from datetime import datetime, timedelta
from typing import Dict, List, Optional
from collections import defaultdict
from models.schema import Repo, RepoStatus, MetricPoint
import asyncio
import time


class InMemoryStorage:
    def __init__(self):
        self.repos: Dict[str, Repo] = {}
        self.statuses: Dict[str, RepoStatus] = {}
        self.raw_metrics: Dict[str, List[MetricPoint]] = defaultdict(list)
        self.aggregated: Dict[str, Dict[str, List[dict]]] = defaultdict(
            lambda: defaultdict(list)
        )
        self._lock = asyncio.Lock()
        self._last_aggregate_time: Dict[str, datetime] = {}

        self._aggregation_intervals = {
            "hour": {"seconds": 30, "raw_ttl": 3600},
            "day": {"seconds": 600, "raw_ttl": 86400},
            "week": {"seconds": 7200, "raw_ttl": 604800},
            "month": {"seconds": 7200, "raw_ttl": 2592000},
        }

    def add_repo(self, repo: Repo):
        self.repos[repo.id] = repo
        self.statuses[repo.id] = RepoStatus(
            state="DISCONNECTED", stage="Unknown", last_updated=datetime.now()
        )
        self.raw_metrics[repo.id] = []
        for range_name in self._aggregation_intervals:
            self.aggregated[repo.id][range_name] = []

    def remove_repo(self, repo_id: str):
        if repo_id in self.repos:
            del self.repos[repo_id]
        if repo_id in self.statuses:
            del self.statuses[repo_id]
        if repo_id in self.raw_metrics:
            del self.raw_metrics[repo_id]
        if repo_id in self.aggregated:
            del self.aggregated[repo_id]
        if repo_id in self._last_aggregate_time:
            del self._last_aggregate_time[repo_id]

    def list_repos(self) -> List[Repo]:
        return list(self.repos.values())

    def get_status(self, repo_id: str) -> Optional[RepoStatus]:
        return self.statuses.get(repo_id)

    def update_status(self, repo_id: str, state: str, stage: str):
        if repo_id in self.statuses:
            self.statuses[repo_id].state = state
            self.statuses[repo_id].stage = stage
            self.statuses[repo_id].last_updated = datetime.now()

    def add_metric(self, repo_id: str, data: dict):
        if repo_id not in self.repos:
            return
        try:
            cpu_usage = data.get("cpu_usage_pct", 0)
            memory_used = data.get("memory_used_bytes", 0)
            memory_total = data.get("memory_total_bytes", 1)
            memory_pct = (memory_used / memory_total * 100) if memory_total > 0 else 0

            point = MetricPoint(
                timestamp=datetime.now(),
                cpu_usage_pct=cpu_usage,
                memory_used_bytes=memory_used,
                memory_total_bytes=memory_total,
            )
            self.raw_metrics[repo_id].append(point)

            if len(self.raw_metrics[repo_id]) > 3600:
                self.raw_metrics[repo_id] = self.raw_metrics[repo_id][-3600:]
        except Exception:
            pass

    def aggregate(self, repo_id: str):
        if repo_id not in self.repos or repo_id not in self.raw_metrics:
            return

        now = datetime.now()
        raw = self.raw_metrics.get(repo_id, [])
        if not raw:
            return

        last_agg = self._last_aggregate_time.get(repo_id)
        if last_agg and (now - last_agg).total_seconds() < 30:
            return

        self._last_aggregate_time[repo_id] = now

        cpu_values = [m.cpu_usage_pct for m in raw]
        mem_values = [(m.memory_used_bytes / m.memory_total_bytes * 100) for m in raw]

        for range_name, config in self._aggregation_intervals.items():
            interval_seconds = config["seconds"]
            target_time = now.replace(
                second=(now.second // 30) * 30, microsecond=0
            )

            if range_name == "hour":
                pass_interval = 30
            elif range_name == "day":
                pass_interval = 600
            else:
                pass_interval = 7200

            existing = self.aggregated[repo_id][range_name]
            if existing and existing[-1]["timestamp"] == target_time.isoformat():
                continue

            agg_data = {
                "timestamp": target_time.isoformat(),
                "cpu_avg": sum(cpu_values) / len(cpu_values) if cpu_values else 0,
                "cpu_max": max(cpu_values) if cpu_values else 0,
                "cpu_min": min(cpu_values) if cpu_values else 0,
                "mem_avg": sum(mem_values) / len(mem_values) if mem_values else 0,
                "mem_max": max(mem_values) if mem_values else 0,
                "mem_min": min(mem_values) if mem_values else 0,
            }
            self.aggregated[repo_id][range_name].append(agg_data)

            if len(self.aggregated[repo_id][range_name]) > 2000:
                self.aggregated[repo_id][range_name] = self.aggregated[repo_id][range_name][-2000:]

        cutoff = now - timedelta(seconds=3600)
        self.raw_metrics[repo_id] = [m for m in raw if m.timestamp > cutoff]

    def get_metrics(
        self, repo_id: str, range_name: str = "hour"
    ) -> Optional[dict]:
        if repo_id not in self.aggregated:
            return None
        data = self.aggregated[repo_id].get(range_name, [])
        return {
            "timestamps": [m["timestamp"] for m in data],
            "cpu": {
                "avg": [m["cpu_avg"] for m in data],
                "max": [m["cpu_max"] for m in data],
                "min": [m["cpu_min"] for m in data],
            },
            "memory": {
                "avg": [m["mem_avg"] for m in data],
                "max": [m["mem_max"] for m in data],
                "min": [m["mem_min"] for m in data],
            },
        }


storage = InMemoryStorage()