python啟用gzip實(shí)現(xiàn)壓縮響應(yīng)體
1. Flask
服務(wù)器端代碼 (使用 Flask)
from flask import Flask, jsonify, request from flask_compress import Compress import logging app = Flask(__name__) Compress(app) # 啟用 gzip 壓縮 # 配置日志 logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @app.route('/data', methods=['GET']) def get_data(): try: # 處理請(qǐng)求參數(shù) count = int(request.args.get('count', 100)) # 返回一些示例 JSON 數(shù)據(jù) data = { 'message': 'Hello, this is compressed data!', 'numbers': list(range(count)) } return jsonify(data) except Exception as e: logger.error(f"Error occurred: {e}") return jsonify({'error': 'Internal Server Error'}), 500 @app.errorhandler(404) def page_not_found(e): return jsonify({'error': 'Not Found'}), 404 if __name__ == '__main__': app.run(debug=True)
客戶端代碼 (接收并解壓 gzip 響應(yīng))
import requests import gzip import json from io import BytesIO def fetch_data(url): try: # 發(fā)送請(qǐng)求到服務(wù)器端 response = requests.get(url) # 檢查響應(yīng)頭,確認(rèn)數(shù)據(jù)是否被 gzip 壓縮 if response.headers.get('Content-Encoding') == 'gzip': # 使用 gzip 解壓響應(yīng)內(nèi)容 compressed_content = BytesIO(response.content) with gzip.GzipFile(fileobj=compressed_content, mode='rb') as f: decompressed_data = f.read() # 解碼解壓后的數(shù)據(jù) data = json.loads(decompressed_data.decode('utf-8')) return data else: return response.json() except requests.RequestException as e: print(f"HTTP request failed: {e}") return None except json.JSONDecodeError as e: print(f"Failed to decode JSON: {e}") return None except Exception as e: print(f"An error occurred: {e}") return None if __name__ == '__main__': url = 'http://127.0.0.1:5000/data?count=50' data = fetch_data(url) if data: print(data) else: print("Failed to fetch data.")
2. FastAPI
服務(wù)器端代碼 (使用 FastAPI)
pip install fastapi uvicorn fastapi-compress
from fastapi import FastAPI, Request, HTTPException from fastapi.responses import JSONResponse from fastapi_compress import Compress import logging app = FastAPI() compressor = Compress() compressor.init_app(app) # 配置日志 logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @app.get("/data") async def get_data(count: int = 100): try: # 返回一些示例 JSON 數(shù)據(jù) data = { 'message': 'Hello, this is compressed data!', 'numbers': list(range(count)) } return JSONResponse(content=data) except Exception as e: logger.error(f"Error occurred: {e}") raise HTTPException(status_code=500, detail="Internal Server Error") @app.exception_handler(404) async def not_found_handler(request: Request, exc: HTTPException): return JSONResponse(status_code=404, content={'error': 'Not Found'}) if __name__ == '__main__': import uvicorn uvicorn.run(app, host="127.0.0.1", port=8000, log_level="info")
客戶端代碼 (接收并解壓 gzip 響應(yīng))
import requests import gzip import json from io import BytesIO def fetch_data(url): try: # 發(fā)送請(qǐng)求到服務(wù)器端 response = requests.get(url) # 檢查響應(yīng)頭,確認(rèn)數(shù)據(jù)是否被 gzip 壓縮 if response.headers.get('Content-Encoding') == 'gzip': # 使用 gzip 解壓響應(yīng)內(nèi)容 compressed_content = BytesIO(response.content) with gzip.GzipFile(fileobj=compressed_content, mode='rb') as f: decompressed_data = f.read() # 解碼解壓后的數(shù)據(jù) data = json.loads(decompressed_data.decode('utf-8')) return data else: return response.json() except requests.RequestException as e: print(f"HTTP request failed: {e}") return None except json.JSONDecodeError as e: print(f"Failed to decode JSON: {e}") return None except Exception as e: print(f"An error occurred: {e}") return None if __name__ == '__main__': url = 'http://127.0.0.1:8000/data?count=50' data = fetch_data(url) if data: print(data) else: print("Failed to fetch data.")
到此這篇關(guān)于python啟用gzip實(shí)現(xiàn)壓縮響應(yīng)體的文章就介紹到這了,更多相關(guān)python gzip壓縮響應(yīng)體內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家!
相關(guān)文章
一個(gè)基于flask的web應(yīng)用誕生 記錄用戶賬戶登錄狀態(tài)(6)
一個(gè)基于flask的web應(yīng)用誕生第六篇,這篇文章主要介紹了記錄用戶賬戶登錄狀態(tài)功能開(kāi)發(fā),具有一定的參考價(jià)值,感興趣的小伙伴們可以參考一下2017-04-04解決Numpy與Pytorch彼此轉(zhuǎn)換時(shí)的坑
這篇文章主要介紹了解決Numpy與Pytorch彼此轉(zhuǎn)換時(shí)的坑,具有很好的參考價(jià)值,希望對(duì)大家有所幫助。如有錯(cuò)誤或未考慮完全的地方,望不吝賜教2021-05-05Python利用operator模塊實(shí)現(xiàn)對(duì)象的多級(jí)排序詳解
python中的operator模塊提供了一系列的函數(shù)操作。下面這篇文章主要給大家介紹了在Python中利用operator模塊實(shí)現(xiàn)對(duì)象的多級(jí)排序的相關(guān)資料,需要的朋友可以參考借鑒,下面來(lái)一起看看吧。2017-05-05Python替換NumPy數(shù)組中大于某個(gè)值的所有元素實(shí)例
這篇文章主要介紹了Python替換NumPy數(shù)組中大于某個(gè)值的所有元素實(shí)例,具有很好的參考價(jià)值,希望對(duì)大家有所幫助。一起跟隨小編過(guò)來(lái)看看吧2020-06-06Python實(shí)現(xiàn)文件按照日期命名的方法
這篇文章主要介紹了Python實(shí)現(xiàn)文件按照日期命名的方法,涉及Python針對(duì)文件的遍歷、讀寫及時(shí)間操作相關(guān)技巧,需要的朋友可以參考下2015-07-07