def compress_images(container,
report=None,
names=None,
jpeg_quality=None,
progress_callback=lambda n, t, name: True):
images = get_compressible_images(container)
if names is not None:
images &= set(names)
results = {}
queue = Queue()
abort = Event()
for name in images:
queue.put(name)
def pc(name):
keep_going = progress_callback(len(results), len(images), name)
if not keep_going:
abort.set()
progress_callback(0, len(images), '')
[
Worker(abort, 'CompressImage%d' % i, queue, results, container,
jpeg_quality, pc)
for i in range(min(detect_ncpus(), len(images)))
]
queue.join()
before_total = after_total = 0
changed = False
for name, (ok, res) in results.iteritems():
name = force_unicode(name, filesystem_encoding)
if ok:
before, after = res
if before != after:
changed = True
before_total += before
after_total += after
if report:
if before != after:
report(
_('{0} compressed from {1} to {2} bytes [{3:.1%} reduction]'
).format(name, human_readable(before),
human_readable(after),
(before - after) / before))
else:
report(
_('{0} could not be further compressed').format(name))
else:
report(_('Failed to process {0} with error:').format(name))
report(res)
if report:
if changed:
report('')
report(
_('Total image filesize reduced from {0} to {1} [{2:.1%} reduction]'
).format(human_readable(before_total),
human_readable(after_total),
(before_total - after_total) / before_total))
else:
report(_('Images are already fully optimized'))
return changed, results
def launch_workers(self, names, in_process_container):
num_workers = min(detect_ncpus(), len(names))
if self.max_workers:
num_workers = min(num_workers, self.max_workers)
if num_workers > 1:
if len(names) < 3 or sum(os.path.getsize(in_process_container.name_path_map[n]) for n in names) < 128 * 1024:
num_workers = 1
if num_workers > 1:
num_other_workers = num_workers - 1
while len(self.workers) < num_other_workers:
self.launch_worker()
return num_workers
def __init__(self, max_workers=None, name=None):
Thread.__init__(self, name=name)
self.max_workers = max_workers or detect_ncpus()
self.available_workers = []
self.busy_workers = {}
self.pending_jobs = []
self.events = Queue()
self.results = Queue()
self.tracker = Queue()
self.terminal_failure = None
self.common_data = pickle_dumps(None)
self.shutting_down = False
self.start()
def __init__(self, max_workers=None, name=None):
Thread.__init__(self, name=name)
self.max_workers = max_workers or detect_ncpus()
self.available_workers = []
self.busy_workers = {}
self.pending_jobs = []
self.events = Queue()
self.results = Queue()
self.tracker = Queue()
self.terminal_failure = None
self.common_data = cPickle.dumps(None, -1)
self.worker_data = None
self.shutting_down = False
self.start()
def __init__(self, opts, log):
mj = opts.max_jobs
if mj < 1:
mj = detect_ncpus()
self.log = log
self.max_jobs = max(1, mj)
self.max_job_time = max(0, opts.max_job_time * 60)
self.lock = RLock()
self.jobs = {}
self.finished_jobs = {}
self.events = Queue()
self.job_id = count()
self.waiting_job_ids = set()
self.waiting_jobs = deque()
self.max_block = None
self.shutting_down = False
self.event_loop = None
def __init__(self, opts, log):
mj = opts.max_jobs
if mj < 1:
mj = detect_ncpus()
self.log = log
self.max_jobs = max(1, mj)
self.max_job_time = max(0, opts.max_job_time * 60)
self.lock = RLock()
self.jobs = {}
self.finished_jobs = {}
self.events = Queue()
self.job_id = count()
self.waiting_job_ids = set()
self.waiting_jobs = deque()
self.max_block = None
self.shutting_down = False
self.event_loop = None
def __init__(self, opts, log, container_root):
QObject.__init__(self)
self.interceptor = RequestInterceptor(self)
self.has_maths = {}
self.interceptor.log = self.log = log
self.interceptor.container_root = os.path.normcase(os.path.abspath(container_root))
self.interceptor.resources_root = os.path.normcase(os.path.abspath(os.path.dirname(mathjax_dir())))
ans = QWebEngineProfile(QApplication.instance())
ua = 'calibre-pdf-output ' + __version__
ans.setHttpUserAgent(ua)
s = ans.settings()
s.setDefaultTextEncoding('utf-8')
ans.setUrlRequestInterceptor(self.interceptor)
self.profile = ans
self.opts = opts
self.workers = []
self.max_workers = detect_ncpus()
if iswindows:
self.original_signal_handlers = {}
else:
