partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | QA_indicator_PBX | 瀑布线 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_PBX(DataFrame, N1=3, N2=5, N3=8, N4=13, N5=18, N6=24):
'瀑布线'
C = DataFrame['close']
PBX1 = (EMA(C, N1) + EMA(C, 2 * N1) + EMA(C, 4 * N1)) / 3
PBX2 = (EMA(C, N2) + EMA(C, 2 * N2) + EMA(C, 4 * N2)) / 3
PBX3 = (EMA(C, N3) + EMA(C, 2 * N3) + EMA(C, 4 * N3)) / 3
PBX4 = (EMA(C, N4) + ... | def QA_indicator_PBX(DataFrame, N1=3, N2=5, N3=8, N4=13, N5=18, N6=24):
'瀑布线'
C = DataFrame['close']
PBX1 = (EMA(C, N1) + EMA(C, 2 * N1) + EMA(C, 4 * N1)) / 3
PBX2 = (EMA(C, N2) + EMA(C, 2 * N2) + EMA(C, 4 * N2)) / 3
PBX3 = (EMA(C, N3) + EMA(C, 2 * N3) + EMA(C, 4 * N3)) / 3
PBX4 = (EMA(C, N4) + ... | [
"瀑布线"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L121-L133 | [
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train | QA_indicator_DMA | 平均线差 DMA | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_DMA(DataFrame, M1=10, M2=50, M3=10):
"""
平均线差 DMA
"""
CLOSE = DataFrame.close
DDD = MA(CLOSE, M1) - MA(CLOSE, M2)
AMA = MA(DDD, M3)
return pd.DataFrame({
'DDD': DDD, 'AMA': AMA
}) | def QA_indicator_DMA(DataFrame, M1=10, M2=50, M3=10):
"""
平均线差 DMA
"""
CLOSE = DataFrame.close
DDD = MA(CLOSE, M1) - MA(CLOSE, M2)
AMA = MA(DDD, M3)
return pd.DataFrame({
'DDD': DDD, 'AMA': AMA
}) | [
"平均线差",
"DMA"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L136-L145 | [
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train | QA_indicator_MTM | 动量线 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_MTM(DataFrame, N=12, M=6):
'动量线'
C = DataFrame.close
mtm = C - REF(C, N)
MTMMA = MA(mtm, M)
DICT = {'MTM': mtm, 'MTMMA': MTMMA}
return pd.DataFrame(DICT) | def QA_indicator_MTM(DataFrame, N=12, M=6):
'动量线'
C = DataFrame.close
mtm = C - REF(C, N)
MTMMA = MA(mtm, M)
DICT = {'MTM': mtm, 'MTMMA': MTMMA}
return pd.DataFrame(DICT) | [
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train | QA_indicator_EXPMA | 指数平均线 EXPMA | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_EXPMA(DataFrame, P1=5, P2=10, P3=20, P4=60):
""" 指数平均线 EXPMA"""
CLOSE = DataFrame.close
MA1 = EMA(CLOSE, P1)
MA2 = EMA(CLOSE, P2)
MA3 = EMA(CLOSE, P3)
MA4 = EMA(CLOSE, P4)
return pd.DataFrame({
'MA1': MA1, 'MA2': MA2, 'MA3': MA3, 'MA4': MA4
}) | def QA_indicator_EXPMA(DataFrame, P1=5, P2=10, P3=20, P4=60):
""" 指数平均线 EXPMA"""
CLOSE = DataFrame.close
MA1 = EMA(CLOSE, P1)
MA2 = EMA(CLOSE, P2)
MA3 = EMA(CLOSE, P3)
MA4 = EMA(CLOSE, P4)
return pd.DataFrame({
'MA1': MA1, 'MA2': MA2, 'MA3': MA3, 'MA4': MA4
}) | [
"指数平均线",
"EXPMA"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L158-L167 | [
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train | QA_indicator_CHO | 佳庆指标 CHO | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_CHO(DataFrame, N1=10, N2=20, M=6):
"""
佳庆指标 CHO
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
VOL = DataFrame.volume
MID = SUM(VOL*(2*CLOSE-HIGH-LOW)/(HIGH+LOW), 0)
CHO = MA(MID, N1)-MA(MID, N2)
MACHO = MA(CHO, M)
return pd.DataFrame({... | def QA_indicator_CHO(DataFrame, N1=10, N2=20, M=6):
"""
佳庆指标 CHO
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
VOL = DataFrame.volume
MID = SUM(VOL*(2*CLOSE-HIGH-LOW)/(HIGH+LOW), 0)
CHO = MA(MID, N1)-MA(MID, N2)
MACHO = MA(CHO, M)
return pd.DataFrame({... | [
"佳庆指标",
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L170-L183 | [
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train | QA_indicator_BIAS | 乖离率 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_BIAS(DataFrame, N1, N2, N3):
'乖离率'
CLOSE = DataFrame['close']
BIAS1 = (CLOSE - MA(CLOSE, N1)) / MA(CLOSE, N1) * 100
BIAS2 = (CLOSE - MA(CLOSE, N2)) / MA(CLOSE, N2) * 100
BIAS3 = (CLOSE - MA(CLOSE, N3)) / MA(CLOSE, N3) * 100
DICT = {'BIAS1': BIAS1, 'BIAS2': BIAS2, 'BIAS3': BIAS3}... | def QA_indicator_BIAS(DataFrame, N1, N2, N3):
'乖离率'
CLOSE = DataFrame['close']
BIAS1 = (CLOSE - MA(CLOSE, N1)) / MA(CLOSE, N1) * 100
BIAS2 = (CLOSE - MA(CLOSE, N2)) / MA(CLOSE, N2) * 100
BIAS3 = (CLOSE - MA(CLOSE, N3)) / MA(CLOSE, N3) * 100
DICT = {'BIAS1': BIAS1, 'BIAS2': BIAS2, 'BIAS3': BIAS3}... | [
"乖离率"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L216-L224 | [
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train | QA_indicator_ROC | 变动率指标 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_ROC(DataFrame, N=12, M=6):
'变动率指标'
C = DataFrame['close']
roc = 100 * (C - REF(C, N)) / REF(C, N)
ROCMA = MA(roc, M)
DICT = {'ROC': roc, 'ROCMA': ROCMA}
return pd.DataFrame(DICT) | def QA_indicator_ROC(DataFrame, N=12, M=6):
'变动率指标'
C = DataFrame['close']
roc = 100 * (C - REF(C, N)) / REF(C, N)
ROCMA = MA(roc, M)
DICT = {'ROC': roc, 'ROCMA': ROCMA}
return pd.DataFrame(DICT) | [
"变动率指标"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L227-L234 | [
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train | QA_indicator_CCI | TYP:=(HIGH+LOW+CLOSE)/3;
CCI:(TYP-MA(TYP,N))/(0.015*AVEDEV(TYP,N)); | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_CCI(DataFrame, N=14):
"""
TYP:=(HIGH+LOW+CLOSE)/3;
CCI:(TYP-MA(TYP,N))/(0.015*AVEDEV(TYP,N));
"""
typ = (DataFrame['high'] + DataFrame['low'] + DataFrame['close']) / 3
cci = ((typ - MA(typ, N)) / (0.015 * AVEDEV(typ, N)))
a = 100
b = -100
return pd.DataFrame({
... | def QA_indicator_CCI(DataFrame, N=14):
"""
TYP:=(HIGH+LOW+CLOSE)/3;
CCI:(TYP-MA(TYP,N))/(0.015*AVEDEV(TYP,N));
"""
typ = (DataFrame['high'] + DataFrame['low'] + DataFrame['close']) / 3
cci = ((typ - MA(typ, N)) / (0.015 * AVEDEV(typ, N)))
a = 100
b = -100
return pd.DataFrame({
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train | QA_indicator_WR | 威廉指标 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_WR(DataFrame, N, N1):
'威廉指标'
HIGH = DataFrame['high']
LOW = DataFrame['low']
CLOSE = DataFrame['close']
WR1 = 100 * (HHV(HIGH, N) - CLOSE) / (HHV(HIGH, N) - LLV(LOW, N))
WR2 = 100 * (HHV(HIGH, N1) - CLOSE) / (HHV(HIGH, N1) - LLV(LOW, N1))
DICT = {'WR1': WR1, 'WR2': WR2}
... | def QA_indicator_WR(DataFrame, N, N1):
'威廉指标'
HIGH = DataFrame['high']
LOW = DataFrame['low']
CLOSE = DataFrame['close']
WR1 = 100 * (HHV(HIGH, N) - CLOSE) / (HHV(HIGH, N) - LLV(LOW, N))
WR2 = 100 * (HHV(HIGH, N1) - CLOSE) / (HHV(HIGH, N1) - LLV(LOW, N1))
DICT = {'WR1': WR1, 'WR2': WR2}
... | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L252-L261 | [
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train | QA_indicator_OSC | 变动速率线
震荡量指标OSC，也叫变动速率线。属于超买超卖类指标,是从移动平均线原理派生出来的一种分析指标。
它反应当日收盘价与一段时间内平均收盘价的差离值,从而测出股价的震荡幅度。
按照移动平均线原理，根据OSC的值可推断价格的趋势，如果远离平均线，就很可能向平均线回归。 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_OSC(DataFrame, N=20, M=6):
"""变动速率线
震荡量指标OSC，也叫变动速率线。属于超买超卖类指标,是从移动平均线原理派生出来的一种分析指标。
它反应当日收盘价与一段时间内平均收盘价的差离值,从而测出股价的震荡幅度。
按照移动平均线原理，根据OSC的值可推断价格的趋势，如果远离平均线，就很可能向平均线回归。
"""
C = DataFrame['close']
OS = (C - MA(C, N)) * 100
MAOSC = EMA(OS, M)
DICT = {'OSC': OS, 'MAOS... | def QA_indicator_OSC(DataFrame, N=20, M=6):
"""变动速率线
震荡量指标OSC，也叫变动速率线。属于超买超卖类指标,是从移动平均线原理派生出来的一种分析指标。
它反应当日收盘价与一段时间内平均收盘价的差离值,从而测出股价的震荡幅度。
按照移动平均线原理，根据OSC的值可推断价格的趋势，如果远离平均线，就很可能向平均线回归。
"""
C = DataFrame['close']
OS = (C - MA(C, N)) * 100
MAOSC = EMA(OS, M)
DICT = {'OSC': OS, 'MAOS... | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L264-L278 | [
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train | QA_indicator_RSI | 相对强弱指标RSI1:SMA(MAX(CLOSE-LC,0),N1,1)/SMA(ABS(CLOSE-LC),N1,1)*100; | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_RSI(DataFrame, N1=12, N2=26, N3=9):
'相对强弱指标RSI1:SMA(MAX(CLOSE-LC,0),N1,1)/SMA(ABS(CLOSE-LC),N1,1)*100;'
CLOSE = DataFrame['close']
LC = REF(CLOSE, 1)
RSI1 = SMA(MAX(CLOSE - LC, 0), N1) / SMA(ABS(CLOSE - LC), N1) * 100
RSI2 = SMA(MAX(CLOSE - LC, 0), N2) / SMA(ABS(CLOSE - LC), N2) * 1... | def QA_indicator_RSI(DataFrame, N1=12, N2=26, N3=9):
'相对强弱指标RSI1:SMA(MAX(CLOSE-LC,0),N1,1)/SMA(ABS(CLOSE-LC),N1,1)*100;'
CLOSE = DataFrame['close']
LC = REF(CLOSE, 1)
RSI1 = SMA(MAX(CLOSE - LC, 0), N1) / SMA(ABS(CLOSE - LC), N1) * 100
RSI2 = SMA(MAX(CLOSE - LC, 0), N2) / SMA(ABS(CLOSE - LC), N2) * 1... | [
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train | QA_indicator_ADTM | 动态买卖气指标 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_ADTM(DataFrame, N=23, M=8):
'动态买卖气指标'
HIGH = DataFrame.high
LOW = DataFrame.low
OPEN = DataFrame.open
DTM = IF(OPEN > REF(OPEN, 1), MAX((HIGH - OPEN), (OPEN - REF(OPEN, 1))), 0)
DBM = IF(OPEN < REF(OPEN, 1), MAX((OPEN - LOW), (OPEN - REF(OPEN, 1))), 0)
STM = SUM(DTM, N)
... | def QA_indicator_ADTM(DataFrame, N=23, M=8):
'动态买卖气指标'
HIGH = DataFrame.high
LOW = DataFrame.low
OPEN = DataFrame.open
DTM = IF(OPEN > REF(OPEN, 1), MAX((HIGH - OPEN), (OPEN - REF(OPEN, 1))), 0)
DBM = IF(OPEN < REF(OPEN, 1), MAX((OPEN - LOW), (OPEN - REF(OPEN, 1))), 0)
STM = SUM(DTM, N)
... | [
