diff --git a/config_shiyoujiao_lvyong.py b/config_shiyoujiao_lvyong.py index 3c03d06..cc230e6 100644 --- a/config_shiyoujiao_lvyong.py +++ b/config_shiyoujiao_lvyong.py @@ -139,8 +139,31 @@ edbnamelist = ['ds', 'y']+[edbcodenamedict[edbcodename] for edbcodename in edbcodelist] # eta自有数据指标编码，石油焦铝用还没新增，暂且留空 -modelsindex = { -} +modelsindex = [{ + "NHITS":"SELF0000363", +"Informer":"SELF0000364", +"LSTM":"SELF0000365", +"iTransformer":"SELF0000366", +"TSMixer":"SELF0000367", +"TSMixerx":"SELF0000368", +"PatchTST":"SELF0000369", +"RNN":"SELF0000370", +"GRU":"SELF0000371", +"TCN":"SELF0000372", +"BiTCN":"SELF0000373", +"DilatedRNN":"SELF0000374", +"MLP":"SELF0000375", +"DLinear":"SELF0000376", +"NLinear":"SELF0000377", +"TFT":"SELF0000378", +"FEDformer":"SELF0000379", +"StemGNN":"SELF0000380", +"MLPMultivariate":"SELF0000381", +"TiDE":"SELF0000382", +"DeepNPTS":"SELF0000383", +"NBEATS":"SELF0000384", + +}] # 百川数据指标编码 baichuanidnamedict = { diff --git a/config_shiyoujiao_lvyong_yuedu.py b/config_shiyoujiao_lvyong_yuedu.py new file mode 100644 index 0000000..804fc24 --- /dev/null +++ b/config_shiyoujiao_lvyong_yuedu.py @@ -0,0 +1,617 @@ +import logging +import os +import logging.handlers +import datetime +from lib.tools import MySQLDB, SQLiteHandler + + +# eta 接口token +APPID = "XNLDvxZHHugj7wJ7" +SECRET = "iSeU4s6cKKBVbt94htVY1p0sqUMqb2xa" + +# eta 接口url +sourcelisturl = 'http://10.189.2.78:8108/v1/edb/source/list' +classifylisturl = 'http://10.189.2.78:8108/v1/edb/classify/list?ClassifyType=' +uniquecodedataurl = 'http://10.189.2.78:8108/v1/edb/data?UniqueCode=4991c37becba464609b409909fe4d992&StartDate=2024-02-01' +classifyidlisturl = 'http://10.189.2.78:8108/v1/edb/list?ClassifyId=' +edbcodedataurl = 'http://10.189.2.78:8108/v1/edb/data?EdbCode=' +edbdatapushurl = 'http://10.189.2.78:8108/v1/edb/push' +edbdeleteurl = 'http://10.189.2.78:8108/v1/edb/business/edb/del' +edbbusinessurl = 'http://10.189.2.78:8108/v1/edb/business/data/del' + +edbcodenamedict = { + 'C2403283369': '预赔阳极加工利润（高端）', + 'C2403285560': '预培阳极加工利润（低端）', + 'C2403288616': '低硫石油焦煅烧利润', + 'S6949656': '平均价：氧化铝：一级：全国', + 'S5807052': '氧化铝：一级：贵阳', + 'S5443355': '市场价：煤沥青：河北地区', + 'S5443357': '市场价：煤沥青：山西地区', + 'W000294': '国内主要港口石油焦出货量（隆重）', + 'W000293': '日照港库存（隆重）', + 'W000292': '港口总库存（隆重）', + 'W000283': '主营石油焦产量（隆重）', + 'W000282': '地炼石油焦产量（隆重）', + 'W000281': '中国石油焦产量（隆重）', + 'W000280': '主营石油焦开工负荷率（隆重）', + 'W000279': '地炼石油焦开工负荷率（隆重）', + 'ID00150273': '石油焦：1 # ：市场低端价：东北地区（日）', + 'ID00150281': '石油焦：1 # ：市场主流价：东北地区（日）', + 'ID00150277': '石油焦：1 # ：市场高端价：东北地区（日）', + 'ID00150289': '石油焦：2 # ：市场低端价：华东地区（日）', + 'ID00150285': '石油焦：2 # ：市场低端价：西北地区（日）', + 'ID00150313': '石油焦：2 # ：市场主流价：华东地区（日）', + 'ID00150309': '石油焦：2 # ：市场主流价：西北地区（日）', + 'ID00150301': '石油焦：2 # ：市场高端价：华东地区（日）', + 'ID00150297': '石油焦：2 # ：市场高端价：西北地区（日）', + 'ID00150321': '石油焦：2 # A：市场低端价：山东（日）', + 'ID00150329': '石油焦：2 # A：市场主流价：山东（日）', + 'ID00150325': '石油焦：2 # A：市场高端价：山东（日）', + 'ID00150337': '石油焦：2 # B：市场低端价：华南地区（日）', + 'ID00150341': '石油焦：2 # B：市场低端价：华中地区（日）', + 'ID00150361': '石油焦：2 # B：市场主流价：华南地区（日）', + 'ID00150365': '石油焦：2 # B：市场主流价：华中地区（日）', + 'ID00150349': '石油焦：2 # B：市场高端价：华南地区（日）', + 'ID00150353': '石油焦：2 # B：市场高端价：华中地区（日）', + 'ID00150333': '石油焦：2 # B：市场低端价：山东（日）', + 'ID00150357': '石油焦：2 # B：市场主流价：山东（日）', + 'ID00150345': '石油焦：2 # B：市场高端价：山东（日）', + 'ID00150369': '石油焦：3 # ：市场低端价：华中地区（日）', + 'ID00150373': '石油焦：3 # ：市场高端价：华中地区（日）', + 'ID00150385': '石油焦：3 # A：市场高端价：山东（日）', + 'ID00150393': '石油焦：3 # B：市场低端价：华东地区（日）', + 'ID00150409': '石油焦：3 # B：市场主流价：华东地区（日）', + 'ID00150401': '石油焦：3 # B：市场高端价：华东地区（日）', + 'ID00146589': '海绵焦：4 # ：出厂价：华中地区：洛阳石化（日）', + 'ID01242846': '石油焦：4 # B：挂牌价：华北地区：中石化燕山（日）', + 'ID01300358': '石油焦：3 # C：市场低端价：山东（日）', + 'ID01300357': '石油焦：3 # C：市场高端价：山东（日）', + 'ID00150377': '石油焦：3 # ：市场主流价：华中地区（日）', + 'ID01387643': '煅烧焦：低硫：0.5 % S：市场价：东北地区（日）', + 'ID01387646': '煅烧焦：低硫：3.5 % S：市场价：东北地区（日）', + 'ID01387660': '煅烧焦：中硫：3 % S，400V：市场价：山东（日）', + 'ID00150381': '石油焦：3 # A：市场低端价：山东（日）', + 'ID00150397': '石油焦：3 # B：市场低端价：山东（日）', + 'ID00150405': '石油焦：3 # B：市场高端价：山东（日）', + 'ID00146545': '海绵焦：3B：出厂价：山东：山东东明（日）', + 'B3e90b34e4b9e7a6ea3': '石油焦市场均价(元/吨)', + 'B6b5c53b270a3af12ac': '石油焦1 # 市场均价(元/吨)', + 'B10721189a11c209a20': '石油焦2 # 市场均价(元/吨)', + 'B6accfa9d2bf4735a50': '石油焦3 # 市场均价(元/吨)', + 'B8a0ab5357569c385a9': '石油焦海绵焦市场均价(元/吨)', + 'B19dcf45e22fbfd3e43': '石油焦海绵焦东北1 # A焦（低端）(元/吨)（百川）', + 'B5832a62d1e0fba50b6': '石油焦海绵焦东北1 # A焦（高端）(元/吨)（百川）', + 'B1de4fba026d4609cc7': '石油焦海绵焦东北1 # B焦（低端）(元/吨)（百川）', + 'B38f89180736172490d': '石油焦海绵焦东北1 # B焦（高端）(元/吨)（百川）', + 'B4f847871674c3d77f2': '石油焦海绵焦山东地炼1 # -3#焦（低端）(元/吨)', + 'B1aefb8a64a5200adbd': '石油焦海绵焦山东地炼1 # -3#焦（高端）(元/吨)', + 'B1df7d0afbfedfb628a': '煅烧焦东北低硫(高端S < 0.5)(元/吨)', + 'B5f8f9859635876da28': '煅烧焦东北低硫(低端S < 0.5)(元/吨)', + 'B2342a8c5a39fa00348': '煅烧焦华北中硫(高端S < 3.0，钒 < 400)(元/吨)', + 'B051f27900397c6a35f': '煅烧焦山东中硫(高端S < 3.0，钒 < 400)(元/吨)', + 'Be2a8050a48e86cae1f': '煅烧焦华东中硫(高端S < 3.0，钒 < 400)(元/吨)', + 'B4a1811938f85065f6a': '煅烧焦华中中硫(高端S < 3.0，钒 < 400)(元/吨)', + 'Bc197d4834ef7fb98ec': '煅烧焦华东高硫(高端S < 3.5，钒 < 400)(元/吨)', + 'B62be5dbdb8c6454530': '煅烧焦低硫参考价格(元/吨)（百川）', + 'Bdd813140bffc4edfa6': '煅烧焦中硫微量市场均价(元/吨)（百川）', + 'B185a597decfc71915a': '预焙阳极山东低端(元/吨)（百川）', + 'B1bcde6130de031bd42': '山西 改质沥青(元/吨)', + 'Bb9f4a1f6dd32b4ad8a': '山东 改质沥青(元/吨)', + 'C2411261557491549': '石油焦市场均价(元/吨)/4DMA', + 'C2411271143174617': '石油焦市场均价(元/吨)/9DMA', + 'ID01387649': '煅烧焦：中硫：3 % S，350V：市场价：华东地区（日）', + 'ID01387655': '煅烧焦：中硫：3 % S，350V：市场价：山东（日）', + 'RE00010076': '煅烧焦：低硫：生产毛利：东北地区（周）', + 'B9d1acaf80383683da3': '石油焦总产量（周）(吨)', + 'Bdaa719a38936c8dd76': '石油焦开工率（周）( % )', + 'B9459d549a332b200e7': '石油焦行业总库存（周）(吨)', + 'Bce6e098b9518370cff': '石油焦工厂库存（周）(吨)', + 