BrandCultivation/api.py

from config import load_service_config
from fastapi import FastAPI, Request, status, BackgroundTasks, HTTPException
from fastapi.exceptions import RequestValidationError
from fastapi.responses import JSONResponse
from database.dao.mysql_dao import MySqlDao
from models import Recommend
import os
from pydantic import BaseModel
import uvicorn
from utils import ReportUtils
import requests
from typing import List, Dict

app = FastAPI()
dao = MySqlDao()

cfgs = load_service_config()
# 添加全局异常处理器
@app.exception_handler(RequestValidationError)
async def validation_exception_handler(request: Request, exc: RequestValidationError):
    return JSONResponse(
        status_code=status.HTTP_400_BAD_REQUEST,
        content={
            "code": 400,
            "msg": "请求参数错误",
            "data": {
                "detail": exc.errors(),
                "body": exc.body
            }
        },
    )

# 定义请求体
class RecommendRequest(BaseModel):
    city_uuid: str              # 城市id
    product_code: str           # 卷烟编码
    recall_cust_count: int      # 推荐的商户数量
    delivery_count: int              # 投放的品规数量
    
class ReportRequest(BaseModel):
    city_uuid: str              # 城市id
    product_code: str           # 卷烟编码
    
@app.post("/brandcultivation/api/v1/recommend")
async def recommend(request: RecommendRequest, backgroundTasks: BackgroundTasks):
    gbdtlr_model_path = os.path.join("./models/rank/weights", request.city_uuid, "gbdtlr_model.pkl")
    if not os.path.exists(gbdtlr_model_path):
        return {"code": 200, "msg": "model not defined", "data": {"recommendationInfo": "该城市的模型未训练，请先进行训练"}}
    
    # 初始化模型
    recommend_model = Recommend(request.city_uuid)
    
    # 判断该品规是否是新品规
    products_in_oreder = dao.get_product_from_order(request.city_uuid)["product_code"].unique().tolist()
    if request.product_code in products_in_oreder:
        recommend_list = recommend_model.get_recommend_list_by_gbdtlr(request.product_code, recall_count=request.recall_cust_count)
    else:
        recommend_list = recommend_model.get_recommend_list_by_item2vec(request.product_code, recall_count=request.recall_cust_count)
    recommend_data = recommend_model.get_recommend_and_delivery(recommend_list, delivery_count=request.delivery_count)
    request_data = []
    for index, data in enumerate(recommend_data):
        id = index + 1
        request_data.append(
            {
                "id": id,
                "cust_code": data["cust_code"],
                "recommend_score": data["recommend_score"],
                "delivery_count": data["delivery_count"]
            }
        )
    
    # 异步执行报告生成任务
    backgroundTasks.add_task(
        generate_report,
        request.city_uuid,
        request.product_code,
        request.recall_cust_count,
        request.delivery_count
    )
    
    return {"code": 200, "msg": "success", "data": {"recommendationInfo": request_data}}

def generate_report(city_uuid, product_id, recall_count, delivery_count):
    """生成报告"""
    report_util = ReportUtils(city_uuid, product_id)
    report_util.generate_all_data(recall_count, delivery_count)
    repots_dir = os.path.join('./data/reports', city_uuid, product_id)
    upload_file(repots_dir)
    