"动态买卖气指标"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L293-L307 | [
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train | QA_indicator_ASI | LC=REF(CLOSE,1);
AA=ABS(HIGH-LC);
BB=ABS(LOW-LC);
CC=ABS(HIGH-REF(LOW,1));
DD=ABS(LC-REF(OPEN,1));
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SI=16*X/R*MAX(AA,BB);
ASI:SUM(SI,M1);
ASIT:MA(ASI,M2); | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_ASI(DataFrame, M1=26, M2=10):
"""
LC=REF(CLOSE,1);
AA=ABS(HIGH-LC);
BB=ABS(LOW-LC);
CC=ABS(HIGH-REF(LOW,1));
DD=ABS(LC-REF(OPEN,1));
R=IF(AA>BB AND AA>CC,AA+BB/2+DD/4,IF(BB>CC AND BB>AA,BB+AA/2+DD/4,CC+DD/4));
X=(CLOSE-LC+(CLOSE-OPEN)/2+LC-REF(OPEN,1));
SI=16*X/R*MAX... | def QA_indicator_ASI(DataFrame, M1=26, M2=10):
"""
LC=REF(CLOSE,1);
AA=ABS(HIGH-LC);
BB=ABS(LOW-LC);
CC=ABS(HIGH-REF(LOW,1));
DD=ABS(LC-REF(OPEN,1));
R=IF(AA>BB AND AA>CC,AA+BB/2+DD/4,IF(BB>CC AND BB>AA,BB+AA/2+DD/4,CC+DD/4));
X=(CLOSE-LC+(CLOSE-OPEN)/2+LC-REF(OPEN,1));
SI=16*X/R*MAX... | [
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train | QA_indicator_OBV | 能量潮 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_OBV(DataFrame):
"""能量潮"""
VOL = DataFrame.volume
CLOSE = DataFrame.close
return pd.DataFrame({
'OBV': np.cumsum(IF(CLOSE > REF(CLOSE, 1), VOL, IF(CLOSE < REF(CLOSE, 1), -VOL, 0)))/10000
}) | def QA_indicator_OBV(DataFrame):
"""能量潮"""
VOL = DataFrame.volume
CLOSE = DataFrame.close
return pd.DataFrame({
'OBV': np.cumsum(IF(CLOSE > REF(CLOSE, 1), VOL, IF(CLOSE < REF(CLOSE, 1), -VOL, 0)))/10000
}) | [
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train | QA_indicator_BOLL | 布林线 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_BOLL(DataFrame, N=20, P=2):
'布林线'
C = DataFrame['close']
boll = MA(C, N)
UB = boll + P * STD(C, N)
LB = boll - P * STD(C, N)
DICT = {'BOLL': boll, 'UB': UB, 'LB': LB}
return pd.DataFrame(DICT) | def QA_indicator_BOLL(DataFrame, N=20, P=2):
'布林线'
C = DataFrame['close']
boll = MA(C, N)
UB = boll + P * STD(C, N)
LB = boll - P * STD(C, N)
DICT = {'BOLL': boll, 'UB': UB, 'LB': LB}
return pd.DataFrame(DICT) | [
"布林线"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L456-L464 | [
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train | QA_indicator_MIKE | MIKE指标
指标说明
MIKE是另外一种形式的路径指标。
买卖原则
1 WEAK-S，MEDIUM-S，STRONG-S三条线代表初级、中级、强力支撑。
2 WEAK-R，MEDIUM-R，STRONG-R三条线代表初级、中级、强力压力。 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_MIKE(DataFrame, N=12):
"""
MIKE指标
指标说明
MIKE是另外一种形式的路径指标。
买卖原则
1 WEAK-S，MEDIUM-S，STRONG-S三条线代表初级、中级、强力支撑。
2 WEAK-R，MEDIUM-R，STRONG-R三条线代表初级、中级、强力压力。
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
TYP = (HIGH+LOW+CLOSE)/3
LL = ... | def QA_indicator_MIKE(DataFrame, N=12):
"""
MIKE指标
指标说明
MIKE是另外一种形式的路径指标。
买卖原则
1 WEAK-S，MEDIUM-S，STRONG-S三条线代表初级、中级、强力支撑。
2 WEAK-R，MEDIUM-R，STRONG-R三条线代表初级、中级、强力压力。
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
TYP = (HIGH+LOW+CLOSE)/3
LL = ... | [
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train | QA_indicator_BBI | 多空指标 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_BBI(DataFrame, N1=3, N2=6, N3=12, N4=24):
'多空指标'
C = DataFrame['close']
bbi = (MA(C, N1) + MA(C, N2) + MA(C, N3) + MA(C, N4)) / 4
DICT = {'BBI': bbi}
return pd.DataFrame(DICT) | def QA_indicator_BBI(DataFrame, N1=3, N2=6, N3=12, N4=24):
'多空指标'
C = DataFrame['close']
bbi = (MA(C, N1) + MA(C, N2) + MA(C, N3) + MA(C, N4)) / 4
DICT = {'BBI': bbi}
return pd.DataFrame(DICT) | [
"多空指标"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAIndicator/indicators.py#L496-L502 | [
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train | QA_indicator_MFI | 资金指标
TYP := (HIGH + LOW + CLOSE)/3;
V1:=SUM(IF(TYP>REF(TYP,1),TYP*VOL,0),N)/SUM(IF(TYP<REF(TYP,1),TYP*VOL,0),N);
MFI:100-(100/(1+V1));
赋值: (最高价 + 最低价 + 收盘价)/3
V1赋值:如果TYP>1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和/如果TYP<1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和
输出资金流量指标:100-(100/(1+V1)) | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_MFI(DataFrame, N=14):
"""
资金指标
TYP := (HIGH + LOW + CLOSE)/3;
V1:=SUM(IF(TYP>REF(TYP,1),TYP*VOL,0),N)/SUM(IF(TYP<REF(TYP,1),TYP*VOL,0),N);
MFI:100-(100/(1+V1));
赋值: (最高价 + 最低价 + 收盘价)/3
V1赋值:如果TYP>1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和/如果TYP<1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和
输出资金流... | def QA_indicator_MFI(DataFrame, N=14):
"""
资金指标
TYP := (HIGH + LOW + CLOSE)/3;
V1:=SUM(IF(TYP>REF(TYP,1),TYP*VOL,0),N)/SUM(IF(TYP<REF(TYP,1),TYP*VOL,0),N);
MFI:100-(100/(1+V1));
赋值: (最高价 + 最低价 + 收盘价)/3
V1赋值:如果TYP>1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和/如果TYP<1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和
输出资金流... | [
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train | QA_indicator_ATR | 输出TR:(最高价-最低价)和昨收-最高价的绝对值的较大值和昨收-最低价的绝对值的较大值
输出真实波幅:TR的N日简单移动平均
算法：今日振幅、今日最高与昨收差价、今日最低与昨收差价中的最大值，为真实波幅，求真实波幅的N日移动平均
参数：N 天数，一般取14 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_ATR(DataFrame, N=14):
"""
输出TR:(最高价-最低价)和昨收-最高价的绝对值的较大值和昨收-最低价的绝对值的较大值
输出真实波幅:TR的N日简单移动平均
算法：今日振幅、今日最高与昨收差价、今日最低与昨收差价中的最大值，为真实波幅，求真实波幅的N日移动平均
参数：N 天数，一般取14
"""
C = DataFrame['close']
H = DataFrame['high']
L = DataFrame['low']
TR = MAX(MAX((H - L), ABS(REF(C, 1)... | def QA_indicator_ATR(DataFrame, N=14):
"""
输出TR:(最高价-最低价)和昨收-最高价的绝对值的较大值和昨收-最低价的绝对值的较大值
输出真实波幅:TR的N日简单移动平均
算法：今日振幅、今日最高与昨收差价、今日最低与昨收差价中的最大值，为真实波幅，求真实波幅的N日移动平均
参数：N 天数，一般取14
"""
C = DataFrame['close']
H = DataFrame['high']
L = DataFrame['low']
TR = MAX(MAX((H - L), ABS(REF(C, 1)... | [
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train | QA_indicator_SKDJ | 1.指标>80 时，回档机率大；指标<20 时，反弹机率大；
2.K在20左右向上交叉D时，视为买进信号参考；
3.K在80左右向下交叉D时，视为卖出信号参考；
4.SKDJ波动于50左右的任何讯号，其作用不大。 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_SKDJ(DataFrame, N=9, M=3):
"""
1.指标>80 时，回档机率大；指标<20 时，反弹机率大；
2.K在20左右向上交叉D时，视为买进信号参考；
3.K在80左右向下交叉D时，视为卖出信号参考；
4.SKDJ波动于50左右的任何讯号，其作用不大。
"""
CLOSE = DataFrame['close']
LOWV = LLV(DataFrame['low'], N)
HIGHV = HHV(DataFrame['high'], N)
RSV = EMA((CLOSE - LOWV) /... | def QA_indicator_SKDJ(DataFrame, N=9, M=3):
"""
1.指标>80 时，回档机率大；指标<20 时，反弹机率大；
2.K在20左右向上交叉D时，视为买进信号参考；
3.K在80左右向下交叉D时，视为卖出信号参考；
4.SKDJ波动于50左右的任何讯号，其作用不大。
"""
CLOSE = DataFrame['close']
LOWV = LLV(DataFrame['low'], N)
HIGHV = HHV(DataFrame['high'], N)
RSV = EMA((CLOSE - LOWV) /... | [
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train | QA_indicator_DDI | '方向标准离差指数'
分析DDI柱状线，由红变绿(正变负)，卖出信号参考；由绿变红，买入信号参考。 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_DDI(DataFrame, N=13, N1=26, M=1, M1=5):
"""
'方向标准离差指数'
分析DDI柱状线，由红变绿(正变负)，卖出信号参考；由绿变红，买入信号参考。
"""
H = DataFrame['high']
L = DataFrame['low']
DMZ = IF((H + L) > (REF(H, 1) + REF(L, 1)),
MAX(ABS(H - REF(H, 1)), ABS(L - REF(L, 1))), 0)
DMF = IF((H + L) < (REF... | def QA_indicator_DDI(DataFrame, N=13, N1=26, M=1, M1=5):
"""
'方向标准离差指数'
分析DDI柱状线，由红变绿(正变负)，卖出信号参考；由绿变红，买入信号参考。
"""
H = DataFrame['high']
L = DataFrame['low']
DMZ = IF((H + L) > (REF(H, 1) + REF(L, 1)),
MAX(ABS(H - REF(H, 1)), ABS(L - REF(L, 1))), 0)
DMF = IF((H + L) < (REF... | [
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train | QA_indicator_shadow | 上下影线指标 | QUANTAXIS/QAIndicator/indicators.py | def QA_indicator_shadow(DataFrame):
"""
上下影线指标
"""
return {
'LOW': lower_shadow(DataFrame), 'UP': upper_shadow(DataFrame),
'BODY': body(DataFrame), 'BODY_ABS': body_abs(DataFrame), 'PRICE_PCG': price_pcg(DataFrame)
} | def QA_indicator_shadow(DataFrame):
"""
上下影线指标
"""
return {
'LOW': lower_shadow(DataFrame), 'UP': upper_shadow(DataFrame),
'BODY': body(DataFrame), 'BODY_ABS': body_abs(DataFrame), 'PRICE_PCG': price_pcg(DataFrame)
} | [
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train | RSanalysis.run | :type series: List
:type exponent: int
:rtype: float | QUANTAXIS/QAIndicator/hurst.py | def run(self, series, exponent=None):
'''
:type series: List
:type exponent: int
:rtype: float
'''
try:
return self.calculateHurst(series, exponent)
except Exception as e:
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'''
:type series: List
:type exponent: int
:rtype: float
'''
try:
return self.calculateHurst(series, exponent)
except Exception as e:
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train | RSanalysis.bestExponent | :type seriesLenght: int
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'''
:type seriesLenght: int
:rtype: int
'''
i = 0
cont = True
while(cont):
if(int(seriesLenght/int(math.pow(2, i))) <= 1):
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:type seriesLenght: int
:rtype: int
'''
i = 0
cont = True
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train | RSanalysis.mean | :type start: int
:type limit: int
:rtype: float | QUANTAXIS/QAIndicator/hurst.py | def mean(self, series, start, limit):
'''
:type start: int
:type limit: int
:rtype: float
'''
