压缩图片
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scripts/__init__.py
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1
scripts/__init__.py
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scripts/__pycache__/__init__.cpython-314.pyc
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scripts/__pycache__/__init__.cpython-314.pyc
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scripts/__pycache__/optimize_assets.cpython-314.pyc
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scripts/__pycache__/optimize_assets.cpython-314.pyc
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scripts/optimize_assets.py
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scripts/optimize_assets.py
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#!/usr/bin/env python3
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from __future__ import annotations
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import argparse
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import re
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import shutil
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import subprocess
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from collections import Counter
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from dataclasses import dataclass
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent.parent
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ASSETS_DIR = ROOT / "assets"
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IMAGES_DIR = ASSETS_DIR / "images"
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BACKUP_DIR = ROOT / "assets_backup"
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TEXT_EXTENSIONS = {".html", ".css", ".js"}
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SOURCE_EXTENSIONS = {".png", ".jpg", ".jpeg", ".gif"}
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MANAGED_IMAGE_EXTENSIONS = SOURCE_EXTENSIONS | {".webp"}
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MAX_FILE_SIZE = 300_000
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MAX_DIMENSION = 2560
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SMALL_FILE_LIMIT = 150 * 1024
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SMALL_MIN_SAVINGS = 8 * 1024
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LARGE_MIN_RATIO = 0.05
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@dataclass(frozen=True)
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class ImageInfo:
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width: int
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height: int
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colors: int
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def run(cmd: list[str], capture: bool = False) -> str:
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result = subprocess.run(
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cmd,
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check=True,
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text=True,
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capture_output=capture,
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)
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return result.stdout.strip() if capture else ""
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def should_keep_conversion(source_size: int, candidate_size: int) -> bool:
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savings = source_size - candidate_size
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if savings <= 0:
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return False
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if source_size < SMALL_FILE_LIMIT:
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return savings >= SMALL_MIN_SAVINGS
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return (savings / source_size) >= LARGE_MIN_RATIO
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def classify_large_image(source_size: int, width: int, height: int) -> bool:
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return source_size > MAX_FILE_SIZE or max(width, height) > MAX_DIMENSION
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def image_info(path: Path) -> ImageInfo:
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output = run(
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["magick", "identify", "-ping", "-format", "%w %h %k", str(path)],
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capture=True,
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)
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width_text, height_text, colors_text = output.split()
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return ImageInfo(int(width_text), int(height_text), int(colors_text))
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def text_files() -> list[Path]:
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return sorted(
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path
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for path in ROOT.rglob("*")
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if path.is_file()
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and path.suffix.lower() in TEXT_EXTENSIONS
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and "assets_backup" not in path.parts
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and ".git" not in path.parts
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and "docs" not in path.parts
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and "tests" not in path.parts
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)
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def source_images() -> list[Path]:
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return sorted(
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path
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for path in IMAGES_DIR.rglob("*")
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if path.is_file() and path.suffix.lower() in SOURCE_EXTENSIONS and not path.name.startswith("._")
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)
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def colliding_stems(paths: list[Path]) -> set[str]:
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counts = Counter(path.with_suffix("").relative_to(ROOT).as_posix() for path in paths)
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return {stem for stem, count in counts.items() if count > 1}
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def build_webp_path(source: Path, duplicate_stems: set[str]) -> Path:
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stem_key = source.with_suffix("").as_posix()
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if not source.is_absolute():
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stem_key = source.with_suffix("").as_posix()
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else:
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stem_key = source.with_suffix("").relative_to(ROOT).as_posix()
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if stem_key in duplicate_stems:
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return source.with_name(f"{source.name}.webp")
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return source.with_suffix(".webp")
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def managed_webps() -> list[Path]:
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return sorted(
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path
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for path in IMAGES_DIR.rglob("*.webp")
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if path.is_file() and not path.name.startswith("._")
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)
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def render_candidate(source: Path, operations: list[str], suffix: str) -> Path:
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target = source.with_name(f"{source.stem}.{suffix}{source.suffix}")
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run(["magick", str(source), *operations, str(target)])
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return target
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def render_webp_candidate(source: Path, operations: list[str], suffix: str) -> Path:
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target = source.with_name(f"{source.stem}.{suffix}.webp")
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run(["magick", str(source), *operations, str(target)])
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return target
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def choose_smaller_original(source: Path, info: ImageInfo) -> tuple[int, int]:
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original_size = source.stat().st_size
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extension = source.suffix.lower()
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candidates: list[Path] = []
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try:
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if extension in {".jpg", ".jpeg"}:
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jpeg_profiles = [
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["-strip", "-sampling-factor", "4:2:0", "-quality", "86", "-interlace", "Plane"],
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]
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if classify_large_image(original_size, info.width, info.height):
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jpeg_profiles.extend(
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[
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["-strip", "-sampling-factor", "4:2:0", "-quality", "82", "-interlace", "Plane"],
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["-strip", "-sampling-factor", "4:2:0", "-quality", "78", "-interlace", "Plane"],
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]
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)
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if max(info.width, info.height) > MAX_DIMENSION:
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jpeg_profiles.extend(
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[
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[
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"-strip",
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"-resize",
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f"{MAX_DIMENSION}x{MAX_DIMENSION}>",
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"-sampling-factor",
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"4:2:0",