'B577ce2809772779710': '石油焦市场库存（周）(吨)', + 'B5d8c564c62f3e6b77f': '石油焦成本（周）(吨)', + 'B43baa98bcaa06c11a5': '石油焦利润（周）(吨)', + 'Bdd0c1361d94081211c': '煅烧石油焦总产量（周）(吨)', + 'B65315111fa28951b1e': '煅烧石油焦开工率（周）( % )', + 'B2aff5f2632a20027d0': '煅烧石油焦行业总库存（周）(吨)', + 'B29fbd31128cd71b212': '煅烧石油焦工厂库存（周）(吨)', + 'B7a88313a89d1261c53': '煅烧石油焦成本（周）(吨)', + 'Bd4fa36b4decec0aafa': '煅烧石油焦利润（周）(吨)', + 'B9bd80eac7df81ffbd4': '预焙阳极总产量（周）(吨)', + 'B27074786605f4660d2': '预焙阳极开工率（周）( % )', + 'Bdc2a5985ecb56b6a0c': '预焙阳极行业总库存（周）(吨)', + 'Bce8511f899e487e5b6': '预焙阳极工厂库存（周）(吨)', + 'B13ec89105bd866a2bd': '预焙阳极成本（周）(吨)', + 'B66c3abcfa15a2e611c': '预焙阳极利润（周）(吨)', + 'Bf7efe3200f9abc0453': '电解铝开工率（周）( % )', + 'Be193166f347267b1a7': '电解铝行业总库存（周）(吨)', + 'Baa744fc97769353175': '电解铝工厂库存（周）(吨)', + 'Bf9654603913cfc5282': '电解铝市场库存（周）(吨)', + 'Bef1535c96da0d70fbc': '电解铝利润（周）(吨)', + 'B7d1d0b24316d49cbdc': '煤沥青总产量（周）(吨)', + 'B4303fb002ea1c214da': '煤沥青开工率（周）( % )', + 'Be9a470c97e9efe660c': '煤沥青行业总库存（周）(吨)', + 'B50d4d87f6b78bca587': '煤沥青工厂库存（周）(吨)', + 'B46cc7d0a90155b5bfd': '煅烧焦山东高硫(高端S < 3.5，普货)(元/吨)' +} + +edbcodelist = edbcodenamedict.keys() +# 临时写死用指定的列,与上面的edbcode对应，后面更改 +edbnamelist = ['ds', 'y']+[edbcodenamedict[edbcodename] + for edbcodename in edbcodelist] + +# eta自有数据指标编码，石油焦铝用还没新增，暂且留空 +# eta自有数据指标编码 次周,隔周 +bdwdname = [ + '次月', + '次二月', + '次三月', + '次四月', +] +modelsindex = [{"NHITS":"SELF0000451", +"Informer":"SELF0000452", +"LSTM":"SELF0000453", +"iTransformer":"SELF0000454", +"TSMixer":"SELF0000455", +"TSMixerx":"SELF0000456", +"PatchTST":"SELF0000457", +"RNN":"SELF0000458", +"GRU":"SELF0000459", +"TCN":"SELF0000460", +"BiTCN":"SELF0000461", +"DilatedRNN":"SELF0000462", +"MLP":"SELF0000463", +"DLinear":"SELF0000464", +"NLinear":"SELF0000465", +"TFT":"SELF0000466", +"FEDformer":"SELF0000467", +"StemGNN":"SELF0000468", +"MLPMultivariate":"SELF0000469", +"TiDE":"SELF0000470", +"DeepNPTS":"SELF0000471", +"NBEATS":"SELF0000472", +},{"NHITS":"SELF0000473", +"Informer":"SELF0000474", +"LSTM":"SELF0000475", +"iTransformer":"SELF0000476", +"TSMixer":"SELF0000477", +"TSMixerx":"SELF0000478", +"PatchTST":"SELF0000479", +"RNN":"SELF0000480", +"GRU":"SELF0000481", +"TCN":"SELF0000482", +"BiTCN":"SELF0000483", +"DilatedRNN":"SELF0000484", +"MLP":"SELF0000485", +"DLinear":"SELF0000486", +"NLinear":"SELF0000487", +"TFT":"SELF0000488", +"FEDformer":"SELF0000489", +"StemGNN":"SELF0000490", +"MLPMultivariate":"SELF0000491", +"TiDE":"SELF0000492", +"DeepNPTS":"SELF0000493", +"NBEATS":"SELF0000494", +},{"NHITS":"SELF0000495", +"Informer":"SELF0000496", +"LSTM":"SELF0000497", +"iTransformer":"SELF0000498", +"TSMixer":"SELF0000499", +"TSMixerx":"SELF0000500", +"PatchTST":"SELF0000501", +"RNN":"SELF0000502", +"GRU":"SELF0000503", +"TCN":"SELF0000504", +"BiTCN":"SELF0000505", +"DilatedRNN":"SELF0000506", +"MLP":"SELF0000507", +"DLinear":"SELF0000508", +"NLinear":"SELF0000509", +"TFT":"SELF0000510", +"FEDformer":"SELF0000511", +"StemGNN":"SELF0000512", +"MLPMultivariate":"SELF0000513", +"TiDE":"SELF0000514", +"DeepNPTS":"SELF0000515", +"NBEATS":"SELF0000516", +},{"NHITS":"SELF0000517", +"Informer":"SELF0000518", +"LSTM":"SELF0000519", +"iTransformer":"SELF0000520", +"TSMixer":"SELF0000521", +"TSMixerx":"SELF0000522", +"PatchTST":"SELF0000523", +"RNN":"SELF0000524", +"GRU":"SELF0000525", +"TCN":"SELF0000526", +"BiTCN":"SELF0000527", +"DilatedRNN":"SELF0000528", +"MLP":"SELF0000529", +"DLinear":"SELF0000530", +"NLinear":"SELF0000531", +"TFT":"SELF0000532", +"FEDformer":"SELF0000533", +"StemGNN":"SELF0000534", +"MLPMultivariate":"SELF0000535", +"TiDE":"SELF0000536", +"DeepNPTS":"SELF0000537", +"NBEATS":"SELF0000538", +}] + +# 百川数据指标编码 +baichuanidnamedict = { + '1588348470396480901': '石油焦滨州-友泰', + '1588348470396480903': '石油焦东营-海科瑞林', + '1588348470396480902': '石油焦东营-华联2', + '1588348470396481080': '石油焦东营-华联3', + '1588348470396480905': '石油焦东营-联合', + '1588348470396481081': '石油焦东营-联合3', + '1588348470396480915': '石油焦淄博-汇丰', + '1588348470396480888': '石油焦沧州-鑫海', + '1588348470396480917': '石油焦东营-万通', + '1588348470396480925': '石油焦东营-齐润', + '1588348470396481084': '石油焦东营-尚能4', + '1588348470396480930': '石油焦潍坊-寿光鲁清', + '1588348470396480929': '石油焦滨州-鑫岳' +} + + +# baichuanidnamedict = {'1588348470396475286': 'test1', '1666': 'test2'} # 北京环境测试用 + +# eta 上传预测结果的请求体，后面发起请求的时候更改 model datalist 数据 +data = { + "IndexCode": "", + "IndexName": "石油焦铝用价格预测xx模型-yy", + "Unit": "无", + "Frequency": "日度", + "SourceName": f"价格预测", + "Remark": 'ddd', + "DataList": [ + { + "Date": "2024-05-02", + "Value": 333444 + } + ] +} + +# eta 分类 +# level：3才可以获取到数据，所以需要人工把能源化工下所有的level3级都找到 +# url = 'http://10.189.2.78:8108/v1/edb/list?ClassifyId=1214' +# ParentId ":1160, 能源化工 +# ClassifyId ":1214,原油 3912 石油焦 +# ParentId ":1214,"，就是原油下所有的数据。 +ClassifyId = 3707 + + +# 变量定义--线上环境 +# server_host = '10.200.32.39' +# login_pushreport_url = "http://10.200.32.39/jingbo-api/api/server/login" +# upload_url = "http://10.200.32.39/jingbo-api/api/analysis/reportInfo/researchUploadReportSave" +# upload_warning_url = "http://10.200.32.39/jingbo-api/api/basicBuiness/crudeOilWarning/save" +# query_data_list_item_nos_url = f"http://{server_host}/jingbo-api/api/warehouse/dwDataItem/queryDataListItemNos" +# # 上传数据项值 +# push_data_value_list_url = f"http://{server_host}/jingbo-api/api/dw/dataValue/pushDataValueList" + +# login_data = { +# "data": { +# "account": "api_dev", +# "password": "ZTEwYWRjMzk0OWJhNTlhYmJlNTZlMDU3ZjIwZjg4M2U=", +# "tenantHashCode": "8a4577dbd919675758d57999a1e891fe", +# "terminal": "API" +# }, +# "funcModule": "API", +# "funcOperation": "获取token" +# } + + +# upload_data = { +# "funcModule":'研究报告信息', +# "funcOperation":'上传原油价格预测报告', +# "data":{ +# "groupNo":'', # 用户组id +# "ownerAccount":'27663', #报告所属用户账号 27663 - 刘小朋 +# "reportType":'OIL_PRICE_FORECAST', # 报告类型，固定为OIL_PRICE_FORECAST +# "fileName": '', #文件名称 +# "fileBase64": '' ,#文件内容base64 +# "categoryNo":'yyjgycbg', # 研究报告分类编码 +# "smartBusinessClassCode":'YCJGYCBG', #分析报告分类编码 +# "reportEmployeeCode":"E40482" ,# 报告人 E40482 - 管理员 0000027663 - 刘小朋 +# "reportDeptCode" :"002000621000", # 报告部门 - 002000621000 SH期货研究部 +# "productGroupCode":"RAW_MATERIAL" # 商品分类 +# } +# } + +# warning_data = { +# "groupNo":'', # 用户组id +# "funcModule":'原油特征停更预警', +# "funcOperation":'原油特征停更预警', +# "data":{ +# 'WARNING_TYPE_NAME':'特征数据停更预警', +# 'WARNING_CONTENT':'', +# 'WARNING_DATE':'' +# } +# } + +# query_data_list_item_nos_data = { +# "funcModule": "数据项", +# "funcOperation": "查询", +# "data": { +# "dateStart":"20200101", +# "dateEnd":"20241231", +# "dataItemNoList":["Brentzdj","Brentzgj"] # 数据项编码,代表 brent最低价和最高价 +# } +# } + + +# push_data_value_list_data = { +# "funcModule": "数据表信息列表", +# "funcOperation": "新增", +# "data": [ +# {"dataItemNo": "91230600716676129", +# "dataDate": "20230113", +# "dataStatus": "add", +# "dataValue": 100.11 +# }, +# {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", +# "dataDate": "20230113", +# "dataStatus": "add", +# "dataValue": 100.55 +# }, +# {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", +# "dataDate": "20230113", +# "dataStatus": "add", +# "dataValue": 100.55 +# } +# ] +# } +# # 八大维度数据项编码 +# bdwd_items = { +# 'ciri': '原油大数据预测|FORECAST|PRICE|T', +# 'benzhou': '原油大数据预测|FORECAST|PRICE|W', +# 'cizhou': '原油大数据预测|FORECAST|PRICE|W_1', +# 'gezhou': '原油大数据预测|FORECAST|PRICE|W_2', +# 'ciyue': '原油大数据预测|FORECAST|PRICE|M_1', +# 'cieryue': '原油大数据预测|FORECAST|PRICE|M_2', +# 'cisanyue': '原油大数据预测|FORECAST|PRICE|M_3', +# 'cisiyue': '原油大数据预测|FORECAST|PRICE|M_4', +# } + + +# # 生产环境数据库 +# host = 'rm-2zehj3r1n60ttz9x5.mysql.rds.aliyuncs.com' +# port = 3306 +# dbusername ='jingbo' +# password = 'shihua@123' +# dbname = 'jingbo' +# table_name = 'v_tbl_crude_oil_warning' + + +# # 变量定义--测试环境 +server_host = '192.168.100.53:8080' # 内网 +# server_host = '183.242.74.28' # 外网 +login_pushreport_url = f"http://{server_host}/jingbo-dev/api/server/login" +upload_url = f"http://{server_host}/jingbo-dev/api/analysis/reportInfo/researchUploadReportSave" +upload_warning_url = f"http://{server_host}/jingbo-dev/api/basicBuiness/crudeOilWarning/save" +query_data_list_item_nos_url = f"http://{server_host}/jingbo-dev/api/warehouse/dwDataItem/queryDataListItemNos" +# 上传数据项值 +push_data_value_list_url = f"http://{server_host}/jingbo-dev/api/dw/dataValue/pushDataValueList" + +login_data = { + "data": { + "account": "api_test", + # "password": "MmVmNzNlOWI0MmY0ZDdjZGUwNzE3ZjFiMDJiZDZjZWU=", # Shihua@123456 + "password": "ZTEwYWRjMzk0OWJhNTlhYmJlNTZlMDU3ZjIwZjg4M2U=", # 123456 + "tenantHashCode": "8a4577dbd919675758d57999a1e891fe", + "terminal": "API" + }, + "funcModule": "API", + "funcOperation": "获取token" +} + +upload_data = { + "groupNo": '', # 用户组id + "funcModule": '研究报告信息', + "funcOperation": '上传原油价格预测报告', + "data": { + "ownerAccount": 'arui', # 报告所属用户账号 + "reportType": 'OIL_PRICE_FORECAST', # 报告类型，固定为OIL_PRICE_FORECAST + "fileName": '2000-40-5-50--100-原油指标数据.xlsx-Brent活跃合约--2024-09-06-15-01-29-预测报告.pdf', # 文件名称 + "fileBase64": '', # 文件内容base64 + "categoryNo": 'yyjgycbg', # 研究报告分类编码 + "smartBusinessClassCode": 'YCJGYCBG', # 分析报告分类编码 + "reportEmployeeCode": "E40116", # 报告人 + "reportDeptCode": "D0044", # 报告部门 + "productGroupCode": "RAW_MATERIAL" # 商品分类 + } +} + + +warning_data = { + "groupNo": '', # 用户组id + "funcModule": '原油特征停更预警', + "funcOperation": '原油特征停更预警', + "data": { + 'WARNING_TYPE_NAME': '特征数据停更预警', + 'WARNING_CONTENT': '', + 'WARNING_DATE': '' + } +} + +query_data_list_item_nos_data = { + "funcModule": "数据项", + "funcOperation": "查询", + "data": { + "dateStart": "20200101", + "dateEnd": "20241231", + "dataItemNoList": ["Brentzdj", "Brentzgj"] # 数据项编码,代表 brent最低价和最高价 + } +} + +push_data_value_list_data = { + "funcModule": "数据表信息列表", + "funcOperation": "新增", + "data": [ + {"dataItemNo": "91230600716676129", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.11 + }, + {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.55 + }, + {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.55 + } + ] +} +# 八大维度数据项编码 +bdwd_items = { + 'ciri': 'syjlyycbdwdcr', + 'benzhou': 'syjlyycbdwdbz', + 'cizhou': 'syjlyycbdwdcz', + 'gezhou': 'syjlyycbdwdgz', + 'ciyue': 'syjlyycbdwdcy', + 'cieryue': 'syjlyycbdwdcey', + 'cisanyue': 'syjlyycbdwdcsy', + 'cisiyue': 'syjlyycbdwdcsiy', +} + +# 报告中八大维度数据项重命名 +columnsrename={'syjlyycbdwdbz': '本周', 'syjlyycbdwdcey': '次二月', 'syjlyycbdwdcr': '次日', 'syjlyycbdwdcsiy': '次四月', + 'syjlyycbdwdcsy': '次三月', 'syjlyycbdwdcy': '次月', 'syjlyycbdwdcz': '次周', 'syjlyycbdwdgz': '隔周', } +# 北京环境数据库 +host = '192.168.101.27' +port = 3306 +dbusername = 'root' +password = '123456' +dbname = 'jingbo_test' + +# 京博测试环境 +# host = 'rm-2zehj3r1n60ttz9x5ko.mysql.rds.aliyuncs.com' +# port = 3306 +# dbusername = 'jingbo' +# password = 'shihua@123' +# dbname = 'jingbo-test' + + +table_name = 'v_tbl_crude_oil_warning' +baichuan_table_name = 'V_TBL_BAICHUAN_YINGFU_VALUE' +# select BAICHUAN_ID, DATA_DATE, DATA_VALUE from V_TBL_BAICHUAN_YINGFU_VALUE where BAICHUAN_ID in ('1588348470396475286', '1666') +# 开关 +is_train = True # 是否训练 +is_debug = False # 是否调试 +is_eta = True # 是否使用eta接口 +is_market = False # 是否通过市场信息平台获取特征 ,在is_eta 为true 的情况下生效 +is_timefurture = True # 是否使用时间特征 +is_fivemodels = False # 是否使用之前保存的最佳的5个模型 +is_edbcode = False # 特征使用edbcoding列表中的 +is_edbnamelist = False # 自定义特征，对应上面的edbnamelist +is_update_eta = True # 预测结果上传到eta +is_update_report = True # 是否上传报告 +is_update_warning_data = False # 是否上传预警数据 +is_update_predict_value = True # 是否上传预测值到市场信息平台 +is_del_corr = 0.6 # 是否删除相关性高的特征,取值为 0-1 ，0 为不删除，0.6 表示删除相关性小于0.6的特征 +is_del_tow_month = False # 是否删除两个月不更新的特征 +is_bdwd = True # 是否使用八大维度 + + +# 连接到数据库 +db_mysql = MySQLDB(host=host, user=dbusername, + password=password, database=dbname) +db_mysql.connect() +print("数据库连接成功", host, dbname, dbusername) + + +# 数据截取日期 +start_year = 2000 # 数据开始年份 +end_time = '' # 数据截取日期 +freq = 'M' # 时间频率，"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日 "WW" 自定义周 +delweekenday = True if freq == 'B' else False # 是否删除周末数据 +is_corr = False # 特征是否参与滞后领先提升相关系数 +add_kdj = False # 是否添加kdj指标 +if add_kdj and is_edbnamelist: + edbnamelist = edbnamelist+['K', 'D', 'J'] + +# 模型参数 +y = '石油焦：3 # B：市场低端价：山东（日）' +avg_cols = [ + +] +offsite = 80 +offsite_col = [] +horizon = 4 # 预测的步长 +input_size = 16 # 输入序列长度 +train_steps = 50 if is_debug else 1000 # 训练步数,用来限定epoch次数 +val_check_steps = 30 # 评估频率 +early_stop_patience_steps = 5 # 早停的耐心步数 +# --- 交叉验证用的参数 +test_size = 100 # 测试集大小，定义100，后面使用的时候重新赋值 +val_size = test_size # 验证集大小,同测试集大小 + +# 特征筛选用到的参数 +k = 100 # 特征筛选数量，如果是0或者值比特征数量大，代表全部特征 +corr_threshold = 0.6 # 相关性大于0.6的特征 +rote = 0.06 # 绘图上下界阈值 + +# 计算准确率 +weight_dict = [0.4, 0.15, 0.1, 0.1, 0.25] # 权重 + + +# 文件 +data_set = '石油焦铝用指标数据.xlsx' # 数据集文件 +dataset = 'shiyoujiaolvyongyuedudataset' # 数据集文件夹 + +# 数据库名称 +db_name = os.path.join(dataset, 'jbsh_shiyoujiao_lvyong_yuedu.db') +sqlitedb = SQLiteHandler(db_name) +sqlitedb.connect() + +settings = f'{input_size}-{horizon}-{train_steps}--{k}-{data_set}' +# 获取日期时间 +# now = datetime.datetime.now().strftime('%Y%m%d%H%M%S') # 获取当前日期时间 +now = datetime.datetime.now().strftime('%Y-%m-%d') # 获取当前日期时间 +reportname = f'石油焦铝用大模型月度预测报告--{end_time}.pdf' # 报告文件名 +reportname = reportname.replace(':', '-') # 替换冒号 +if end_time == '': + end_time = now +# 邮件配置 +username = '1321340118@qq.com' +passwd = 'wgczgyhtyyyyjghi' +# recv=['liurui_test@163.com','52585119@qq.com'] +recv = ['liurui_test@163.com'] +# recv=['liurui_test@163.com'] +title = 'reportname' +content = y+'预测报告请看附件' +file = os.path.join(dataset, 'reportname') +# file=os.path.join(dataset,'14-7-50--100-原油指标数据.xlsx-Brent连1合约价格--20240731175936-预测报告.pdf') +ssl = True + + +# 日志配置 + +# 创建日志目录（如果不存在） +log_dir = 'logs' +if not os.path.exists(log_dir): + os.makedirs(log_dir) + +# 配置日志记录器 +logger = logging.getLogger('my_logger') +logger.setLevel(logging.INFO) + +# 配置文件处理器，将日志记录到文件 +file_handler = logging.handlers.RotatingFileHandler(os.path.join( + log_dir, 'pricepredict.log'), maxBytes=1024 * 1024, backupCount=5) +file_handler.setFormatter(logging.Formatter( + '%(asctime)s - %(name)s - %(levelname)s - %(message)s')) + +# 配置控制台处理器，将日志打印到控制台 +console_handler = logging.StreamHandler() +console_handler.setFormatter(logging.Formatter('%(message)s')) + +# 