| 1 |
import datetime |
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| 2 |
import linecache |
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| 3 |
import os |
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| 4 |
import sys |
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| 5 |
import thread |
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| 6 |
import threading |
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| 7 |
|
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| 8 |
__version__ = "0.2" |
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| 9 |
|
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| 10 |
delta_zero = datetime.timedelta(0) |
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| 11 |
|
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| 12 |
|
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microseconds = usec = 1e6 |
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| 14 |
milliseconds = msec = 1e3 |
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| 15 |
seconds = 1 |
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| 16 |
minutes = 1 / 60.0 |
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| 17 |
hours = 1 / 3600.0 |
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| 18 |
|
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| 19 |
|
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| 20 |
def seconds(td): |
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| 21 |
"""Return the given timedelta as a floating-point number of seconds.""" |
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| 22 |
return (td.days * 86400) + td.seconds + (td.microseconds / 1e6) |
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| 23 |
|
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| 24 |
class Race(list): |
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| 25 |
"""A list of elapsed times.""" |
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| 26 |
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| 27 |
start = None |
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| 28 |
end = None |
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| 29 |
clicktime = None |
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| 30 |
|
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| 31 |
|
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| 32 |
class Stopwatch(object): |
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| 33 |
"""A thread-safe code timer. |
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| 34 |
|
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| 35 |
Usage: |
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| 36 |
sw = Stopwatch() |
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| 37 |
sw.click('start') |
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| 38 |
foo |
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| 39 |
sw.click('foo done') |
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| 40 |
bar |
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| 41 |
sw.click('bar done') |
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| 42 |
baz |
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| 43 |
sw.click() |
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| 44 |
print sw.format() |
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| 45 |
sw.reset() |
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| 46 |
|
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| 47 |
Clicks and Races |
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| 48 |
---------------- |
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| 49 |
|
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| 50 |
When you call the "click" method, you store the elapsed time since the |
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| 51 |
previous click (or 0 if this is the first click). When you call the "reset" |
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| 52 |
method, that collection of elapsed times (and any labels) is stored as |
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| 53 |
an individual "race" in self.races. |
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| 54 |
|
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| 55 |
Swimlanes |
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| 56 |
--------- |
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| 57 |
|
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| 58 |
By default, calls to the "click" method are threadsafe; that is, |
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| 59 |
you can use the same Stopwatch instance in multiple threads at the |
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| 60 |
same time. Each thread runs its own race. |
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| 61 |
|
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| 62 |
Sometimes, however, you want to collect clicks across threads, |
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| 63 |
or collect several 'races' of clicks in parallel within a single- |
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| 64 |
threaded application. In these cases, you can supply any hashable |
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| 65 |
value, or callable which produces a hashable value, as the swimlane |
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| 66 |
argument to the constructor, and it will be used to isolate and |
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| 67 |
aggregate clicks for that value. You can also pass individual |
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| 68 |
swimlane arguments to the "click", "reset", and "format" methods. |
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| 69 |
For example, you might be tracking various updates to a database |
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| 70 |
row across several web requests; you can pass the row's PK as the |
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| 71 |
swimlane argument to collect those clicks() together into a single |
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| 72 |
race. |
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| 73 |
|
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| 74 |
Note that clicks are stored in RAM, so all clicks within the same race |
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| 75 |
need to at least occur in the same process, if not the same thread. |
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| 76 |
""" |
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| 77 |
|
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| 78 |
