aindapy 0.0.14

Ainda Package made for python lovers. This is inteded to be used on ainda private cloud

import aindapy import random import time import json import datetime

from numpy.core.numeric import _correlate_dispatcher

import logging

import http.client as http_client

http_client.HTTPConnection.debuglevel = 1

logging.basicConfig()

logging.getLogger().setLevel(logging.DEBUG)

requests_log = logging.getLogger("requests.packages.urllib3")

requests_log.setLevel(logging.DEBUG)

requests_log.propagate = True

aindapy.config(logLevel=1)

auth = aindapy.Auth( apiUrl='https://aindaanalytics.com/ainda/api/', userName='asdfasdfasdfsdfsdf', passWord='asdfasdfsdf' )

The datasource now accepts only the ids, so pls check what is the correct id for it.

Demo WareHouse dataWareHouseId=7, dataSourceId=20

Ainda Packaging Line WareHouse dataWareHouseId=8, dataSourceId=22

dataSource = aindapy.DataSource( auth=auth, dataWareHouseId=7, dataSourceId=20 )

Generate Data for graphics that are not timeseries

data = aindapy.Data(auth=auth, dataSource=dataSource, bufferSize=1000)

Generate Data Sample for pie

data.deleteDataKeys([ 'basicdemo/pie1', 'basicdemo/pie2', 'basicdemo/bar1', 'basicdemo/bar2', 'basicdemo/bar10Columns', 'basicdemo/bar50Columns', 'basicdemo/scaleline250points', 'basicdemo/scaleline500points' ]) data.addToBuffer('basicdemo/pie1', random.randint(50, 150), 'Ilha 1') data.addToBuffer('basicdemo/pie1', random.randint(70, 180), 'Ilha 2') data.addToBuffer('basicdemo/pie1', random.randint(10, 75), 'Ilha 3') data.addToBuffer('basicdemo/pie1', random.randint(25, 45), 'Ilha 4')

data.addToBuffer('basicdemo/pie2', random.randint(50, 150), 'Ilha 1') data.addToBuffer('basicdemo/pie2', random.randint(70, 180), 'Ilha 2') data.addToBuffer('basicdemo/pie2', random.randint(10, 75), 'Ilha 3') data.addToBuffer('basicdemo/pie2', random.randint(25, 45), 'Ilha 4') data.addToBuffer('basicdemo/pie2', random.randint(25, 45), 'Ilha 4') data.addToBuffer('basicdemo/pie2', random.randint(25, 45), 'Ilha 4') data.addToBuffer('basicdemo/pie2', random.randint(25, 45), 'Ilha 4')

Generate Data Sample for one bar graphic with 10 columns

for step in range(10): data.addToBuffer('basicdemo/bar10Columns', random.randint(50, 150), step)

Generate Data Sample for one bar graphic with 50 columns

for step in range(50): data.addToBuffer('basicdemo/bar50Columns', random.randint(50, 150), step)

Generate Data Sample for line

for step in range(250): data.addToBuffer('basicdemo/scaleline250points', random.randint(50, 150), step)

for step in range(500): data.addToBuffer('basicdemo/scaleline500points', random.randint(50, 150), step)

data.commit()

Generate data for one timeseries datatag. This data we can not deleted what was added before

If the tag do not exist, the code create this tag inside our system.

stag1 = aindapy.SensorTag(auth=auth, dataSource=dataSource, channel='1', datatag='XRND1', tag='Random Value 1', tag_unit='KG', tag_updaterate=1000) stag2 = aindapy.SensorTag(auth=auth, dataSource=dataSource, channel='1', datatag='XRND2', tag='Random Value 2', tag_unit='KG', tag_updaterate=1000)

tdata = aindapy.DataTimeSeries(auth=auth, dataSource=dataSource, bufferSize=1000) for step in range(10000): tdata.addToBuffer(sensorTag=stag1, timeStamp=datetime.datetime.now(), value=random.randint(45,90))

# if you do not pass timestamp, we will generate internaly
tdata.addToBuffer(sensorTag=stag2, value=random.randint(45,90))

tdata.commit()