"""
StatsCollector - ring buffer of per-flow traffic statistics.

Stores the last 300 samples (5 minutes at 1-second intervals) per flow,
with derived rates and loss calculations.
"""

import threading
import time
from collections import defaultdict, deque


class StatsCollector:
    """Collects and stores per-flow traffic statistics in a ring buffer."""

    def __init__(self, max_samples: int = 300):
        self._lock = threading.Lock()
        self._max_samples = max_samples
        # flow_id -> deque of sample dicts
        self._history = defaultdict(lambda: deque(maxlen=self._max_samples))
        # flow_id -> previous counters for rate calculation
        self._prev = {}

    def record(self, flow_id: str, tx_packets: int, tx_bytes: int,
               rx_packets: int = 0, rx_bytes: int = 0,
               latency: dict = None):
        """Record a stats sample for a flow.

        Args:
            flow_id: Flow identifier.
            tx_packets: Cumulative transmitted packets.
            tx_bytes: Cumulative transmitted bytes.
            rx_packets: Cumulative received packets.
            rx_bytes: Cumulative received bytes.
            latency: Optional dict with min_ms, avg_ms, max_ms, jitter_ms.
        """
        now = time.time()

        with self._lock:
            prev = self._prev.get(flow_id)

            if prev is not None:
                dt = now - prev['time']
                if dt > 0:
                    d_tx_pkts = tx_packets - prev['tx_packets']
                    d_tx_bytes = tx_bytes - prev['tx_bytes']
                    d_rx_pkts = rx_packets - prev['rx_packets']
                    d_rx_bytes = rx_bytes - prev['rx_bytes']

                    tx_pps = d_tx_pkts / dt
                    rx_pps = d_rx_pkts / dt
                    tx_mbps = (d_tx_bytes * 8) / (dt * 1_000_000)
                    rx_mbps = (d_rx_bytes * 8) / (dt * 1_000_000)
                else:
                    tx_pps = rx_pps = tx_mbps = rx_mbps = 0.0
            else:
                tx_pps = rx_pps = tx_mbps = rx_mbps = 0.0

            # Loss calculation
            loss_pct = 0.0
            if tx_packets > 0 and rx_packets > 0:
                loss_pct = max(0.0, ((tx_packets - rx_packets) / tx_packets) * 100)

            sample = {
                'timestamp': now,
                'tx_packets': tx_packets,
                'tx_bytes': tx_bytes,
                'rx_packets': rx_packets,
                'rx_bytes': rx_bytes,
                'tx_pps': round(tx_pps, 2),
                'rx_pps': round(rx_pps, 2),
                'tx_mbps': round(tx_mbps, 4),
                'rx_mbps': round(rx_mbps, 4),
                'loss_pct': round(loss_pct, 3),
            }

            if latency:
                sample['latency'] = latency

            self._history[flow_id].append(sample)
            self._prev[flow_id] = {
                'time': now,
                'tx_packets': tx_packets,
                'tx_bytes': tx_bytes,
                'rx_packets': rx_packets,
                'rx_bytes': rx_bytes,
            }

    def get_history(self, flow_id: str, count: int = 60) -> list:
        """Get the last N samples for a flow."""
        with self._lock:
            history = self._history.get(flow_id)
            if not history:
                return []
            samples = list(history)
            return samples[-count:]

    def get_latest(self, flow_id: str) -> dict:
        """Get the most recent sample for a flow."""
        with self._lock:
            history = self._history.get(flow_id)
            if not history:
                return {}
            return dict(history[-1])

    def get_all_latest(self) -> dict:
        """Get the most recent sample for every flow."""
        with self._lock:
            result = {}
            for flow_id, history in self._history.items():
                if history:
                    result[flow_id] = dict(history[-1])
            return result

    def remove_flow(self, flow_id: str):
        """Remove all data for a flow."""
        with self._lock:
            self._history.pop(flow_id, None)
            self._prev.pop(flow_id, None)