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wubloader/common/common/segments.py

837 lines
31 KiB
Python

"""A place for common utilities between wubloader components"""
import base64
import datetime
import errno
import itertools
import json
import logging
import os
import shutil
from collections import namedtuple
from contextlib import closing
from tempfile import TemporaryFile
from uuid import uuid4
import gevent
from gevent import subprocess
from .cached_iterator import CachedIterator
from .stats import timed
from .fixts import FixTS
def unpadded_b64_decode(s):
"""Decode base64-encoded string that has had its padding removed.
Note it takes a unicode and returns a bytes."""
# right-pad with '=' to multiple of 4
s = s + '=' * (- len(s) % 4)
return base64.b64decode(s.encode(), b"-_")
class SegmentInfo(
namedtuple('SegmentInfoBase', [
'path', 'channel', 'quality', 'start', 'duration', 'type', 'hash'
])
):
"""Info parsed from a segment path, including original path.
Note that start time is a datetime and duration is a timedelta, and hash is a decoded binary string."""
@property
def end(self):
return self.start + self.duration
@property
def is_partial(self):
"""Note that suspect is considered partial"""
return self.type != "full"
def parse_segment_timestamp(hour_str, min_str):
"""This is faster than strptime, which dominates our segment processing time.
It takes strictly formatted hour = "%Y-%m-%dT%H" and time = "%M:%S.%f"."""
year = int(hour_str[0:4])
month = int(hour_str[5:7])
day = int(hour_str[8:10])
hour = int(hour_str[11:13])
min = int(min_str[0:2])
sec = int(min_str[3:5])
microsec_str = min_str[6:]
microsec_str += '0' * (6 - len(microsec_str)) # right-pad zeros to 6 digits, eg. "123" -> "123000"
microsec = int(microsec_str)
return datetime.datetime(year, month, day, hour, min, sec, microsec)
def parse_segment_path(path):
"""Parse segment path, returning a SegmentInfo. If path is only the trailing part,
eg. just a filename, it will leave unknown fields as None."""
parts = path.split('/')
# left-pad parts with None up to 4 parts
parts = [None] * (4 - len(parts)) + parts
# pull info out of path parts
channel, quality, hour, filename = parts[-4:]
# split filename, which should be TIME-DURATION-TYPE-HASH.ts
try:
if not filename.endswith('.ts'):
raise ValueError("Does not end in .ts")
filename = filename[:-len('.ts')] # chop off .ts
parts = filename.split('-', 3)
if len(parts) != 4:
raise ValueError("Not enough dashes in filename")
time, duration, type, hash = parts
if type not in ('full', 'suspect', 'partial', 'temp'):
raise ValueError("Unknown type {!r}".format(type))
hash = None if type == 'temp' else unpadded_b64_decode(hash)
start = None if hour is None else parse_segment_timestamp(hour, time)
return SegmentInfo(
path = path,
channel = channel,
quality = quality,
start = start,
duration = datetime.timedelta(seconds=float(duration)),
type = type,
hash = hash,
)
except ValueError as e:
# wrap error but preserve original traceback
raise ValueError("Bad path {!r}: {}".format(path, e)).with_traceback(e.__traceback__)
class ContainsHoles(Exception):
"""Raised by get_best_segments() when a hole is found and allow_holes is False"""
def get_best_segments_for_frame(hour_path, timestamp):
# Add some leeway before and after so that we don't have errors related to
# landing on a segment edge.
leeway = datetime.timedelta(seconds=1)
return get_best_segments(hour_path, timestamp - leeway, timestamp + leeway)
@timed(
hours_path=lambda ret, hours_path, *args, **kwargs: hours_path,
has_holes=lambda ret, *args, **kwargs: None in ret,
normalize=lambda ret, *args, **kwargs: len([x for x in ret if x is not None]),
)
def get_best_segments(hours_path, start, end, allow_holes=True):
"""Return a list of the best sequence of non-overlapping segments
we have for a given time range. Hours path should be the directory containing hour directories.
Time args start and end should be given as datetime objects.
The first segment may start before the time range, and the last may end after it.
The returned list contains items that are either:
SegmentInfo: a segment
None: represents a discontinuity between the previous segment and the next one.
ie. as long as two segments appear next to each other, we guarentee there is no gap between
them, the second one starts right as the first one finishes.
