def test_optimize_images_task_failure(tmp_path, font):
tmp_fl = tmp_path / "tmp.jpg"
dst = tmp_path / "out.jpg"
# send an unreadable file
tmp_fl.touch(mode=0o377)
task = Task(
src_path=str(tmp_fl.resolve()),
quality=50,
remove_transparency=False,
reduce_colors=False,
max_colors=256,
max_w=0,
max_h=0,
keep_exif=False,
convert_all=False,
conv_big=False,
force_del=False,
bg_color=(255, 255, 255),
grayscale=False,
no_size_comparison=True,
fast_mode=False,
)
with pytest.raises(Exception):
run_optimize_images_task(task, tmp_fl, dst)
assert not tmp_fl.exists()
assert not dst.exists()
def on_created(self, event):
t = self.t
if '~temp~' in event.src_path:
return
if event.is_directory:
return
if event.src_path in self.paths_to_ignore:
return
self.paths_to_ignore.append(event.src_path)
if is_image(event.src_path) and '~temp~' not in event.src_path:
self.wait_for_write_finish(event.src_path)
self.new_files += 1
img_task = Task(event.src_path, t.quality, t.remove_transparency,
t.reduce_colors, t.max_colors, t.max_w, t.max_h,
t.keep_exif, t.convert_all, t.conv_big,
t.force_del, t.bg_color, t.grayscale,
t.no_size_comparison, t.fast_mode)
r = do_optimization(img_task)
self.total_src_size += r.orig_size
if r.was_optimized:
self.optimized_files += 1
self.total_bytes_saved += r.orig_size - r.final_size
show_file_status(r, self.line_width, self.icons)
def on_created(self, event):
if (event.is_directory
or not is_image(event.src_path)
or '~temp~' in event.src_path
or event.src_path in self.paths_to_ignore):
return
self.paths_to_ignore.append(event.src_path)
self.wait_for_write_finish(event.src_path)
self.new_files += 1
task = self.task
img_task = Task(event.src_path, task.quality, task.remove_transparency,
task.reduce_colors, task.max_colors, task.max_w,
task.max_h, task.keep_exif, task.convert_all,
task.conv_big, task.force_del, task.bg_color,
task.grayscale, task.no_size_comparison, task.fast_mode)
result: TaskResult = do_optimization(img_task)
self.total_src_size += result.orig_size
if result.was_optimized:
self.optimized_files += 1
self.total_bytes_saved += result.orig_size - result.final_size
show_file_status(result, self.line_width, self.icons)
def optimize(filepath):
remove_transparency = True
reduce_colors = False
max_colors = 255
max_w = 0
max_h = 0
keep_exif = True
convert_all = False
conv_big = False
force_del = False
bg_color = (255, 255, 255) # By default, apply a white background
grayscale = False
ignore_size_comparison = False
fast_mode = False
task = Task(
filepath, constants.DEFAULT_QUALITY, remove_transparency,
reduce_colors, max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale, ignore_size_comparison,
fast_mode
)
r = do_optimization(task)
total_src_size = r.orig_size
report = json_report(r, filepath)
print(report)
return report
def optimize_jpeg(
src: pathlib.Path,
dst: pathlib.Path,
quality: Optional[int] = 85,
fast_mode: Optional[bool] = True,
keep_exif: Optional[bool] = True,
grayscale: Optional[bool] = False,
**options,
) -> bool:
"""method to optimize JPEG files using a pure python external optimizer
quality: JPEG quality (integer between 1 and 100)
values: 50 | 55 | 35 | 100 | XX
keep_exif: Whether to keep EXIF data in JPEG (boolean)
values: True | False
grayscale: Whether to convert image to grayscale (boolean)
values: True | False
fast_mode: Whether to use faster but weaker compression (boolean)
values: True | False"""
ensure_matches(src, "JPEG")
# use a temporary file as source as optimization is done destructively
tmp_path = get_temporary_copy(src)