races = None |
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| 79 |
"""An ordered list of Race objects (lists of (index from self.points, elapsed)).""" |
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| 80 |
|
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| 81 |
points = None |
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| 82 |
"""A dict of (label, index) pairs.""" |
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| 83 |
|
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| 84 |
_current = None |
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| 85 |
swimlane = None |
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| 86 |
format_template = u"ST\u00f6PWATCH start: %(start)s clicks: %(points)s \u03a3: %(total)s" |
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| 87 |
|
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| 88 |
def __init__(self, swimlane=thread.get_ident): |
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| 89 |
self.points = {} |
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| 90 |
self.clear() |
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| 91 |
self.swimlane = swimlane |
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| 92 |
|
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| 93 |
def get_current(self, swimlane=None): |
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| 94 |
"""Return the current race, creating a new Race if neceessary. |
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| 95 |
|
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| 96 |
If swimlane is None, self.swimlane is used. |
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| 97 |
""" |
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| 98 |
if swimlane is None: |
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| 99 |
swimlane = self.swimlane |
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| 100 |
if callable(swimlane): |
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| 101 |
swimlane = swimlane() |
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| 102 |
try: |
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| 103 |
return self._current[swimlane] |
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| 104 |
except KeyError: |
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| 105 |
race = Race() |
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| 106 |
self._current[swimlane] = race |
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| 107 |
return race |
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| 108 |
current = property(get_current, doc="The current race") |
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| 109 |
|
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| 110 |
def click(self, label=None, swimlane=None): |
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| 111 |
"""Record the elapsed time, using a label if given. |
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| 112 |
|
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| 113 |
If this is the first click for the current race, |
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| 114 |
datetime.timedelta(0) is recorded as the elapsed time. |
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| 115 |
|
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| 116 |
If swimlane is None, self.swimlane is used. |
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| 117 |
""" |
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| 118 |
now = datetime.datetime.now() |
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| 119 |
race = self.get_current(swimlane) |
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| 120 |
|
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| 121 |
if race.clicktime is None: |
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| 122 |
elapsed = delta_zero |
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| 123 |
race.start = now |
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| 124 |
else: |
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| 125 |
elapsed = now - race.clicktime |
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| 126 |
race.clicktime = now |
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| 127 |
|
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| 128 |
line_count = len(self.points) |
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| 129 |
if label is None: |
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| 130 |
label = u'Point %d' % line_count |
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| 131 |
|
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| 132 |
idx = self.points.setdefault(label, line_count) |
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| 133 |
race.append((idx, elapsed)) |
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| 134 |
|
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| 135 |
def get_labels(self): |
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| 136 |
"""Return a dict of (idx, label) pairs from self.points.""" |
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| 137 |
|
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| 138 |
|
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| 139 |
|
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| 140 |
return dict((idx, label) for (label, idx) in self.points.iteritems()) |
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| 141 |
|
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| 142 |
def reset(self, swimlane=None, record=True): |
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| 143 |
"""Stop and return the current race. If 'record', store it in self.races. |
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| 144 |
|
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| 145 |
If swimlane is None, self.swimlane is used. |
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| 146 |
""" |
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| 147 |
if swimlane is None: |
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| 148 |
swimlane = self.swimlane |
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| 149 |
if callable(swimlane): |
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| 150 |
swimlane = swimlane() |
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| 151 |
|
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| 152 |
current = self._current.pop(swimlane, Race()) |
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| 153 |
|
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| 154 |
current.end = current.clicktime |
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| 155 |
|
