khulnasoft-pandas

A helper library to pull data from khulnasoft api into a pandas dataframe.

Install

pip install khulnasoft-pandas

Documentation

More detailed documentation can be found at https://khulnasoft.github.io/khulnasoft-pandas

Quickstart

Get some data into a pandas dataframe.

from khulnasoft_pandas.data import get_data

df = get_data('london.my-khulnasoft.com', ['system.cpu','system.load'], after=-60, before=0)
print(df.shape)
print(df.head())

(60, 12)
            system.cpu|guest  system.cpu|guest_nice  system.cpu|iowait  \
time_idx                                                                 
1604928205               0.0                    0.0                0.0   
1604928206               0.0                    0.0                0.0   
1604928207               0.0                    0.0                0.0   
1604928208               0.0                    0.0                0.0   
1604928209               0.0                    0.0                0.0   

            system.cpu|irq  system.cpu|nice  system.cpu|softirq  \
time_idx                                                          
1604928205             0.0              0.0                 0.0   
1604928206             0.0              0.0                 0.0   
1604928207             0.0              0.0                 0.0   
1604928208             0.0              0.0                 0.0   
1604928209             0.0              0.0                 0.0   

            system.cpu|steal  system.cpu|system  system.cpu|user  \
time_idx                                                           
1604928205          0.000000           0.501253         0.501253   
1604928206          0.000000           0.753769         0.502513   
1604928207          0.000000           0.505050         0.505050   
1604928208          0.000000           0.751880         0.501253   
1604928209          0.251256           0.251256         0.502513   

            system.load|load1  system.load|load15  system.load|load5  
time_idx                                                              
1604928205               0.03                 0.0               0.04  
1604928206               0.03                 0.0               0.04  
1604928207               0.03                 0.0               0.04  
1604928208               0.03                 0.0               0.04  
1604928209               0.03                 0.0               0.04  

An alternative way to call get_data() is to define what hosts and charts you want via the host_charts_dict param:

# define list of charts for each host you want data for
host_charts_dict = {
    "london.my-khulnasoft.com" : ['system.io','system.ip'],
    "newyork.my-khulnasoft.com" : ['system.io','system.net'],
}
df = get_data(host_charts_dict=host_charts_dict, host_prefix=True)
print(df.shape)
print(df.head())

(61, 8)
            london.my-khulnasoft.com::system.io|in  \
time_idx                                         
1604928340                                 NaN   
1604928341                                 0.0   
1604928342                                 0.0   
1604928343                                 0.0   
1604928344                                 0.0   

            london.my-khulnasoft.com::system.io|out  \
time_idx                                          
1604928340                                  NaN   
1604928341                            -53.89722   
1604928342                            -26.10278   
1604928343                              0.00000   
1604928344                              0.00000   

            london.my-khulnasoft.com::system.ip|received  \
time_idx                                               
1604928340                                       NaN   
1604928341                                  49.25227   
1604928342                                 227.22840   
1604928343                                 123.56787   
1604928344                                  31.99060   

            london.my-khulnasoft.com::system.ip|sent  \
time_idx                                           
1604928340                                   NaN   
1604928341                             -51.85469   
1604928342                             -85.22854   
1604928343                             -43.00154   
1604928344                             -19.55536   

            newyork.my-khulnasoft.com::system.io|in  \
time_idx                                          
1604928340                                  0.0   
1604928341                                  0.0   
1604928342                                  0.0   
1604928343                                  0.0   
1604928344                                  0.0   

            newyork.my-khulnasoft.com::system.io|out  \
time_idx                                           
1604928340                              0.000000   
1604928341                             -6.545929   
1604928342                             -9.454071   
1604928343                              0.000000   
1604928344                              0.000000   

            newyork.my-khulnasoft.com::system.net|received  \
time_idx                                                 
1604928340                                   13.778033   
1604928341                                   18.281470   
1604928342                                   24.811770   
1604928343                                   26.406000   
1604928344                                   26.457510   

            newyork.my-khulnasoft.com::system.net|sent  
time_idx                                            
1604928340                               -16.97193  
1604928341                               -19.23857  
1604928342                               -76.86994  
1604928343                              -165.55492  
1604928344                              -115.83034  

Examples

You can find some more examples in the examples folder.

Or if you just want to play with it right now you can use this Google Colab notebook to quickly get started.