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201 lines
6.9 KiB
201 lines
6.9 KiB
from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from fastapi.middleware.cors import CORSMiddleware
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import random
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import time
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from fastapi import FastAPI, File, UploadFile
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from fastapi.responses import JSONResponse
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import pandas as pd
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# from openpyxl import Workbook, load_workbook
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import math
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import os
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from fastapi import Depends
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app = FastAPI()
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# CORS 中间件
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"], # 允许所有来源
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# DATA_PATH = os.path.abspath(__file__) + "\\data\\"
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DATA_PATH = "./demo/Data/"
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initial_data = {
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'学号': ['*********'],
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'姓名': ['BOSS_K'],
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'积分': [9.9]
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}
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initial_info = {
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'basicProbability': [1.0],
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# 'lastRow': [0],
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'maxPoint': [0.0],
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'minPoint': [0.0]
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}
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initial_data_df = pd.DataFrame(initial_data)
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initial_info_df = pd.DataFrame(initial_info)
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# 定义请求体模型
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class StudentRequest(BaseModel):
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id: str
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name: str
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points: float
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# 获取文件路径
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async def get_file_path(class_name: str):
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file_path = DATA_PATH + class_name + ".xlsx"
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if not os.path.exists(file_path):
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raise HTTPException(status_code=403, detail="Not authenticated")
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return file_path
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# 上传excel
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@app.post("/{class_name}/upload")
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async def upload_file(file_path: str = Depends(get_file_path), file: UploadFile = File(...)):
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# 检查文件类型
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if not (file.filename.endswith('.xlsx') or file.filename.endswith('.xls')):
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return JSONResponse(content={"error": "无效的文件类型"}, status_code=400)
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try:
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# 将 Excel 文件读取为 DataFrame
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df_data = pd.read_excel(file_path, sheet_name='Data')
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df_info = pd.read_excel(file_path, sheet_name='Info')
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df_upload = pd.read_excel(file.file)
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new_rows = []
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# maxPoint = df_info.loc[0, 'maxPoint']
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# minPoint = df_info.loc[0, 'minPoint']
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for index, row in df_upload.iterrows():
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id = row['学号'] # 根据列名访问学号
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name = row['姓名'] # 根据列名访问姓名
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points = 0.0
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if '积分' in row:
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points = row['积分']
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# maxPoint = math.max(points, maxPoint)
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# minPoint = math.min(points, minPoint)
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new_rows.append({'学号': id, '姓名': name, '积分': points})
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df_data = pd.concat([df_data, pd.DataFrame(new_rows)], ignore_index=True)
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# 根据 '积分' 列降序排序
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df_data = df_data.sort_values(by='积分', ascending=False)
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with pd.ExcelWriter(file_path, mode='a', engine='openpyxl') as writer:
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del writer.book['Data'] # 删除旧的工作表
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df_data.to_excel(writer, sheet_name='Data', index=False)
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df_info.loc[0, 'basicProbability'] = 1.0
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# df_info.loc[0, 'maxPoint'] = maxPoint
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# df_info.loc[0, 'minPoint'] = minPoint
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with pd.ExcelWriter(file_path, mode='a', engine='openpyxl') as writer:
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del writer.book['Info'] # 删除旧的工作表
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df_info.to_excel(writer, sheet_name='Info', index=False)
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return {"message": "文件上传成功"}
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except Exception as e:
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return JSONResponse(content={"error": str(e)}, status_code=500)
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# 创建班级的接口
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@app.get("/create-class/{class_name}")
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async def create_class(class_name: str):
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# return {"ok":"ok"}
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file_path = DATA_PATH + class_name + ".xlsx"
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if os.path.exists(file_path):
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return {"message": "班级已存在"}
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# 创建excel
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initial_data_df.to_excel(file_path, sheet_name='Data', index=False)
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with pd.ExcelWriter(file_path, mode='a', engine='openpyxl') as writer:
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initial_info_df.to_excel(writer, sheet_name='Info', index=False)
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return {"message": "班级创建成功"}
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# 随机点名的接口
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@app.get("/{class_name}/random-call")
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async def random_call(file_path: str = Depends(get_file_path)):
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df_data = pd.read_excel(file_path, sheet_name='Data')
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df_info = pd.read_excel(file_path, sheet_name='Info')
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n = len(df_data)
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if n <= 0:
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raise HTTPException(status_code=404, detail="没有学生可供点名")
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# 进行随机
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basicProbability = float(df_info.iloc[0]['basicProbability'])
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# lastRow = int(df_info.iloc[0]['lastRow'])
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maxPoint = float(df_info.iloc[0]['maxPoint'])
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minPoint = float(df_info.iloc[0]['minPoint'])
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res = {}
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basicProbability *= 0.8
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while (True):
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# print(basicProbability)
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# lastRow = (lastRow + 1) % n
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i = math.floor(random.random() * n)
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points = df_data.iloc[i]['积分']
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hit_probability = (maxPoint - points + 1) / (maxPoint - minPoint + 20) * basicProbability
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if random.random() <= hit_probability: #成功命中倒霉蛋
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res = {"name": str(df_data.iloc[i]['姓名']),
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"id": str(df_data.iloc[i]['学号']),
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"points": float(points)}
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break
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basicProbability *= 1.03
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# 更新信息
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df_info.loc[0, 'basicProbability'] = basicProbability
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# df_info.loc[0, 'lastRow'] = lastRow
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with pd.ExcelWriter(file_path, mode='a', engine='openpyxl') as writer:
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del writer.book['Info'] # 删除旧的工作表
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df_info.to_excel(writer, sheet_name='Info', index=False)
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return res
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# 修改积分的接口
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@app.post("/{class_name}/change-points")
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async def change_points(student_request: StudentRequest, file_path: str = Depends(get_file_path)):
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df_data = pd.read_excel(file_path, sheet_name='Data')
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df_info = pd.read_excel(file_path, sheet_name='Info')
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print(df_data)
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index = -1
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for i, row in df_data.iterrows():
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print(row['学号'], student_request.id)
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print(row['姓名'], student_request.name)
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if (str(row['学号']) == str(student_request.id) and str(row['姓名']) == str(student_request.name)):
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index = i
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break
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if (index < 0):
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raise HTTPException(status_code=400, detail="学号姓名无效")
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df_data.loc[index, '积分'] = student_request.points
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df_data = df_data.sort_values(by='积分', ascending=False)
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with pd.ExcelWriter(file_path, mode='a', engine='openpyxl') as writer:
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del writer.book['Data'] # 删除旧的工作表
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df_data.to_excel(writer, sheet_name='Data', index=False)
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df_info.loc[0, 'maxPoint'] = max(df_info.loc[0, 'maxPoint'], student_request.points)
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df_info.loc[0, 'minPoint'] = min(df_info.loc[0, 'minPoint'], student_request.points)
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with pd.ExcelWriter(file_path, mode='a', engine='openpyxl') as writer:
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del writer.book['Info'] # 删除旧的工作表
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df_info.to_excel(writer, sheet_name='Info', index=False)
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return {"message": "积分已修改"}
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if __name__ == "__main__":
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import uvicorn
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import sys
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random.seed(int(time.time()))
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# 使用 uvicorn 启动服务器
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uvicorn.run(app, host="0.0.0.0", port=8000) |