# generate JPEG task for optimize_images
optimization_task = Task(
src_path=str(tmp_path.resolve()),
quality=quality,
# remove_transparency is specific to PNG and hence is ignored, but we need to supply the default value
remove_transparency=False,
# reduce_colors is specific to PNG and hence is ignored, but we need to supply the default value
reduce_colors=False,
# max_colors is specific to PNG and hence is ignored, but we need to supply the default value
max_colors=256,
# max_w and max_h is 0 because we have a better image resizing function in scraperlib already
max_w=0,
max_h=0,
keep_exif=keep_exif,
# convert_all is specific to PNG and hence is ignored, but we need to supply the default value
convert_all=False,
# convert_big is specific to PNG and hence is ignored, but we need to supply the default value
conv_big=False,
# force_del is specific to PNG and hence is ignored, but we need to supply the default value
force_del=False,
# bg_color is specific to PNG and hence is ignored, but we need to supply the default value
bg_color=(255, 255, 255),
grayscale=grayscale,
no_size_comparison=True,
fast_mode=fast_mode,
)
# optimize the image
return run_optimize_images_task(optimization_task, tmp_path, dst)
def main():
appstart = timer()
line_width, our_pool_executor, workers = adjust_for_platform()
(src_path, recursive, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all, conv_big, force_del,
bg_color, grayscale, ignore_size_comparison, fast_mode) = get_args()
found_files = 0
optimized_files = 0
total_src_size = 0
total_bytes_saved = 0
# Optimize all images in a directory
if os.path.isdir(src_path):
recursion_txt = 'Recursively searching' if recursive else 'Searching'
opt_msg = 'and optimizing image files'
exif_txt = '(keeping exif data) ' if keep_exif else ''
print(f"\n{recursion_txt} {opt_msg} {exif_txt}in:\n{src_path}\n")
tasks = (Task(img_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale,
ignore_size_comparison, fast_mode)
for img_path in search_images(src_path, recursive=recursive))
with our_pool_executor(max_workers=workers) as executor:
for r in executor.map(do_optimization, tasks):
found_files += 1
total_src_size += r.orig_size
if r.was_optimized:
optimized_files += 1
total_bytes_saved += r.orig_size - r.final_size
show_file_status(r, line_width)
# Optimize a single image
elif os.path.isfile(src_path):
found_files += 1
img_task = Task(src_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale,
ignore_size_comparison, fast_mode)
r = do_optimization(img_task)
total_src_size = r.orig_size
if r.was_optimized:
optimized_files = 1
total_bytes_saved = r.orig_size - r.final_size
show_file_status(r, line_width)
else:
print(
"No image files were found. Please enter a valid path to the "
"image file or the folder containing any images to be processed.")
exit()
if found_files:
time_passed = timer() - appstart
show_final_report(found_files, optimized_files, total_src_size,
total_bytes_saved, time_passed)
else:
print(
"No supported image files were found in the specified directory.\n"
)
def optimize_batch(src_path, watch_dir, recursive, quality, remove_transparency,
reduce_colors, max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale, ignore_size_comparison,
fast_mode, jobs, output_config):
appstart = timer()
line_width, our_pool_executor, workers = adjust_for_platform()
if jobs != 0:
workers = jobs
found_files = 0
optimized_files = 0
skipped_files = 0
total_src_size = 0
total_bytes_saved = 0
if watch_dir:
if not os.path.isdir(os.path.abspath(src_path)):
msg = "\nPlease specify a valid path to an existing folder."
