college-infos/pronote_sync/pipeline/run.py

"""Composition root et orchestrateur du pipeline Pronote → CalDAV → XMPP."""

from __future__ import annotations

import logging
from collections.abc import Callable
from contextlib import AbstractContextManager, nullcontext
from datetime import datetime
from typing import Protocol, runtime_checkable

from pronote_sync.channels import get_channel
from pronote_sync.channels.protocol import Channel
from pronote_sync.config.settings import Settings
from pronote_sync.errors import PipelineCriticalError, PipelineError, PipelineWarning
from pronote_sync.models.blog import ExternalInfo
from pronote_sync.models.pronote import PronoteData
from pronote_sync.models.sync import CalDAVSyncResult, CalDAVSyncStatus
from pronote_sync.models.synthesis import SynthesisInput
from pronote_sync.models.xmpp import XmppMessage
from pronote_sync.pipeline.steps.caldav_sync import CalDAVSynchronizer, caldav_sync_step
from pronote_sync.pipeline.steps.compare import compare_step
from pronote_sync.pipeline.steps.fetch import fetch_step
from pronote_sync.pipeline.steps.fetch_blog import fetch_blog_step
from pronote_sync.pipeline.steps.normalize import normalize_step
from pronote_sync.pipeline.steps.send import send_step
from pronote_sync.pipeline.steps.synthesis import synthesis_step
from pronote_sync.sources.blog.rss import BlogRSSClient
from pronote_sync.sources.blog.state import BlogRSSState
from pronote_sync.sources.pronote.client import PronoteClient
from pronote_sync.sources.pronote.fallback import PronoteFetcher, PronoteFetcherProtocol
from pronote_sync.sources.theoretical import get_theoretical_provider
from pronote_sync.sync.diff import AgendaComparator
from pronote_sync.sync.synchronizer import synchronize
from pronote_sync.synthesis import get_synthesis_provider
from pronote_sync.synthesis.provider import SynthesisProvider
from pronote_sync.utils.redaction import redact_exception, redact_secrets

logger = logging.getLogger(__name__)


def _synchronize_caldav(data: PronoteData, settings: Settings) -> CalDAVSyncResult:
    """Adapte le synchroniseur CalDAV de production au protocole injecté.

    :param data: Données Pronote normalisées à synchroniser.
    :param settings: Configuration effective de l'exécution.
    :return: Résultat de la synchronisation CalDAV.
    :rtype: CalDAVSyncResult
    """
    return synchronize(data, settings)


@runtime_checkable
class _RunContextFetcher(PronoteFetcherProtocol, Protocol):
    """Protocole interne d'un fetcher capable d'isoler un cache par run."""

    def run_context(self) -> AbstractContextManager[None]:
        """Retourne le contexte de durée de vie d'une exécution.

        :return: Contexte éphémère associé à l'exécution.
        :rtype: AbstractContextManager[None]
        """
        ...


class PipelineRunner:
    """Orchestre les étapes fetch → normalize → blog → compare → CalDAV → IA → XMPP.

    Toutes les dépendances sont injectables. La méthode :meth:`from_settings`
    constitue la composition root de production et ne crée aucun singleton.
    """

    def __init__(
        self,
        *,
        settings: Settings,
        pronote_fetcher: PronoteFetcherProtocol,
        caldav_synchronizer: CalDAVSynchronizer = _synchronize_caldav,
        agenda_comparator: AgendaComparator | None = None,
        synthesis_provider: SynthesisProvider | None = None,
        channel: Channel | None = None,
        blog_client: BlogRSSClient | None = None,
        blog_state: BlogRSSState | None = None,
        dry_run: bool | None = None,
        now_provider: Callable[[], datetime] = datetime.now,
    ) -> None:
        """Initialise un pipeline entièrement injectable.

        :param settings: Configuration de base du pipeline.
        :param pronote_fetcher: Source Pronote à utiliser.
        :param caldav_synchronizer: Service CalDAV injecté.
        :param agenda_comparator: Comparateur théorique, absent si désactivé.
        :param synthesis_provider: Fournisseur IA optionnel.
        :param channel: Canal XMPP optionnel.
        :param blog_client: Client RSS optionnel.
        :param blog_state: État RSS associé au client optionnel.
        :param dry_run: Surcharge optionnelle du mode dry-run de la configuration.
        :param now_provider: Horloge injectée pour rendre l'exécution testable.
        """
        self._settings = settings
        self._pronote_fetcher = pronote_fetcher
        self._caldav_synchronizer = caldav_synchronizer
        self._agenda_comparator = agenda_comparator
        self._synthesis_provider = synthesis_provider
        self._channel = channel
        self._blog_client = blog_client
        self._blog_state = blog_state
        self._dry_run = settings.app.dry_run if dry_run is None else dry_run
        self._now_provider = now_provider
        self._errors: list[PipelineError] = []
        self._warnings: list[PipelineWarning] = []

    @classmethod
    def from_settings(cls, settings: Settings, *, dry_run: bool | None = None) -> PipelineRunner:
        """Construit les dépendances de production sans singleton global.