return float(np.mean(series[start:limit])) | def mean(self, series, start, limit):
'''
:type start: int
:type limit: int
:rtype: float
'''
return float(np.mean(series[start:limit])) | [
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train | RSanalysis.deviation | :type start: int
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'''
:type start: int
:type limit: int
:type mean: int
:rtype: list()
'''
d = []
for x in range(start, limit):
d.append(float(series[x] - mean))
return d | def deviation(self, series, start, limit, mean):
'''
:type start: int
:type limit: int
:type mean: int
:rtype: list()
'''
d = []
for x in range(start, limit):
d.append(float(series[x] - mean))
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train | RSanalysis.standartDeviation | :type start: int
:type limit: int
:rtype: float | QUANTAXIS/QAIndicator/hurst.py | def standartDeviation(self, series, start, limit):
'''
:type start: int
:type limit: int
:rtype: float
'''
return float(np.std(series[start:limit])) | def standartDeviation(self, series, start, limit):
'''
:type start: int
:type limit: int
:rtype: float
'''
return float(np.std(series[start:limit])) | [
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train | RSanalysis.calculateHurst | :type series: List
:type exponent: int
:rtype: float | QUANTAXIS/QAIndicator/hurst.py | def calculateHurst(self, series, exponent=None):
'''
:type series: List
:type exponent: int
:rtype: float
'''
rescaledRange = list()
sizeRange = list()
rescaledRangeMean = list()
if(exponent is None):
exponent = self.bestExponent(len(s... | def calculateHurst(self, series, exponent=None):
'''
:type series: List
:type exponent: int
:rtype: float
'''
rescaledRange = list()
sizeRange = list()
rescaledRangeMean = list()
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train | QA_util_send_mail | 邮件发送
Arguments:
msg {[type]} -- [description]
title {[type]} -- [description]
from_user {[type]} -- [description]
from_password {[type]} -- [description]
to_addr {[type]} -- [description]
smtp {[type]} -- [description] | QUANTAXIS/QAUtil/QAMail.py | def QA_util_send_mail(msg, title, from_user, from_password, to_addr, smtp):
"""邮件发送
Arguments:
msg {[type]} -- [description]
title {[type]} -- [description]
from_user {[type]} -- [description]
from_password {[type]} -- [description]
to_addr {[type]} -- [description]
... | def QA_util_send_mail(msg, title, from_user, from_password, to_addr, smtp):
"""邮件发送
Arguments:
msg {[type]} -- [description]
title {[type]} -- [description]
from_user {[type]} -- [description]
from_password {[type]} -- [description]
to_addr {[type]} -- [description]
... | [
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train | QA_fetch_get_stock_analysis | 'zyfw', 主营范围 'jyps'#经营评述 'zygcfx' 主营构成分析
date 主营构成 主营收入(元) 收入比例cbbl 主营成本(元) 成本比例 主营利润(元) 利润比例 毛利率(%)
行业 /产品/ 区域 hq cp qy | QUANTAXIS/QAFetch/QAEastMoney.py | def QA_fetch_get_stock_analysis(code):
"""
'zyfw', 主营范围 'jyps'#经营评述 'zygcfx' 主营构成分析
date 主营构成 主营收入(元) 收入比例cbbl 主营成本(元) 成本比例 主营利润(元) 利润比例 毛利率(%)
行业 /产品/ 区域 hq cp qy
"""
market = 'sh' if _select_market_code(code) == 1 else 'sz'
null = 'none'
data = eval(requests.get(BusinessAnalysis_url.f... | def QA_fetch_get_stock_analysis(code):
"""
'zyfw', 主营范围 'jyps'#经营评述 'zygcfx' 主营构成分析
date 主营构成 主营收入(元) 收入比例cbbl 主营成本(元) 成本比例 主营利润(元) 利润比例 毛利率(%)
行业 /产品/ 区域 hq cp qy
"""
market = 'sh' if _select_market_code(code) == 1 else 'sz'
null = 'none'
data = eval(requests.get(BusinessAnalysis_url.f... | [
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"jyps",
"#经营评述",
"zygcfx",
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QAEastMoney.py#L35-L66 | [
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train | QA_TTSBroker.send_order | 下单
Arguments:
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
towards {[type]} -- [description]
order_model {[type]} -- [description]
market:市场，SZ 深交所，SH 上交所
Returns:
[ty... | QUANTAXIS/QAMarket/QATTSBroker.py | def send_order(self, code, price, amount, towards, order_model, market=None):
"""下单
Arguments:
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
towards {[type]} -- [description]
order_model {[typ... | def send_order(self, code, price, amount, towards, order_model, market=None):
"""下单
Arguments:
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
towards {[type]} -- [description]
order_model {[typ... | [
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train | QA_util_getBetweenMonth | #返回所有月份，以及每月的起始日期、结束日期，字典格式 | QUANTAXIS/QAUtil/QADateTools.py | def QA_util_getBetweenMonth(from_date, to_date):
"""
#返回所有月份，以及每月的起始日期、结束日期，字典格式
"""
date_list = {}
begin_date = datetime.datetime.strptime(from_date, "%Y-%m-%d")
end_date = datetime.datetime.strptime(to_date, "%Y-%m-%d")
while begin_date <= end_date:
date_str = begin_date.strftime("... | def QA_util_getBetweenMonth(from_date, to_date):
"""
#返回所有月份，以及每月的起始日期、结束日期，字典格式
"""
date_list = {}
begin_date = datetime.datetime.strptime(from_date, "%Y-%m-%d")
end_date = datetime.datetime.strptime(to_date, "%Y-%m-%d")
while begin_date <= end_date:
date_str = begin_date.strftime("... | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADateTools.py#L6-L19 | [
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train | QA_util_add_months | #返回dt隔months个月后的日期，months相当于步长 | QUANTAXIS/QAUtil/QADateTools.py | def QA_util_add_months(dt, months):
"""
#返回dt隔months个月后的日期，months相当于步长
"""
dt = datetime.datetime.strptime(
dt, "%Y-%m-%d") + relativedelta(months=months)
return(dt) | def QA_util_add_months(dt, months):
"""
#返回dt隔months个月后的日期，months相当于步长
"""
dt = datetime.datetime.strptime(
dt, "%Y-%m-%d") + relativedelta(months=months)
return(dt) | [
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train | QA_util_get_1st_of_next_month | 获取下个月第一天的日期
:return: 返回日期 | QUANTAXIS/QAUtil/QADateTools.py | def QA_util_get_1st_of_next_month(dt):
"""
获取下个月第一天的日期
:return: 返回日期
"""
year = dt.year
month = dt.month
if month == 12:
month = 1
year += 1
else:
month += 1
res = datetime.datetime(year, month, 1)
return res | def QA_util_get_1st_of_next_month(dt):
"""
获取下个月第一天的日期
:return: 返回日期
"""
year = dt.year
month = dt.month
if month == 12:
month = 1
year += 1
else:
month += 1
res = datetime.datetime(year, month, 1)
return res | [
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train | QA_util_getBetweenQuarter | #加上每季度的起始日期、结束日期 | QUANTAXIS/QAUtil/QADateTools.py | def QA_util_getBetweenQuarter(begin_date, end_date):
"""
#加上每季度的起始日期、结束日期
"""
quarter_list = {}
month_list = QA_util_getBetweenMonth(begin_date, end_date)
for value in month_list:
tempvalue = value.split("-")
year = tempvalue[0]
if tempvalue[1] in ['01', '02', '03']:
... | def QA_util_getBetweenQuarter(begin_date, end_date):
"""
#加上每季度的起始日期、结束日期
"""
quarter_list = {}
month_list = QA_util_getBetweenMonth(begin_date, end_date)
for value in month_list:
tempvalue = value.split("-")
year = tempvalue[0]
if tempvalue[1] in ['01', '02', '03']:
... | [
"#加上每季度的起始日期、结束日期"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QADateTools.py#L47-L64 | [
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train | save_account | save account
Arguments:
message {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE}) | QUANTAXIS/QASU/save_account.py | def save_account(message, collection=DATABASE.account):
"""save account
Arguments:
message {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE})
"""
try:
collection.create_index(
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"""save account
Arguments:
message {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE})
"""
try:
collection.create_index(
[("account_cookie", ASCENDING), (... | [
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"account"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/save_account.py#L32-L51 | [
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train | QA_SU_save_financial_files | 本地存储financialdata | QUANTAXIS/QASU/save_financialfiles.py | def QA_SU_save_financial_files():
"""本地存储financialdata
"""
download_financialzip()
coll = DATABASE.financial
coll.create_index(
[("code", ASCENDING), ("report_date", ASCENDING)], unique=True)
for item in os.listdir(download_path):
if item[0:4] != 'gpcw':
print(
... | def QA_SU_save_financial_files():
"""本地存储financialdata
"""
download_financialzip()
coll = DATABASE.financial
coll.create_index(
[("code", ASCENDING), ("report_date", ASCENDING)], unique=True)
for item in os.listdir(download_path):
if item[0:4] != 'gpcw':
print(
... | [
"本地存储financialdata"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QASU/save_financialfiles.py#L39-L71 | [
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train | QA_util_log_info | QUANTAXIS Log Module
@yutiansut
