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 pathlib import Path 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 = {} self.logsFolderPath = self.cbpi.config_folder.logsFolderPath self.logger.info("Log folder path : " + self.logsFolderPath) 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", 100000)) 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(os.path.join(self.logsFolderPath, f"sensor_{name}.log"), 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 = os.path.join(self.logsFolderPath, f"sensor_{name}.log*") # 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(os.path.join(self.logsFolderPath,f"sensor_{id}.log*")) 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 os.path.join(self.logsFolderPath, f"sensor_{name}.log*")] def clear_log(self, name:str ) -> str: all_filenames = glob.glob(os.path.join(self.logsFolderPath, f"sensor_{name}.log*")) 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(os.path.join(self.logsFolderPath, f"*-sensor-{name}.zip"))] def clear_zip(self, name:str ) -> None: """ clear all zip files for a sensor :param name: sensor name :return: None """ all_filenames = glob.glob(os.path.join(self.logsFolderPath, f"*-sensor-{name}.zip")) 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 = os.path.join(self.logsFolderPath, f"{formatted_time}-sensor-{name}.zip" % (formatted_time, name)) zip = zipfile.ZipFile(file_name, 'w', zipfile.ZIP_DEFLATED) all_filenames = os.path.join(self.logsFolderPath, f"sensor_{name}.log*") for f in all_filenames: zip.write(os.path.join(f)) zip.close() return os.path.basename(file_name)