Similarly, unless the first item is None, the first segment starts <= the start of the time
range, and unless the last item is None, the last segment ends >= the end of the time range.
Example:
Suppose you ask for a time range from 10 to 60. We have 10-second segments covering
the following times:
5 to 15
15 to 25
30 to 40
40 to 50
Then the output would look like:
segment from 5 to 15
segment from 15 to 25
None, as the previous segment ends 5sec before the next one begins
segment from 30 to 40
segment from 40 to 50
None, as the previous segment ends 10sec before the requested end time of 60.
Note that any is_partial=True segment will be followed by a None, since we can't guarentee
it joins on to the next segment fully intact.
If allow_holes is False, then we fail fast at the first discontinuity found
and raise ContainsHoles. If ContainsHoles is not raised, the output is guarenteed to not contain
any None items.
"""
# Note: The exact equality checks in this function are not vulnerable to floating point error,
# but only because all input dates and durations are only precise to the millisecond, and
# python's datetime types represent these as integer microseconds internally. So the parsing
# to these types is exact, and all operations on them are exact, so all operations are exact.
# ...however in the wild we sometimes see timestamps or durations that differ by a few ms.
# So we allow some fudge factors.
ALLOWABLE_OVERLAP = 0.01 # 10ms
ALLOWABLE_GAP = 0.01 # 10ms
result = []
for hour in hour_paths_for_range(hours_path, start, end):
# Especially when processing multiple hours, this routine can take a signifigant amount
# of time with no blocking. To ensure other stuff is still completed in a timely fashion,
# we yield to let other things run.
gevent.idle()
# best_segments_by_start will give us the best available segment for each unique start time
for segment in best_segments_by_start(hour):
# special case: first segment
if not result:
# first segment is allowed to be before start as long as it includes it
if segment.start <= start < segment.end:
# segment covers start
result.append(segment)
elif start < segment.start < end:
# segment is after start (but before end), so there was no segment that covers start
# so we begin with a None
if not allow_holes:
raise ContainsHoles
result.append(None)
result.append(segment)
else:
# segment is before start, and doesn't cover start, or starts after end.
# ignore and go to next.
continue
else:
# normal case: check against previous segment end time
prev_end = result[-1].end
gap = (segment.start - prev_end).total_seconds()
if gap < -ALLOWABLE_OVERLAP:
# Overlap! This shouldn't happen, though it might be possible due to weirdness
# if the stream drops then starts again quickly. We simply ignore the overlapping
# segment and let the algorithm continue.
logging.info("Overlapping segments: {} overlaps end of {}".format(segment, result[-1]))
continue
if result[-1].is_partial or gap > ALLOWABLE_GAP:
# there's a gap between prev end and this start, so add a None
if not allow_holes:
raise ContainsHoles
result.append(None)
result.append(segment)
# check if we've reached the end
if end <= segment.end:
break
# this is a weird little construct that says "if we broke from the inner loop,
# then also break from the outer one. otherwise continue."
else:
continue
break
# check if we need a trailing None because last segment is partial or doesn't reach end,
# or we found nothing at all
if not result or result[-1].is_partial or result[-1].end < end:
if not allow_holes:
raise ContainsHoles
result.append(None)
return result
def hour_paths_for_range(hours_path, start, end):
"""Generate a list of hour paths to check when looking for segments between start and end."""
# truncate start and end to the hour
def truncate(dt):
return dt.replace(microsecond=0, second=0, minute=0)
current = truncate(start)
end = truncate(end)
# Begin in the hour prior to start, as there may be a segment that starts in that hour
# but contains the start time, eg. if the start time is 01:00:01 and there's a segment
# at 00:59:59 which goes for 3 seconds.
# Checking the entire hour when in most cases it won't be needed is wasteful, but it's also
# pretty quick and the complexity of only checking this case when needed just isn't worth it.
current -= datetime.timedelta(hours=1)
while current <= end:
yield os.path.join(hours_path, current.strftime("%Y-%m-%dT%H"))
current += datetime.timedelta(hours=1)
def list_segment_files(hour_path, include_tombstones=False, include_chat=False):
"""Return a list of filenames of segments in the given hour path.