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| 156 |
if record: |
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| 157 |
self.races.append(current) |
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| 158 |
|
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| 159 |
return current |
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| 160 |
|
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| 161 |
def clear(self): |
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| 162 |
"""Remove all current and recorded races.""" |
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| 163 |
self.races = [] |
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| 164 |
self._current = {} |
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| 165 |
|
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| 166 |
def format(self, race=None, swimlane=None): |
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| 167 |
"""Return the current race in a format suitable for logging. |
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| 168 |
|
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| 169 |
If race is None, the current race (defined either by the given swimlane |
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| 170 |
or self.swimlane) will be used. |
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| 171 |
""" |
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| 172 |
if race is None: |
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| 173 |
race = self.get_current(swimlane) |
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| 174 |
|
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| 175 |
labels = self.get_labels() |
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| 176 |
p = {'points': u"".join([u"[%s=%s]" % (labels[idx], td) |
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| 177 |
for idx, td in race]), |
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| 178 |
'start': race.start, |
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| 179 |
'total': sum([td for idx, td in race], delta_zero), |
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| 180 |
} |
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| 181 |
return self.format_template % p |
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| 182 |
|
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| 183 |
def _filter_minima(self, minimum): |
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| 184 |
"""Return {idx: bool(c.peak/total >= minimum)} for c in self.points.""" |
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| 185 |
mask = dict((idx, False) for idx in self.points.itervalues()) |
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| 186 |
for race in self.races: |
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| 187 |
tot = sum([td for idx, td in race], delta_zero) |
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| 188 |
if tot: |
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| 189 |
tot = seconds(tot) |
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| 190 |
for idx, td in race: |
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| 191 |
if mask[idx]: |
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| 192 |
|
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| 193 |
continue |
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| 194 |
if (seconds(td) / tot) >= minimum: |
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mask[idx] = True |
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| 196 |
if False not in mask.itervalues(): |
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| 197 |
return mask |
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| 198 |
return mask |
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| 199 |
|
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| 200 |
def csv_gen(self, scale=1, minimum=None): |
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| 201 |
"""Yield CSV lines for all races recorded by this stopwatch. |
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| 202 |
|
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| 203 |
All numbers yielded will be multiplied by the 'scale' argument, which |
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| 204 |
defaults to 1. Use stopwatch.usec (1e6), for example, to output |
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| 205 |
microseconds instead of seconds with fractions. |
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| 206 |
|
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| 207 |
If 'minimum' is provided, it must be a fraction between 0.0 and 1.0, |
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| 208 |
and will be used to filter out lines which have no peak times |
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| 209 |
above the minimum percentage given of the total time for each race. |
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| 210 |
For example, if minimum is 0.1, then for each column, at least one |
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| 211 |
race must have that column take 10% of the total time for that race; |
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| 212 |
if no such race exists, the column will not be included in the output. |
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| 213 |
However, if any lines are filtered out in this way, an "Extra" |
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| 214 |
column is included with the sum of all removed lines for each race. |
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| 215 |
This allows you to reduce output width but still make proper percentage |
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| 216 |
calculations wih the displayed lines. |
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| 217 |
""" |
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| 218 |
if minimum: |
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| 219 |
minmask = self._filter_minima(minimum) |
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| 220 |
else: |
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| 221 |
minmask = {} |
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| 222 |
|
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| 223 |
if False not in minmask.itervalues(): |
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| 224 |
|
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| 225 |
labels = self.get_labels() |
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| 226 |
order = self.points.values() |
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| 227 |
order.sort() |
