-
Notifications
You must be signed in to change notification settings - Fork 82
/
_KEYS_DICT.py
222 lines (202 loc) · 11.6 KB
/
_KEYS_DICT.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
"""https://github.com/Leci37/LecTrade LecTrade is a tool created by github user @Leci37. instagram @luis__leci Shared on 2022/11/12 . . No warranty, rights reserved """
from enum import Enum
from datetime import datetime
Y_TARGET = 'buy_sell_point'
# **DOCU**
# 0.3 In the file _KEYS_DICT.py all the configurations are stored, take a look and know where it is.
# In it there is the dictionary DICT_COMPANYS
# Which contains the IDs (google quotes with the ID: GOOG) of the companies to analyze can be customized and create class from the nasdaq tikers, by default will use the key @FOLO3 which will analyze these 39 companies.
DICT_COMPANYS = {
"@CHILL":
["UBER", "PYPL"],
"@FAV":
["MELI", "TWLO", "RIVN", "SNOW", "UBER", "U" , "PYPL", "GTLB", "MDB", "TSLA", "DDOG"],
"@ROLL" :
["MELI", "TWLO","RIVN","SNOW", "UBER", "U" , "PYPL", "GTLB","MDB", "TSLA", "DDOG","SHOP", "NIO","RBLX", "TTD", "APPS", "ASAN", "DOCN", "AFRM", "PINS"],
"@VOLA" :
["UPST", "RIVN", "SNOW", "LYFT", "SPOT", "GTLB", "MDB", "HUBS", "TTD", "APPS", "ASAN", "AFRM", "DOCN", "DDOG", "SHOP", "NIO", "U", "RBLX"],
#top LAS MÁS activas por Volumen realizado por https://www.webull.com/quote/us/actives
"@TOP200": #Xpath //p[@class="tit bold"]/text() good side https://codebeautify.org/Xpath-Tester
["AMD", "TSLA", "AAPL", "MULN", "NVDA", "AMZN", "AGFY", "CCL", "NIO", "BAC", "F", "INTC", "T", "FNHC", "VALE", "ACI", "ILAG", "IMRA", "PLTR", "SOFI", "AAL", "WFC", "NU", "JPM", "XPEV", "SHOP", "MSFT", "NOK", "DBGI", "C", "PBR", "CMCSA", "SNAP", "HBAN", "DNA", "PLUG", "SWN", "VZ", "LASE", "NCLH", "GOOGL", "PTON", "CEI", "PCG", "ZVO", "META", "LCID", "ABEV", "MMAT", "GOOG", "UBER", "RIVN", "DAL", "AMC", "DKNG", "WISH", "WBD", "MU", "UMC", "KR", "CSCO", "TSM", "USB", "GOLD", "OPEN", "NKLA", "PBTS", "OXY", "ARVL", "BEKE", "TLRY", "KMI", "BB", "PFE", "MPW", "FFIE", "GRAB", "SQ", "HPE", "CCJ", "ASX", "KEY", "KO", "MARA", "CSX", "RIG", "NFLX", "SIRI", "XOM", "BCS", "KGC", "CS", "RBLX", "SYTA", "LUMN", "CPG", "AGNC", "FCX", "NTNX", "COIN", "BABA", "MS", "INFY", "LU", "SCHW", "LYG", "AUY", "MRVL", "JD", "SMRT", "ACB", "ET", "GM", "PYPL", "PINS", "AFRM", "SLB", "PING", "NUTX", "MO", "HAL", "MRO", "UAL", "CGC", "TELL", "KHC", "NVTA", "HPQ", "CVE", "BP", "WBA", "RUN", "AMAT", "ERIC", "CVNA", "CLF", "TOP", "TWTR", "BMY", "RIOT", "MRK", "NEM", "IDEX", "X", "TFC", "LYFT", "BTG", "UEC", "RF", "PDD", "KDP", "DVN", "FCEL", "VTGN", "HST", "RTO", "NEE", "CPNG", "FTCH", "MF", "JBLU", "CARR", "COMS", "AG", "VRM", "FTI", "TEVA", "MOS", "ROKU", "CHPT", "DIS", "IBN", "ORCL", "QCOM", "VOD", "MDLZ", "GILD", "NLY", "NKE", "LI", "GFI", "BSX", "M", "HMY", "COP", "APA", "NYCB", "IQ", "HUT", "VTRS", "TXN", "AZN", "AMCR", "HL", "QS", "BBBY", "IMUX", "PATH", "CVX"],
