openpilot/selfdrive/statsd.py

#!/usr/bin/env python3
import os
import zmq
import time
from pathlib import Path
from collections import defaultdict
from datetime import datetime, timezone
from typing import NoReturn, Union, List, Dict

from common.params import Params
from cereal.messaging import SubMaster
from system.swaglog import cloudlog
from system.hardware import HARDWARE
from common.file_helpers import atomic_write_in_dir
from system.version import get_normalized_origin, get_short_branch, get_short_version, is_dirty
from system.loggerd.config import STATS_DIR, STATS_DIR_FILE_LIMIT, STATS_SOCKET, STATS_FLUSH_TIME_S


class METRIC_TYPE:
  GAUGE = 'g'
  SAMPLE = 'sa'

class StatLog:
  def __init__(self):
    self.pid = None

  def connect(self) -> None:
    self.zctx = zmq.Context()
    self.sock = self.zctx.socket(zmq.PUSH)
    self.sock.setsockopt(zmq.LINGER, 10)
    self.sock.connect(STATS_SOCKET)
    self.pid = os.getpid()

  def _send(self, metric: str) -> None:
    if os.getpid() != self.pid:
      self.connect()

    try:
      self.sock.send_string(metric, zmq.NOBLOCK)
    except zmq.error.Again:
      # drop :/
      pass

  def gauge(self, name: str, value: float) -> None:
    self._send(f"{name}:{value}|{METRIC_TYPE.GAUGE}")

  # Samples will be recorded in a buffer and at aggregation time,
  # statistical properties will be logged (mean, count, percentiles, ...)
  def sample(self, name: str, value: float):
    self._send(f"{name}:{value}|{METRIC_TYPE.SAMPLE}")


def main() -> NoReturn:
  dongle_id = Params().get("DongleId", encoding='utf-8')
  def get_influxdb_line(measurement: str, value: Union[float, Dict[str, float]],  timestamp: datetime, tags: dict) -> str:
    res = f"{measurement}"
    for k, v in tags.items():
      res += f",{k}={str(v)}"
    res += " "

    if isinstance(value, float):
      value = {'value': value}

    for k, v in value.items():
      res += f"{k}={v},"

    res += f"dongle_id=\"{dongle_id}\" {int(timestamp.timestamp() * 1e9)}\n"
    return res

  # open statistics socket
  ctx = zmq.Context().instance()
  sock = ctx.socket(zmq.PULL)
  sock.bind(STATS_SOCKET)

  # initialize stats directory
  Path(STATS_DIR).mkdir(parents=True, exist_ok=True)

  # initialize tags
  tags = {
    'started': False,
    'version': get_short_version(),
    'branch': get_short_branch(),
    'dirty': is_dirty(),
    'origin': get_normalized_origin(),
    'deviceType': HARDWARE.get_device_type(),
  }

  # subscribe to deviceState for started state
  sm = SubMaster(['deviceState'])

  idx = 0
  last_flush_time = time.monotonic()
  gauges = {}
  samples: Dict[str, List[float]] = defaultdict(list)
  while True:
    started_prev = sm['deviceState'].started
    sm.update()

    # Update metrics
    while True:
      try:
        metric = sock.recv_string(zmq.NOBLOCK)
        try:
          metric_type = metric.split('|')[1]
          metric_name = metric.split(':')[0]
          metric_value = float(metric.split('|')[0].split(':')[1])

          if metric_type == METRIC_TYPE.GAUGE:
            gauges[metric_name] = metric_value
          elif metric_type == METRIC_TYPE.SAMPLE:
            samples[metric_name].append(metric_value)
          else:
            cloudlog.event("unknown metric type", metric_type=metric_type)
        except Exception:
          cloudlog.event("malformed metric", metric=metric)
      except zmq.error.Again:
        break

    # flush when started state changes or after FLUSH_TIME_S
    if (time.monotonic() > last_flush_time + STATS_FLUSH_TIME_S) or (sm['deviceState'].started != started_prev):
      result = ""
      current_time = datetime.utcnow().replace(tzinfo=timezone.utc)
      tags['started'] = sm['deviceState'].started

      for key, value in gauges.items():
        result += get_influxdb_line(f"gauge.{key}", value, current_time, tags)

      for key, values in samples.items():
        values.sort()
        sample_count = len(values)
        sample_sum = sum(values)

        stats = {
          'count': sample_count,
          'min': values[0],
          'max': values[-1],
          'mean': sample_sum / sample_count,
        }
        for percentile in [0.05, 0.5, 0.95]:
          value = values[int(round(percentile * (sample_count - 1)))]
          stats[f"p{int(percentile * 100)}"] = value

        result += get_influxdb_line(f"sample.{key}", stats, current_time, tags)

      # clear intermediate data
      gauges.clear()
      samples.clear()
      last_flush_time = time.monotonic()

      # check that we aren't filling up the drive
      if len(os.listdir(STATS_DIR)) < STATS_DIR_FILE_LIMIT:
        if len(result) > 0:
          stats_path = os.path.join(STATS_DIR, f"{current_time.timestamp():.0f}_{idx}")
          with atomic_write_in_dir(stats_path) as f:
            f.write(result)
          idx += 1
      else:
        cloudlog.error("stats dir full")


if __name__ == "__main__":
  main()
else:
  statlog = StatLog()