mirror of https://github.com/ekimekim/wubloader
common: Split segment-related stuff into its own module
We still import them into __init__.py so they're accessible externally just the samepull/32/head
Mike Lang
6 years ago
committed by
Christopher Usher
parent
6f84a23ba6
commit
5175b099af
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"""A place for common utilities between wubloader components"""
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import base64
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import datetime
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import errno
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import itertools
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import logging
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import os
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import sys
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from collections import namedtuple
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import dateutil.parser
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from .stats import timed
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def unpadded_b64_decode(s):
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"""Decode base64-encoded string that has had its padding removed"""
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# right-pad with '=' to multiple of 4
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s = s + '=' * (- len(s) % 4)
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return base64.b64decode(s, "-_")
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class SegmentInfo(
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namedtuple('SegmentInfoBase', [
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'path', 'stream', 'variant', 'start', 'duration', 'is_partial', 'hash'
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])
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):
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"""Info parsed from a segment path, including original path.
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Note that start time is a datetime and duration is a timedelta, and hash is a decoded binary string."""
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@property
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def end(self):
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return self.start + self.duration
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def parse_segment_path(path):
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"""Parse segment path, returning a SegmentInfo. If path is only the trailing part,
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eg. just a filename, it will leave unknown fields as None."""
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parts = path.split('/')
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# left-pad parts with None up to 4 parts
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parts = [None] * (4 - len(parts)) + parts
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# pull info out of path parts
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stream, variant, hour, filename = parts[-4:]
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# split filename, which should be TIME-DURATION-TYPE-HASH.ts
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try:
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if not filename.endswith('.ts'):
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raise ValueError("Does not end in .ts")
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filename = filename[:-len('.ts')] # chop off .ts
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parts = filename.split('-', 3)
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if len(parts) != 4:
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raise ValueError("Not enough dashes in filename")
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time, duration, type, hash = parts
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if type not in ('full', 'partial'):
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raise ValueError("Unknown type {!r}".format(type))
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return SegmentInfo(
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path = path,
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stream = stream,
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variant = variant,
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start = dateutil.parser.parse("{}:{}".format(hour, time)),
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duration = datetime.timedelta(seconds=float(duration)),
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is_partial = type == "partial",
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hash = unpadded_b64_decode(hash),
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)
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except ValueError as e:
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# wrap error but preserve original traceback
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_, _, tb = sys.exc_info()
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raise ValueError, ValueError("Bad path {!r}: {}".format(path, e)), tb
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@timed(
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hours_path=lambda ret, hours_path, start, end: hours_path,
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has_holes=lambda ret, hours_path, start, end: None in ret,
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normalize=lambda ret, hours_path, start, end: len([x for x in ret if x is not None]),
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)
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def get_best_segments(hours_path, start, end):
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"""Return a list of the best sequence of non-overlapping segments
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we have for a given time range. Hours path should be the directory containing hour directories.
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Time args start and end should be given as datetime objects.
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The first segment may start before the time range, and the last may end after it.
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The returned list contains items that are either:
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SegmentInfo: a segment
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None: represents a discontinuity between the previous segment and the next one.
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ie. as long as two segments appear next to each other, we guarentee there is no gap between
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them, the second one starts right as the first one finishes.
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Similarly, unless the first item is None, the first segment starts <= the start of the time
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range, and unless the last item is None, the last segment ends >= the end of the time range.
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Example:
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Suppose you ask for a time range from 10 to 60. We have 10-second segments covering
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the following times:
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5 to 15
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15 to 25
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30 to 40
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40 to 50
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Then the output would look like:
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segment from 5 to 15
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segment from 15 to 25
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None, as the previous segment ends 5sec before the next one begins
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segment from 30 to 40
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segment from 40 to 50
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None, as the previous segment ends 10sec before the requested end time of 60.
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Note that any is_partial=True segment will be followed by a None, since we can't guarentee
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it joins on to the next segment fully intact.
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"""
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# Note: The exact equality checks in this function are not vulnerable to floating point error,
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# but only because all input dates and durations are only precise to the millisecond, and
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# python's datetime types represent these as integer microseconds internally. So the parsing
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# to these types is exact, and all operations on them are exact, so all operations are exact.