QA_util_log_x is under [QAStandard#0.0.2@602-x] Protocol | QUANTAXIS/QAUtil/QALogs.py | def QA_util_log_info(
logs,
ui_log=None,
ui_progress=None,
ui_progress_int_value=None,
):
"""
QUANTAXIS Log Module
@yutiansut
QA_util_log_x is under [QAStandard#0.0.2@602-x] Protocol
"""
logging.warning(logs)
# 给GUI使用，更新当前任务到日志和进度
if ui_log is not None:
... | def QA_util_log_info(
logs,
ui_log=None,
ui_progress=None,
ui_progress_int_value=None,
):
"""
QUANTAXIS Log Module
@yutiansut
QA_util_log_x is under [QAStandard#0.0.2@602-x] Protocol
"""
logging.warning(logs)
# 给GUI使用，更新当前任务到日志和进度
if ui_log is not None:
... | [
"QUANTAXIS",
"Log",
"Module",
"@yutiansut"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QALogs.py#L86-L109 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_save_tdx_to_mongo | save file
Arguments:
file_dir {str:direction} -- 文件的地址
Keyword Arguments:
client {Mongodb:Connection} -- Mongo Connection (default: {DATABASE}) | QUANTAXIS/QASU/save_tdx_file.py | def QA_save_tdx_to_mongo(file_dir, client=DATABASE):
"""save file
Arguments:
file_dir {str:direction} -- 文件的地址
Keyword Arguments:
client {Mongodb:Connection} -- Mongo Connection (default: {DATABASE})
"""
reader = TdxMinBarReader()
__coll = client.stock_min_five
for... | def QA_save_tdx_to_mongo(file_dir, client=DATABASE):
"""save file
Arguments:
file_dir {str:direction} -- 文件的地址
Keyword Arguments:
client {Mongodb:Connection} -- Mongo Connection (default: {DATABASE})
"""
reader = TdxMinBarReader()
__coll = client.stock_min_five
for... | [
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train | exclude_from_stock_ip_list | 从stock_ip_list删除列表exclude_ip_list中的ip
从stock_ip_list删除列表future_ip_list中的ip
:param exclude_ip_list: 需要删除的ip_list
:return: None | QUANTAXIS/QAUtil/QASetting.py | def exclude_from_stock_ip_list(exclude_ip_list):
""" 从stock_ip_list删除列表exclude_ip_list中的ip
从stock_ip_list删除列表future_ip_list中的ip
:param exclude_ip_list: 需要删除的ip_list
:return: None
"""
for exc in exclude_ip_list:
if exc in stock_ip_list:
stock_ip_list.remove(exc)
# 扩展市场
... | def exclude_from_stock_ip_list(exclude_ip_list):
""" 从stock_ip_list删除列表exclude_ip_list中的ip
从stock_ip_list删除列表future_ip_list中的ip
:param exclude_ip_list: 需要删除的ip_list
:return: None
"""
for exc in exclude_ip_list:
if exc in stock_ip_list:
stock_ip_list.remove(exc)
# 扩展市场
... | [
"从stock_ip_list删除列表exclude_ip_list中的ip",
"从stock_ip_list删除列表future_ip_list中的ip"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QASetting.py#L209-L223 | [
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"... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_Setting.get_config | [summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
default_value {[type]} -- [description] (default: {DEFAULT_DB_URI})
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QASetting.py | def get_config(
self,
section='MONGODB',
option='uri',
default_value=DEFAULT_DB_URI
):
"""[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
... | def get_config(
self,
section='MONGODB',
option='uri',
default_value=DEFAULT_DB_URI
):
"""[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
... | [
"[",
"summary",
"]"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QASetting.py#L78-L101 | [
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train | QA_Setting.set_config | [summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
default_value {[type]} -- [description] (default: {DEFAULT_DB_URI})
Returns:
[type] -- [description] | QUANTAXIS/QAUtil/QASetting.py | def set_config(
self,
section='MONGODB',
option='uri',
default_value=DEFAULT_DB_URI
):
"""[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
... | def set_config(
self,
section='MONGODB',
option='uri',
default_value=DEFAULT_DB_URI
):
"""[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
... | [
"[",
"summary",
"]"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAUtil/QASetting.py#L103-L121 | [
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train | QA_Setting.get_or_set_section | [summary]
Arguments:
config {[type]} -- [description]
section {[type]} -- [description]
option {[type]} -- [description]
DEFAULT_VALUE {[type]} -- [description]
Keyword Arguments:
method {str} -- [description] (default: {'get'})
Retu... | QUANTAXIS/QAUtil/QASetting.py | def get_or_set_section(
self,
config,
section,
option,
DEFAULT_VALUE,
method='get'
):
"""[summary]
Arguments:
config {[type]} -- [description]
section {[type]} -- [description]
option {[type]... | def get_or_set_section(
self,
config,
section,
option,
DEFAULT_VALUE,
method='get'
):
"""[summary]
Arguments:
config {[type]} -- [description]
section {[type]} -- [description]
option {[type]... | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_util_date_str2int | 日期字符串 '2011-09-11' 变换成 整数 20110911
日期字符串 '2018-12-01' 变换成 整数 20181201
:param date: str日期字符串
:return: 类型int | QUANTAXIS/QAUtil/QADate.py | def QA_util_date_str2int(date):
"""
日期字符串 '2011-09-11' 变换成 整数 20110911
日期字符串 '2018-12-01' 变换成 整数 20181201
:param date: str日期字符串
:return: 类型int
"""
# return int(str(date)[0:4] + str(date)[5:7] + str(date)[8:10])
if isinstance(date, str):
return int(str().join(date.split('-')))
... | def QA_util_date_str2int(date):
"""
日期字符串 '2011-09-11' 变换成 整数 20110911
日期字符串 '2018-12-01' 变换成 整数 20181201
:param date: str日期字符串
:return: 类型int
"""
# return int(str(date)[0:4] + str(date)[5:7] + str(date)[8:10])
if isinstance(date, str):
return int(str().join(date.split('-')))
... | [
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train | QA_util_date_int2str | 类型datetime.datatime
:param date: int 8位整数
:return: 类型str | QUANTAXIS/QAUtil/QADate.py | def QA_util_date_int2str(int_date):
"""
类型datetime.datatime
:param date: int 8位整数
:return: 类型str
"""
date = str(int_date)
if len(date) == 8:
return str(date[0:4] + '-' + date[4:6] + '-' + date[6:8])
elif len(date) == 10:
return date | def QA_util_date_int2str(int_date):
"""
类型datetime.datatime
:param date: int 8位整数
:return: 类型str
"""
date = str(int_date)
if len(date) == 8:
return str(date[0:4] + '-' + date[4:6] + '-' + date[6:8])
elif len(date) == 10:
return date | [
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train | QA_util_to_datetime | 字符串 '2018-01-01' 转变成 datatime 类型
:param time: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型datetime.datatime | QUANTAXIS/QAUtil/QADate.py | def QA_util_to_datetime(time):
"""
字符串 '2018-01-01' 转变成 datatime 类型
:param time: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型datetime.datatime
"""
if len(str(time)) == 10:
_time = '{} 00:00:00'.format(time)
elif len(str(time)) == 19:
_time = str(time)
else:
QA_ut... | def QA_util_to_datetime(time):
"""
字符串 '2018-01-01' 转变成 datatime 类型
:param time: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型datetime.datatime
"""
if len(str(time)) == 10:
_time = '{} 00:00:00'.format(time)
elif len(str(time)) == 19:
_time = str(time)
else:
QA_ut... | [
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train | QA_util_datetime_to_strdate | :param dt: pythone datetime.datetime
:return: 1999-02-01 string type | QUANTAXIS/QAUtil/QADate.py | def QA_util_datetime_to_strdate(dt):
"""
:param dt: pythone datetime.datetime
:return: 1999-02-01 string type
"""
strdate = "%04d-%02d-%02d" % (dt.year, dt.month, dt.day)
return strdate | def QA_util_datetime_to_strdate(dt):
"""
:param dt: pythone datetime.datetime
:return: 1999-02-01 string type
"""
strdate = "%04d-%02d-%02d" % (dt.year, dt.month, dt.day)
return strdate | [
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train | QA_util_datetime_to_strdatetime | :param dt: pythone datetime.datetime
:return: 1999-02-01 09:30:91 string type | QUANTAXIS/QAUtil/QADate.py | def QA_util_datetime_to_strdatetime(dt):
"""
:param dt: pythone datetime.datetime
:return: 1999-02-01 09:30:91 string type
"""
strdatetime = "%04d-%02d-%02d %02d:%02d:%02d" % (
dt.year,
dt.month,
dt.day,
dt.hour,
dt.minute,
dt.second
)
return... | def QA_util_datetime_to_strdatetime(dt):
"""
:param dt: pythone datetime.datetime
:return: 1999-02-01 09:30:91 string type
"""
strdatetime = "%04d-%02d-%02d %02d:%02d:%02d" % (
dt.year,
dt.month,
dt.day,
dt.hour,
dt.minute,
dt.second
)
return... | [
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train | QA_util_date_stamp | 字符串 '2018-01-01' 转变成 float 类型时间 类似 time.time() 返回的类型
:param date: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型float | QUANTAXIS/QAUtil/QADate.py | def QA_util_date_stamp(date):
"""
字符串 '2018-01-01' 转变成 float 类型时间 类似 time.time() 返回的类型
:param date: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型float
"""
datestr = str(date)[0:10]
date = time.mktime(time.strptime(datestr, '%Y-%m-%d'))
return date | def QA_util_date_stamp(date):
"""
字符串 '2018-01-01' 转变成 float 类型时间 类似 time.time() 返回的类型
