contrib/perf-utils/perf-revlog-write-plot.py

packaging: support building WiX installers with PyOxidizer

We initially implemented PyOxidizer support for Inno installers.
That did most of the heavy work of integrating PyOxidizer into
the packaging system. Implementing WiX installer support was
pretty straightforward.

Aspects of this patch look very similar to Inno's.

The main difference is the handling of the Visual C++
Redistributable Runtime files.

The WiX installer was formerly using merge modules to
install the VC++ 9.0 runtime because this feature is
supported by the WiX installer (it isn't easily available
to Inno installers).

Our strategy for the runtime files is to install the
vcruntime140.dll file next to hg.exe just like any other
file. While we could leverage WiX's functionality for invoking
a VCRedist installer, I don't want to deal with the complexity
at this juncture. So, we let run_pyoxidizer() copy vcruntime140.dll
into the staging directory (like it does for Inno) and our
dynamic WiX XML generator picks it up as a regular file and
installs it.

We did, however, have to teach mercurial.wxs how to conditionally
use the merge modules. But this was rather straightforward.

Comparing the file layout of the WiX installers before and
after:

* Various lib/*.{pyd, dll} files no longer exist
* python27.dll was replaced by python37.dll
* vcruntime140.dll was added

All these changes are expected due to the transition to
Python 3 and to PyOxidizer, which embeded the .pyd and .dll files
in hg.exe.

Differential Revision: https://phab.mercurial-scm.org/D8477

#!/usr/bin/env python
#
#  Copyright 2018 Paul Morelle <[e-mail]>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
#
# This script use the output of `hg perfrevlogwrite -T json --details` to draw
# various plot related to write performance in a revlog
#
# usage: perf-revlog-write-plot.py details.json
from __future__ import absolute_import, print_function
import json
import re

import numpy as np
import scipy.signal

from matplotlib import (
    pyplot as plt,
    ticker as mticker,
)


def plot(data, title=None):
    items = {}
    re_title = re.compile(r'^revisions #\d+ of \d+, rev (\d+)$')
    for item in data:
        m = re_title.match(item['title'])
        if m is None:
            continue

        rev = int(m.group(1))
        items[rev] = item

    min_rev = min(items.keys())
    max_rev = max(items.keys())
    ary = np.empty((2, max_rev - min_rev + 1))
    for rev, item in items.items():
        ary[0][rev - min_rev] = rev
        ary[1][rev - min_rev] = item['wall']

    fig = plt.figure()
    comb_plt = fig.add_subplot(211)
    other_plt = fig.add_subplot(212)

    comb_plt.plot(
        ary[0], np.cumsum(ary[1]), color='red', linewidth=1, label='comb'
    )

    plots = []
    p = other_plt.plot(ary[0], ary[1], color='red', linewidth=1, label='wall')
    plots.append(p)

    colors = {
        10: ('green', 'xkcd:grass green'),
        100: ('blue', 'xkcd:bright blue'),
        1000: ('purple', 'xkcd:dark pink'),
    }
    for n, color in colors.items():
        avg_n = np.convolve(ary[1], np.full(n, 1.0 / n), 'valid')
        p = other_plt.plot(
            ary[0][n - 1 :],
            avg_n,
            color=color[0],
            linewidth=1,
            label='avg time last %d' % n,
        )
        plots.append(p)

        med_n = scipy.signal.medfilt(ary[1], n + 1)
        p = other_plt.plot(
            ary[0],
            med_n,
            color=color[1],
            linewidth=1,
            label='median time last %d' % n,
        )
        plots.append(p)

    formatter = mticker.ScalarFormatter()
    formatter.set_scientific(False)
    formatter.set_useOffset(False)

    comb_plt.grid()
    comb_plt.xaxis.set_major_formatter(formatter)
    comb_plt.legend()

    other_plt.grid()
    other_plt.xaxis.set_major_formatter(formatter)
    leg = other_plt.legend()
    leg2plot = {}
    for legline, plot in zip(leg.get_lines(), plots):
        legline.set_picker(5)
        leg2plot[legline] = plot

    def onpick(event):
        legline = event.artist
        plot = leg2plot[legline]
        visible = not plot[0].get_visible()
        for l in plot:
            l.set_visible(visible)

        if visible:
            legline.set_alpha(1.0)
        else:
            legline.set_alpha(0.2)
        fig.canvas.draw()

    if title is not None:
        fig.canvas.set_window_title(title)
    fig.canvas.mpl_connect('pick_event', onpick)

    plt.show()


if __name__ == '__main__':
    import sys

    if len(sys.argv) > 1:
        print('reading from %r' % sys.argv[1])
        with open(sys.argv[1], 'r') as fp:
            plot(json.load(fp), title=sys.argv[1])
    else:
        print('reading from stdin')
        plot(json.load(sys.stdin))