def sendRequest(self, query):
"""
Description : Accesses the new relic query end point and fetches the data
Parameters : 1. self
2. query - to query the new relic data
Return Value : Response of the New Relic Query
"""
logging.debug("Getting daily data from New Relic API")
#Accessing NewRelic API with Query
try:
data = {"nrql":query}
constants = Constants()
response = requests.get(url = constants.NEWRELIC_API_ENDPOINT,headers= constants.HEADERS, params=data)
except requests.exceptions.Timeout as e:
logging.error("Timeout Error: \n {0}".format(e))
except requests.exceptions.TooManyRedirects as e:
logging.error("Bad URL: \n {0}".format(e))
except requests.exceptions.HTTPError as e:
logging.error("HTTP Error: \n {0}".format(e))
except requests.exceptions.RequestException as e:
logging.error("Error occured while connecting to New Relic: \n {0}".format(e))
return response
def __init__(self):
"""
Description : Constructor to class FeedbackLoop, initializes the connection to COS
Parameters : 1. self
"""
constants = Constants()
self.client = ibm_boto3.client(service_name='s3',ibm_api_key_id=constants.API_KEY,ibm_auth_endpoint=constants.AUTH_ENDPOINT,config=Config(signature_version='oauth'),endpoint_url=constants.COS_API_ENDPOINT)
column_names = ['Timestamp','CPU','Instances']
util = COSUtils()
self.bucketName = 'getcsvdata'
self.data = {}
self.score = {}
self.modelSelector = {}
self.response = {}
for region in ['Dallas', 'London', 'Tokyo']:
self.initialDataset = 'initial_'+region+'.csv'
self.fetchedDataset = 'data_'+region+'.csv'
self.data[region] = util.get_dataframe(column_names, self.bucketName, self.initialDataset)
self.data[region].columns = column_names
self.data[region] = self.convertTimestampToFloat(self.data[region])
self.modelSelector[region] = RegressionSelector()
self.score[region] = self.getScore(self.data[region], region)['Best Score']
logging.info("Score:" + str(self.score[region]))
logging.debug("Response:")
logging.debug(self.response)
def __init__(self):
"""
Description : Constructor to class COSUtils, initializes the connection to COS
Parameters : 1. self
"""
constants = Constants()
self.client = ibm_boto3.client(
service_name='s3',
ibm_api_key_id=constants.API_KEY,
ibm_auth_endpoint=constants.AUTH_ENDPOINT,
config=Config(signature_version='oauth'),
endpoint_url=constants.COS_API_ENDPOINT)
def create_app(platform_):
# Load user settings and components
user = UserContent()
user_settings = user.get_user_settings()
user_tabs = user.load_user_tabs()
conf = Constants(
user_settings["app_title"],
user_settings["app_subtitle"],
user_settings["contact_email"],
)
page_layout = AppLayout(
conf.APP_TITLE,
conf.APP_SUBTITLE,
conf.PATH_LOGO,
conf.EMAIL,
conf.FOOTER_TEXT,
conf.CONTACT_MAIL_SUBJECT,
user_tabs,
)
page_layout.create_layout()
# Create the app instance
external_stylesheets = [
'https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css',
]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = conf.APP_TITLE
app.config.suppress_callback_exceptions = True
if platform_ == "local":
requests_prefix = ''
app.config.update({'requests_pathname_prefix': requests_prefix})
else:
requests_prefix = ''
app.layout = page_layout.layout
cc = CallbackControls(app)
cc.load_tab_callbacks(user_tabs)
return app
simplefilter(action='ignore', category=DeprecationWarning)
from numpy import array
import pandas as pd
import numpy as np
import os
from sklearn import metrics, svm
import threading
import time, json
import urllib
import csv
import datetime
from numpy.random import seed
import logging
seed(500)
constants = Constants()
class RegressionSelector():
def __init__(self):
"""
Description : Constructor to class RegressionSelector
Parameters : 1. self
"""
self.bestModel = None
self.models = None
def getResponse(self):
"""
import tweepy
import logging
from app.config import create_api
from app.aws_services import AWSConnection
import time
from app.constants import Constants
from app.logger import LoggerService
ls = LoggerService()
_log = ls.get_logger()
con = Constants()
awsc = AWSConnection()
def follow_followers(api):
_log.info("Retrieving and following followers")
for follower in tweepy.Cursor(api.followers).items():
if not follower.following:
_log.info(f"Following {follower.name}")
follower.follow()
def validate_friend(api, user):
try:
api.show_friendship(target_screen_name=user)
_log.info(f'{user} exists!')
return True
except Exception as e:
_log.error(f"User {user} does not exist. Response {e}", exc_info=True)