:param date: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型float
"""
datestr = str(date)[0:10]
date = time.mktime(time.strptime(datestr, '%Y-%m-%d'))
return date | [
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train | QA_util_time_stamp | 字符串 '2018-01-01 00:00:00' 转变成 float 类型时间 类似 time.time() 返回的类型
:param time_: 字符串str -- 数据格式 最好是%Y-%m-%d %H:%M:%S 中间要有空格
:return: 类型float | QUANTAXIS/QAUtil/QADate.py | def QA_util_time_stamp(time_):
"""
字符串 '2018-01-01 00:00:00' 转变成 float 类型时间 类似 time.time() 返回的类型
:param time_: 字符串str -- 数据格式 最好是%Y-%m-%d %H:%M:%S 中间要有空格
:return: 类型float
"""
if len(str(time_)) == 10:
# yyyy-mm-dd格式
return time.mktime(time.strptime(time_, '%Y-%m-%d'))
elif l... | def QA_util_time_stamp(time_):
"""
字符串 '2018-01-01 00:00:00' 转变成 float 类型时间 类似 time.time() 返回的类型
:param time_: 字符串str -- 数据格式 最好是%Y-%m-%d %H:%M:%S 中间要有空格
:return: 类型float
"""
if len(str(time_)) == 10:
# yyyy-mm-dd格式
return time.mktime(time.strptime(time_, '%Y-%m-%d'))
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train | QA_util_stamp2datetime | datestamp转datetime
pandas转出来的timestamp是13位整数 要/1000
It’s common for this to be restricted to years from 1970 through 2038.
从1970年开始的纳秒到当前的计数 转变成 float 类型时间 类似 time.time() 返回的类型
:param timestamp: long类型
:return: 类型float | QUANTAXIS/QAUtil/QADate.py | def QA_util_stamp2datetime(timestamp):
"""
datestamp转datetime
pandas转出来的timestamp是13位整数 要/1000
It’s common for this to be restricted to years from 1970 through 2038.
从1970年开始的纳秒到当前的计数 转变成 float 类型时间 类似 time.time() 返回的类型
:param timestamp: long类型
:return: 类型float
"""
try:
retur... | def QA_util_stamp2datetime(timestamp):
"""
datestamp转datetime
pandas转出来的timestamp是13位整数 要/1000
It’s common for this to be restricted to years from 1970 through 2038.
从1970年开始的纳秒到当前的计数 转变成 float 类型时间 类似 time.time() 返回的类型
:param timestamp: long类型
:return: 类型float
"""
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train | QA_util_realtime | 查询数据库中的数据
:param strtime: strtime str字符串 -- 1999-12-11 这种格式
:param client: client pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Dictionary -- {'time_real': 时间,'id': id} | QUANTAXIS/QAUtil/QADate.py | def QA_util_realtime(strtime, client):
"""
查询数据库中的数据
:param strtime: strtime str字符串 -- 1999-12-11 这种格式
:param client: client pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Dictionary -- {'time_real': 时间,'id': id}
"""... | def QA_util_realtime(strtime, client):
"""
查询数据库中的数据
:param strtime: strtime str字符串 -- 1999-12-11 这种格式
:param client: client pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Dictionary -- {'time_real': 时间,'id': id}
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train | QA_util_id2date | 从数据库中查询 通达信时间
:param idx: 字符串 -- 数据库index
:param client: pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Str -- 通达信数据库时间 | QUANTAXIS/QAUtil/QADate.py | def QA_util_id2date(idx, client):
"""
从数据库中查询 通达信时间
:param idx: 字符串 -- 数据库index
:param client: pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Str -- 通达信数据库时间
"""
coll = client.quantaxis.trade_date
temp_str = coll.find_o... | def QA_util_id2date(idx, client):
"""
从数据库中查询 通达信时间
:param idx: 字符串 -- 数据库index
:param client: pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
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coll = client.quantaxis.trade_date
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train | QA_util_is_trade | 判断是否是交易日
从数据库中查询
:param date: str类型 -- 1999-12-11 这种格式 10位字符串
:param code: str类型 -- 股票代码 例如 603658 ， 6位字符串
:param client: pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Boolean -- 是否是交易时间 | QUANTAXIS/QAUtil/QADate.py | def QA_util_is_trade(date, code, client):
"""
判断是否是交易日
从数据库中查询
:param date: str类型 -- 1999-12-11 这种格式 10位字符串
:param code: str类型 -- 股票代码 例如 603658 ， 6位字符串
:param client: pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
:return: Boolean -- 是... | def QA_util_is_trade(date, code, client):
"""
判断是否是交易日
从数据库中查询
:param date: str类型 -- 1999-12-11 这种格式 10位字符串
:param code: str类型 -- 股票代码 例如 603658 ， 6位字符串
:param client: pymongo.MongoClient类型 -- mongodb 数据库 从 QA_util_sql_mongo_setting 中 QA_util_sql_mongo_setting 获取
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train | QA_util_select_hours | quantaxis的时间选择函数,约定时间的范围,比如早上9点到11点 | QUANTAXIS/QAUtil/QADate.py | def QA_util_select_hours(time=None, gt=None, lt=None, gte=None, lte=None):
'quantaxis的时间选择函数,约定时间的范围,比如早上9点到11点'
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fun_list = []
if gt != None:
fun_list.append('>')
if lt != None:
fun_lis... | def QA_util_select_hours(time=None, gt=None, lt=None, gte=None, lte=None):
'quantaxis的时间选择函数,约定时间的范围,比如早上9点到11点'
if time is None:
__realtime = datetime.datetime.now()
else:
__realtime = time
fun_list = []
if gt != None:
fun_list.append('>')
if lt != None:
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train | QA_util_calc_time | '耗时长度的装饰器'
:param func:
:param args:
:param kwargs:
:return: | QUANTAXIS/QAUtil/QADate.py | def QA_util_calc_time(func, *args, **kwargs):
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:param func:
:param args:
:param kwargs:
:return:
"""
_time = datetime.datetime.now()
func(*args, **kwargs)
print(datetime.datetime.now() - _time) | def QA_util_calc_time(func, *args, **kwargs):
"""
'耗时长度的装饰器'
:param func:
:param args:
:param kwargs:
:return:
"""
_time = datetime.datetime.now()
func(*args, **kwargs)
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train | QA_DataStruct_Stock_day.high_limit | 涨停价 | QUANTAXIS/QAData/QADataStruct.py | def high_limit(self):
'涨停价'
return self.groupby(level=1).close.apply(lambda x: round((x.shift(1) + 0.0002)*1.1, 2)).sort_index() | def high_limit(self):
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train | QA_DataStruct_Stock_day.next_day_low_limit | 明日跌停价 | QUANTAXIS/QAData/QADataStruct.py | def next_day_low_limit(self):
"明日跌停价"
return self.groupby(level=1).close.apply(lambda x: round((x + 0.0002)*0.9, 2)).sort_index() | def next_day_low_limit(self):
"明日跌停价"
return self.groupby(level=1).close.apply(lambda x: round((x + 0.0002)*0.9, 2)).sort_index() | [
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train | QA_DataStruct_Stock_transaction.get_medium_order | return medium
Keyword Arguments:
lower {[type]} -- [description] (default: {200000})
higher {[type]} -- [description] (default: {1000000})
Returns:
[type] -- [description] | QUANTAXIS/QAData/QADataStruct.py | def get_medium_order(self, lower=200000, higher=1000000):
"""return medium
Keyword Arguments:
lower {[type]} -- [description] (default: {200000})
higher {[type]} -- [description] (default: {1000000})
Returns:
[type] -- [description]
"""
retu... | def get_medium_order(self, lower=200000, higher=1000000):
"""return medium
Keyword Arguments:
lower {[type]} -- [description] (default: {200000})
higher {[type]} -- [description] (default: {1000000})
Returns:
[type] -- [description]
"""
retu... | [
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train | shadow_calc | 计算上下影线
Arguments:
data {DataStruct.slice} -- 输入的是一个行情切片
Returns:
up_shadow {float} -- 上影线
down_shdow {float} -- 下影线
entity {float} -- 实体部分
date {str} -- 时间
code {str} -- 代码 | QUANTAXIS/QAAnalysis/QAAnalysis_dataframe.py | def shadow_calc(data):
"""计算上下影线
Arguments:
data {DataStruct.slice} -- 输入的是一个行情切片
Returns:
up_shadow {float} -- 上影线
down_shdow {float} -- 下影线
entity {float} -- 实体部分
date {str} -- 时间
code {str} -- 代码
"""
up_shadow = abs(data.high - (max(data.open, da... | def shadow_calc(data):
"""计算上下影线
Arguments:
data {DataStruct.slice} -- 输入的是一个行情切片
Returns:
up_shadow {float} -- 上影线
down_shdow {float} -- 下影线
entity {float} -- 实体部分
date {str} -- 时间
code {str} -- 代码
"""
up_shadow = abs(data.high - (max(data.open, da... | [
"计算上下影线"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAAnalysis/QAAnalysis_dataframe.py#L202-L225 | [
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train | QA_SimulatedBroker.query_data | 标准格式是numpy | QUANTAXIS/QAMarket/QASimulatedBroker.py | def query_data(self, code, start, end, frequence, market_type=None):
"""
标准格式是numpy
"""
try:
return self.fetcher[(market_type, frequence)](
code, start, end, frequence=frequence)
except:
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"""
标准格式是numpy
"""
try:
return self.fetcher[(market_type, frequence)](
code, start, end, frequence=frequence)
except:
pass | [
"标准格式是numpy"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAMarket/QASimulatedBroker.py#L76-L84 | [
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train | QA_SU_save_stock_min | 掘金实现方式
save current day's stock_min data | QUANTAXIS/QASU/save_gm.py | def QA_SU_save_stock_min(client=DATABASE, ui_log=None, ui_progress=None):
"""
掘金实现方式
save current day's stock_min data
"""