        :param settings: Configuration validée de l'application.
        :param dry_run: Surcharge optionnelle du mode dry-run.
        :return: Pipeline prêt à être exécuté.
        :rtype: PipelineRunner
        """
        effective_dry_run = settings.app.dry_run if dry_run is None else dry_run
        theoretical_provider = get_theoretical_provider(
            settings.app.theoretical_agenda_path,
            settings.app.school_holidays_path,
            settings.app.theoretical_week_anchor_date,
            settings.app.theoretical_week_anchor_type,
        )
        comparator = (
            AgendaComparator(theoretical_provider) if theoretical_provider is not None else None
        )
        blog_client = BlogRSSClient(settings.blog.rss_url) if settings.blog.enabled else None
        blog_state = BlogRSSState() if settings.blog.enabled else None
        return cls(
            settings=settings,
            pronote_fetcher=PronoteFetcher(settings, PronoteClient(settings.pronote)),
            agenda_comparator=comparator,
            synthesis_provider=get_synthesis_provider(settings.ai),
            channel=get_channel(settings.xmpp, dry_run=effective_dry_run),
            blog_client=blog_client,
            blog_state=blog_state,
            dry_run=effective_dry_run,
        )

    def _effective_settings(self) -> Settings:
        """Retourne la configuration dont le dry-run reflète l'exécution courante.

        :return: Copie de configuration à passer aux dépendances.
        :rtype: Settings
        """
        if self._settings.app.dry_run == self._dry_run:
            return self._settings
        return self._settings.model_copy(
            update={"app": self._settings.app.model_copy(update={"dry_run": self._dry_run})}
        )

    def _run_context(self) -> AbstractContextManager[None]:
        """Retourne le contexte isolant les éventuels caches de source.

        :return: Contexte de durée de vie du run, vide pour un fetcher générique.
        :rtype: AbstractContextManager[None]
        """
        if isinstance(self._pronote_fetcher, _RunContextFetcher):
            return self._pronote_fetcher.run_context()
        return nullcontext()

    def _warn(self, step: str, message: str) -> None:
        """Enregistre et journalise un avertissement expurgé.

        :param step: Étape ayant échoué.
        :param message: Message déjà expurgé.
        """
        warning = PipelineWarning(message, step=step)
        self._warnings.append(warning)
        logger.warning("Étape %s dégradée : %s", step, warning.message)

    def run(self) -> tuple[PronoteData | None, list[PipelineError]]:
        """Exécute le pipeline complet dans l'ordre contractuel.

        Une erreur de récupération critique interrompt l'exécution. Les erreurs
        des étapes facultatives sont converties en :class:`PipelineWarning` afin
        que les étapes suivantes, notamment XMPP, restent exécutées.

        :return: Données Pronote normalisées ou ``None``, puis erreurs et avertissements.
        :rtype: tuple[PronoteData | None, list[PipelineError]]
        """
        self._errors = []
        self._warnings = []
        now = self._now_provider()
        effective_settings = self._effective_settings()
        try:
            with self._run_context():
                fetched, fetch_warnings = fetch_step(self._pronote_fetcher, today=now.date())
                self._warnings.extend(fetch_warnings)
                data = normalize_step(fetched, generated_at=now)

                try:
                    blog_articles = fetch_blog_step(self._blog_client, self._blog_state)
                except Exception as exc:
                    self._warn("fetch_blog", redact_exception(exc))
                    blog_articles = []

                try:
                    agenda_diff = compare_step(self._agenda_comparator, data)
                except Exception as exc:
                    self._warn("compare", redact_exception(exc))
                    from pronote_sync.models.diff import AgendaDiff

                    agenda_diff = AgendaDiff(target_date=data.target_date)

                try:
                    sync_result = caldav_sync_step(
                        self._caldav_synchronizer, data, effective_settings
                    )
                    if sync_result.status is CalDAVSyncStatus.FAILED:
                        caldav_errors = redact_secrets(
                            "; ".join(sync_result.errors),
                            extra_secrets=(effective_settings.caldav.password,)
                            if effective_settings.caldav.password is not None
                            else (),
                        )
                        self._warn("caldav_sync", caldav_errors or "Échec CalDAV")
                except Exception as exc:
                    self._warn("caldav_sync", redact_exception(exc))

                try:
                    synthesis = synthesis_step(
                        self._synthesis_provider,
                        SynthesisInput(
                            agenda_diff=agenda_diff,
                            messages=data.messages,
                            school_events=data.school_events,
                            target_date=data.target_date,
                        ),
                    )
                except Exception as exc:
                    self._warn("synthesis", redact_exception(exc))
                    synthesis = None

                message = XmppMessage(
                    target_date=data.target_date,
                    synthesis=synthesis.text if synthesis is not None else None,
                    homeworks=tuple(data.homeworks),
                    changes=agenda_diff.changes,
                    messages=tuple(data.messages),
                    external_info=ExternalInfo(blog_articles=tuple(blog_articles))
                    if blog_articles
                    else None,
                )
                if self._channel is not None and not self._dry_run:
                    try:
                        if not send_step(self._channel, message):
                            self._warn("send", "Le canal XMPP a refusé l'envoi")
                    except Exception as exc:
                        self._warn("send", redact_exception(exc))
                return data, [*self._errors, *self._warnings]
        except PipelineCriticalError as exc:
            logger.error("Erreur critique du pipeline : %s", exc.message)
            self._errors.append(exc)
        except Exception as exc:
            error = PipelineCriticalError(
                f"Erreur inattendue du pipeline : {redact_exception(exc)}", step="pipeline"
            )
            logger.error("Erreur critique du pipeline : %s", error.message)
            self._errors.append(error)
        return None, [*self._errors, *self._warnings]

    def get_errors(self) -> list[PipelineError]:
        """Retourne les erreurs critiques de la dernière exécution.

        :return: Copie des erreurs critiques.
        :rtype: list[PipelineError]
        """
        return list(self._errors)

    def get_warnings(self) -> list[PipelineWarning]:
        """Retourne les avertissements de la dernière exécution.

        :return: Copie des avertissements non bloquants.
        :rtype: list[PipelineWarning]
        """
        return list(self._warnings)