def upload_file(reports_dir):
    """上传报告文件"""
    base_url = cfgs["aliyun"]["upload_url"]
    files = [
        "卷烟信息表.xlsx",
        "品规商户特征关系表.xlsx",
        "相似卷烟表.xlsx"
    ]
    # 设置请求头
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
        "Accept": "*/*",
    }
    # 设置Cookie
    cookies = {
        "ecp_token": "ZXlKamIyUmxJam9pTURZMVltUXpZbUV5T0dWaFl6ZzRPREJqTkRjNU5ERXpaV0k0T1dRd1pERWlMQ0p6WTI5d1pTSTZJbkJ5YjNSbFkzUmxaQ0lzSW1Oc2FXVnVkQ0k2SW1Oc2FXVnVkRjlzYjI1bmFta2lmUT09",
        "acw_tc": "0a03176c17452016143048775e73c8e9556c4c3ee2dbc80f405a9314a5d0e5",
        "cna": "09T8H5zH8SoCASeqHG9RyLbu",
        "isg": "BDAwNyXyI9cQD__-0PkIodjTAfiCeRTD-vUtYyqmIw3d5bGP0Y0nUayWOe2F3syb",
        "dd-ztna-token": "eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiIwNTAwMzQzMDM4MjYxNDMwOTQiLCJjb3JwSWQiOiJkaW5nYzc2YTJhMzdiMjRhODYwYTRhYzVkNjk4MDg2NGQzMzUiLCJkZXB0SWRzIjoiW1s4Mzk0NzIxNjAsODM2MjQ1MTUzLDFdXSIsInJvbGVJZHMiOiJbMjEwNDk3MDY1OF0iLCJ1bmlvbklkIjoiVXFyYTB4U0VQcWNxdFNhQTFqSzRzZ2lFaUUiLCJleHAiOjE3NDU4MDY0MjIsImlhdCI6MTc0NTIwMTYyMn0.S0K3UWF0fBP5fF6TQaUkxe8I7piSQjrXqG3DdviqTzdO9Y0J7wsydcRvfp-OuHUkXbY92diIBGRHBr5Bb0eYgmCZ946Q8CHk12WXWvJmMDPrQ4i2C1J7W7uzUuPYJiWQLGQd40iCxNKfZIGq2ML-6r1i_k0iA7L_f6En1e9b5gLIs0GaluUwhCTTpAHBsmb-FquQER2Um9igARbMT6aaNrJzQbcPPWntQ3Pz_65PgjtTUMiFtBZW-YeAm2iB9JtYo_SJUsoX0d_oYo-6D4IfgZtkYKZZxbLj5rWnhoaJHm5acELAO8otQNZYQra0PfRIaKTT1vNkr1L5rShIxZk3yQ"
    }
    files_id = {}
    for file in files:
        file_path = os.path.join(reports_dir, file)
        try:
            with open(file_path, 'rb') as f:
                files = {'file': (os.path.basename(file_path), f)}
                
                response = requests.post(
                    base_url,
                    headers=headers,
                    files=files,
                    verify=True
                )
                
                if response.json()["success"]:
                    file_id = response.json()["data"]["file_info"]["fileid"]
                    files_id[os.path.basename(file_path).split('.')[0]] = file_id
        except requests.exceptions.RequestException as e:
            print("请求出错:", e)
        except Exception as e:
            print("发生错误:", e)
    
    files_id_str = ""
    if files_id:
        for filename, file_id in files_id.items():
            files_id_str += f"{filename},{file_id}\n"
    else:
        files_id_str = "failed"
    with open(os.path.join(reports_dir, "files_id.txt"), 'w', encoding="utf-8") as file:
        file.write(files_id_str)

@app.post("/brandcultivation/api/v1/report")
async def get_file_id(request: ReportRequest):
    files_id_path = os.path.join("./data/reports", request.city_uuid, request.product_code, "files_id.txt")
    if not os.path.exists(files_id_path):
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND,
            detail="Reports not found"
        )
    
    with open(files_id_path, 'r', encoding="utf-8") as file:
        lines = file.readlines()
        
    if lines[0].strip() == "failed":
        raise HTTPException(
            status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
            detail="reports upload failed"
        )
    
    request_data = []
    for index, line in enumerate(lines):
        filename, file_id = line.strip().split(",")
        request_data.append(
            {
                "id": index+1,
                "filename": filename,
                "file_id": file_id
            }
        )
    
    return {"code": 200, "msg": "success", "data": {"reportInfo": request_data}}
        
    
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7960)
    # report_dir = "./data/reports/00000000000000000000000011445301/440298"
    # upload_file(report_dir)