00ccf95cae
- Optimized mobile image loading (180px vs 200px desktop) - Fixed Install App navigation not working on desktop - Fixed replaceChild null error in hero rendering - Added PWA icon (512x512) - Fixed back button navigation issues - Added mobile bottom padding for nav bar - Moved Get App FAB higher to avoid nav overlap - Removed unnecessary pushState from video navigation - Made Search/MyList tabs not scroll to top on mobile - Removed duplicate Android TV section from download page
96 lines
3.1 KiB
Python
96 lines
3.1 KiB
Python
import os
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import httpx
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import hashlib
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from PIL import Image
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from io import BytesIO
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from fastapi.responses import Response
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from typing import Optional
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import asyncio
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from functools import partial
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CACHE_DIR = "cache/images"
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os.makedirs(CACHE_DIR, exist_ok=True)
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def process_image_sync(content: bytes, width: Optional[int], cache_path: str) -> Optional[bytes]:
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"""Sync function to process image in thread pool"""
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try:
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img = Image.open(BytesIO(content))
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# Convert to RGB if necessary
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if img.mode in ("RGBA", "P"):
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img = img.convert("RGB")
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# Resize if width specified
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if width and img.width > width:
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ratio = width / float(img.width)
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height = int(float(img.height) * float(ratio))
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img = img.resize((width, height), Image.LANCZOS)
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# Save to buffer as WebP
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output = BytesIO()
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img.save(output, format="WEBP", quality=80)
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webp_data = output.getvalue()
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# Save to cache
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with open(cache_path, "wb") as f:
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f.write(webp_data)
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return webp_data
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except Exception as e:
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print(f"Error processing image sync: {e}")
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return None
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async def get_proxied_image(url: str, width: Optional[int] = None):
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"""
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Fetch an image, resize it, convert to WebP, and cache it.
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Non-blocking version.
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"""
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# Create a unique cache key based on URL and width
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cache_key = hashlib.md5(f"{url}_{width}".encode()).hexdigest()
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cache_path = os.path.join(CACHE_DIR, f"{cache_key}.webp")
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# 1. Check if cached version exists
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if os.path.exists(cache_path):
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# File IO in asyncio can still block slightly but usually acceptable for small files.
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# Ideally use aiofiles, but standard open is mostly fine for this scale.
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with open(cache_path, "rb") as f:
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return Response(content=f.read(), media_type="image/webp")
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# 2. Fetch original image (Async I/O)
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async with httpx.AsyncClient(follow_redirects=True) as client:
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try:
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response = await client.get(url, timeout=10.0)
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response.raise_for_status()
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except Exception as e:
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return None
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# 3. Process image with Pillow
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try:
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img = Image.open(BytesIO(response.content))
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# Convert to RGB if necessary (e.g., from RGBA or CMYK)
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if img.mode in ("RGBA", "P"):
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img = img.convert("RGB")
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# Resize if width specified
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if width and img.width > width:
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ratio = width / float(img.width)
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height = int(float(img.height) * float(ratio))
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img = img.resize((width, height), Image.LANCZOS)
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# 4. Save to buffer as WebP
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output = BytesIO()
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img.save(output, format="WEBP", quality=80)
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webp_data = output.getvalue()
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# 5. Save to cache
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with open(cache_path, "wb") as f:
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f.write(webp_data)
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return Response(content=webp_data, media_type="image/webp")
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except Exception as e:
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print(f"Error processing image: {e}")
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return None
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