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"-quality",
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"84",
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"-interlace",
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"Plane",
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],
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[
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"-strip",
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"-resize",
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f"{MAX_DIMENSION}x{MAX_DIMENSION}>",
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"-sampling-factor",
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"4:2:0",
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"-quality",
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"80",
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"-interlace",
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"Plane",
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],
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]
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)
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for index, profile in enumerate(jpeg_profiles):
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candidates.append(render_candidate(source, profile, f"jpg-opt-{index}"))
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elif extension == ".png":
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candidates.append(
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render_candidate(
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source,
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["-strip", "-define", "png:compression-level=9", "-define", "png:compression-filter=5"],
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"png-opt",
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)
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)
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elif extension == ".gif":
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candidates.append(render_candidate(source, ["-strip"], "gif-opt"))
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best = min([source, *candidates], key=lambda candidate: candidate.stat().st_size)
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best_size = best.stat().st_size
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if best != source:
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best.replace(source)
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return original_size, best_size
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finally:
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for candidate in candidates:
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if candidate.exists():
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candidate.unlink()
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def choose_webp(source: Path, info: ImageInfo, target_path: Path) -> tuple[bool, int]:
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source_size = source.stat().st_size
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extension = source.suffix.lower()
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candidates: list[Path] = []
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try:
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if extension in {".jpg", ".jpeg"}:
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profiles = [
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["-strip", "-quality", "84", "-define", "webp:method=6"],
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["-strip", "-quality", "80", "-define", "webp:method=6"],
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]
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if classify_large_image(source_size, info.width, info.height):
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profiles.append(["-strip", "-quality", "76", "-define", "webp:method=6"])
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if max(info.width, info.height) > MAX_DIMENSION:
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profiles.extend(
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[
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["-strip", "-resize", f"{MAX_DIMENSION}x{MAX_DIMENSION}>", "-quality", "82", "-define", "webp:method=6"],
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["-strip", "-resize", f"{MAX_DIMENSION}x{MAX_DIMENSION}>", "-quality", "78", "-define", "webp:method=6"],
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]
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)
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elif extension == ".png":
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if info.colors <= 256 and source_size < SMALL_FILE_LIMIT:
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profiles = [
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["-strip", "-define", "webp:lossless=true", "-define", "webp:method=6"],
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]
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else:
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profiles = [
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["-strip", "-quality", "92", "-define", "webp:alpha-quality=95", "-define", "webp:method=6"],
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["-strip", "-quality", "88", "-define", "webp:alpha-quality=90", "-define", "webp:method=6"],
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]
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if max(info.width, info.height) > MAX_DIMENSION:
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profiles.extend(
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[
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[
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"-strip",
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"-resize",
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f"{MAX_DIMENSION}x{MAX_DIMENSION}>",
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"-quality",
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"90",
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"-define",
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"webp:alpha-quality=92",
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"-define",
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"webp:method=6",
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],
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[
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"-strip",
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"-resize",
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f"{MAX_DIMENSION}x{MAX_DIMENSION}>",
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"-quality",
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"86",
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"-define",
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"webp:alpha-quality=88",
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"-define",
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"webp:method=6",
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],
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]
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)
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else:
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profiles = [["-strip", "-define", "webp:lossless=true", "-define", "webp:method=6"]]
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for index, profile in enumerate(profiles):
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candidates.append(render_webp_candidate(source, profile, f"webp-opt-{index}"))
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best = min(candidates, key=lambda candidate: candidate.stat().st_size)
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best_size = best.stat().st_size
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if should_keep_conversion(source_size, best_size):
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best.replace(target_path)
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accepted = True
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else:
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if target_path.exists():
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target_path.unlink()
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accepted = False
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return accepted, best_size
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finally:
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for candidate in candidates:
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if candidate.exists():
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candidate.unlink()
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def build_replacements(accepted_sources: list[Path], duplicate_stems: set[str]) -> dict[str, str]:
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replacements: dict[str, str] = {}
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for source in accepted_sources:
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relative = source.relative_to(ROOT).as_posix()
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target = build_webp_path(source, duplicate_stems).relative_to(ROOT).as_posix()
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replacements[relative] = target
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if relative.startswith("assets/images/"):
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replacements[relative.replace("assets/images/", "../images/", 1)] = target.replace(
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"assets/images/", "../images/", 1
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)
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replacements[relative.replace("assets/", "", 1)] = target.replace("assets/", "", 1)
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return replacements
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def referenced_asset_paths() -> set[str]:
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references: set[str] = set()
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pattern = re.compile(r"(assets/images|../images|images)/[^\"')\s>]+\.(?:png|jpg|jpeg|gif|webp|svg|ico)", re.IGNORECASE)
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for path in text_files():
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content = path.read_text(encoding="utf-8")
