mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-09-19 22:07:28 +02:00
159 lines
4.6 KiB
Python
159 lines
4.6 KiB
Python
import datetime
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import glob
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import logging
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import os
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from logging.handlers import RotatingFileHandler
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from time import strftime, localtime
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import pandas as pd
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import zipfile
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class LogController:
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def __init__(self, cbpi):
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'''
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:param cbpi: craftbeerpi object
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'''
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self.cbpi = cbpi
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self.logger = logging.getLogger(__name__)
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self.datalogger = {}
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def log_data(self, name: str, value: str) -> None:
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if name not in self.datalogger:
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max_bytes = self.cbpi.config.get("SENSOR_LOG_MAX_BYTES", 1048576)
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backup_count = self.cbpi.config.get("SENSOR_LOG_BACKUP_COUNT", 3)
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data_logger = logging.getLogger('cbpi.sensor.%s' % name)
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data_logger.propagate = False
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data_logger.setLevel(logging.DEBUG)
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handler = RotatingFileHandler('./logs/sensor_%s.log' % name, maxBytes=max_bytes, backupCount=backup_count)
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data_logger.addHandler(handler)
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self.datalogger[name] = data_logger
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formatted_time = strftime("%Y-%m-%d %H:%M:%S", localtime())
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self.datalogger[name].info("%s,%s" % (formatted_time, value))
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async def get_data(self, names, sample_rate='60s'):
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'''
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:param names: name as string or list of names as string
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:param sample_rate: rate for resampling the data
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:return:
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'''
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# make string to array
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if isinstance(names, list) is False:
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names = [names]
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# remove duplicates
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names = set(names)
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print(names)
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result = None
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def dateparse(time_in_secs):
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'''
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Internal helper for date parsing
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:param time_in_secs:
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:return:
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'''
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return datetime.datetime.strptime(time_in_secs, '%Y-%m-%d %H:%M:%S')
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def datetime_to_str(o):
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if isinstance(o, datetime.datetime):
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return o.__str__()
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for name in names:
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# get all log names
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all_filenames = glob.glob('./logs/sensor_%s.log*' % name)
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# concat all logs
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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])
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# resample if rate provided
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if sample_rate is not None:
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df = df[name].resample(sample_rate).max()
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df = df.dropna()
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if result is None:
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result = df
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else:
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result = pd.merge(result, df, how='outer', left_index=True, right_index=True)
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data = {"time": df.index.tolist()}
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if len(names) > 1:
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for name in names:
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data[name] = result[name].interpolate(limit_direction='both', limit=10).tolist()
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else:
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data[name] = result.interpolate().tolist()
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print(data)
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return data
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def get_logfile_names(self, name:str ) -> list:
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'''
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Get all log file names
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:param name: log name as string. pattern /logs/sensor_%s.log*
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:return: list of log file names
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'''
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return [os.path.basename(x) for x in glob.glob('./logs/sensor_%s.log*' % name)]
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def clear_log(self, name:str ) -> str:
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'''
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:param name: log name as string. pattern /logs/sensor_%s.log*
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:return: None
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'''
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all_filenames = glob.glob('./logs/sensor_%s.log*' % name)
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for f in all_filenames:
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os.remove(f)
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if name in self.datalogger:
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del self.datalogger[name]
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def get_all_zip_file_names(self, name: str) -> list:
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'''
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Return a list of all zip file names
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:param name:
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:return:
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'''
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return [os.path.basename(x) for x in glob.glob('./logs/*-sensor-%s.zip' % name)]
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def clear_zip(self, name:str ) -> None:
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"""
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clear all zip files for a sensor
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:param name: sensor name
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:return: None
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"""
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all_filenames = glob.glob('./logs/*-sensor-%s.zip' % name)
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for f in all_filenames:
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os.remove(f)
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def zip_log_data(self, name: str) -> str:
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"""
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:param name: sensor name
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:return: zip_file_name
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"""
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formatted_time = strftime("%Y-%m-%d-%H_%M_%S", localtime())
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file_name = './logs/%s-sensor-%s.zip' % (formatted_time, name)
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zip = zipfile.ZipFile(file_name, 'w', zipfile.ZIP_DEFLATED)
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all_filenames = glob.glob('./logs/sensor_%s.log*' % name)
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for f in all_filenames:
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zip.write(os.path.join(f))
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zip.close()
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return os.path.basename(file_name)
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