基于 Django 与爬虫的招聘信息推荐系统实现

核心实现

后端逻辑基于 Django 的 MTV 模式构建，重点处理文件上传、权限校验及数据查询。以下代码展示了部分关键接口的实现细节，包括统计计算、文件 IO 操作及爬虫调度。

# coding:utf-8
def schemaName_cal(request, tableName, columnName):
    ''' 计算规则接口 '''
    if request.method in ["POST", "GET"]:
        msg = {"code": normal_code, 'data': []}
        allModels = apps.get_app_config('main').get_models()
        for m in allModels:
            if m.__tablename__ == tableName:
                data = m.getcomputedbycolumn(m, m, columnName)
                print(data)
                if data:
                    try: sum='%.05f' % float(data.get("sum"))
                    except: sum=0.00
                    try: max='%.05f' % float(data.get("max"))
                    except: max=0.00
                    try: min='%.05f' % float(data.get("min"))
                    except: min=0.00
                    try: avg='%.05f' % float(data.get("avg"))
                    except: avg=0.00
                    msg['data'] = { "sum": sum, "max": max, "min": min, "avg": avg, }
                    break
        return JsonResponse(msg)

def schemaName_file_upload(request):
    ''' 上传 '''
    if request.method in ["POST", "GET"]:
        msg = {"code": normal_code, "msg": "成功", "data": {}}
        file = request.FILES.get("file")
        if file:
            filename = file.name
            filesuffix = filename.split(".")[-1]
            file_name = "{}.{}".format(int(float(time.time()) * 1000), filesuffix)
            filePath = os.path.join(os.getcwd(), "templates/front", file_name)
            print("filePath===========>", filePath)
            with open(filePath, 'wb+') as destination:
                for chunk in file.chunks():
                    destination.write(chunk)
            msg["file"] = file_name
            # 判断是否需要保存为人脸识别基础照片
            req_dict = request.session.get("req_dict")
            type1 = req_dict.get("type", 0)
            print("type1=======>",type1)
            type1 = int(type1)
            if type1 == 1:
                params = {"name":"faceFile","value": file_name}
                config.createbyreq(config, config, params)
        return JsonResponse(msg)

def schemaName_spider(request, tableName):
    if request.method in ["POST", "GET"]:
        msg = {"code": normal_code, "msg": "成功", "data": []}
        # Linux cmd = "cd /yykj/python/9999/spider05zp2 && scrapy crawl "+tableName+"Spider -a databaseName=djangowvp2z"
        # Windows # cmd = "cd C:\\test1\\spider && scrapy crawl " + tableName + "Spider"
        os.system(cmd)
        return JsonResponse(msg)

注意：生产环境中直接使用 os.system 执行爬虫命令存在安全风险，建议改用 Celery 异步任务队列或独立进程管理，避免阻塞主线程并防止命令注入。

测试与总结

系统测试覆盖了黑盒与白盒两个维度，确保功能逻辑与内部结构的一致性。经过多轮验证，系统在信息分发与管理上表现稳定。

项目最终实现了基于 Python 与 MySQL 的高效招聘管理系统。对用户而言，操作界面简洁直观；对管理员而言，后台增删改查流程清晰，数据库建表工作得到简化。整体方案有效节约了时间与资源，提升了招聘信息的流转效率。