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result = []
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for hour in hour_paths_for_range(hours_path, start, end):
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# best_segments_by_start will give us the best available segment for each unique start time
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for segment in best_segments_by_start(hour):
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# special case: first segment
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if not result:
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# first segment is allowed to be before start as long as it includes it
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if segment.start <= start < segment.end:
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# segment covers start
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result.append(segment)
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elif start < segment.start < end:
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# segment is after start (but before end), so there was no segment that covers start
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# so we begin with a None
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result.append(None)
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result.append(segment)
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else:
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# segment is before start, and doesn't cover start, or starts after end.
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# ignore and go to next.
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continue
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else:
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# normal case: check against previous segment end time
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prev_end = result[-1].end
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if segment.start < prev_end:
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# Overlap! This shouldn't happen, though it might be possible due to weirdness
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# if the stream drops then starts again quickly. We simply ignore the overlapping
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# segment and let the algorithm continue.
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logging.warning("Overlapping segments: {} overlaps end of {}".format(segment, result[-1]))
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continue
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if result[-1].is_partial or prev_end < segment.start:
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# there's a gap between prev end and this start, so add a None
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result.append(None)
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result.append(segment)
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# check if we've reached the end
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if end <= segment.end:
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break
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# this is a weird little construct that says "if we broke from the inner loop,
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# then also break from the outer one. otherwise continue."
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else:
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continue
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break
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# check if we need a trailing None because last segment is partial or doesn't reach end
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if result and (result[-1].is_partial or result[-1].end < end):
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result.append(None)
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return result
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def hour_paths_for_range(hours_path, start, end):
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"""Generate a list of hour paths to check when looking for segments between start and end."""
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# truncate start and end to the hour
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def truncate(dt):
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return dt.replace(microsecond=0, second=0, minute=0)
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current = truncate(start)
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end = truncate(end)
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# Begin in the hour prior to start, as there may be a segment that starts in that hour
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# but contains the start time, eg. if the start time is 01:00:01 and there's a segment
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# at 00:59:59 which goes for 3 seconds.
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# Checking the entire hour when in most cases it won't be needed is wasteful, but it's also
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# pretty quick and the complexity of only checking this case when needed just isn't worth it.
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current -= datetime.timedelta(hours=1)
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while current <= end:
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yield os.path.join(hours_path, current.strftime("%Y-%m-%dT%H"))
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current += datetime.timedelta(hours=1)
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def best_segments_by_start(hour):
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"""Within a given hour path, yield the "best" segment per unique segment start time.
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Best is defined as non-partial, or failing that the longest partial.
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Note this means this function may perform os.stat()s in order to find the longest partial.
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"""
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try:
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segment_paths = os.listdir(hour)
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except OSError as e:
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if e.errno != errno.ENOENT:
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raise
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# path does not exist, treat it as having no files
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return
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segment_paths.sort()
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# note we only parse them as we need them, which is unlikely to save us much time overall
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# but is easy enough to do, so we might as well.
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parsed = (parse_segment_path(os.path.join(hour, name)) for name in segment_paths)
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for start_time, segments in itertools.groupby(parsed, key=lambda segment: segment.start):
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segments = list(segments)
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full_segments = [segment for segment in segments if not segment.is_partial]
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if full_segments:
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if len(full_segments) != 1:
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logging.warning("Multiple versions of full segment at start_time {}: {}".format(
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start_time, ", ".join(map(str, segments))
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))
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# We've observed some cases where the same segment (with the same hash) will be reported
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# with different durations (generally at stream end). Prefer the longer duration,
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# as this will ensure that if hashes are different we get the most data, and if they
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# are the same it should keep holes to a minimum.
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# If same duration, we have to pick one, so pick highest-sorting hash just so we're consistent.
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full_segments = [max(full_segments, key=lambda segment: (segment.duration, segment.hash))]
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yield full_segments[0]
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continue
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# no full segments, fall back to measuring partials.
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yield max(segments, key=lambda segment: os.stat(segment.path).st_size)
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