craftbeerpi4-pione/cbpi/controller/log_file_controller.py
2021-02-27 20:09:19 +01:00

161 lines
4.9 KiB
Python

import datetime
import glob
import logging
import os
from logging.handlers import RotatingFileHandler
from time import strftime, localtime
import pandas as pd
import zipfile
class LogController:
def __init__(self, cbpi):
'''
:param cbpi: craftbeerpi object
'''
self.cbpi = cbpi
self.logger = logging.getLogger(__name__)
self.datalogger = {}
def log_data(self, name: str, value: str) -> None:
if name not in self.datalogger:
max_bytes = self.cbpi.config.get("SENSOR_LOG_MAX_BYTES", 1048576)
backup_count = 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, value))
async def get_data(self, names, sample_rate='60s'):
'''
: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])
# resample if rate provided
if sample_rate is not None:
df = df[name].resample(sample_rate).max()
df = df.dropna()
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()
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)
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)