scheduled job executes a UV script published in this same dataset
repository, so the code that produced a revision is always recoverable from the
revision itself.
"""

from __future__ import annotations

from dataclasses import dataclass
from typing import Any

from .config import DEFAULT_HF_REPO

# The work is downloading the sibling datasets and four hundred settlement
# archives, then a few minutes of grouping. Memory is modest; bandwidth is not.
UPDATE_FLAVOR = "cpu-upgrade"
BACKFILL_FLAVOR = "cpu-upgrade"
UPDATE_TIMEOUT = "3h"
BACKFILL_TIMEOUT = "4h"
# Monday 08:10 UTC, an hour after the fundamentals rebuild: this dataset is
# derived entirely from that one, and reading last week's revision would
# publish corporate actions that lag their own source.
DEFAULT_SCHEDULE = "10 8 * * 1"
# One self-contained UV script serves both modes: a Job downloads a single file.
JOB_SCRIPT = "jobs/run.py"
UPDATE_JOB_NAME = "corporate-actions-update"
BACKFILL_JOB_NAME = "corporate-actions-rebuild"


def script_url(
    *, repo_id: str = DEFAULT_HF_REPO, script: str = JOB_SCRIPT, revision: str = "main"
) -> str:
    return f"https://huggingface.co/datasets/{repo_id}/resolve/{revision}/{script}"


@dataclass(frozen=True, slots=True)
class JobSpec:
    """Everything needed to launch or schedule one run, minus the credentials."""

    script: str
    script_url: str
    flavor: str
    timeout: str
    script_args: tuple[str, ...]
    env: dict[str, str]
    name: str

    def as_kwargs(self, *, secrets: dict[str, str]) -> dict[str, Any]:
        """Build the huggingface_hub call arguments.

        The Jobs API takes no ``name`` parameter; a job's display name is the
        ``name`` label. Credentials go through ``secrets`` so they are encrypted
        server side instead of travelling as plain environment variables.
        """

        return {
            "script": self.script_url,
            "script_args": list(self.script_args),
            "flavor": self.flavor,
            "timeout": self.timeout,
            "env": dict(self.env),
            "secrets": secrets,
            "labels": {"name": self.name, "project": "insider-trading"},
        }


def update_spec(
    *,
    repo_id: str = DEFAULT_HF_REPO,
    revision: str = "main",
    flavor: str = UPDATE_FLAVOR,
    timeout: str = UPDATE_TIMEOUT,
) -> JobSpec:
    return JobSpec(
        script=JOB_SCRIPT,
        script_url=script_url(repo_id=repo_id, revision=revision),
        flavor=flavor,
        timeout=timeout,
        script_args=("--mode", "update"),
        env={"HF_DATASET_REPO": repo_id},
        name=UPDATE_JOB_NAME,
    )


def backfill_spec(
    *,
    repo_id: str = DEFAULT_HF_REPO,
    revision: str = "main",
    start: str | None = None,
    end: str | None = None,
    flavor: str = BACKFILL_FLAVOR,
    timeout: str = BACKFILL_TIMEOUT,
) -> JobSpec:
    args = ["--mode", "build"]
    _ = (start, end)
    return JobSpec(
        script=JOB_SCRIPT,
        script_url=script_url(repo_id=repo_id, revision=revision),
        flavor=flavor,
        timeout=timeout,
        script_args=tuple(args),
        env={"HF_DATASET_REPO": repo_id},
        name=BACKFILL_JOB_NAME,
    )


def job_secrets(*, hf_token: str) -> dict[str, str]:
    """Credentials the Job needs, and only those.

    No SEC User-Agent here: this dataset fetches nothing from SEC. It is
    derived entirely from a sibling dataset on the Hub, so the only secret it
    can use is the token that reads and writes it.
    """
    if not hf_token:
        raise ValueError("an HF token is required to run or schedule a Job")
    return {"HF_TOKEN": hf_token}

def _api(token: str | None) -> Any:
    try:
        from huggingface_hub import HfApi
    except ImportError as error:  # pragma: no cover - exercised in the job environment
        raise RuntimeError("install the 'publish' extra to manage Hugging Face Jobs") from error
    return HfApi(token=token)


def _require(api: Any, method: str) -> Any:
    """Fail with an actionable message when the installed hub predates a Jobs API."""

    function = getattr(api, method, None)
    if function is None:
        raise RuntimeError(
            f"the installed huggingface_hub has no {method}(); "
            "upgrade with: pip install -U 'huggingface-hub>=1.19'"
        )
    return function


def create_schedule(
    spec: JobSpec,
    *,
    schedule: str = DEFAULT_SCHEDULE,
    secrets: dict[str, str],
    namespace: str | None = None,
    token: str | None = None,
) -> Any:
    api = _api(token)
    return _require(api, "create_scheduled_uv_job")(
        schedule=schedule,
        namespace=namespace,
        **spec.as_kwargs(secrets=secrets),
    )


def run_once(
    spec: JobSpec,
    *,
    secrets: dict[str, str],
    namespace: str | None = None,
    token: str | None = None,
) -> Any:
    api = _api(token)
    return _require(api, "run_uv_job")(namespace=namespace, **spec.as_kwargs(secrets=secrets))


def list_schedules(*, namespace: str | None = None, token: str | None = None) -> list[Any]:
    api = _api(token)
    return list(_require(api, "list_scheduled_jobs")(namespace=namespace))


def inspect_schedule(
    scheduled_job_id: str, *, namespace: str | None = None, token: str | None = None
) -> Any:
    api = _api(token)
    return _require(api, "inspect_scheduled_job")(
        scheduled_job_id=scheduled_job_id, namespace=namespace
    )


def delete_schedule(
    scheduled_job_id: str, *, namespace: str | None = None, token: str | None = None
) -> None:
    api = _api(token)
    _require(api, "delete_scheduled_job")(scheduled_job_id=scheduled_job_id, namespace=namespace)


def suspend_schedule(
    scheduled_job_id: str, *, namespace: str | None = None, token: str | None = None
) -> Any:
    api = _api(token)
    return _require(api, "suspend_scheduled_job")(
        scheduled_job_id=scheduled_job_id, namespace=namespace
    )


def resume_schedule(
    scheduled_job_id: str, *, namespace: str | None = None, token: str | None = None
) -> Any:
    api = _api(token)
    return _require(api, "resume_scheduled_job")(
        scheduled_job_id=scheduled_job_id, namespace=namespace
    )


__all__ = [
    "BACKFILL_FLAVOR",
    "BACKFILL_TIMEOUT",
    "DEFAULT_SCHEDULE",
    "JOB_SCRIPT",
    "UPDATE_FLAVOR",
    "UPDATE_TIMEOUT",
    "JobSpec",
    "backfill_spec",
    "create_schedule",
    "delete_schedule",
    "inspect_schedule",
    "job_secrets",
    "list_schedules",
    "resume_schedule",
    "run_once",
    "script_url",
    "suspend_schedule",
    "update_spec",
]