How to get slow monitoring data

Connect to InfluxDB

Load a config file



In [1]:

    
import json



In [2]:

    
with open('db.json','r') as fp:
    c = json.load(fp)

Load InfluxDB package



In [3]:

    
from influxdb import InfluxDBClient

Set your database information



In [4]:

    
client = InfluxDBClient(
    c['DBHOST'],
    443,
    c['DBUSER'],
    c['DBPASS'],
    c['DBNAME'],
    ssl=True,
    verify_ssl=True
)

Print measurements (Simular to a MySQL's table)



In [5]:

    
rs = client.query("SHOW MEASUREMENTS")
for row in rs.get_points():
    print(row)









    



{'name': 'cosine_con_status'}
{'name': 'cosine_con_val'}
{'name': 'fortigate'}
{'name': 'korac'}
{'name': 'lutron'}
{'name': 'pcw'}
{'name': 'rad7'}
{'name': 'rrsdehumi'}
{'name': 't_rh_o2'}
{'name': 'temphum'}
{'name': 'towerlamp'}
{'name': 'weather'}
{'name': 'y2ltemphum'}

Get data from a specific measurement

Example query

Ref: https://docs.influxdata.com/influxdb/v1.3/query_language/data_exploration/



In [6]:

    
query = """SELECT * FROM "weather" WHERE time > now() - 7d"""

Export CSV



In [7]:

    
import csv



In [8]:

    
rs = client.query(query)
with open('data.csv', 'w') as csvfile:
    firstrow = next(rs.get_points())
    writer = csv.DictWriter(csvfile, fieldnames=firstrow.keys())
    writer.writeheader()
    writer.writerow(firstrow)
    for row in rs.get_points():
        writer.writerow(row)

Numpy



In [9]:

    
%matplotlib inline



In [10]:

    
import matplotlib
import matplotlib.pyplot as plt



In [11]:

    
import numpy as np



In [12]:

    
temp = []
rs = client.query(query)
for item in rs.get_points():
    temp.append(item['T1H'])



In [13]:

    
temp = np.array(temp)



In [14]:

    
plt.plot(temp)









    Out[14]:





[<matplotlib.lines.Line2D at 0x7f47b72497b8>]

PyROOT



In [15]:

    
from array import array



In [16]:

    
import ROOT









    



Welcome to JupyROOT 6.10/02



In [17]:

    
%jsroot on



In [18]:

    
h1f = ROOT.TH1F('h1f', 'Y2 Temperature', 100, 15, 40)



In [19]:

    
rs = client.query(query)
for item in rs.get_points():
    h1f.Fill(item['T1H'])



In [20]:

    
c = ROOT.TCanvas("CanvasName","Canvas Title",800,600)
h1f.Draw()
c.Draw()

Export data



In [21]:

    
f = ROOT.TFile('test.root', 'RECREATE')
d = array( 'f', [ 0 ])
tree = ROOT.TTree("tree", "tree")
tree.Branch('temperature', d, 'temp/F')
rs = client.query(query)
for item in rs.get_points():
    d[0] = item['T1H']
    tree.Fill()
f.Write()
f.Close()