# 导入掘金模块且进行登录
try:
from gm.api import set_token
from gm.api import history
# 请自行将掘金量化的 TOKEN 替换掉 GMTOKEN
set_token("9c5601171e97994686b47b5cb... | def QA_SU_save_stock_min(client=DATABASE, ui_log=None, ui_progress=None):
"""
掘金实现方式
save current day's stock_min data
"""
# 导入掘金模块且进行登录
try:
from gm.api import set_token
from gm.api import history
# 请自行将掘金量化的 TOKEN 替换掉 GMTOKEN
set_token("9c5601171e97994686b47b5cb... | [
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train | _quotation_base.datetime | 分钟线结构返回datetime 日线结构返回date | QUANTAXIS/QAData/base_datastruct.py | def datetime(self):
'分钟线结构返回datetime 日线结构返回date'
index = self.data.index.remove_unused_levels()
return pd.to_datetime(index.levels[0]) | def datetime(self):
'分钟线结构返回datetime 日线结构返回date'
index = self.data.index.remove_unused_levels()
return pd.to_datetime(index.levels[0]) | [
"分钟线结构返回datetime",
"日线结构返回date"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L391-L394 | [
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train | _quotation_base.price_diff | 返回DataStruct.price的一阶差分 | QUANTAXIS/QAData/base_datastruct.py | def price_diff(self):
'返回DataStruct.price的一阶差分'
res = self.price.groupby(level=1).apply(lambda x: x.diff(1))
res.name = 'price_diff'
return res | def price_diff(self):
'返回DataStruct.price的一阶差分'
res = self.price.groupby(level=1).apply(lambda x: x.diff(1))
res.name = 'price_diff'
return res | [
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train | _quotation_base.pvariance | 返回DataStruct.price的方差 variance | QUANTAXIS/QAData/base_datastruct.py | def pvariance(self):
'返回DataStruct.price的方差 variance'
res = self.price.groupby(level=1
).apply(lambda x: statistics.pvariance(x))
res.name = 'pvariance'
return res | def pvariance(self):
'返回DataStruct.price的方差 variance'
res = self.price.groupby(level=1
).apply(lambda x: statistics.pvariance(x))
res.name = 'pvariance'
return res | [
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train | _quotation_base.bar_pct_change | 返回bar的涨跌幅 | QUANTAXIS/QAData/base_datastruct.py | def bar_pct_change(self):
'返回bar的涨跌幅'
res = (self.close - self.open) / self.open
res.name = 'bar_pct_change'
return res | def bar_pct_change(self):
'返回bar的涨跌幅'
res = (self.close - self.open) / self.open
res.name = 'bar_pct_change'
return res | [
"返回bar的涨跌幅"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L478-L482 | [
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train | _quotation_base.bar_amplitude | 返回bar振幅 | QUANTAXIS/QAData/base_datastruct.py | def bar_amplitude(self):
"返回bar振幅"
res = (self.high - self.low) / self.low
res.name = 'bar_amplitude'
return res | def bar_amplitude(self):
"返回bar振幅"
res = (self.high - self.low) / self.low
res.name = 'bar_amplitude'
return res | [
"返回bar振幅"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L486-L490 | [
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train | _quotation_base.mean_harmonic | 返回DataStruct.price的调和平均数 | QUANTAXIS/QAData/base_datastruct.py | def mean_harmonic(self):
'返回DataStruct.price的调和平均数'
res = self.price.groupby(level=1
).apply(lambda x: statistics.harmonic_mean(x))
res.name = 'mean_harmonic'
return res | def mean_harmonic(self):
'返回DataStruct.price的调和平均数'
res = self.price.groupby(level=1
).apply(lambda x: statistics.harmonic_mean(x))
res.name = 'mean_harmonic'
return res | [
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train | _quotation_base.amplitude | 返回DataStruct.price的百分比变化 | QUANTAXIS/QAData/base_datastruct.py | def amplitude(self):
'返回DataStruct.price的百分比变化'
res = self.price.groupby(
level=1
).apply(lambda x: (x.max() - x.min()) / x.min())
res.name = 'amplitude'
return res | def amplitude(self):
'返回DataStruct.price的百分比变化'
res = self.price.groupby(
level=1
).apply(lambda x: (x.max() - x.min()) / x.min())
res.name = 'amplitude'
return res | [
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train | _quotation_base.close_pct_change | 返回DataStruct.close的百分比变化 | QUANTAXIS/QAData/base_datastruct.py | def close_pct_change(self):
'返回DataStruct.close的百分比变化'
res = self.close.groupby(level=1).apply(lambda x: x.pct_change())
res.name = 'close_pct_change'
return res | def close_pct_change(self):
'返回DataStruct.close的百分比变化'
res = self.close.groupby(level=1).apply(lambda x: x.pct_change())
res.name = 'close_pct_change'
return res | [
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train | _quotation_base.normalized | 归一化 | QUANTAXIS/QAData/base_datastruct.py | def normalized(self):
'归一化'
res = self.groupby('code').apply(lambda x: x / x.iloc[0])
return res | def normalized(self):
'归一化'
res = self.groupby('code').apply(lambda x: x / x.iloc[0])
return res | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L593-L596 | [
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train | _quotation_base.security_gen | 返回一个基于代码的迭代器 | QUANTAXIS/QAData/base_datastruct.py | def security_gen(self):
'返回一个基于代码的迭代器'
for item in self.index.levels[1]:
yield self.new(
self.data.xs(item,
level=1,
drop_level=False),
dtype=self.type,
if_fq=self.if_fq
) | def security_gen(self):
'返回一个基于代码的迭代器'
for item in self.index.levels[1]:
yield self.new(
self.data.xs(item,
level=1,
drop_level=False),
dtype=self.type,
if_fq=self.if_fq
) | [
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L618-L627 | [
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train | _quotation_base.get_dict | 'give the time,code tuple and turn the dict'
:param time:
:param code:
:return: 字典dict 类型 | QUANTAXIS/QAData/base_datastruct.py | def get_dict(self, time, code):
'''
'give the time,code tuple and turn the dict'
:param time:
:param code:
:return: 字典dict 类型
'''
try:
return self.dicts[(QA_util_to_datetime(time), str(code))]
except Exception as e:
raise e | def get_dict(self, time, code):
'''
'give the time,code tuple and turn the dict'
:param time:
:param code:
:return: 字典dict 类型
'''
try:
return self.dicts[(QA_util_to_datetime(time), str(code))]
except Exception as e:
raise e | [
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train | _quotation_base.kline_echarts | plot the market_data | QUANTAXIS/QAData/base_datastruct.py | def kline_echarts(self, code=None):
def kline_formater(param):
return param.name + ':' + vars(param)
"""plot the market_data"""
if code is None:
path_name = '.' + os.sep + 'QA_' + self.type + \
'_codepackage_' + self.if_fq + '.html'
kline = K... | def kline_echarts(self, code=None):
def kline_formater(param):
return param.name + ':' + vars(param)
"""plot the market_data"""
if code is None:
path_name = '.' + os.sep + 'QA_' + self.type + \
'_codepackage_' + self.if_fq + '.html'
kline = K... | [
"plot",
"the",
"market_data"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L680-L769 | [
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train | _quotation_base.query | 查询data | QUANTAXIS/QAData/base_datastruct.py | def query(self, context):
"""
查询data
"""
try:
return self.data.query(context)
except pd.core.computation.ops.UndefinedVariableError:
print('QA CANNOT QUERY THIS {}'.format(context))
pass | def query(self, context):
"""
查询data
"""
try:
return self.data.query(context)
except pd.core.computation.ops.UndefinedVariableError:
print('QA CANNOT QUERY THIS {}'.format(context))
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"查询data"
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train | _quotation_base.groupby | 仿dataframe的groupby写法,但控制了by的code和datetime
Keyword Arguments:
by {[type]} -- [description] (default: {None})
axis {int} -- [description] (default: {0})
level {[type]} -- [description] (default: {None})
as_index {bool} -- [description] (default: {True})
... | QUANTAXIS/QAData/base_datastruct.py | def groupby(
self,
by=None,
axis=0,
level=None,
as_index=True,
sort=False,
group_keys=False,
squeeze=False,
**kwargs
):
"""仿dataframe的groupby写法,但控制了by的code和datetime
Keyword Arguments:
... | def groupby(
self,
by=None,
axis=0,
level=None,
as_index=True,
sort=False,
group_keys=False,
squeeze=False,
**kwargs
):
"""仿dataframe的groupby写法,但控制了by的code和datetime
Keyword Arguments:
... | [
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"但控制了by的code和datetime"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L802-L843 | [
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train | _quotation_base.new | 创建一个新的DataStruct
data 默认是self.data
🛠todo 没有这个？？ inplace 是否是对于原类的修改 ？？ | QUANTAXIS/QAData/base_datastruct.py | def new(self, data=None, dtype=None, if_fq=None):
"""
创建一个新的DataStruct
data 默认是self.data
🛠todo 没有这个？？ inplace 是否是对于原类的修改 ？？
"""
data = self.data if data is None else data
dtype = self.type if dtype is None else dtype
if_fq = self.if_fq if if_fq is None e... | def new(self, data=None, dtype=None, if_fq=None):
"""
创建一个新的DataStruct
data 默认是self.data
🛠todo 没有这个？？ inplace 是否是对于原类的修改 ？？