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for match in pattern.finditer(content):
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ref = match.group(0)
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candidates = [ROOT / ref, path.parent / ref]
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for candidate in candidates:
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if candidate.exists() and candidate.is_file():
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references.add(candidate.resolve().relative_to(ROOT).as_posix())
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break
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return references
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def should_prune_original(source: Path, referenced_paths: set[str], accepted_webp_paths: set[str]) -> bool:
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source_key = source.as_posix() if not source.is_absolute() else source.relative_to(ROOT).as_posix()
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if source_key in referenced_paths:
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return False
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return any(
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webp_key in accepted_webp_paths
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for webp_key in {
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source.with_suffix(".webp").as_posix() if not source.is_absolute() else source.with_suffix(".webp").relative_to(ROOT).as_posix(),
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source.with_name(f"{source.name}.webp").as_posix() if not source.is_absolute() else source.with_name(f"{source.name}.webp").relative_to(ROOT).as_posix(),
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}
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)
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def update_references(accepted_sources: list[Path], duplicate_stems: set[str]) -> int:
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replacements = build_replacements(accepted_sources, duplicate_stems)
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if not replacements:
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return 0
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pattern = re.compile("|".join(sorted((re.escape(item) for item in replacements), key=len, reverse=True)))
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changed = 0
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for path in text_files():
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original = path.read_text(encoding="utf-8")
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updated = pattern.sub(lambda match: replacements[match.group(0)], original)
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if updated != original:
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path.write_text(updated, encoding="utf-8")
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changed += 1
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return changed
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def prune_replaced_originals(images: list[Path], duplicate_stems: set[str]) -> int:
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references = referenced_asset_paths()
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accepted_webp_paths = {
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build_webp_path(source, duplicate_stems).relative_to(ROOT).as_posix()
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for source in images
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if build_webp_path(source, duplicate_stems).exists()
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}
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pruned = 0
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for source in images:
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if should_prune_original(source, references, accepted_webp_paths):
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source.unlink()
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pruned += 1
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return pruned
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def check_rewritten_webps() -> int:
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missing: list[str] = []
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pattern = re.compile(r"(assets/images|../images|images)/[^\"')\s>]+\.webp", re.IGNORECASE)
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for path in text_files():
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content = path.read_text(encoding="utf-8")
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for match in pattern.finditer(content):
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ref = match.group(0)
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candidates = [
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ROOT / ref,
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path.parent / ref,
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]
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if not any(candidate.exists() and candidate.is_file() for candidate in candidates):
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missing.append(f"{path.relative_to(ROOT)}: {ref}")
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if missing:
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print("\n".join(missing))
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return 1
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print("No missing rewritten webp references.")
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return 0
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def ensure_backup_copy() -> None:
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if BACKUP_DIR.exists():
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shutil.rmtree(BACKUP_DIR)
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BACKUP_DIR.mkdir(parents=True, exist_ok=True)
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for child in ASSETS_DIR.iterdir():
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destination = BACKUP_DIR / child.name
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if child.is_dir():
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shutil.copytree(child, destination)
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else:
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shutil.copy2(child, destination)
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def optimize_assets() -> int:
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if shutil.which("magick") is None:
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raise SystemExit("ImageMagick `magick` 未安装，无法继续处理图片。")
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ensure_backup_copy()
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images = source_images()
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duplicate_stems = colliding_stems(images)
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total_before = 0
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total_after_original = 0
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accepted_sources: list[Path] = []
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accepted_count = 0
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skipped_count = 0
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for source in images:
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info = image_info(source)
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before_size, after_original_size = choose_smaller_original(source, info)
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total_before += before_size
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total_after_original += after_original_size
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accepted, _ = choose_webp(source, image_info(source), build_webp_path(source, duplicate_stems))
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if accepted:
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accepted_sources.append(source)
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accepted_count += 1
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else:
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skipped_count += 1
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changed_files = update_references(accepted_sources, duplicate_stems)
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print(f"Backup refreshed at: {BACKUP_DIR.relative_to(ROOT)}")
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print(f"Raster size before optimization: {total_before / 1024 / 1024:.2f} MB")
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print(f"Raster size after original optimization: {total_after_original / 1024 / 1024:.2f} MB")
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print(f"Accepted webp conversions: {accepted_count}")
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print(f"Rejected webp conversions: {skipped_count}")
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print(f"Updated text files: {changed_files}")
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return 0
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def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("--check", action="store_true", help="validate rewritten webp references")
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parser.add_argument("--prune-replaced", action="store_true", help="delete originals already replaced by accepted webp files")
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args = parser.parse_args()
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if args.check:
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return check_rewritten_webps()
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if args.prune_replaced:
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images = source_images()
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duplicate_stems = colliding_stems(images)
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pruned = prune_replaced_originals(images, duplicate_stems)
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print(f"Pruned replaced originals: {pruned}")
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return 0
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return optimize_assets()
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if __name__ == "__main__":
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raise SystemExit(main())
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Reference in New Issue
Block a user