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- package services
- import (
- "bytes"
- "encoding/json"
- "eta/eta_index_lib/models"
- "eta/eta_index_lib/utils"
- "fmt"
- "github.com/shopspring/decimal"
- "os"
- "os/exec"
- "reflect"
- "strings"
- )
- func Test() (err error) {
- defer func() {
- if err != nil {
- fmt.Println("err:", err)
- }
- }()
- ///usr/local/bin/python3.9
- //exec.Command("bin/bash", "-c")
- //cmd := exec.Command("/usr/local/bin/python3.9", "-c", "/Users/roc/go/src/eta/eta_index_lib/test2.py")
- //cmd := exec.Command("python3", "-c", "./test2.py")
- cmd := exec.Command("python3", "/Users/roc/go/src/eta/eta_index_lib/test2.py")
- outputByte, err := cmd.Output()
- //fmt.Println(err)
- fmt.Println("start")
- if err != nil {
- return
- }
- fmt.Println(string(outputByte))
- arr := strings.Split(string(outputByte), "result=")
- arrLen := len(arr)
- //fmt.Println(arr)
- if arrLen <= 1 {
- err = fmt.Errorf("python运算结果异常")
- return
- }
- resultStr := arr[arrLen-1]
- fmt.Println(resultStr)
- var dataMap map[string]float64
- json.Unmarshal([]byte(resultStr), &dataMap)
- fmt.Println(dataMap)
- //i, err := python3.Py_Main(os.Args)
- //if err != nil {
- // fmt.Printf("error launching the python interpreter: %s\n", err)
- // os.Exit(1)
- //}
- ////commStr := "#!/usr/bin/python\n# -*- coding: UTF-8 -*-\n\nimport pymysql\nimport pandas as pd\nfrom test_bak import sql_config\n\ndb = pymysql.connect(**sql_config)\ndb.autocommit(1)\ncursor = db.cursor()\npandas_fetch_all = pd.read_sql\n\n# 返回数据\nresult = {}\n\n# 格式化返回数据\ndef format_data(data: pd.DataFrame,\n index_str: str = \"data_time\",\n value_str: str = \"value\"\n ) -> dict:\n \"\"\"\n Parameters\n ----------\n data : pandas的DataFrame数据结构.\n index_str : 对象下标字符串,在pandas的DataFrame中的列名.\n value_str : 对象值字符串,在pandas的DataFrame中的列名\n\n Returns\n -------\n DataFrame or Iterator[DataFrame]\n 例子:{'2007-01-09': 3220.0, '2007-01-10': 3230.0}\n\n \"\"\"\n tmp_result = {}\n for num in range(1, data.index.size): # 迭代 所有的指标\n tmp_result[data[index_str][num]] = data[value_str][num]\n return tmp_result\n\n\ndef query():\n edb_code = 's0033227'\n data_time = '2002-03-17'\n # field_name = '平均温度'\n sql1 = f\"\"\"SELECT data_time,`value` FROM edb_data_wind WHERE edb_code = '{edb_code}' and data_time > '{data_time}' ;\"\"\"\n raw = pandas_fetch_all(sql1, db)\n raw['data_time_str'] = raw['data_time'].apply(lambda x: x.strftime(\"%Y-%m-%d\"))\n format_result = format_data(raw, \"data_time_str\", \"value\")\n print(format_result)\n return format_result\n\n\nresult = query()\ndb.close()\n"
- ////i := python3.PyRun_SimpleString(commStr)
- //fmt.Println(i)
- return
- }
- // EdbDataStrFromPython 通过python代码获取到的指标数据(interface数据)
- type EdbDataStrFromPython struct {
- Date map[int]string `json:"date"`
- Value map[int]interface{} `json:"value"`
- }
- // ExecPythonCode 执行Python代码
- func ExecPythonCode(edbCode, reqCode string) (dataMap models.EdbDataFromPython, err error, errMsg string) {
- defer func() {
- if err != nil {
- fmt.Println("err:", err)
- }
- }()
- codeStr := strings.ToLower(reqCode)
- // 限制python代码的执行,如果包含特殊的关键词,则报错
