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.gitignore
vendored
2
.gitignore
vendored
@ -9,5 +9,3 @@ dist
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docs
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docs
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*.log
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*.log
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*.err*
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*.swp
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@ -126,7 +126,6 @@ def main():
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logging.info(
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logging.info(
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f"total optimization ({optimized}/{len(result.orig)}): {percent:.2f}% -> {size:.2f} Mb" # noqa
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f"total optimization ({optimized}/{len(result.orig)}): {percent:.2f}% -> {size:.2f} Mb" # noqa
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)
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)
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result.check_errors()
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if __name__ == "__main__":
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if __name__ == "__main__":
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@ -4,7 +4,7 @@ import signal
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import subprocess
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import subprocess
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import time
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import time
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from concurrent.futures import ProcessPoolExecutor, as_completed
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from concurrent.futures import ProcessPoolExecutor, as_completed
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from dataclasses import dataclass, field
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from dataclasses import dataclass
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from typing import Optional
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from typing import Optional
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from tqdm import tqdm
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from tqdm import tqdm
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@ -15,9 +15,7 @@ __all__ = ["ImgOptimizer", "OptimizerResult"]
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# TODO(rmanach): add argument to set the size or leave it empty for loseless optim
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# TODO(rmanach): add argument to set the size or leave it empty for loseless optim
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def _jpeg_optim(
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def _jpeg_optim(dest_dir: str, file: File) -> tuple["File", Optional["File"]] | None:
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dest_dir: str, file: File
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) -> tuple["File", Optional["File"], str | None]:
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"""
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"""
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Optimize the `file` with `jpegoptim` and put the result in
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Optimize the `file` with `jpegoptim` and put the result in
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`dest_dir` directory keeping file path.
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`dest_dir` directory keeping file path.
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@ -37,26 +35,22 @@ def _jpeg_optim(
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try:
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try:
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_ = subprocess.run(cmd, shell=True, check=True)
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_ = subprocess.run(cmd, shell=True, check=True)
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except subprocess.CalledProcessError as e:
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except subprocess.CalledProcessError as e:
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logging.debug("error while running command: %s, err: %s", cmd, e.stderr or "?")
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logging.error("error while running command: %s, err: %s", cmd, e.stderr or "?")
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return file, None, f"command: {cmd} failed, err: {e.stderr}"
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return None
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except Exception:
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except Exception:
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logging.debug("unexpected error while running command: %s", cmd, exc_info=True)
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logging.error("unexpected error while running command: %s", cmd, exc_info=True)
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return (
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return None
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file,
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None,
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f"command: {cmd} failed unexpectedly, set debug mode for more details",
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)
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try:
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try:
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file_optim = File.from_directory(dest_dir, file.name)
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file_optim = File.from_directory(dest_dir, file.name)
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except Exception as e:
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except Exception as e:
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logging.debug("unable to get file: %s after optimization: %s", file, e)
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logging.debug("unable to get file: %s after optimization: %s", file, e)
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return file, None, None
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return file, None
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return file, file_optim, None
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return file, file_optim
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def _optim(dest_dir: str, file: File) -> tuple["File", Optional["File"], str | None]:
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def _optim(dest_dir: str, file: File) -> tuple["File", Optional["File"]] | None:
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"""
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"""
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Entry point of `file` optimization selection the handler.
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Entry point of `file` optimization selection the handler.
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NOTE: Must be launched in separated process.
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NOTE: Must be launched in separated process.
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@ -65,27 +59,7 @@ def _optim(dest_dir: str, file: File) -> tuple["File", Optional["File"], str | N
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signal.signal(signal.SIGINT, signal.SIG_IGN)
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signal.signal(signal.SIGINT, signal.SIG_IGN)
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if file.mimetype == FileImgMimetype.JPEG.value:
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if file.mimetype == FileImgMimetype.JPEG.value:
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return _jpeg_optim(dest_dir, file)
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return _jpeg_optim(dest_dir, file)
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return file, None, f"mimetype: {file.mimetype} not supported for optimization"
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return None
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@dataclass(slots=True, frozen=True)
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class OptimizerErrors:
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_data: dict[str, str] = field(default_factory=dict)
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def save(self):
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if not len(self._data):
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return
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with open("optimg.err.csv", "w") as f:
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f.write("filepath;err\n")
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for filepath, error in self._data.items():
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f.write(f"{filepath};{error}\n")
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def has_errors(self) -> bool:
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return len(self._data) > 0
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def add(self, filepath: str, error: str):
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self._data[filepath] = error
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@dataclass(slots=True, frozen=True)
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@dataclass(slots=True, frozen=True)
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@ -99,7 +73,6 @@ class OptimizerResult:
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orig: FileGroup
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orig: FileGroup
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opti: FileGroup
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opti: FileGroup
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optimized: int
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optimized: int
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err: OptimizerErrors
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def stats(self) -> tuple[int, float, float]:
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def stats(self) -> tuple[int, float, float]:
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"""
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"""
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@ -112,13 +85,6 @@ class OptimizerResult:
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size = self.orig._size - self.opti._size
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size = self.orig._size - self.opti._size
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return (self.optimized, percent, size)
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return (self.optimized, percent, size)
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def check_errors(self):
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if self.err.has_errors():
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logging.error(
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"some errors detected during optimization, check 'optimg.err.csv' for details" # noqa
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)
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self.err.save()
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@dataclass(slots=True, frozen=True)
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@dataclass(slots=True, frozen=True)
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class ImgOptimizer:
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class ImgOptimizer:
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@ -128,8 +94,8 @@ class ImgOptimizer:
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Example:
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Example:
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```python
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```python
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optimizer = ImgOptimizer()
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optimizer = ImgOptimizer("mypath")
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res = optimizer.optimize(file_group)
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optimizer.optimize()
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```
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```
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"""
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"""
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@ -168,19 +134,15 @@ class ImgOptimizer:
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file_group_optim = FileGroup()
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file_group_optim = FileGroup()
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optimized = 0
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optimized = 0
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errors = OptimizerErrors()
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for f in tqdm(
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for f in tqdm(
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as_completed(futures), total=len(futures), desc="Optimizing..."
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as_completed(futures), total=len(futures), desc="Optimizing..."
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):
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):
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match f.result():
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if (res := f.result()) and res is not None:
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case (orig, None, err):
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match res:
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logging.debug(f"optim error for file: {orig}, err: {err}")
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case (orig, None):
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file_group_optim.add(orig)
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errors.add(orig.path, err)
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case (orig, None, None):
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logging.debug(f"no optimization for file: {orig}")
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logging.debug(f"no optimization for file: {orig}")
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file_group_optim.add(orig)
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file_group_optim.add(orig)
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case (orig, opti, None):
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case (orig, opti):
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optimized += 1
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optimized += 1
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logging.debug(
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logging.debug(
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f"optimization for file: {orig} -> {(1 - (opti.size / orig.size)) * 100:.2f}%" # noqa
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f"optimization for file: {orig} -> {(1 - (opti.size / orig.size)) * 100:.2f}%" # noqa
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@ -188,4 +150,4 @@ class ImgOptimizer:
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file_group_optim.add(opti)
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file_group_optim.add(opti)
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logging.info(f"optimization finished in {time.perf_counter() - start:.2f}s")
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logging.info(f"optimization finished in {time.perf_counter() - start:.2f}s")
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return OptimizerResult(file_group, file_group_optim, optimized, errors)
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return OptimizerResult(file_group, file_group_optim, optimized)
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