from data_pipeline.log_writer.log_writer import Logger
LOGGER_DB_NAME = "logs"
LOGGER_MEASUREMENT = "logs"
LOGGER_HOST = "uipserver.ddns.net"
LOGGER_PORT = "8086"
LOGGER_COMPONENT = "Daten klassifizieren"
logger = Logger(LOGGER_DB_NAME, LOGGER_MEASUREMENT, LOGGER_HOST, LOGGER_PORT,
LOGGER_COMPONENT)
from flask import *
import data_pipeline.daten_klassifizieren.trainingsdata_editing_engine as trainingsdata
import data_pipeline.daten_klassifizieren.classification_engine as classification
import data_pipeline.daten_klassifizieren.training_engine as training
import data_pipeline.exception.exceptions as ex
import traceback
app = Flask(__name__)
http_status_codes = {
"HTTPOK": 200,
"HTTPBadRequest": 400,
"HTTPInternalServerError": 500,
"ConfigException": 900,
"DBException": 901,
"PersistorException": 902,
"FileException": 903,
"SklearnException": 904
}
@app.route('/')
from flask import *
from datetime import datetime
import time
from data_pipeline.daten_bereinigen.src.bereinigungs_engine import bereinigungs_engine as cleaning_eng
import data_pipeline.exception.exceptions as exceptions
import data_pipeline.konfiguration.src.config_validator as validator
from data_pipeline.log_writer.log_writer import Logger
app = Flask(__name__)
logger = Logger("logs", "cleaning_logs", "uipserver.ddns.net", 8086,
"Cleaning_API")
expected_keys = set([
'sensor_data_timeframe', 'to', 'from', 'sensor_data', 'from_db', 'to_db',
'from_measurement', 'to_measurement', 'value_name', 'register',
'frame_width', 'freq', 'threshold', 'historic_weatherdata', 'from_db',
'to_db', 'from_measurement', 'to_measurement', 'value_name', 'register',
'frame_width', 'freq', 'threshold', 'forecast_weatherdata', 'from_db',
'to_db', 'from_measurement', 'to_measurement', 'value_name', 'register',
'frame_width', 'freq', 'threshold'
])
def check_if_request_empty():
""" Checks if the incoming http-post-request comes with an empty body.
:raise InvalidConfigException if the body is empty.
:return request-object.
"""
if int(request.headers.get('Content-Length')) == 0:
raise exceptions.NoDataException('Message must not be empty', 900)
import multiprocessing
import pandas as pd
from datetime import datetime
import data_pipeline.exception.exceptions as exc
import data_pipeline.db_connector.src.read_manager.read_manager as rm
import data_pipeline.db_connector.src.write_manager.write_manager as wm
from data_pipeline.log_writer.log_writer import Logger
# initialize logger
logger = Logger("logs", "logs", "uipserver.ddns.net", 8086, "Cleaning_Engine")
def get_data(from_db, from_measurement, value_name, register, time):
"""
Retrieve data from database
Name in documentation: get_data
:param from_db: database from which the data should be extracted
:param from_measurement: the measurement from which the data should be extracted
:param value_name: name of the field in influxdb
:param register: register of the desired curve which should be cleaned
:param time: tart and end time of the desired period where the curve should be cleaned
:return: returns temperature data as a Pandas.Series
"""
query = ""
if isInt(register):
query = "SELECT {0} FROM {1} WHERE register='{2}' and time >= {3}ms and time <= {4}ms".format(
value_name, from_measurement, register, time["from"], time["to"])
else:
query = "SELECT {0} FROM {1} WHERE time >={2}ms AND time <={3}ms".format(
value_name, from_measurement, time["from"], time["to"])