- if strings.Contains(codeStr, "drop table") || strings.Contains(codeStr, "delete") || strings.Contains(codeStr, "update") || strings.Contains(codeStr, "alter") || strings.Contains(codeStr, "truncate") {
- err = fmt.Errorf("不支持该命令")
- return
- }
- //获取python文件的绝对地址
- pythonFile, err := getPythonFileAbsolutePath(edbCode)
- if err != nil {
- return
- }
- pythonCodeStr := getPythonFrontStr() + reqCode + getPythonLaterStr()
- fileHandle, err := os.OpenFile(pythonFile, os.O_RDWR|os.O_CREATE|os.O_EXCL, 0766)
- if err != nil {
- return
- }
- defer func() {
- os.Remove(pythonFile)
- }()
- _, err = fileHandle.Write([]byte(pythonCodeStr))
- if err != nil {
- return
- }
- fileHandle.Close()
- cmd := exec.Command(utils.PYTHON_PATH, pythonFile)
- var out, errMsgOut bytes.Buffer
- cmd.Stdout = &out
- cmd.Stderr = &errMsgOut
- err = cmd.Run()
- if err != nil {
- errMsg = errMsgOut.String()
- return
- }
- outputByte := out.String()
- if err != nil {
- return
- }
- //fmt.Println(string(outputByte))
- arr := strings.Split(string(outputByte), "result=")
- arrLen := len(arr)
- //fmt.Println(arr)
- if arrLen <= 1 {
- err = fmt.Errorf("python运算结果异常")
- return
- }
- resultStr := arr[arrLen-1]
- //fmt.Println(resultStr)
- var dataMapStr EdbDataStrFromPython
- //先将value转为interface
- err = json.Unmarshal([]byte(resultStr), &dataMapStr)
- if err != nil {
- return
- }
- dataMap.Date = make(map[int]string)
- dataMap.Value = make(map[int]float64)
- //将value为nil的给过滤掉
- i := 0
- lenData := len(dataMapStr.Date)
- for k := 0; k < lenData; k++ {
- date := dataMapStr.Date[k]
- tmpValue := dataMapStr.Value[k]
- if reflect.TypeOf(tmpValue) != nil {
- if reflect.TypeOf(tmpValue).Kind() == reflect.Float64 {
- dataMap.Date[i] = date
- dataMap.Value[i], _ = decimal.NewFromFloat(reflect.ValueOf(tmpValue).Float()).Truncate(4).Float64() //保留4位小数
- i++
- }
- }
- }
- //err = json.Unmarshal([]byte(resultStr), &dataMap)
- //fmt.Println(dataMap)
- return
- }
- // getPythonFileAbsolutePath 获取python文件的绝对地址
- func getPythonFileAbsolutePath(edbCode string) (pythonFile string, err error) {
- uploadDir := utils.STATIC_DIR + "python/"
- err = os.MkdirAll(uploadDir, 0766)
- if err != nil {
- return
- }
- pythonFile = uploadDir + fmt.Sprint(edbCode, "_", utils.GetRandDigit(16), ".py")
- if utils.RunMode != "release" {
- dir, tmpErr := os.Getwd()
- if tmpErr != nil {
- err = tmpErr
- return
- }
- pythonFile = dir + "/" + pythonFile
- }
- return
- }
- // getPythonFrontStr 获取python前面的代码
- func getPythonFrontStr() string {
- //return "#!/usr/bin/python\n# -*- coding: UTF-8 -*-\nimport json\n\nimport pymysql\nimport pandas as pd\n\nsql_config = {\n 'host': 'rm-uf67kg347rhjfep5c1o.mysql.rds.aliyuncs.com',\n 'port': 3306,#主机号\n 'user': 'hz_technology',#账户名\n 'passwd': 'hongze@2021',#密码\n 'db': 'test_hz_data',\n 'charset': 'utf8mb4',\n 'cursorclass': pymysql.cursors.DictCursor\n}\n\ndb = pymysql.connect(**sql_config)\ndb.autocommit(1)\ncursor = db.cursor()\npandas_fetch_all = pd.read_sql\n\n# 返回数据\nresult = {}\n\n# 格式化返回数据\ndef format_data(data: pd.DataFrame,\n index_str: str = \"data_time\",\n value_str: str = \"value\"\n ) -> pd.DataFrame:\n \"\"\"\n Parameters\n ----------\n data : pandas的DataFrame数据结构.\n index_str : 对象下标字符串,在pandas的DataFrame中的列名.\n value_str : 对象值字符串,在pandas的DataFrame中的列名\n\n Returns\n -------\n DataFrame or Iterator[DataFrame]\n 例子:{'2007-01-09': 3220.0, '2007-01-10': 3230.0}\n\n \"\"\"\n index_list = [] # 空列表\n value_list = [] # 空列表\n\n for num in range(1, data.index.size): # 迭代 所有的指标\n index_list.append(data[index_str][num])\n value_list.append(data[value_str][num])\n\n tmp_data = {\n \"date\": index_list,\n \"value\": value_list\n }\n pd_data = pd.DataFrame(tmp_data)\n # print(pd_data)\n return pd_data\n"