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| 228 |
|
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| 229 |
header = [] |
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| 230 |
for idx in order: |
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label = labels[idx] |
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| 232 |
if not isinstance(label, basestring): |
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| 233 |
label = repr(label) |
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| 234 |
header.append('"%s"' % label.replace('"', '""')) |
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| 235 |
yield u",".join(header) + os.linesep |
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| 236 |
|
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for race in self.races: |
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cells = [""] * len(order) |
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| 239 |
for idx, td in race: |
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cells[order.index(idx)] = "%f" % (seconds(td) * scale) |
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| 241 |
yield u",".join(cells) + os.linesep |
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| 242 |
else: |
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| 243 |
labels = self.get_labels() |
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| 244 |
order = [idx for idx in minmask if minmask[idx]] |
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| 245 |
order.sort() |
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| 246 |
|
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| 247 |
header = [] |
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| 248 |
for idx in order: |
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label = labels[idx] |
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| 250 |
if not isinstance(label, basestring): |
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label = repr(label) |
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| 252 |
header.append('"%s"' % label.replace('"', '""')) |
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| 253 |
header.append(u'"Extra"') |
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| 254 |
yield u",".join(header) + os.linesep |
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| 255 |
|
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| 256 |
for race in self.races: |
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| 257 |
cells = [""] * len(order) |
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| 258 |
extra = 0 |
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| 259 |
for idx, td in race: |
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| 260 |
td = (seconds(td) * scale) |
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| 261 |
if minmask[idx]: |
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| 262 |
cells[order.index(idx)] = "%f" % td |
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| 263 |
else: |
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| 264 |
extra += td |
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| 265 |
cells.append("%f" % extra) |
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| 266 |
yield u",".join(cells) + os.linesep |
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| 267 |
|
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| 268 |
def write_csv(self, file, mode="ab+", scale=1, minimum=None): |
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| 269 |
"""Write CSV lines for all races recorded by this stopwatch to a file. |
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| 270 |
|
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| 271 |
All numbers yielded will be multiplied by the 'scale' argument, which |
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| 272 |
defaults to 1. Use stopwatch.usec (1e6), for example, to output |
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| 273 |
microseconds instead of seconds with fractions. |
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| 274 |
""" |
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| 275 |
|
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| 276 |
open(file, mode).writelines(self.csv_gen(scale=scale, minimum=minimum)) |
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| 277 |
|
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| 278 |
def totals(self): |
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| 279 |
"""Return the total of all races (as a race itself). |
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| 280 |
|
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| 281 |
For example, given the races: |
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| 282 |
|
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| 283 |
Race([(0, td("00:00")), (1, td("00:02")), (2, td("00:04"))]) |
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| 284 |
Race([(0, td("00:00")), (1, td("00:04")), (2, td("00:08"))]) |
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| 285 |
Race([(0, td("00:00")), (1, td("00:06")), (2, td("00:18"))]) |
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| 286 |
|
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| 287 |
This will return: |
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| 288 |
|
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| 289 |
Race([(0, td("00:00")), (1, td("00:12")), (2, td("00:30"))]) |
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| 290 |
""" |
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| 291 |
t = dict((idx, delta_zero) for idx in self.points.itervalues()) |
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| 292 |
for race in self.races: |
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| 293 |
for idx, elapsed in race: |
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| 294 |
if elapsed: |
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| 295 |
t[idx] += elapsed |
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| 296 |
totalrace = Race(sorted(t.items())) |
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| 297 |
if self.races: |
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| 298 |
totalrace.start = self.races[0].start |
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| 299 |
totalrace.end = self.races[-1].end |
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| 300 |
return totalrace |
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| 301 |
|
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| 302 |
def average(self): |
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| 303 |