Segment names are not parsed or verified, but only non-hidden .ts files
without an associated tombstone file will be listed.
If include_tombstones = true, the tombstone files themselves will also be listed.
If include_chat = true, .json files will also be listed.
"""
try:
names = os.listdir(hour_path)
except OSError as e:
if e.errno != errno.ENOENT:
raise
# path does not exist, treat it as having no files
return []
# Split into name and extension, this makes the later processing easier.
# Note that ext will include the leading dot, ie. "foo.bar" -> ("foo", ".bar").
# Files with no extension produce empty string, ie. "foo" -> ("foo", "")
# and files with leading dots treat them as part of the name, ie. ".foo" -> (".foo", "").
splits = [os.path.splitext(name) for name in names]
# Look for any tombstone files, which indicate we should treat the segment file of the same
# name as though it doesn't exist.
tombstones = [name for name, ext in splits if ext == '.tombstone']
# Return non-hidden ts files, except those that match a tombstone.
segments = [
name + ext for name, ext in splits
if name not in tombstones
and (ext == ".ts" or (include_chat and ext == ".json"))
and not name.startswith('.')
]
if include_tombstones:
return segments + ["{}.tombstone".format(name) for name in tombstones]
else:
return segments
# Maps hour path to (directory contents, cached result).
# If the directory contents are identical, then we can use the cached result for that hour
# instead of re-calculating. If they have changed, we throw out the cached result.
# Since best_segments_by_start returns an iterator that may not be entirely consumed,
# our cached result stores both all results returned so far, and the live iterator
# in case we need to continue consuming.
_best_segments_by_start_cache = {}
def best_segments_by_start(hour):
"""Within a given hour path, yield the "best" segment per unique segment start time.
Best is defined as type=full, or failing that type=suspect, or failing that the longest type=partial.
Note this means this function may perform os.stat()s.
"""
segment_paths = list_segment_files(hour)
segment_paths.sort()
# if result is in the cache and the segment_paths haven't changed, return cached result
if hour in _best_segments_by_start_cache:
prev_segment_paths, cached_result = _best_segments_by_start_cache[hour]
if prev_segment_paths == segment_paths:
return cached_result
# otherwise create new result and cache it
result = CachedIterator(_best_segments_by_start(hour, segment_paths))
_best_segments_by_start_cache[hour] = segment_paths, result
return result
def _best_segments_by_start(hour, segment_paths):
# raise a warning for any files that don't parse as segments and ignore them
parsed = []
for name in segment_paths:
try:
parsed.append(parse_segment_path(os.path.join(hour, name)))
except ValueError:
logging.warning("Failed to parse segment {!r}".format(os.path.join(hour, name)), exc_info=True)
for start_time, segments in itertools.groupby(parsed, key=lambda segment: segment.start):
# ignore temp segments as they might go away by the time we want to use them
segments = [segment for segment in segments if segment.type != "temp"]
if not segments:
# all segments were temp, move on
continue
full_segments = [segment for segment in segments if not segment.is_partial]
if full_segments:
if len(full_segments) != 1:
logging.info("Multiple versions of full segment at start_time {}: {}".format(
start_time, ", ".join(map(str, segments))
))
# We've observed some cases where the same segment (with the same hash) will be reported
# with different durations (generally at stream end). Prefer the longer duration (followed by longest size),
# as this will ensure that if hashes are different we get the most data, and if they
# are the same it should keep holes to a minimum.
# If same duration and size, we have to pick one, so pick highest-sorting hash just so we're consistent.
sizes = {segment: os.stat(segment.path).st_size for segment in segments}
full_segments = [max(full_segments, key=lambda segment: (segment.duration, sizes[segment], segment.hash))]
yield full_segments[0]
continue
# no full segments, fall back to measuring partials. Prefer suspect over partial.
yield max(segments, key=lambda segment: (
1 if segment.type == 'suspect' else 0,
os.stat(segment.path).st_size,
))
def streams_info(segment):
"""Return ffprobe's info on streams as a list of dicts"""
output = subprocess.check_output([
'ffprobe',
'-hide_banner', '-loglevel', 'fatal', # suppress noisy output
'-of', 'json', '-show_streams', # get streams info as json
segment.path,
])
# output here is a bytes, but json.loads will accept it
return json.loads(output)['streams']
def ffmpeg_cut_segment(segment, cut_start=None, cut_end=None):
"""Return a Popen object which is ffmpeg cutting the given single segment.
