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#!/usr/bin/env python
# Plot bars comparing different implementations of mail pipeline.
#
# This script can be improved to account for arbitrary number of data sets, but
# it is not doing it right now.
import json
import matplotlib.pyplot as plt
import numpy as np
import re
# make a prettier graph
from mpltools import style
style.use('ggplot')
OUTPUT_FILENAME = 'blobs-sqlite-backend.png'
graphs = [
'1_10000k',
'10_1000k',
'100_100k',
'1000_10k',
]
# the JSON structure returned by the following function is ugly, but the
# original JSONs are even uglier, so this is here just to make the life of the
# script easier.
#
# We want to have something like:
#
# data[get/put][amount_size] = <stats>
def get_data():
data = {}
for fname in ['get', 'put']:
data[fname] = {}
with open('data/%s.json' % fname) as f:
d = json.loads(f.read())
benchmarks = d['benchmarks']
for item in benchmarks:
name = re.sub('^[^1]+', '', item['name'])
data[fname][name] = item['stats']
return data
def plot_data(data):
N = 4
get_means = tuple([data['get'][graph]['mean'] for graph in graphs])
put_means = tuple([data['put'][graph]['mean'] for graph in graphs])
ind = np.arange(N) # the x locations for the groups
width = 0.40 # the width of the bars
fig, ax = plt.subplots()
rects1 = ax.bar(ind, get_means, width)
rects2 = ax.bar(ind + width, put_means, width)
# add some text for labels, title and axes ticks
ax.set_ylabel('Time for operation (s)')
ax.set_xlabel('Amount and size of blobs')
ax.set_title('Blobs storage and retrieval time')
ax.set_xticks(ind + (0.5 * width))
ax.set_xticklabels(
tuple(map(lambda name: name.replace('_', ' x '), graphs)))
ax.legend(
(rects1[0], rects2[0]),
('retrieval time', 'storage time'))
# ax.grid()
plt.savefig(OUTPUT_FILENAME)
# plt.show()
if __name__ == '__main__':
data = get_data()
plot_data(data)
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