Lambda@Edge로 서버 비용 다이어트하기

{ "Records": [ { "cf": { "config": { "distributionDomainName": "d111111abcdef8.cloudfront.net", "distributionId": "EDFDVBD6EXAMPLE", "eventType": "origin-response", "requestId": "4TyzHTaYWb1GX1qTfsHhEqV6HUDd_BzoBZnwfnvQc_1oF26ClkoUSEQ==" }, "request": { "clientIp": "203.0.113.178", "headers": { "x-forwarded-for": [ { "key": "X-Forwarded-For", "value": "203.0.113.178" } ], "user-agent": [ { "key": "User-Agent", "value": "Amazon CloudFront" } ], "via": [ { "key": "Via", "value": "2.0 8f22423015641505b8c857a37450d6c0.cloudfront.net (CloudFront)" } ], "host": [ { "key": "Host", "value": "example.org" } ], "cache-control": [ { "key": "Cache-Control", "value": "no-cache" } ] }, "method": "GET", "origin": { "custom": { "customHeaders": {}, "domainName": "example.org", "keepaliveTimeout": 5, "path": "", "port": 443, "protocol": "https", "readTimeout": 30, "sslProtocols": [ "TLSv1", "TLSv1.1", "TLSv1.2" ] } }, "querystring": "", "uri": "/" }, "response": { "headers": { "access-control-allow-credentials": [ { "key": "Access-Control-Allow-Credentials", "value": "true" } ], "access-control-allow-origin": [ { "key": "Access-Control-Allow-Origin", "value": "*" } ], "date": [ { "key": "Date", "value": "Mon, 13 Jan 2020 20:12:38 GMT" } ], "referrer-policy": [ { "key": "Referrer-Policy", "value": "no-referrer-when-downgrade" } ], "server": [ { "key": "Server", "value": "ExampleCustomOriginServer" } ], "x-content-type-options": [ { "key": "X-Content-Type-Options", "value": "nosniff" } ], "x-frame-options": [ { "key": "X-Frame-Options", "value": "DENY" } ], "x-xss-protection": [ { "key": "X-XSS-Protection", "value": "1; mode=block" } ], "content-type": [ { "key": "Content-Type", "value": "text/html; charset=utf-8" } ], "content-length": [ { "key": "Content-Length", "value": "9593" } ] }, "status": "200", "statusDescription": "OK" } } } ] }

import boto3 import urllib.parse import io import base64 import mimetypes from PIL import Image import pillow_avif s3 = boto3.client('s3') mimetypes.add_type('image/avif', '.avif') def handler(event, context): config = event['Records'][0]['cf']['config'] request = event['Records'][0]['cf']['request'] response = event['Records'][0]['cf']['response'] # 정상 response가 오지 않는 경우 early return if int(response.get('status')) != 200: return response # S3 Object 가져오기 if not (s3_object := get_s3_object(config, request)): return response original_image = Image.open(s3_object["Body"]) # 쿼리 파라미터 추출 query = request['querystring'] image_spec = get_image_spec(original_image, query) # 리사이징 converted_image = convert_image(original_image, image_spec) # 응답 생성 content_type, _ = mimetypes.guess_type("dummy." + image_spec['image_format']) content_length = str(len(converted_image.get('data'))) response["status"] = "200" response["statusDescription"] = "OK" response["body"] = converted_image.get('data') response["bodyEncoding"] = "base64" response["headers"]["content-type"] = [{ "key": "Content-Type", "value": content_type }] response["headers"]["content-length"] = [{ "key": "Content-Length", "value": content_length }] return response def get_s3_object(config, request): bucket = 'bucket' key = request['uri'][1:] try: return s3.get_object(Bucket=bucket, Key=key) except Exception as e: print(e) print('Error getting object {} from bucket {}. Make sure they exist and your bucket is in the same region as this function.'.format(key, bucket)) raise e def get_image_spec(image, query): params = urllib.parse.parse_qs(query) width = int(params.get('w', [0])[0]) if 'w' in params else None height = int(params.get('h', [0])[0]) if 'h' in params else None image_format = params.get('f', [image.format])[0] return { 'width': width, 'height': height, 'image_format': image_format } def is_empty_image_spec(spec): return (spec['width'] is None or spec['width'] == 0) or (spec['height'] is None or spec['height'] == 0) def convert_image(image, spec): try: output = io.BytesIO() resized_image = image if is_empty_image_spec(spec): resized_image.save(output, format=spec['image_format']) else: resized_image = image.resize((spec['width'], spec['height']), Image.LANCZOS) redrawn_image = resized_image.convert('RGB') redrawn_image.save(output, format=spec['image_format']) converted_image = { 'width': resized_image.width, 'height': resized_image.height, 'format': spec['image_format'], 'data': base64.standard_b64encode(output.getvalue()).decode() } image.close() output.close() return converted_image except Exception as e: print(e)

ImportError: cannot import name '_imaging' from 'PIL'