This is used when doing a fast cut.
"""
args = [
'ffmpeg',
'-hide_banner', '-loglevel', 'error', # suppress noisy output
'-i', segment.path,
]
# output from ffprobe is generally already sorted but let's be paranoid,
# because the order of map args matters.
for stream in sorted(streams_info(segment), key=lambda stream: stream['index']):
# map the same stream in the same position from input to output
args += ['-map', '0:{}'.format(stream['index'])]
if stream['codec_type'] in ('video', 'audio'):
# for non-metadata streams, make sure we use the same codec (metadata streams
# are a bit weirder, and ffmpeg will do the right thing anyway)
args += ['-codec:{}'.format(stream['index']), stream['codec_name']]
# now add trim args
if cut_start:
args += ['-ss', str(cut_start)]
if cut_end:
args += ['-to', str(cut_end)]
# disable B-frames (frames which contain data needed by earlier frames) as a codec option,
# as it changes the order that frames go in the file, which messes with our "concatenate the
# packets" method of concatenating the video.
args += ['-bf', '0']
# output to stdout as MPEG-TS
args += ['-f', 'mpegts', '-']
# run it
logging.info("Running segment cut with args: {}".format(" ".join(args)))
return subprocess.Popen(args, stdout=subprocess.PIPE)
def ffmpeg_cut_stdin(output_file, cut_start, duration, encode_args):
"""Return a Popen object which is ffmpeg cutting from stdin.
This is used when doing a full cut.
If output_file is not subprocess.PIPE,
uses explicit output file object instead of using a pipe,
because some video formats require a seekable file.
"""
args = [
'ffmpeg',
'-hide_banner', '-loglevel', 'error', # suppress noisy output
'-i', '-',
]
if cut_start is not None:
args += ['-ss', cut_start]
if duration is not None:
args += ['-t', duration]
args += list(encode_args)
if output_file is subprocess.PIPE:
args.append('-') # output to stdout
else:
args += [
# We want ffmpeg to write to our tempfile, which is its stdout.
# However, it assumes that '-' means the output is not seekable.
# We trick it into understanding that its stdout is seekable by
# telling it to write to the fd via its /proc/self filename.
'/proc/self/fd/1',
# But of course, that file "already exists", so we need to give it
# permission to "overwrite" it.
'-y',
]
args = list(map(str, args))
logging.info("Running full cut with args: {}".format(" ".join(args)))
return subprocess.Popen(args, stdin=subprocess.PIPE, stdout=output_file)
def read_chunks(fileobj, chunk_size=16*1024):
"""Read fileobj until EOF, yielding chunk_size sized chunks of data."""
while True:
chunk = fileobj.read(chunk_size)
if not chunk:
break
yield chunk
def range_total(ranges):
return sum([
end - start for start, end in ranges
], datetime.timedelta()).total_seconds()
@timed('cut', cut_type='rough', normalize=lambda ret, sr, ranges: range_total(ranges))
def rough_cut_segments(segment_ranges, ranges):
"""Yields chunks of a MPEGTS video file covering at least the timestamp ranges,
likely with a few extra seconds on either side of each range. Ranges are cut between
with no transitions.
This method works by simply concatenating all the segments, without any re-encoding.
"""
for segments in segment_ranges:
for segment in segments:
if segment is None:
continue
with open(segment.path, 'rb') as f:
for chunk in read_chunks(f):
yield chunk
@timed('cut', cut_type='fast', normalize=lambda ret, sr, ranges: range_total(ranges))
def fast_cut_segments(segment_ranges, ranges):
"""Yields chunks of a MPEGTS video file covering the exact timestamp ranges.
segments should be a list of segment lists as returned by get_best_segments() for each range.
This method works by only cutting the first and last segments of each range,
and concatenating everything together. Ranges are cut between with no transitions.
This only works if the same codec settings etc are used across all segments.
This should almost always be true but may cause weird results if not.
