import datetime import glob import logging import os from logging.handlers import RotatingFileHandler from time import strftime, localtime import pandas as pd import zipfile import base64 import urllib3 from cbpi.api import * from cbpi.api.config import ConfigType from cbpi.api.base import CBPiBase import asyncio class LogController: def __init__(self, cbpi): ''' :param cbpi: craftbeerpi object ''' self.cbpi = cbpi self.logger = logging.getLogger(__name__) self.configuration = False self.datalogger = {} def log_data(self, name: str, value: str) -> None: self.logfiles = self.cbpi.config.get("CSVLOGFILES", "Yes") self.influxdb = self.cbpi.config.get("INFLUXDB", "No") if self.logfiles == "Yes": if name not in self.datalogger: max_bytes = int(self.cbpi.config.get("SENSOR_LOG_MAX_BYTES", 131072)) backup_count = int(self.cbpi.config.get("SENSOR_LOG_BACKUP_COUNT", 3)) data_logger = logging.getLogger('cbpi.sensor.%s' % name) data_logger.propagate = False data_logger.setLevel(logging.DEBUG) handler = RotatingFileHandler('./logs/sensor_%s.log' % name, maxBytes=max_bytes, backupCount=backup_count) data_logger.addHandler(handler) self.datalogger[name] = data_logger formatted_time = strftime("%Y-%m-%d %H:%M:%S", localtime()) self.datalogger[name].info("%s,%s" % (formatted_time, str(value))) if self.influxdb == "Yes": self.influxdbcloud = self.cbpi.config.get("INFLUXDBCLOUD", "No") self.influxdbaddr = self.cbpi.config.get("INFLUXDBADDR", None) self.influxdbport = self.cbpi.config.get("INFLUXDBPORT", None) self.influxdbname = self.cbpi.config.get("INFLUXDBNAME", None) self.influxdbuser = self.cbpi.config.get("INFLUXDBUSER", None) self.influxdbpwd = self.cbpi.config.get("INFLUXDBPWD", None) id = name try: chars = {'ö':'oe','ä':'ae','ü':'ue','Ö':'Oe','Ä':'Ae','Ü':'Ue'} sensor=self.cbpi.sensor.find_by_id(name) if sensor is not None: itemname=sensor.name.replace(" ", "_") for char in chars: itemname = itemname.replace(char,chars[char]) out="measurement,source=" + itemname + ",itemID=" + str(id) + " value="+str(value) except Exception as e: logging.error("InfluxDB ID Error: {}".format(e)) if self.influxdbcloud == "Yes": self.influxdburl="https://" + self.influxdbaddr + "/api/v2/write?org=" + self.influxdbuser + "&bucket=" + self.influxdbname + "&precision=s" try: header = {'User-Agent': name, 'Authorization': "Token {}".format(self.influxdbpwd)} http = urllib3.PoolManager() req = http.request('POST',self.influxdburl, body=out, headers = header) except Exception as e: logging.error("InfluxDB cloud write Error: {}".format(e)) else: self.base64string = base64.b64encode(('%s:%s' % (self.influxdbuser,self.influxdbpwd)).encode()) self.influxdburl='http://' + self.influxdbaddr + ':' + str(self.influxdbport) + '/write?db=' + self.influxdbname try: header = {'User-Agent': name, 'Content-Type': 'application/x-www-form-urlencoded','Authorization': 'Basic %s' % self.base64string.decode('utf-8')} http = urllib3.PoolManager() req = http.request('POST',self.influxdburl, body=out, headers = header) except Exception as e: logging.error("InfluxDB write Error: {}".format(e)) async def get_data(self, names, sample_rate='60s'): logging.info("Start Log for {}".format(names)) ''' :param names: name as string or list of names as string :param sample_rate: rate for resampling the data :return: ''' # make string to array if isinstance(names, list) is False: names = [names] # remove duplicates names = set(names) result = None def dateparse(time_in_secs): ''' Internal helper for date parsing :param time_in_secs: :return: ''' return datetime.datetime.strptime(time_in_secs, '%Y-%m-%d %H:%M:%S') def datetime_to_str(o): if isinstance(o, datetime.datetime): return o.__str__() for name in names: # get all log names all_filenames = glob.glob('./logs/sensor_%s.log*' % name) # concat all logs df = pd.concat([pd.read_csv(f, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime', name], header=None) for f in all_filenames]) logging.info("Read all files for {}".format(names)) # resample if rate provided if sample_rate is not None: df = df[name].resample(sample_rate).max() logging.info("Sampled now for {}".format(names)) df = df.dropna() # take every nth row so that total number of rows does not exceed max_rows * 2 max_rows = 500 total_rows = df.shape[0] if (total_rows > 0) and (total_rows > max_rows): nth = int(total_rows/max_rows) if nth > 1: df = df.iloc[::nth] if result is None: result = df else: result = pd.merge(result, df, how='outer', left_index=True, right_index=True) data = {"time": df.index.tolist()} if len(names) > 1: for name in names: data[name] = result[name].interpolate(limit_direction='both', limit=10).tolist() else: data[name] = result.interpolate().tolist() logging.info("Send Log for {}".format(names)) return data async def get_data2(self, ids) -> dict: def dateparse(time_in_secs): return datetime.datetime.strptime(time_in_secs, '%Y-%m-%d %H:%M:%S') result = dict() for id in ids: # df = pd.read_csv("./logs/sensor_%s.log" % id, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime',"Values"], header=None) # concat all logs all_filenames = glob.glob('./logs/sensor_%s.log*' % id) df = pd.concat([pd.read_csv(f, parse_dates=True, date_parser=dateparse, index_col='DateTime', names=['DateTime', 'Values'], header=None) for f in all_filenames]) df = df.resample('60s').max() df = df.dropna() result[id] = {"time": df.index.astype(str).tolist(), "value":df.Values.tolist()} return result def get_logfile_names(self, name:str ) -> list: ''' Get all log file names :param name: log name as string. pattern /logs/sensor_%s.log* :return: list of log file names ''' return [os.path.basename(x) for x in glob.glob('./logs/sensor_%s.log*' % name)] def clear_log(self, name:str ) -> str: all_filenames = glob.glob('./logs/sensor_%s.log*' % name) for f in all_filenames: os.remove(f) if name in self.datalogger: del self.datalogger[name] def get_all_zip_file_names(self, name: str) -> list: ''' Return a list of all zip file names :param name: :return: ''' return [os.path.basename(x) for x in glob.glob('./logs/*-sensor-%s.zip' % name)] def clear_zip(self, name:str ) -> None: """ clear all zip files for a sensor :param name: sensor name :return: None """ all_filenames = glob.glob('./logs/*-sensor-%s.zip' % name) for f in all_filenames: os.remove(f) def zip_log_data(self, name: str) -> str: """ :param name: sensor name :return: zip_file_name """ formatted_time = strftime("%Y-%m-%d-%H_%M_%S", localtime()) file_name = './logs/%s-sensor-%s.zip' % (formatted_time, name) zip = zipfile.ZipFile(file_name, 'w', zipfile.ZIP_DEFLATED) all_filenames = glob.glob('./logs/sensor_%s.log*' % name) for f in all_filenames: zip.write(os.path.join(f)) zip.close() return os.path.basename(file_name)