"@TOP100":
["AMD", "TSLA", "AAPL", "MULN", "NVDA", "AMZN", "AGFY", "CCL", "NIO", "BAC", "F", "INTC", "T", "FNHC", "VALE", "ACI", "ILAG", "IMRA", "PLTR", "SOFI", "AAL", "WFC", "NU", "JPM", "XPEV", "SHOP", "MSFT", "NOK", "DBGI", "C", "PBR", "CMCSA", "SNAP", "HBAN", "DNA", "PLUG", "SWN", "VZ", "LASE", "NCLH", "GOOGL", "PTON", "CEI", "PCG", "ZVO", "META", "LCID", "ABEV", "MMAT", "GOOG", "UBER", "RIVN", "DAL", "AMC", "DKNG", "WISH", "WBD", "MU", "UMC", "KR", "CSCO", "TSM", "USB", "GOLD", "OPEN", "NKLA", "PBTS", "OXY", "ARVL", "BEKE", "TLRY", "KMI", "BB", "PFE", "MPW", "FFIE", "GRAB", "SQ", "HPE", "CCJ", "ASX", "KEY", "KO", "MARA", "CSX", "RIG", "NFLX", "SIRI", "XOM", "BCS", "KGC", "CS", "RBLX", "SYTA", "LUMN", "CPG", "AGNC", "FCX"],
"@TOP50":
["AMD", "TSLA", "AAPL", "MULN", "NVDA", "AMZN", "AGFY", "CCL", "NIO", "BAC", "F", "INTC", "T", "FNHC", "VALE", "ACI", "ILAG", "IMRA", "PLTR", "SOFI", "AAL", "WFC", "NU", "JPM", "XPEV", "SHOP", "MSFT", "NOK", "DBGI", "C", "PBR", "CMCSA", "SNAP", "HBAN", "DNA", "PLUG", "SWN", "VZ", "LASE", "NCLH", "GOOGL", "PTON", "CEI", "PCG", "ZVO", "META", "LCID", "ABEV"],
"@TOP25":
["AMD", "TSLA", "AAPL", "MULN", "NVDA", "AMZN", "AGFY", "CCL", "NIO", "BAC", "ATXI", "F", "INTC", "T", "FNHC", "VALE", "ACI", "ILAG", "IMRA", "PLTR", "SOFI", "AAL", "WFC", "NU", "JPM"],
#lista de seguimiento @FOLO1, lista Aux seguimiento @FOLO2 ambas @FOLO3 19/10/2022
"@FOLO1":
["UPST", "MELI", "TWLO", "RIVN", "SNOW", "LYFT", "ADBE", "UBER", "ZI", "QCOM", "PYPL", "SPOT", "RUN", "GTLB", "MDB", "NVDA", "AMD", "ADSK", "AMZN", "BABA", "NFLX", "FFIV", "GOOG", "MSFT", "ABNB", "TSLA", "META"],
"@FOLO2":
["DBX", "PTON", "CRWD", "NVST", "HUBS", "EPAM", "PINS", "TTD", "SNAP", "APPS", "ASAN", "AFRM", "DOCN", "ETSY", "DDOG", "SHOP", "NIO", "U", "GME", "RBLX", "CRSR"],
"@FOLO3": #"META", ERROR no buy points "GOOG", "MSFT", "TSLA", #"
[ "GOOG","MSFT", "TSLA","UPST", "MELI", "TWLO", "RIVN", "SNOW", "LYFT", "ADBE", "UBER", "ZI", "QCOM", "PYPL", "SPOT", "GTLB", "MDB", "NVDA", "AMD" , "ADSK", "AMZN", "CRWD", "NVST", "HUBS", "EPAM", "PINS", "TTD", "SNAP", "APPS", "ASAN", "AFRM", "DOCN", "ETSY", "DDOG", "SHOP", "NIO", "U", "GME", "RBLX", "CRSR"],
#"PTON", error callearly no se xq
#[ "CRWD", "NVST", "HUBS", "EPAM", "PINS", "TTD", "SNAP", "APPS", "ASAN", "AFRM", "DOCN", "ETSY", "DDOG", "SHOP", "NIO", "U", "GME", "RBLX", "CRSR"],
"@CHIC":# "MU", "CRM", "SNPS", "DHI", "MPWR", "CZR", "NOW", "BBWI",