"""
if len(segment_ranges) != len(ranges):
raise ValueError("You need to provide one segment list for each range")
for segments, (start, end) in zip(segment_ranges, ranges):
# We could potentially optimize here by cutting all firsts/lasts in parallel
# instead of doing them in order, but that's probably not that helpful and would
# greatly complicate things.
yield from fast_cut_range(segments, start, end)
class FixTSSequence:
"""Manages state for concatenating several videos while fixing all their timestamps.
Has the same api as FixTS except instead of end(), we have next(), which also
resets the FixTS to take the next input video."""
def __init__(self):
self.fixts = FixTS(0)
def feed(self, data):
return self.fixts.feed(data)
def next(self):
# Note that if FixTS was unused (no data given) this is a no-op.
# In fact it's theoretically safe to call this function as often as you want
# (as long as you're sure you have no partial packets) as the only consequence
# is that we use a fixed time before the next timestamp instead of the timing from
# the original segments.
t = self.fixts.end()
self.fixts = FixTS(t)
@timed('cut', cut_type='smart', normalize=lambda ret, sr, ranges: range_total(ranges))
def smart_cut_segments(segment_ranges, ranges):
"""
As per fast_cut_segments(), except we also do a "fix" pass over the resulting video stream
to re-time internal timestamps to avoid discontinuities and make sure the video starts at t=0.
"""
if len(segment_ranges) != len(ranges):
raise ValueError("You need to provide one segment list for each range")
fixts = FixTSSequence()
for segments, (start, end) in zip(segment_ranges, ranges):
yield from fast_cut_range(segments, start, end, fixts=fixts)
@timed('cut_range', cut_type='fast', normalize=lambda _, segments, start, end, **k: (end - start).total_seconds())
def fast_cut_range(segments, start, end, fixts=None):
"""Does a fast cut for an individual range of segments.
If a FixTSSequence is given, fixes timestamps to avoid discontinuities
between cut segments and passed through segments.
"""
# how far into the first segment to begin (if no hole at start)
cut_start = None
if segments[0] is not None:
cut_start = (start - segments[0].start).total_seconds()
if cut_start < 0:
raise ValueError("First segment doesn't begin until after cut start, but no leading hole indicated")
# how far into the final segment to end (if no hole at end)
cut_end = None
if segments[-1] is not None:
cut_end = (end - segments[-1].start).total_seconds()
if cut_end < 0:
raise ValueError("Last segment ends before cut end, but no trailing hole indicated")
# Set first and last only if they actually need cutting.
# Note this handles both the cut_start = None (no first segment to cut)
# and cut_start = 0 (first segment already starts on time) cases.
first = segments[0] if cut_start else None
last = segments[-1] if cut_end else None
for segment in segments:
# Since long smart cuts can be CPU and disk bound for quite a while,
# yield to give other things a chance to run.
gevent.idle()
if segment is None:
logging.debug("Skipping discontinuity while cutting")
# TODO: If we want to be safe against the possibility of codecs changing,
# we should check the streams_info() after each discontinuity.
# To keep our output clean, we reset our FixTS so the output doesn't contain
# the discontinuity. The video just cuts to the next segment.
if fixts:
fixts.next()
continue
# note first and last might be the same segment.
# note a segment will only match if cutting actually needs to be done
# (ie. cut_start or cut_end is not 0)
if segment in (first, last):
if fixts:
fixts.next()
proc = None
try:
proc = ffmpeg_cut_segment(
segment,
cut_start if segment == first else None,
cut_end if segment == last else None,
)
with closing(proc.stdout):
for chunk in read_chunks(proc.stdout):
yield fixts.feed(chunk) if fixts else chunk
proc.wait()
except Exception as ex:
# try to clean up proc, ignoring errors
if proc is not None:
try:
proc.kill()
except OSError:
pass
raise ex
else:
# check if ffmpeg had errors
if proc.returncode != 0:
raise Exception(
"Error while streaming cut: ffmpeg exited {}".format(proc.returncode)
)
if fixts:
fixts.next()
else:
# no cutting needed, just serve the file
with open(segment.path, 'rb') as f:
for chunk in read_chunks(f):
yield fixts.feed(chunk) if fixts else chunk
if fixts:
# check for errors and indicate range is finished
fixts.next()
def feed_input(segments, pipe):
"""Write each segment's data into the given pipe in order.
