matrix-capnproto-fed

What if Matrix was written using Cap'n'proto and a RPC federation API?
git clone git://archive.git.mtrnord.blog/MTRNord/matrix-capnproto-fed.git
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plot_progression.py (1955B)

      1 #!/usr/bin/env python
      2 
      3 """This program shows `hyperfine` benchmark results in a sequential way
      4 in order to debug possible background interference, caching effects,
      5 thermal throttling and similar effects.
      6 """
      7 
      8 import argparse
      9 import json
     10 import matplotlib.pyplot as plt
     11 import numpy as np
     12 
     13 
     14 def moving_average(times, num_runs):
     15     times_padded = np.pad(
     16         times, (num_runs // 2, num_runs - 1 - num_runs // 2), mode="edge"
     17     )
     18     kernel = np.ones(num_runs) / num_runs
     19     return np.convolve(times_padded, kernel, mode="valid")
     20 
     21 
     22 parser = argparse.ArgumentParser(description=__doc__)
     23 parser.add_argument("file", help="JSON file with benchmark results")
     24 parser.add_argument("--title", help="Plot Title")
     25 parser.add_argument("-o", "--output", help="Save image to the given filename.")
     26 parser.add_argument(
     27     "-w",
     28     "--moving-average-width",
     29     type=int,
     30     metavar="num_runs",
     31     help="Width of the moving-average window (default: N/5)",
     32 )
     33 parser.add_argument(
     34     "--no-moving-average",
     35     action="store_true",
     36     help="Do not show moving average curve",
     37 )
     38 
     39 
     40 args = parser.parse_args()
     41 
     42 with open(args.file) as f:
     43     results = json.load(f)["results"]
     44 
     45 for result in results:
     46     label = result["command"]
     47     times = result["times"]
     48     num = len(times)
     49     nums = range(num)
     50 
     51     plt.scatter(x=nums, y=times, marker=".")
     52     plt.ylim([0, None])
     53     plt.xlim([-1, num])
     54 
     55     if not args.no_moving_average:
     56         moving_average_width = (
     57             num // 5 if args.moving_average_width is None else args.moving_average_width
     58         )
     59 
     60         average = moving_average(times, moving_average_width)
     61         plt.plot(nums, average, "-")
     62 
     63 if args.title:
     64     plt.title(args.title)
     65 
     66 legend = []
     67 for result in results:
     68     legend.append(result["command"])
     69     if not args.no_moving_average:
     70         legend.append("moving average")
     71 plt.legend(legend)
     72 
     73 plt.ylabel("Time [s]")
     74 
     75 if args.output:
     76     plt.savefig(args.output)
     77 else:
     78     plt.show()