将处理器添加到日志记录器 +logger.addHandler(file_handler) +logger.addHandler(console_handler) + +# logger.info('当前配置：'+settings) diff --git a/config_shiyoujiao_lvyong_zhoudu.py b/config_shiyoujiao_lvyong_zhoudu.py index 0169aba..029d1e3 100644 --- a/config_shiyoujiao_lvyong_zhoudu.py +++ b/config_shiyoujiao_lvyong_zhoudu.py @@ -144,8 +144,53 @@ bdwdname = [ '次周', '隔周', ] -modelsindex = { -} +modelsindex = [ + {"NHITS":"SELF0000407", +"Informer":"SELF0000408", +"LSTM":"SELF0000409", +"iTransformer":"SELF0000410", +"TSMixer":"SELF0000411", +"TSMixerx":"SELF0000412", +"PatchTST":"SELF0000413", +"RNN":"SELF0000414", +"GRU":"SELF0000415", +"TCN":"SELF0000416", +"BiTCN":"SELF0000417", +"DilatedRNN":"SELF0000418", +"MLP":"SELF0000419", +"DLinear":"SELF0000420", +"NLinear":"SELF0000421", +"TFT":"SELF0000422", +"FEDformer":"SELF0000423", +"StemGNN":"SELF0000424", +"MLPMultivariate":"SELF0000425", +"TiDE":"SELF0000426", +"DeepNPTS":"SELF0000427", +"NBEATS":"SELF0000428", + +},{"NHITS":"SELF0000429", +"Informer":"SELF0000430", +"LSTM":"SELF0000431", +"iTransformer":"SELF0000432", +"TSMixer":"SELF0000433", +"TSMixerx":"SELF0000434", +"PatchTST":"SELF0000435", +"RNN":"SELF0000436", +"GRU":"SELF0000437", +"TCN":"SELF0000438", +"BiTCN":"SELF0000439", +"DilatedRNN":"SELF0000440", +"MLP":"SELF0000441", +"DLinear":"SELF0000442", +"NLinear":"SELF0000443", +"TFT":"SELF0000444", +"FEDformer":"SELF0000445", +"StemGNN":"SELF0000446", +"MLPMultivariate":"SELF0000447", +"TiDE":"SELF0000448", +"DeepNPTS":"SELF0000449", +"NBEATS":"SELF0000450",} +] # 百川数据指标编码 baichuanidnamedict = { @@ -290,18 +335,18 @@ bdwd_items = { } # 北京环境数据库 -host = '192.168.101.27' -port = 3306 -dbusername = 'root' -password = '123456' -dbname = 'jingbo_test' +# host = '192.168.101.27' +# port = 3306 +# dbusername = 'root' +# password = '123456' +# dbname = 'jingbo_test' # 京博测试环境 -# host = 'rm-2zehj3r1n60ttz9x5ko.mysql.rds.aliyuncs.com' -# port = 3306 -# dbusername = 'jingbo' -# password = 'shihua@123' -# dbname = 'jingbo-test' +host = 'rm-2zehj3r1n60ttz9x5ko.mysql.rds.aliyuncs.com' +port = 3306 +dbusername = 'jingbo' +password = 'shihua@123' +dbname = 'jingbo-test' table_name = 'v_tbl_crude_oil_warning' diff --git a/main_shiyoujiao_lvyong_zhoudu.py b/main_shiyoujiao_lvyong_zhoudu.py index 32c7ec7..66b75f1 100644 --- a/main_shiyoujiao_lvyong_zhoudu.py +++ b/main_shiyoujiao_lvyong_zhoudu.py @@ -235,7 +235,7 @@ def predict_main(): df_zhibiaoliebiao.to_excel(file, sheet_name='指标列表', index=False) # 数据处理 - df = datachuli(df_zhibiaoshuju, df_zhibiaoliebiao, y=global_config['y'], dataset=dataset, add_kdj=add_kdj, is_timefurture=is_timefurture, + df = zhoududatachuli(df_zhibiaoshuju, df_zhibiaoliebiao, y=global_config['y'], dataset=dataset, add_kdj=add_kdj, is_timefurture=is_timefurture, end_time=end_time) else: