Wednesday, August 08, 2007

Pylot - Dev Update #5 - Web Performance/Load Test Tool (Graphs With MatPlotlib)

We performance practioners love our graphs! Visualizing data is helpful in analyzing performance results. Sometimes a quick glance at a graph provides better understanding than a mound of raw or summarized data. Pylot's Results Reporting feature creates graphs of response times (latency) and Throughput.

For the graphing toolkit, Pylot uses Matplotlib to produce fancy graphs like these:

Matplotlib allows you to graph data from Python. Here is a simple script that gives a glimpse of how a line/marker graph is created as a png image:

#!/usr/bin/env python

from pylab import *  # Matplotlib

def main():
    # sequence of data points to graph (x, y coordinates)
    points = [(1, 3), (2, 6), (3, 2), (4, 5)]
    graph(points)
   
   
def graph(points):
    fig = figure(figsize=(6, 2))  # image dimensions  
    ax = fig.add_subplot(111)
    ax.grid(True, color='#666666')
    xticks(size='x-small')
    yticks(size='x-small')
    x_seq = [item[0] for item in points] 
    y_seq = [item[1] for item in points] 
    ax.plot(x_seq, y_seq, 
        color='blue', linestyle='-', linewidth=1.0, marker='o', 
        markeredgecolor='blue', markerfacecolor='yellow', markersize=2.0)
    savefig('graph.png') 
    
    
if __name__ == '__main__':
    main()