- str := fmt.Sprintf("#!/usr/bin/python\n# -*- coding: UTF-8 -*-\nimport json\n\nimport pymysql\nimport pandas as pd\nfrom pymongo import MongoClient\nimport pytz\n\nsql_config = {\n 'host': '%s',\n 'port': 3306,#主机号\n 'user': '%s',#账户名\n 'passwd': '%s',#密码\n 'db': '%s',\n 'charset': 'utf8mb4',\n 'cursorclass': pymysql.cursors.DictCursor\n}\n\ndb = pymysql.connect(**sql_config)\ndb.autocommit(1)\ncursor = db.cursor()\npandas_fetch_all = pd.read_sql\n\n", utils.PYTHON_MYSQL_HOST, utils.PYTHON_MYSQL_USER, utils.PYTHON_MYSQL_PASSWD, utils.PYTHON_MYSQL_DB)
- // mongo部分
- if utils.PYTHON_MONGO_HOST != `` {
- str += getPythonFront2Str()
- }
- // 格式化数据部分
- str += getPythonFront3Str()
- return str
- }
- // getPythonFront2Str
- // @Description: mongo部分
- // @author: Roc
- // @datetime 2024-05-07 18:38:03
- // @return string
- func getPythonFront2Str() string {
- str := fmt.Sprintf("\nfrom pymongo import MongoClient\nfrom dateutil.tz import tzlocal\n# MongoDB 连接配置\nmongo_config = {\n 'host': '%s', # 替换为你的 MongoDB 连接字符串\n 'database': '%s', # 替换为你的数据库名\n 'collection': '%s', # 替换为你的集合名\n 'auth_mechanism': '%s' # 替换为你的认证机制\n}\n\n# 创建 MongoClient 并连接到数据库\nclient = MongoClient(mongo_config['host'], authMechanism=mongo_config['auth_mechanism'])\nmgo_db = client[mongo_config['database']]\ncollection = mgo_db[mongo_config['collection']]\n\n# 定义时区\nutc_tz = pytz.utc\nlocal_tz = tzlocal() # 本地时区", utils.PYTHON_MONGO_HOST, utils.PYTHON_MONGO_DATABASE, "edb_data_business", utils.PYTHON_MONGO_AUTH_MECHANISM)
- return str
- }
- // getPythonFront3Str
- // @Description: 第三部分
- // @author: Roc
- // @datetime 2024-05-07 18:37:56
- // @return string
- func getPythonFront3Str() string {
- str := fmt.Sprintf("\n# 返回数据\nresult = {}\n\n# 格式化返回数据\ndef format_data(data: pd.DataFrame,\n index_str: str = \"data_time\",\n value_str: str = \"value\"\n ) -> pd.DataFrame:\n \"\"\"\n Parameters\n ----------\n data : pandas的DataFrame数据结构.\n index_str : 对象下标字符串,在pandas的DataFrame中的列名.\n value_str : 对象值字符串,在pandas的DataFrame中的列名\n\n Returns\n -------\n DataFrame or Iterator[DataFrame]\n 例子:{'2007-01-09': 3220.0, '2007-01-10': 3230.0}\n\n \"\"\"\n index_list = [] # 空列表\n value_list = [] # 空列表\n\n for num in range(0, data.index.size): # 迭代 所有的指标\n date=data[index_str][num]\n if isinstance(date,str) is False:\n index_list.append(data[index_str][num].strftime(\"%%Y-%%m-%%d\"))\n else:\n index_list.append(data[index_str][num])\n value_list.append(data[value_str][num])\n\n tmp_data = {\n \"date\": index_list,\n \"value\": value_list\n }\n pd_data = pd.DataFrame(tmp_data)\n return pd_data\n\n")
- return str
- }
- // getPythonLaterStr 获取python结尾的代码
- func getPythonLaterStr() string {
- return "\n\nprint(\"result=\", result.to_json())\ndb.close()"
- }
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