package models

import (
	"errors"
	"fmt"
	"github.com/beego/beego/v2/client/orm"
	"github.com/shopspring/decimal"
	"hongze/hongze_edb_lib/services"
	"hongze/hongze_edb_lib/utils"
	"strings"
	"time"
)

// EdbDataPython python指标数据结构体
type EdbDataPython struct {
	EdbDataId     int `orm:"column(edb_data_id);pk"`
	EdbInfoId     int
	EdbCode       string
	DataTime      string
	Value         float64
	CreateTime    time.Time
	ModifyTime    time.Time
	DataTimestamp int64
}

// AddPythonEdb 新增python运算指标
func AddPythonEdb(edbInfoId int, edbCode string, item services.EdbDataFromPython) (err error) {
	var errMsg string
	o := orm.NewOrm()
	defer func() {
		if err != nil {
			go utils.SendEmail(utils.APP_NAME_CN+"【"+utils.RunMode+"】"+"失败提醒", " 同花顺数据获取失败:err:"+errMsg, utils.EmailSendToUsers)
		}
	}()

	var isAdd bool
	addSql := ` INSERT INTO edb_data_python (edb_info_id,edb_code,data_time,value,create_time,modify_time,data_timestamp) values `
	for k, dateTimeStr := range item.Date {
		//格式化时间
		currentDate, tmpErr := time.Parse(utils.FormatDate, dateTimeStr)
		if tmpErr != nil {
			err = tmpErr
			return
		}
		timestamp := currentDate.UnixNano() / 1e6
		timestampStr := fmt.Sprintf("%d", timestamp)

		//值
		val := item.Value[k]
		saveVal := utils.SubFloatToString(val, 20)
		addSql += GetAddSql(fmt.Sprint(edbInfoId), edbCode, dateTimeStr, timestampStr, saveVal)

		isAdd = true
	}

	if isAdd {
		addSql = strings.TrimRight(addSql, ",")
		_, err = o.Raw(addSql).Exec()
		if err != nil {
			errMsg = " tx.Exec Err :" + err.Error()
			return
		}
	}
	return
}

// EditPythonEdb 编辑python运算指标
func EditPythonEdb(edbInfoId int, edbCode string, item services.EdbDataFromPython) (err error) {
	var errMsg string
	o := orm.NewOrm()
	defer func() {
		if err != nil {
			go utils.SendEmail(utils.APP_NAME_CN+"【"+utils.RunMode+"】"+"失败提醒", " 同花顺数据获取失败:err:"+errMsg, utils.EmailSendToUsers)
		}
	}()

	var isAdd bool
	addSql := ` INSERT INTO edb_data_python (edb_info_id,edb_code,data_time,value,create_time,modify_time,data_timestamp) values `
	for k, dateTimeStr := range item.Date {
		//格式化时间
		currentDate, tmpErr := time.Parse(utils.FormatDate, dateTimeStr)
		if tmpErr != nil {
			err = tmpErr
			return
		}
		timestamp := currentDate.UnixNano() / 1e6
		timestampStr := fmt.Sprintf("%d", timestamp)

		//值
		val := item.Value[k]
		saveVal := utils.SubFloatToString(val, 20)
		addSql += GetAddSql(fmt.Sprint(edbInfoId), edbCode, dateTimeStr, timestampStr, saveVal)

		isAdd = true
	}

	if isAdd {
		addSql = strings.TrimRight(addSql, ",")
		_, err = o.Raw(addSql).Exec()
		if err != nil {
			errMsg = " tx.Exec Err :" + err.Error()
			return
		}
	}
	return
}

// RefreshAllPythonEdb 刷新所有 python运算指标
func RefreshAllPythonEdb(edbInfo *EdbInfo, item services.EdbDataFromPython) (err error) {
	o := orm.NewOrm()
	to, err := o.Begin()
	if err != nil {
		return
	}
	defer func() {
		if err != nil {
			fmt.Println("RefreshAllPythonEdb,Err:" + err.Error())
			_ = to.Rollback()
		} else {
			_ = to.Commit()
		}
	}()

	pythonDataMap := make(map[string]float64)
	pythonDate := make([]string, 0)
	for k, dateTimeStr := range item.Date {
		pythonDataMap[dateTimeStr] = item.Value[k]
		pythonDate = append(pythonDate, dateTimeStr)
	}

	//查询当前指标现有的数据
	var condition string
	var pars []interface{}
	condition += " AND edb_info_id=? "
	pars = append(pars, edbInfo.EdbInfoId)

	//所有的数据
	dataList, err := GetAllEdbDataPythonByEdbInfoId(edbInfo.EdbInfoId)
	if err != nil {
		return err
	}