"""Return the average of all races (as a race itself). |
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| 304 |
|
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| 305 |
For example, given the races: |
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| 306 |
|
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| 307 |
Race([(0, td("00:00")), (1, td("00:02")), (2, td("00:04"))]) |
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| 308 |
Race([(0, td("00:00")), (1, td("00:04")), (2, td("00:08"))]) |
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| 309 |
Race([(0, td("00:00")), (1, td("00:06")), (2, td("00:18"))]) |
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| 310 |
|
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| 311 |
This will return: |
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| 312 |
|
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| 313 |
Race([(0, td("00:00")), (1, td("00:04")), (2, td("00:10"))]) |
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| 314 |
""" |
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| 315 |
t = self.totals() |
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| 316 |
|
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| 317 |
numraces = len(self.races) |
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| 318 |
avgrace = Race([(idx, (td / numraces)) for idx, td in t]) |
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| 319 |
if self.races: |
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| 320 |
avgrace.start = self.races[0].start |
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| 321 |
avgrace.end = self.races[-1].end |
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| 322 |
return avgrace |
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| 323 |
|
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| 324 |
|
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| 325 |
class _GlobalHookLocalStorage(threading.local): |
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| 326 |
|
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| 327 |
def __init__(self): |
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| 328 |
self.settrace_depth = 0 |
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| 329 |
self.swimlane = 0 |
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| 330 |
|
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| 331 |
|
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| 332 |
class _GlobalTraceHook(list): |
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| 333 |
|
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| 334 |
local = _GlobalHookLocalStorage() |
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| 335 |
|
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| 336 |
def append(self, autowatch): |
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| 337 |
|
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| 338 |
list.append(self, autowatch) |
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| 339 |
|
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| 340 |
|
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| 341 |
|
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| 342 |
if self.local.settrace_depth == 0: |
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| 343 |
|
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| 344 |
|
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| 345 |
|
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| 346 |
sys.settrace(self.hook) |
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| 347 |
|
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| 348 |
|
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| 349 |
self.local.swimlane = max(autowatch.watch._current.keys() + [0]) |
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| 350 |
|
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| 351 |
self.local.settrace_depth += 1 |
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| 352 |
|
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| 353 |
def remove(self, autowatch): |
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| 354 |
self.local.settrace_depth -= 1 |
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| 355 |
if self.local.settrace_depth == 0: |
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| 356 |
sys.settrace(None) |
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| 357 |
autowatch.watch.reset(swimlane=self.local.swimlane) |
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| 358 |
list.remove(self, autowatch) |
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| 359 |
|
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| 360 |
def hook(self, frame, event, arg): |
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| 361 |
if event == 'call': |
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| 362 |
for autowatch in self[:]: |
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| 363 |
curframe = frame |
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| 364 |
for hop in xrange(autowatch.depth): |
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| 365 |
if curframe.f_code is autowatch.target.func_code: |
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| 366 |
if ( |
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| 367 |
autowatch._instance is None or |
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| 368 |
|
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| 369 |
|
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| 370 |
autowatch._instance in curframe.f_locals.values()): |
|---|
| 371 |
return _LocalTraceHook(autowatch, self.local.swimlane, hop) |
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| 372 |
break |
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| 373 |
|
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| 374 |
curframe = curframe.f_back |
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| 375 |
if curframe is None: |
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| 376 |
break |
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| 377 |
return None |
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| 378 |
_globaltracehook = _GlobalTraceHook() |
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| 379 |
|
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| 380 |
|
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| 381 |
class _LocalTraceHook(object): |
|---|
| 382 |
|
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| 383 |
lastline = None |
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| 384 |
|
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| 385 |
def __init__(self, autowatch, swimlane, depth): |