raise OIInvalidPathError(msg)
watch_task = Task(src_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale,
ignore_size_comparison, fast_mode, output_config)
from optimize_images.watch import watch_for_new_files
watch_for_new_files(watch_task)
return
# Optimize all images in a directory
elif os.path.isdir(src_path):
if not output_config.quiet_mode:
icons = IconGenerator()
recursion_txt = 'Recursively searching' if recursive else 'Searching'
opt_msg = 'and optimizing image files'
exif_txt = '(keeping exif data) ' if keep_exif else ''
print(f"\n{recursion_txt} {opt_msg} {exif_txt}in:\n{src_path}\n")
tasks = (Task(img_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all, conv_big,
force_del, bg_color, grayscale, ignore_size_comparison, fast_mode,
output_config)
for img_path in search_images(src_path, recursive=recursive))
num_images, tasks = count_gen(tasks)
with our_pool_executor(max_workers=workers) as executor:
current_img = ''
try:
for result in executor.map(do_optimization, tasks):
current_img = result.img
found_files += 1
total_src_size += result.orig_size
if result.was_optimized:
optimized_files += 1
total_bytes_saved += result.orig_size - result.final_size
else:
skipped_files += 1
if result.output_config.quiet_mode:
continue
if result.output_config.show_overall_progress:
cur_time_passed = round(timer() - appstart)
perc_done = found_files / num_images * 100
message = f"[{cur_time_passed:.1f}s {perc_done:.1f}%] {icons.optimized} {optimized_files} {icons.skipped} {skipped_files}, saved {human(total_bytes_saved)}"
print(message, end='\r')
else:
show_file_status(result, line_width, icons)
except concurrent.futures.process.BrokenProcessPool as bppex:
show_img_exception(bppex, current_img)
except KeyboardInterrupt:
msg = "\b \n\n == Operation was interrupted by the user. ==\n"
raise OIKeyboardInterrupt(msg)
# Optimize a single image
elif os.path.isfile(src_path) and '~temp~' not in src_path:
found_files += 1
img_task = Task(src_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all, conv_big,
force_del, bg_color, grayscale, ignore_size_comparison, fast_mode,
output_config)
result = do_optimization(img_task)
total_src_size = result.orig_size
if result.was_optimized:
optimized_files = 1
total_bytes_saved = result.orig_size - result.final_size
if not result.output_config.quiet_mode:
icons = IconGenerator()
show_file_status(result, line_width, icons)
else:
msg = "\nNo image files were found. Please enter a valid path to the " \
"image file or the folder containing any images to be processed."
raise OIImagesNotFoundError(msg)
if found_files:
time_passed = timer() - appstart
show_final_report(found_files, optimized_files, total_src_size,
total_bytes_saved, time_passed, output_config)
else:
msg = "\nNo supported image files were found in the specified directory."
raise OIImagesNotFoundError(msg)
def main():
appstart = timer()
line_width, our_pool_executor, workers = adjust_for_platform()
(watch_dir, src_path, recursive, quality, remove_transparency,
reduce_colors, max_colors, max_w, max_h, keep_exif, convert_all, conv_big,
force_del, bg_color, grayscale, ignore_size_comparison, fast_mode, jobs) \
= get_args()
if jobs != 0:
workers = jobs
found_files = 0
optimized_files = 0
total_src_size = 0
total_bytes_saved = 0
if watch_dir:
if not os.path.isdir(os.path.abspath(src_path)):
print("\nPlease secify a valid path to an existing folder.")