[ "TER", "KLAC", "ALGN", "UONE", "SPG", "STAG" ],#"O", "CARV","ATHE", "DXCM","PSEC" ERROR
"@CHIC3":#"ATHE", "MU", "CRM", "SNPS", "DHI", "MPWR", "CZR", "NOW", "BBWI", "DXCM",
["DBX", "BABA", "FFVI","CVNA", "KLAC", "ALGN", "CARV", "SPG", "STAG"], #, "FFVI","CVNA", "TER", "KLAC", "ALGN", "CARV", "UONE", "SPG", "STAG", "O", "PSEC"],
"@CRT":#etoro and xtb use
["BTC-USD", "ETH-USD", "DASH-USD", "LTC-USD", "XLM-USD", "LINK-USD", "DOGE-USD",'BNB-USD', "ADA-USD",'DOT-USD', 'DYDX-USD'], #"ZEC-USD",,'BCH-USD'
#['BTC-USD', 'ETH-USD', 'USDT-USD', , 'XRP-USD', 'ADA-USD', 'HEX-USD','SOL-USD', 'AVAX-USD', 'DOGE-USD', 'DOT-USD', 'DOT-USD', 'SHIB-USD', 'MATIC-USD'
# ["BTC", "ETH", "BCH", "XRP", "DASH", "LTC", "ETC", "API3", "CRO", "SKL", "IMX", "ADA", "MIOTA", "XLM", "EOS", "NEO", "TRX", "ZEC", "BNB", "XTZ", "DOT", "MKR", "COMP", "LINK", "UNI", "YFI", "DOGE", "AAVE", "FIL", "ALGO", "ATOM", "MANA", "APE", "LRC", "ENJ", "BICO", "BAT", "BNT", "OGN", "MATIC", "FLR", "GALA", "ALICE", "CHZ", "HBAR", "DYDX", "SOL", "THETA", "FTM", "GRT"]
}
PATH_REGISTER_RESULT_REAL_TIME = "d_result/prediction_real_time.csv"
PATH_REGISTER_RESULT_MULTI_REAL_TIME = "d_result/predi_MULTI_real_time_"+datetime.now().strftime("%Y_%m_%d")+".csv"
PATH_REGISTER_RESULT_MULTI_REAL_TIME_SENT = "d_result/sent_predi_MULTI_real_time_"+datetime.now().strftime("%Y_%m_%d")+".csv"
MIN_SCALER = 0
MAX_SCALER = 1
PATH_SCALERS_FOLDER = "Models/TF_multi/Scalers/"
PERCENTAGES_SCORE = [0.25, 0.5, 0.6, 0.7, 0.75, 0.8, 0.85, 0.86, 0.87, 0.88, 0.89, 0.9, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97,0.98]
BACHT_SIZE_LOOKBACK = 10 #cuantos t se usan para hacer una prediccion
PATH_PNG_TRADER_VIEW = "plots_relations/Trader_View_png/"
USE_GPU = "No" # If you have a GPU and want to use. Possible values [Yes or No]
PER_PROCESS_GPU_MEMORY_FRACTION = 0.333 # Assume that you have 12GB of GPU memory and want to allocate ~4GB
class MODEL_TYPE_COLM(Enum):
VGOOD = "_vgood16_"
GOOD = "_good9_"
REG = "_reg4_"
LOW = "_low1_"
class Option_Historical(Enum):
YEARS_3 = 1
MONTH_3 = 2
MONTH_3_AD = 3
DAY_6 = 4
DAY_1 = 5
#should be removed from the training because they use global averages, i.e. if you remove the last column, they change the value of all previous columns, useless in realtime.
LIST_TECH_REMOVE_NOT_EQUAL_IF_REMOVE_THE_FIRSH = ["mtum_APO", "mtum_CCI", "mtum_MACD_ext", "mtum_MACD_ext_signal", "mtum_MACD_ext_list", "mtum_PPO",
"mtum_STOCH_RSI_d", "mtum_STOCH_RSI_kd", "ma_TRIMA_5", "ma_TRIMA_20", "ma_WMA_20", "ma_TRIMA_50",
"ma_TRIMA_100", "mtum_BIAS_SMA_26", "mtum_BR_26", "olap_VMAP", "perf_CUMLOGRET_1", "perf_CUMPCTRET_1", "sti_ENTP_10"]
#should be removed because they generate a lot of None, in the last columns, useless in RealTime.