|---|
| 386 |
self.autowatch = autowatch |
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| 387 |
self.swimlane = swimlane |
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| 388 |
self.depth = depth |
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| 389 |
|
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| 390 |
def __call__(self, frame, event, arg): |
|---|
| 391 |
if event in ('line', 'return', 'exception'): |
|---|
| 392 |
filename = frame.f_globals["__file__"] |
|---|
| 393 |
if (filename.endswith(".pyc") or |
|---|
| 394 |
filename.endswith(".pyo")): |
|---|
| 395 |
filename = filename[:-1] |
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| 396 |
|
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| 397 |
if self.lastline is None: |
|---|
| 398 |
|
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| 399 |
self.lastline = (filename, frame.f_lineno - 1, self.depth) |
|---|
| 400 |
|
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| 401 |
self.autowatch.watch.click(self.lastline, swimlane=self.swimlane) |
|---|
| 402 |
|
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| 403 |
if event == 'line': |
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| 404 |
|
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| 405 |
self.lastline = (filename, frame.f_lineno, self.depth) |
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| 406 |
|
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| 407 |
return self |
|---|
| 408 |
|
|---|
| 409 |
|
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| 410 |
class Autowatch(object): |
|---|
| 411 |
"""A wrapper to automatically watch significant lines of a single function. |
|---|
| 412 |
|
|---|
| 413 |
Usage: |
|---|
| 414 |
|
|---|
| 415 |
# Wrap the target func |
|---|
| 416 |
obj.func = Autowatch(obj.func, ) |
|---|
| 417 |
# Wait for some timing data to accumulate |
|---|
| 418 |
time.passes() |
|---|
| 419 |
# Unwrap our wrapper |
|---|
| 420 |
obj.func = obj.func.target |
|---|
| 421 |
""" |
|---|
| 422 |
|
|---|
| 423 |
def __init__(self, target, watch=None, enabled=True, depth=1, |
|---|
| 424 |
_instance=None, on_finish=None): |
|---|
| 425 |
self.target = target |
|---|
| 426 |
self.watch = watch or Stopwatch() |
|---|
| 427 |
self.enabled = enabled |
|---|
| 428 |
self.depth = depth |
|---|
| 429 |
self.swimlane = id(self) |
|---|
| 430 |
while self.swimlane in self.watch._current: |
|---|
| 431 |
self.swimlane += 1 |
|---|
| 432 |
self._instance = _instance |
|---|
| 433 |
self.on_finish = on_finish |
|---|
| 434 |
|
|---|
| 435 |
def trace(self): |
|---|
| 436 |
_globaltracehook.append(self) |
|---|
| 437 |
|
|---|
| 438 |
def untrace(self): |
|---|
| 439 |
_globaltracehook.remove(self) |
|---|
| 440 |
|
|---|
| 441 |
@property |
|---|
| 442 |
def is_tracing(self): |
|---|
| 443 |
return self in _globaltracehook |
|---|
| 444 |
|
|---|
| 445 |
def __call__(self, *args, **kwargs): |
|---|
| 446 |
if not self.enabled: |
|---|
| 447 |
if self._instance is None: |
|---|
| 448 |
return self.target(*args, **kwargs) |
|---|
| 449 |
else: |
|---|
| 450 |
return self.target(self._instance, *args, **kwargs) |
|---|
| 451 |
|
|---|
| 452 |
try: |
|---|
| 453 |
self.trace() |
|---|
| 454 |
if self._instance is None: |
|---|
| 455 |
result = self.target(*args, **kwargs) |
|---|
| 456 |
else: |
|---|
| 457 |
result = self.target(self._instance, *args, **kwargs) |
|---|
| 458 |
finally: |
|---|
| 459 |
self.untrace() |
|---|
| 460 |
|
|---|
| 461 |
if self.on_finish: |
|---|
| 462 |
self.on_finish(self) |
|---|
| 463 |
|
|---|
| 464 |
return result |
|---|
| 465 |
|
|---|
| 466 |
def __get__(self, instance, owner): |
|---|
| 467 |
if instance is None: |
|---|
| 468 |
return self |
|---|
| 469 |
|
|---|
| 470 |
|
|---|
| 471 |
|
|---|
| 472 |
return self.__class__( |
|---|
| 473 |
target=self.target, watch=self.watch, enabled=self.enabled, |
|---|
| 474 |
depth=self.depth, _instance=instance, on_finish=self.on_finish) |
|---|
| 475 |
|
|---|
| 476 |
def get_trace(self, race): |
|---|
| 477 |
"""Yield (filename, lineno, depth, linetext, elapsed td) for each race.""" |
|---|
| 478 |
labels = self.watch.get_labels() |
|---|
| 479 |
for idx, td in race: |
|---|
| 480 |
filename, lineno, depth = labels[idx] |
|---|
| 481 |
yield (filename, lineno, depth, |
|---|
| 482 |
linecache.getline(filename, lineno).rstrip()[:80], td) |
|---|
| 483 |
|
|---|
| 484 |
def report(self, race): |
|---|
| 485 |
"""Yield (filename, lineno, depth, linetext, elapsed td) for each race. |
|---|
| 486 |
|
|---|
| 487 |
The last line yielded will be ("", 0, -1, "", total time). |
|---|
| 488 |
""" |
|---|
| 489 |
subtotals = [] |
|---|
| 490 |
for filename, lineno, depth, text, td in self.get_trace(race): |
|---|
| 491 |
if depth > len(subtotals) - 1: |
|---|
| 492 |
subtotals.append(delta_zero) |
|---|
| 493 |
elif depth < len(subtotals) - 1: |
|---|
| 494 |
td = subtotals.pop() |
|---|
| 495 |
else: |
|---|
| 496 |
subtotals = [t + td for t in subtotals] |
|---|
| 497 |
|
|---|
| 498 |
yield filename, lineno, depth, text, td |
|---|
| 499 |
|
|---|
| 500 |
if subtotals: |
|---|
| 501 |
yield "", 0, -1, "", subtotals[0] |
|---|
| 502 |
else: |
|---|
| 503 |
yield "", 0, -1, "", delta_zero |
|---|
| 504 |
|
|---|
| 505 |
def format(self, race, filedepth=2, percent_to_mark=10): |
|---|
| 506 |
"""Yield a list of formatted lines reporting on the given race.""" |
|---|
| 507 |
tds = [(line[-1], i) for i, line in enumerate(self.report(race))] |
|---|
| 508 |
tds.sort() |
|---|
| 509 |
tds = tds[-int(len(tds) * (percent_to_mark / 100.0)):] |
|---|
| 510 |
top_i = [i for td, i in tds] |
|---|
| 511 |
del tds |
|---|
| 512 |
|
|---|
| 513 |
for i, line in enumerate(self.report(race)): |
|---|
| 514 |
filename, lineno, depth, text, td = line |
|---|
| 515 |
yield ('%s%s<%s:%d>%s (%s)' % |
|---|
| 516 |
('*' if i in top_i else ' ', '-' * (depth * 4), |
|---|
| 517 |
'/'.join(filename.split('/')[-filedepth:]), |
|---|
| 518 |
lineno, text, td)) |
|---|
| 519 |
|
|---|
| 520 |
|
|---|
| 521 |
def autowatch(watch=None, enabled=True, depth=1): |
|---|
| 522 |
"""A decorator to automatically watch significant lines of a single function. |
|---|
| 523 |
|
|---|
| 524 |
Usage: |
|---|
| 525 |
|
|---|
| 526 |
@stopwatch.autowatch() |
|---|
| 527 |
def f(a, b, c): |
|---|
| 528 |
... |
|---|
| 529 |
|
|---|
| 530 |
[f(1, 2, 3) for i in range(100)] |
|---|
| 531 |
f.watch.write_csv('f.csv', scale=stopwatch.usec, minimum=0.1) |
|---|
| 532 |
""" |
|---|
| 533 |
def autowatch_wrapper(f): |
|---|
| 534 |
return Autowatch(target=f, watch=watch, enabled=enabled, depth=depth) |
|---|
| 535 |
return autowatch_wrapper |
|---|
| 536 |
|
|---|