"""
data = self.data if data is None else data
dtype = self.type if dtype is None else dtype
if_fq = self.if_fq if if_fq is None e... | [
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train | _quotation_base.reindex | reindex
Arguments:
ind {[type]} -- [description]
Raises:
RuntimeError -- [description]
RuntimeError -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAData/base_datastruct.py | def reindex(self, ind):
"""reindex
Arguments:
ind {[type]} -- [description]
Raises:
RuntimeError -- [description]
RuntimeError -- [description]
Returns:
[type] -- [description]
"""
if isinstance(ind, pd.MultiIndex):
... | def reindex(self, ind):
"""reindex
Arguments:
ind {[type]} -- [description]
Raises:
RuntimeError -- [description]
RuntimeError -- [description]
Returns:
[type] -- [description]
"""
if isinstance(ind, pd.MultiIndex):
... | [
"reindex"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L863-L885 | [
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train | _quotation_base.to_json | 转换DataStruct为json | QUANTAXIS/QAData/base_datastruct.py | def to_json(self):
"""
转换DataStruct为json
"""
data = self.data
if self.type[-3:] != 'min':
data = self.data.assign(datetime= self.datetime)
return QA_util_to_json_from_pandas(data.reset_index()) | def to_json(self):
"""
转换DataStruct为json
"""
data = self.data
if self.type[-3:] != 'min':
data = self.data.assign(datetime= self.datetime)
return QA_util_to_json_from_pandas(data.reset_index()) | [
"转换DataStruct为json"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L965-L973 | [
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train | _quotation_base.to_hdf | IO --> hdf5 | QUANTAXIS/QAData/base_datastruct.py | def to_hdf(self, place, name):
'IO --> hdf5'
self.data.to_hdf(place, name)
return place, name | def to_hdf(self, place, name):
'IO --> hdf5'
self.data.to_hdf(place, name)
return place, name | [
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train | _quotation_base.is_same | 判断是否相同 | QUANTAXIS/QAData/base_datastruct.py | def is_same(self, DataStruct):
"""
判断是否相同
"""
if self.type == DataStruct.type and self.if_fq == DataStruct.if_fq:
return True
else:
return False | def is_same(self, DataStruct):
"""
判断是否相同
"""
if self.type == DataStruct.type and self.if_fq == DataStruct.if_fq:
return True
else:
return False | [
"判断是否相同"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L998-L1005 | [
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] | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | _quotation_base.splits | 将一个DataStruct按code分解为N个DataStruct | QUANTAXIS/QAData/base_datastruct.py | def splits(self):
"""
将一个DataStruct按code分解为N个DataStruct
"""
return list(map(lambda x: self.select_code(x), self.code)) | def splits(self):
"""
将一个DataStruct按code分解为N个DataStruct
"""
return list(map(lambda x: self.select_code(x), self.code)) | [
"将一个DataStruct按code分解为N个DataStruct"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1007-L1011 | [
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train | _quotation_base.add_func | QADATASTRUCT的指标/函数apply入口
Arguments:
func {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAData/base_datastruct.py | def add_func(self, func, *arg, **kwargs):
"""QADATASTRUCT的指标/函数apply入口
Arguments:
func {[type]} -- [description]
Returns:
[type] -- [description]
"""
return self.groupby(level=1, sort=False).apply(func, *arg, **kwargs) | def add_func(self, func, *arg, **kwargs):
"""QADATASTRUCT的指标/函数apply入口
Arguments:
func {[type]} -- [description]
Returns:
[type] -- [description]
"""
return self.groupby(level=1, sort=False).apply(func, *arg, **kwargs) | [
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"/",
"函数apply入口"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1029-L1039 | [
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train | _quotation_base.get_data | 获取不同格式的数据
Arguments:
columns {[type]} -- [description]
Keyword Arguments:
type {str} -- [description] (default: {'ndarray'})
with_index {bool} -- [description] (default: {False})
Returns:
[type] -- [description] | QUANTAXIS/QAData/base_datastruct.py | def get_data(self, columns, type='ndarray', with_index=False):
"""获取不同格式的数据
Arguments:
columns {[type]} -- [description]
Keyword Arguments:
type {str} -- [description] (default: {'ndarray'})
with_index {bool} -- [description] (default: {False})
Retu... | def get_data(self, columns, type='ndarray', with_index=False):
"""获取不同格式的数据
Arguments:
columns {[type]} -- [description]
Keyword Arguments:
type {str} -- [description] (default: {'ndarray'})
with_index {bool} -- [description] (default: {False})
Retu... | [
"获取不同格式的数据"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1052-L1081 | [
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train | _quotation_base.pivot | 增加对于多列的支持 | QUANTAXIS/QAData/base_datastruct.py | def pivot(self, column_):
"""增加对于多列的支持"""
if isinstance(column_, str):
try:
return self.data.reset_index().pivot(
index='datetime',
columns='code',
values=column_
)
except:
... | def pivot(self, column_):
"""增加对于多列的支持"""
if isinstance(column_, str):
try:
return self.data.reset_index().pivot(
index='datetime',
columns='code',
values=column_
)
except:
... | [
"增加对于多列的支持"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1083-L1110 | [
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train | _quotation_base.selects | 选择code,start,end
如果end不填写,默认获取到结尾
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pandas索引问题已经解决
... | QUANTAXIS/QAData/base_datastruct.py | def selects(self, code, start, end=None):
"""
选择code,start,end
如果end不填写,默认获取到结尾
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间... | def selects(self, code, start, end=None):
"""
选择code,start,end
如果end不填写,默认获取到结尾
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间... | [
"选择code",
"start",
"end"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1112-L1146 | [
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train | _quotation_base.select_time | 选择起始时间
如果end不填写,默认获取到结尾
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pandas索引问题已经解决
全部恢... | QUANTAXIS/QAData/base_datastruct.py | def select_time(self, start, end=None):
"""
选择起始时间
如果end不填写,默认获取到结尾
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,rais... | def select_time(self, start, end=None):
"""
选择起始时间
如果end不填写,默认获取到结尾
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,rais... | [
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"如果end不填写",
"默认获取到结尾"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1148-L1178 | [
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train | _quotation_base.select_day | 选取日期(一般用于分钟线)
Arguments:
day {[type]} -- [description]
Raises:
ValueError -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAData/base_datastruct.py | def select_day(self, day):
"""选取日期(一般用于分钟线)
Arguments:
day {[type]} -- [description]
Raises:
ValueError -- [description]
Returns:
[type] -- [description]
"""
def _select_day(day):
return self.data.loc[day, slice(None)]
... | def select_day(self, day):
"""选取日期(一般用于分钟线)
Arguments:
day {[type]} -- [description]
Raises:
ValueError -- [description]
Returns:
[type] -- [description]
"""
def _select_day(day):
return self.data.loc[day, slice(None)]
... | [
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train | _quotation_base.select_month | 选择月份
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pandas索引问题已经解决
全部恢复 | QUANTAXIS/QAData/base_datastruct.py | def select_month(self, month):
"""
选择月份
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pa... | def select_month(self, month):
"""
选择月份
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pa... | [
"选择月份"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1201-L1224 | [
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train | _quotation_base.select_code | 选择股票
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pandas索引问题已经解决
全部恢复 | QUANTAXIS/QAData/base_datastruct.py | def select_code(self, code):
"""
选择股票
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pand... | def select_code(self, code):
"""
选择股票
@2018/06/03 pandas 的索引问题导致
https://github.com/pandas-dev/pandas/issues/21299
因此先用set_index去重做一次index
影响的有selects,select_time,select_month,get_bar
@2018/06/04
当选择的时间越界/股票不存在,raise ValueError
@2018/06/04 pand... | [
"选择股票"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1226-L1249 | [
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train | _quotation_base.get_bar | 获取一个bar的数据
返回一个series
如果不存在,raise ValueError | QUANTAXIS/QAData/base_datastruct.py | def get_bar(self, code, time):
"""
获取一个bar的数据
返回一个series
如果不存在,raise ValueError
"""
try:
return self.data.loc[(pd.Timestamp(time), code)]
except:
raise ValueError(