This is used to provide input to ffmpeg in a full cut."""
for segment in segments:
with open(segment.path, 'rb') as f:
try:
shutil.copyfileobj(f, pipe)
except OSError as e:
# ignore EPIPE, as this just means the end cut meant we didn't need all it
if e.errno != errno.EPIPE:
raise
pipe.close()
@timed('cut_range',
cut_type=lambda _, segments, start, end, encode_args, stream=False: ("full-streamed" if stream else "full-buffered"),
normalize=lambda _, segments, start, end, *a, **k: (end - start).total_seconds(),
)
def full_cut_segments(segments, start, end, encode_args, stream=False):
"""If stream=true, assume encode_args gives a streamable format,
and begin returning output immediately instead of waiting for ffmpeg to finish
and buffering to disk."""
# Remove holes
segments = [segment for segment in segments if segment is not None]
# how far into the first segment to begin
cut_start = max(0, (start - segments[0].start).total_seconds())
# duration
duration = (end - start).total_seconds()
ffmpeg = None
input_feeder = None
try:
if stream:
# When streaming, we can just use a pipe
tempfile = subprocess.PIPE
else:
# Some ffmpeg output formats require a seekable file.
# For the same reason, it's not safe to begin uploading until ffmpeg
# has finished. We create a temporary file for this.
tempfile = TemporaryFile()
ffmpeg = ffmpeg_cut_stdin(tempfile, cut_start, duration, encode_args)
input_feeder = gevent.spawn(feed_input, segments, ffmpeg.stdin)
# When streaming, we can return data as it is available
if stream:
for chunk in read_chunks(ffmpeg.stdout):
yield chunk
# check if any errors occurred in input writing, or if ffmpeg exited non-success.
if ffmpeg.wait() != 0:
raise Exception("Error while streaming cut: ffmpeg exited {}".format(ffmpeg.returncode))
input_feeder.get() # re-raise any errors from feed_input()
# When not streaming, we can only return the data once ffmpeg has exited
if not stream:
for chunk in read_chunks(tempfile):
yield chunk
finally:
# if something goes wrong, try to clean up ignoring errors
if input_feeder is not None:
input_feeder.kill()
if ffmpeg is not None and ffmpeg.poll() is None:
for action in (ffmpeg.kill, ffmpeg.stdin.close, ffmpeg.stdout.close):
try:
action()
except (OSError, IOError):
pass
@timed('cut', cut_type='archive', normalize=lambda ret, sr, ranges: range_total(ranges))
def archive_cut_segments(segment_ranges, ranges, tempdir):
"""
Archive cuts are special in a few ways.
Like a rough cut, they do not take explicit start/end times but instead
use the entire segment range.
Like a full cut, they are passed entirely through ffmpeg.
They explicitly use ffmpeg arguments to copy the video without re-encoding,
but are placed into an MKV container.
They are split at each discontinuity into seperate videos.
Finally, because the files are expected to be very large and non-streamable,
instead of streaming the data back to the caller, we return a list of temporary filenames
which the caller should then do something with (probably either read then delete, or rename).
"""
# don't re-encode anything, just put it into an MKV container
encode_args = ["-c", "copy", "-f", "matroska"]
# We treat multiple segment ranges as having an explicit discontinuity between them.
# So we apply split_contiguous() to each range, then flatten.
contiguous_ranges = []
for segments in segment_ranges:
contiguous_ranges += list(split_contiguous(segments))
for segments in contiguous_ranges:
ffmpeg = None
input_feeder = None
tempfile_name = os.path.join(tempdir, "archive-temp-{}.mkv".format(uuid4()))
try:
tempfile = open(tempfile_name, "wb")
ffmpeg = ffmpeg_cut_stdin(tempfile, None, None, encode_args)
input_feeder = gevent.spawn(feed_input, segments, ffmpeg.stdin)
# since we've now handed off the tempfile fd to ffmpeg, close ours
tempfile.close()
# check if any errors occurred in input writing, or if ffmpeg exited non-success.
if ffmpeg.wait() != 0:
raise Exception("Error while streaming cut: ffmpeg exited {}".format(ffmpeg.returncode))
input_feeder.get() # re-raise any errors from feed_input()
except:
# if something goes wrong, try to clean up ignoring errors
if input_feeder is not None:
input_feeder.kill()
if ffmpeg is not None and ffmpeg.poll() is None:
for action in (ffmpeg.kill, ffmpeg.stdin.close, ffmpeg.stdout.close):
try:
action()
except (OSError, IOError):
pass
try:
os.remove(tempfile_name)
except (OSError, IOError):
pass
raise
else:
# Success, inform caller of tempfile. It's now their responsibility to delete.
yield tempfile_name
@timed('waveform')
def render_segments_waveform(segments, size=(1024, 128), scale='sqrt', color='#000000'):
"""
Render an audio waveform of given list of segments. Yields chunks of PNG data.
Note we do not validate our inputs before passing them into an ffmpeg filtergraph.
Do not provide untrusted input without verifying, or else they can run arbitrary filters
(this MAY be fine but I wouldn't be shocked if some obscure filter lets them do arbitrary
filesystem writes).
"""
width, height = size
# Remove holes
segments = [segment for segment in segments if segment is not None]
ffmpeg = None
input_feeder = None
try:
args = [
# create waveform from input audio
'-filter_complex',
f'[0:a]showwavespic=size={width}x{height}:colors={color}:scale={scale}[out]',
# use created waveform as our output
'-map', '[out]',
# output as png
'-f', 'image2', '-c', 'png',
]
ffmpeg = ffmpeg_cut_stdin(subprocess.PIPE, cut_start=None, duration=None, encode_args=args)
input_feeder = gevent.spawn(feed_input, segments, ffmpeg.stdin)
for chunk in read_chunks(ffmpeg.stdout):
yield chunk
# check if any errors occurred in input writing, or if ffmpeg exited non-success.
if ffmpeg.wait() != 0:
raise Exception("Error while rendering waveform: ffmpeg exited {}".format(ffmpeg.returncode))
input_feeder.get() # re-raise any errors from feed_input()
finally:
# if something goes wrong, try to clean up ignoring errors
if input_feeder is not None:
input_feeder.kill()
if ffmpeg is not None and ffmpeg.poll() is None:
for action in (ffmpeg.kill, ffmpeg.stdin.close, ffmpeg.stdout.close):
try:
action()
except (OSError, IOError):
pass
@timed('extract_frame')
def extract_frame(segments, timestamp):
"""
Extract the frame at TIMESTAMP within SEGMENT, yielding it as chunks of PNG data.
"""
# Remove holes
segments = [segment for segment in segments if segment is not None]
if not segments:
raise ValueError("No data at timestamp within segment list")
# "cut" input so that first frame is our target frame
cut_start = (timestamp - segments[0].start).total_seconds()
ffmpeg = None
input_feeder = None
try:
args = [
# get a single frame
'-vframes', '1',
# output as png
'-f', 'image2', '-c', 'png',
]
ffmpeg = ffmpeg_cut_stdin(subprocess.PIPE, cut_start=cut_start, duration=None, encode_args=args)
input_feeder = gevent.spawn(feed_input, segments, ffmpeg.stdin)
for chunk in read_chunks(ffmpeg.stdout):
yield chunk
# check if any errors occurred in input writing, or if ffmpeg exited non-success.
if ffmpeg.wait() != 0:
raise Exception("Error while extracting frame: ffmpeg exited {}".format(ffmpeg.returncode))
input_feeder.get() # re-raise any errors from feed_input()
finally:
# if something goes wrong, try to clean up ignoring errors
if input_feeder is not None:
input_feeder.kill()
if ffmpeg is not None and ffmpeg.poll() is None:
for action in (ffmpeg.kill, ffmpeg.stdin.close, ffmpeg.stdout.close):
try:
action()
except (OSError, IOError):
pass
def split_contiguous(segments):
"""For a list of segments, return a list of contiguous ranges of segments.
In other words, it splits the list every time there is a hole.
Each range will contain at least one segment.
"""
contiguous = []
for segment in segments:
if segment is None:
if contiguous:
yield contiguous
contiguous = []
else:
contiguous.append(segment)
if contiguous:
yield contiguous