sys.exit(1)
watch_task = Task(src_path, quality, remove_transparency,
reduce_colors, max_colors, max_w, max_h, keep_exif,
convert_all, conv_big, force_del, bg_color,
grayscale, ignore_size_comparison, fast_mode)
watch_for_new_files(watch_task)
sys.exit()
# Optimize all images in a directory
elif os.path.isdir(src_path):
icons = IconGenerator()
recursion_txt = 'Recursively searching' if recursive else 'Searching'
opt_msg = 'and optimizing image files'
exif_txt = '(keeping exif data) ' if keep_exif else ''
print(f"\n{recursion_txt} {opt_msg} {exif_txt}in:\n{src_path}\n")
tasks = (Task(img_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale,
ignore_size_comparison, fast_mode)
for img_path in search_images(src_path, recursive=recursive))
with our_pool_executor(max_workers=workers) as executor:
current_img = ''
try:
for result in executor.map(do_optimization, tasks):
current_img = result.img
found_files += 1
total_src_size += result.orig_size
if result.was_optimized:
optimized_files += 1
total_bytes_saved += result.orig_size - result.final_size
show_file_status(result, line_width, icons)
except concurrent.futures.process.BrokenProcessPool as bppex:
show_img_exception(bppex, current_img)
except KeyboardInterrupt:
print(
"\b \n\n == Operation was interrupted by the user. ==\n")
# Optimize a single image
elif os.path.isfile(src_path) and '~temp~' not in src_path:
icons = IconGenerator()
found_files += 1
img_task = Task(src_path, quality, remove_transparency, reduce_colors,
max_colors, max_w, max_h, keep_exif, convert_all,
conv_big, force_del, bg_color, grayscale,
ignore_size_comparison, fast_mode)
result = do_optimization(img_task)
total_src_size = result.orig_size
if result.was_optimized:
optimized_files = 1
total_bytes_saved = result.orig_size - result.final_size
show_file_status(result, line_width, icons)
else:
print(
"\nNo image files were found. Please enter a valid path to the "
"image file or the folder containing any images to be processed.")
sys.exit()
if found_files:
time_passed = timer() - appstart
show_final_report(found_files, optimized_files, total_src_size,
total_bytes_saved, time_passed)
else:
print(
"\nNo supported image files were found in the specified directory.\n"
)
def optimize_png(
src: pathlib.Path,
dst: pathlib.Path,
reduce_colors: Optional[bool] = False,
max_colors: Optional[int] = 256,
fast_mode: Optional[bool] = True,
remove_transparency: Optional[bool] = False,
background_color: Optional[Tuple[int, int, int]] = (255, 255, 255),
grayscale: Optional[bool] = False,
**options,
) -> bool:
"""method to optimize PNG files using a pure python external optimizer
Arguments:
reduce_colors: Whether to reduce colors using adaptive color pallette (boolean)
values: True | False
max_colors: Maximum number of colors if reduce_colors is True (integer between 1 and 256)
values: 35 | 64 | 256 | 128 | XX
fast_mode: Whether to use faster but weaker compression (boolean)
values: True | False
remove_transparency: Whether to remove transparency (boolean)
values: True | False
background_color: Background color if remove_transparency is True (tuple containing RGB values)
values: (255, 255, 255) | (221, 121, 108) | (XX, YY, ZZ)
grayscale: Whether to convert image to grayscale (boolean)
values: True | False"""
ensure_matches(src, "PNG")
# use a temporary file as source as optimization is done destructively
tmp_path = get_temporary_copy(src)
# generate PNG task for optimize_images
optimization_task = Task(
src_path=str(tmp_path.resolve()),
# quality is specific to JPEG and hence is ignored, but we need to supply the default value
quality=90,
remove_transparency=remove_transparency,
reduce_colors=reduce_colors,
# max_colors is ignored if reduce_colors is False, but we need to provide a default value
max_colors=max_colors,
# max_w and max_h is 0 because we have a better image resizing function in scraperlib already
max_w=0,
max_h=0,
# keep_exif is specific to JPEG and hence is ignored, but we need to supply the default value
keep_exif=False,
# convert_all converts all PNG to JPEG, hence set to False
convert_all=False,
# conv_big converts big PNG images to JPEG, hence set to False
conv_big=False,
# force_del deletes the original PNG after convertion to JPEG if the above two options are used, hence kept False
force_del=False,
# bg_color is only used if remove_transparency is True, but we need to supply a default value always
bg_color=background_color,
grayscale=grayscale,
no_size_comparison=True,
fast_mode=fast_mode,
)
# optimize the image
return run_optimize_images_task(optimization_task, tmp_path, dst)