LIST_TECH_REMOVE_GENERATED_NONE_LAST = ['ti_acc_dist']
LIST_TECH_REMOVE_GENERATED_INFINITE = ['olap_MCGD_10']
LIST_TECH_REMOVE = LIST_TECH_REMOVE_NOT_EQUAL_IF_REMOVE_THE_FIRSH + LIST_TECH_REMOVE_GENERATED_NONE_LAST +LIST_TECH_REMOVE_GENERATED_INFINITE
class ExtendedEnum(Enum):
@classmethod
def list_values(cls):
return list(map(lambda c: c.sub_dict, cls))
@classmethod
def list(cls):
return list(map(lambda c: c, cls))
class Op_buy_sell(ExtendedEnum):
BOTH = "both"
POS = "pos"
NEG = "neg"
class MODEL_TF_DENSE_TYPE_MULTI_DIMENSI(Enum):
@classmethod
def list_values(cls):
return list(map(lambda c: c.sub_dict, cls))
@classmethod
def list(cls):
return list(map(lambda c: c, cls))
SIMP_DENSE28 = "mult_28"
SIMP_DENSE64 = "mult_64"
SIMP_DENSE128 = "mult_128"
SIMP_CONV2 = "mult_conv2"
SIMP_CONV = "mult_conv"
SIMP_CORDO = "_simp_cordo"
#SIMP_DENSE = "_simp_dense"
#MULT_DENSE = "_mult_dense"
MULT_LINEAR = "mult_linear"
MULT_DENSE2 = "mult_dense2"
#MULT_CONV = "_mult_conv" #error al save()
MULT_LSTM = "mult_lstm"
####SIMPL_BIDI = "_simpl_bidi"
# MULT_TIME = "_mult_time"
MULT_GRU = "_mult_gru"
class MODEL_TF_DENSE_TYPE_ONE_DIMENSI(Enum):
@classmethod
def list_values(cls):
return list(map(lambda c: c.sub_dict, cls))
@classmethod
def list(cls):
return list(map(lambda c: c, cls))
SIMP_28 = "s28"
SIMP_64 = "s64"
SIMP_128 = "s128"
#In case of does not have a value form webull.com , the tool to obtains news code: Utils/Volume_WeBull_get_tikcers.py
DICT_WEBULL_ID = {
#@CRPTO
"BTC-USD" : 950160802,
"ETH-USD" : 950160804,
"DASH-USD" : 950181555,
"LTC-USD" : 950160801,
"ADA-USD" : 950185924,
"XLM-USD" : 950181553,
"ZEC-USD" : 950181635,
"LINK-USD" : 950188154,
"DOGE-USD" : 950181551,
#@FOLO3
"UPST" : 950177837,
"MELI" : 913323930,
"TWLO" : 913254831,
"RIVN" : 950188536,
"SNOW" : 950173560,
"LYFT" : 950116149,
"ADBE" : 913256192,
"UBER" : 950121423,
"ZI" : 950157730,
"QCOM" : 913323878,
"PYPL" : 913256043,
"SPOT" : 925418520,
"RUN" : 913256036,
"GTLB" : 950188178,
"MDB" : 925377113,
"NVDA" : 913257561,
"AMD" : 913254235,
"ADSK" : 913256187,
"AMZN" : 913256180,
"BABA" : 913254558,
"NFLX" : 913257027,
"FFIV" : 913256674,
"GOOG" : 913303964,
"MSFT" : 913323997,
"ABNB" : 950178075,
"TSLA" : 913255598,
"META" : 913303928,
"DBX" : 925418496,
"PTON" : 950138392,
"CRWD" : 950126602,
"NVST" : 950135009,
"HUBS" : 913254682,
"EPAM" : 913254390,
"PINS" : 950118597,
"TTD" : 913431510,
"SNAP" : 925186755,
"APPS" : 913253434,
"ASAN" : 950172459,
"AFRM" : 950178219,
"DOCN" : 950181409,
"ETSY" : 913255993,
"DDOG" : 950136998,
"SHOP" : 913254746,
"NIO" : 950076017,
"U" : 950172451,
"GME" : 913255341,
"RBLX" : 950178170,
"CRSR" : 950172441,
#@CHIC
"ATHE" : 913323301,
"MU" : 913324077,
"CRM" : 913255140,
"SNPS" : 913323483,
"DHI" : 913255191,
"MPWR" : 913323959,
"CZR" : 913255942,
"NOW" : 913254427,
"BBWI" : 913255499,
"DXCM" : 913256616,
"TER" : 913324414,
"KLAC" : 913257399,
"ALGN" : 913256164,
"CARV" : 913253685,
"UONE" : 913323315,
"SPG" : 913324356,
"STAG" : 913254301,
"O" : 913324022,
"PSEC" : 913323566,
"SOFI" : 950178653,
"STNE" : 950091058,
"PDD" : 950064710,
"INMD" : 950134104}