self.original_signal_handlers = setup_unix_signals(self)
def compress_covers(path_map, jpeg_quality, progress_callback):
input_queue = Queue()
output_queue = Queue()
num_workers = detect_ncpus()
sz_map = {}
for book_id, (path, sz) in path_map.items():
input_queue.put((book_id, path))
sz_map[book_id] = sz
workers = [
Thread(target=compress_worker,
args=(input_queue, output_queue, jpeg_quality),
daemon=True,
name=f'CCover-{i}') for i in range(num_workers)
]
[w.start() for w in workers]
pending = set(path_map)
while pending:
book_id, new_sz = output_queue.get()
pending.remove(book_id)
progress_callback(book_id, sz_map[book_id], new_sz)
for w in workers:
input_queue.put(None)
for w in workers:
w.join()
def create_spare_pool(self, *args):
if self._spare_pool is None:
num = min(detect_ncpus(), int(config['worker_limit'] / 2.0))
self._spare_pool = Pool(max_workers=num, name='GUIPool')
def create_spare_pool(self, *args):
if self._spare_pool is None:
num = min(detect_ncpus(), int(config['worker_limit']/2.0))
self._spare_pool = Pool(max_workers=num, name='GUIPool')
def compress_images(container, report=None, names=None, jpeg_quality=None, progress_callback=lambda n, t, name:True):
images = get_compressible_images(container)
if names is not None:
images &= set(names)
results = {}
queue = Queue()
abort = Event()
for name in images:
queue.put(name)
def pc(name):
keep_going = progress_callback(len(results), len(images), name)
if not keep_going:
abort.set()
progress_callback(0, len(images), '')
[Worker(abort, 'CompressImage%d' % i, queue, results, container, jpeg_quality, pc) for i in xrange(min(detect_ncpus(), len(images)))]
queue.join()
before_total = after_total = 0
for name, (ok, res) in results.iteritems():
name = force_unicode(name, filesystem_encoding)
if ok:
before, after = res
before_total += before
after_total += after
if report:
if before != after:
report(_('{0} compressed from {1} to {2} bytes [{3:.1%} reduction]').format(
name, human_readable(before), human_readable(after), (before - after)/before))
else:
report(_('{0} could not be further compressed').format(name))
else:
report(_('Failed to process {0} with error:').format(name))
report(res)
if report:
if before_total > 0:
report('')
report(_('Total image filesize reduced from {0} to {1} [{2:.1%} reduction]').format(
human_readable(before_total), human_readable(after_total), (before_total - after_total)/before_total))
else:
report(_('Images are already fully optimized'))
return before_total > 0, results
def compress_images(container, report=None, names=None, jpeg_quality=None, progress_callback=lambda n, t, name:True):
images = get_compressible_images(container)
if names is not None:
images &= set(names)
results = {}
queue = Queue()
abort = Event()
seen = set()
num_to_process = 0
for name in sorted(images):
path = os.path.abspath(container.get_file_path_for_processing(name))
path_key = os.path.normcase(path)
if path_key not in seen:
num_to_process += 1
queue.put((name, path, container.mime_map[name]))
seen.add(path_key)
def pc(name):
keep_going = progress_callback(len(results), num_to_process, name)
if not keep_going:
abort.set()
progress_callback(0, num_to_process, '')
[Worker(abort, 'CompressImage%d' % i, queue, results, jpeg_quality, pc) for i in range(min(detect_ncpus(), num_to_process))]
queue.join()
before_total = after_total = 0
processed_num = 0
changed = False
for name, (ok, res) in iteritems(results):
name = force_unicode(name, filesystem_encoding)
if ok:
before, after = res
if before != after:
changed = True
processed_num += 1
before_total += before
after_total += after
if report:
if before != after:
report(_('{0} compressed from {1} to {2} bytes [{3:.1%} reduction]').format(
name, human_readable(before), human_readable(after), (before - after)/before))
else:
report(_('{0} could not be further compressed').format(name))
else:
report(_('Failed to process {0} with error:').format(name))
report(res)
if report:
if changed:
report('')
report(_('Total image filesize reduced from {0} to {1} [{2:.1%} reduction, {3} images changed]').format(
human_readable(before_total), human_readable(after_total), (before_total - after_total)/before_total, processed_num))
else:
report(_('Images are already fully optimized'))
return changed, results