'DATASTRUCT CURRENTLY CANNOT FIND THIS BAR WITH {} {}'.forma... | def get_bar(self, code, time):
"""
获取一个bar的数据
返回一个series
如果不存在,raise ValueError
"""
try:
return self.data.loc[(pd.Timestamp(time), code)]
except:
raise ValueError(
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] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAData/base_datastruct.py#L1264-L1278 | [
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"'DATA... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_SU_trans_stock_min | 将天软本地数据导入 QA 数据库
:param client:
:param ui_log:
:param ui_progress:
:param data_path: 存放天软数据的路径，默认文件名格式为类似 "SH600000.csv" 格式 | QUANTAXIS/QASU/trans_ss.py | def QA_SU_trans_stock_min(client=DATABASE, ui_log=None, ui_progress=None,
data_path: str = "D:\\skysoft\\", type_="1min"):
"""
将天软本地数据导入 QA 数据库
:param client:
:param ui_log:
:param ui_progress:
:param data_path: 存放天软数据的路径，默认文件名格式为类似 "SH600000.csv" 格式
"""
code_li... | def QA_SU_trans_stock_min(client=DATABASE, ui_log=None, ui_progress=None,
data_path: str = "D:\\skysoft\\", type_="1min"):
"""
将天软本地数据导入 QA 数据库
:param client:
:param ui_log:
:param ui_progress:
:param data_path: 存放天软数据的路径，默认文件名格式为类似 "SH600000.csv" 格式
"""
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train | get_best_ip_by_real_data_fetch | 用特定的数据获取函数测试数据获得的时间,从而选择下载数据最快的服务器ip
默认使用特定品种1min的方式的获取 | QUANTAXIS/QAFetch/QATdx.py | def get_best_ip_by_real_data_fetch(_type='stock'):
"""
用特定的数据获取函数测试数据获得的时间,从而选择下载数据最快的服务器ip
默认使用特定品种1min的方式的获取
"""
from QUANTAXIS.QAUtil.QADate import QA_util_today_str
import time
#找到前两天的有效交易日期
pre_trade_date=QA_util_get_real_date(QA_util_today_str())
pre_trade_date=QA_util_get... | def get_best_ip_by_real_data_fetch(_type='stock'):
"""
用特定的数据获取函数测试数据获得的时间,从而选择下载数据最快的服务器ip
默认使用特定品种1min的方式的获取
"""
from QUANTAXIS.QAUtil.QADate import QA_util_today_str
import time
#找到前两天的有效交易日期
pre_trade_date=QA_util_get_real_date(QA_util_today_str())
pre_trade_date=QA_util_get... | [
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"从而选择下载数据最快的服务器ip",
"默认使用特定品种1min的方式的获取"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L158-L206 | [
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train | get_ip_list_by_multi_process_ping | 根据ping排序返回可用的ip列表
2019 03 31 取消参数filename
:param ip_list: ip列表
:param n: 最多返回的ip数量， 当可用ip数量小于n，返回所有可用的ip；n=0时，返回所有可用ip
:param _type: ip类型
:return: 可以ping通的ip列表 | QUANTAXIS/QAFetch/QATdx.py | def get_ip_list_by_multi_process_ping(ip_list=[], n=0, _type='stock'):
''' 根据ping排序返回可用的ip列表
2019 03 31 取消参数filename
:param ip_list: ip列表
:param n: 最多返回的ip数量， 当可用ip数量小于n，返回所有可用的ip；n=0时，返回所有可用ip
:param _type: ip类型
:return: 可以ping通的ip列表
'''
cache = QA_util_cache()
results = cache.get(... | def get_ip_list_by_multi_process_ping(ip_list=[], n=0, _type='stock'):
''' 根据ping排序返回可用的ip列表
2019 03 31 取消参数filename
:param ip_list: ip列表
:param n: 最多返回的ip数量， 当可用ip数量小于n，返回所有可用的ip；n=0时，返回所有可用ip
:param _type: ip类型
:return: 可以ping通的ip列表
'''
cache = QA_util_cache()
results = cache.get(... | [
"根据ping排序返回可用的ip列表",
"2019",
"03",
"31",
"取消参数filename"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L208-L246 | [
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train | get_mainmarket_ip | [summary]
Arguments:
ip {[type]} -- [description]
port {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAFetch/QATdx.py | def get_mainmarket_ip(ip, port):
"""[summary]
Arguments:
ip {[type]} -- [description]
port {[type]} -- [description]
Returns:
[type] -- [description]
"""
global best_ip
if ip is None and port is None and best_ip['stock']['ip'] is None and best_ip['stock']['port'] is No... | def get_mainmarket_ip(ip, port):
"""[summary]
Arguments:
ip {[type]} -- [description]
port {[type]} -- [description]
Returns:
[type] -- [description]
"""
global best_ip
if ip is None and port is None and best_ip['stock']['ip'] is None and best_ip['stock']['port'] is No... | [
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train | QA_fetch_get_security_bars | 按bar长度推算数据
Arguments:
code {[type]} -- [description]
_type {[type]} -- [description]
lens {[type]} -- [description]
Keyword Arguments:
ip {[type]} -- [description] (default: {best_ip})
port {[type]} -- [description] (default: {7709})
Returns:
[type] -- [des... | QUANTAXIS/QAFetch/QATdx.py | def QA_fetch_get_security_bars(code, _type, lens, ip=None, port=None):
"""按bar长度推算数据
Arguments:
code {[type]} -- [description]
_type {[type]} -- [description]
lens {[type]} -- [description]
Keyword Arguments:
ip {[type]} -- [description] (default: {best_ip})
port {[... | def QA_fetch_get_security_bars(code, _type, lens, ip=None, port=None):
"""按bar长度推算数据
Arguments:
code {[type]} -- [description]
_type {[type]} -- [description]
lens {[type]} -- [description]
Keyword Arguments:
ip {[type]} -- [description] (default: {best_ip})
port {[... | [
"按bar长度推算数据"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L300-L333 | [
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train | QA_fetch_get_stock_day | 获取日线及以上级别的数据
Arguments:
code {str:6} -- code 是一个单独的code 6位长度的str
start_date {str:10} -- 10位长度的日期 比如'2017-01-01'
end_date {str:10} -- 10位长度的日期 比如'2018-01-01'
Keyword Arguments:
if_fq {str} -- '00'/'bfq' -- 不复权 '01'/'qfq' -- 前复权 '02'/'hfq' -- 后复权 '03'/'ddqfq' -- 定点前复权 '04'/'ddhf... | QUANTAXIS/QAFetch/QATdx.py | def QA_fetch_get_stock_day(code, start_date, end_date, if_fq='00', frequence='day', ip=None, port=None):
"""获取日线及以上级别的数据
Arguments:
code {str:6} -- code 是一个单独的code 6位长度的str
start_date {str:10} -- 10位长度的日期 比如'2017-01-01'
end_date {str:10} -- 10位长度的日期 比如'2018-01-01'
Keyword Argument... | def QA_fetch_get_stock_day(code, start_date, end_date, if_fq='00', frequence='day', ip=None, port=None):
"""获取日线及以上级别的数据
Arguments:
code {str:6} -- code 是一个单独的code 6位长度的str
start_date {str:10} -- 10位长度的日期 比如'2017-01-01'
end_date {str:10} -- 10位长度的日期 比如'2018-01-01'
Keyword Argument... | [
"获取日线及以上级别的数据"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L336-L409 | [
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train | for_sz | 深市代码分类
Arguments:
code {[type]} -- [description]
Returns:
[type] -- [description] | QUANTAXIS/QAFetch/QATdx.py | def for_sz(code):
"""深市代码分类
Arguments:
code {[type]} -- [description]
Returns:
[type] -- [description]
"""
if str(code)[0:2] in ['00', '30', '02']:
return 'stock_cn'
elif str(code)[0:2] in ['39']:
return 'index_cn'
elif str(code)[0:2] in ['15']:
ret... | def for_sz(code):
"""深市代码分类
Arguments:
code {[type]} -- [description]
Returns:
[type] -- [description]
"""
if str(code)[0:2] in ['00', '30', '02']:
return 'stock_cn'
elif str(code)[0:2] in ['39']:
return 'index_cn'
elif str(code)[0:2] in ['15']:
ret... | [
"深市代码分类"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L591-L617 | [
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train | QA_fetch_get_index_list | 获取指数列表
Keyword Arguments:
ip {[type]} -- [description] (default: {None})
port {[type]} -- [description] (default: {None})
Returns:
[type] -- [description] | QUANTAXIS/QAFetch/QATdx.py | def QA_fetch_get_index_list(ip=None, port=None):
"""获取指数列表
Keyword Arguments:
ip {[type]} -- [description] (default: {None})
port {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
ip, port = get_mainmarket_ip(ip, port)
api = TdxHq_API()
... | def QA_fetch_get_index_list(ip=None, port=None):
"""获取指数列表
Keyword Arguments:
ip {[type]} -- [description] (default: {None})
port {[type]} -- [description] (default: {None})
Returns:
[type] -- [description]
"""
ip, port = get_mainmarket_ip(ip, port)
api = TdxHq_API()
... | [
"获取指数列表"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L672-L697 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
train | QA_fetch_get_stock_transaction_realtime | 实时分笔成交 包含集合竞价 buyorsell 1--sell 0--buy 2--盘前 | QUANTAXIS/QAFetch/QATdx.py | def QA_fetch_get_stock_transaction_realtime(code, ip=None, port=None):
'实时分笔成交 包含集合竞价 buyorsell 1--sell 0--buy 2--盘前'
ip, port = get_mainmarket_ip(ip, port)
api = TdxHq_API()
try:
with api.connect(ip, port):
data = pd.DataFrame()
data = pd.concat([api.to_df(api.get_transa... | def QA_fetch_get_stock_transaction_realtime(code, ip=None, port=None):
'实时分笔成交 包含集合竞价 buyorsell 1--sell 0--buy 2--盘前'
ip, port = get_mainmarket_ip(ip, port)
api = TdxHq_API()
try:
with api.connect(ip, port):
data = pd.DataFrame()
data = pd.concat([api.to_df(api.get_transa... | [
"实时分笔成交",
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"buyorsell",
"1",
"--",
"sell",
"0",
"--",
"buy",
"2",
"--",
"盘前"
] | QUANTAXIS/QUANTAXIS | python | https://github.com/QUANTAXIS/QUANTAXIS/blob/bb1fe424e4108b62a1f712b81a05cf829297a5c0/QUANTAXIS/QAFetch/QATdx.py#L983-L1001 | [
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... | bb1fe424e4108b62a1f712b81a05cf829297a5c0 |
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