	//待修改的指标数据map（index：日期，value：值）
	updateEdbDataMap := make(map[string]float64)
	removeDateList := make([]string, 0) //需要删除的日期
	for _, v := range dataList {
		currDataTime := v.DataTime
		pythonData, ok := pythonDataMap[currDataTime]
		if !ok {
			// 如果python运算出来的数据中没有该日期，那么需要移除该日期的数据
			removeDateList = append(removeDateList, currDataTime)
		} else {
			currValue, _ := decimal.NewFromFloat(pythonData).Truncate(4).Float64() //保留4位小数
			//如果计算出来的值与库里面的值不匹配，那么就去修改该值
			if v.Value != currValue {
				//将计算后的数据存入待拼接指标map里面，以便后续计算
				updateEdbDataMap[currDataTime] = currValue
			}
		}
		//移除python指标数据中当天的日期
		delete(pythonDataMap, currDataTime)
	}

	//sort.Strings(tbzEdbDataTimeList)

	//新增的数据入库
	{
		addDataList := make([]*EdbDataPython, 0)
		for dataTime, dataValue := range pythonDataMap {
			//时间戳
			currentDate, _ := time.Parse(utils.FormatDate, dataTime)
			timestamp := currentDate.UnixNano() / 1e6

			edbDataPython := &EdbDataPython{
				EdbInfoId:     edbInfo.EdbInfoId,
				EdbCode:       edbInfo.EdbCode,
				DataTime:      dataTime,
				Value:         dataValue,
				CreateTime:    time.Now(),
				ModifyTime:    time.Now(),
				DataTimestamp: timestamp,
			}
			addDataList = append(addDataList, edbDataPython)
		}
		//最后如果还有需要新增的数据，那么就统一入库
		if len(addDataList) > 0 {
			_, tmpErr := o.InsertMulti(len(addDataList), addDataList)
			if tmpErr != nil {
				err = tmpErr
				return
			}
		}
	}

	//删除已经不存在的累计同比拼接指标数据（由于同比值当日的数据删除了）
	{
		if len(removeDateList) > 0 {
			removeDateStr := strings.Join(removeDateList, `","`)
			removeDateStr = `"` + removeDateStr + `"`
			//如果拼接指标变更了，那么需要删除所有的指标数据
			tableName := GetEdbDataTableName(edbInfo.Source)
			sql := fmt.Sprintf(` DELETE FROM %s WHERE edb_info_id = ? and data_time in (%s) `, tableName, removeDateStr)

			_, err = o.Raw(sql, edbInfo.EdbInfoId).Exec()
			if err != nil {
				err = errors.New("删除不存在的Python运算指标数据失败,Err:" + err.Error())
				return
			}
		}
	}

	//修改现有的数据中对应的值
	{
		tableName := GetEdbDataTableName(edbInfo.Source)
		for edbDate, edbDataValue := range updateEdbDataMap {
			sql := fmt.Sprintf(` UPDATE  %s set value = ?,modify_time=now() WHERE edb_info_id = ? and data_time = ? `, tableName)

			_, err = o.Raw(sql, edbDataValue, edbInfo.EdbInfoId, edbDate).Exec()
			if err != nil {
				err = errors.New("更新现有的Python运算指标数据失败,Err:" + err.Error())
				return
			}
		}
	}
	return
}

// GetAllEdbDataPythonByEdbInfoId 根据指标id获取全部的数据
func GetAllEdbDataPythonByEdbInfoId(edbInfoId int) (items []*EdbDataPython, err error) {
	o := orm.NewOrm()
	sql := ` SELECT * FROM edb_data_python WHERE edb_info_id=? ORDER BY data_time DESC `
	_, err = o.Raw(sql, edbInfoId).QueryRows(&items)
	return
}

// EdbInfoPythonSaveReq 计算（运算）指标请求参数
type EdbInfoPythonSaveReq struct {
	AdminId          int    `description:"添加人id"`
	AdminName        string `description:"添加人名称"`
	EdbName          string `description:"指标名称"`
	Frequency        string `description:"频率"`
	Unit             string `description:"单位"`
	ClassifyId       int    `description:"分类id"`
	CalculateFormula string `description:"计算公式"`
	EdbInfoIdArr     []struct {
		EdbInfoId int    `description:"指标id"`
		FromTag   string `description:"指标对应标签"`
	}
}

// ExecPythonEdbReq 执行python代码运算指标的请求参数
type ExecPythonEdbReq struct {
	PythonCode string `description:"python代码"`
}

// AddPythonEdbReq 添加python代码运算指标的请求参数
type AddPythonEdbReq struct {
	AdminId    int    `description:"添加人id"`
	AdminName  string `description:"添加人名称"`
	EdbInfoId  int    `description:"指标id"`
	EdbName    string `description:"指标名称"`
	Frequency  string `description:"频度"`
	Unit       string `description:"单位"`
	ClassifyId int    `description:"分类id"`
	PythonCode string `description:"python代码"`
}