init
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dsyoon
193
Bithumb.py
193
Bithumb.py
@@ -422,6 +422,183 @@ class Bithumb(HTS):
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log_file.close()
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return False
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def notBuy(self, data, i):
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if i > 5:
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check = True
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for l in range(i-4, i+1):
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if (
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data['gradients_avg60'][l - 1] > data['gradients_avg60'][l] or
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data['gradients_avg20'][l - 1] > data['gradients_avg20'][l] or
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data['gradients_low'][l - 1] > data['gradients_low'][l]
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):
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check = False
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break
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if not check:
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return False
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return True
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def checkWithEnvelope(self, data, analyzed_day=120, isRealTime=False):
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bsLine = {}
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size = len(data["close"])
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bsLine['buy'] = [-1 for i in range(size)]
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bsLine['buy_weight'] = [-1 for i in range(size)]
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bsLine['sell'] = [-1 for i in range(size)]
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bsLine['sell_weight'] = [-1 for i in range(size)]
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gap_interval = analyzed_day
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gap_state = False
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for i in range(size):
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if isRealTime:
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if i < size - 1:
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continue
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if i > 10:
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# 만약 전일 저가와 오늘 종의 차이가 1만원이 넘으면 향후 60일은 분석하지 않는다.
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if data['high'][i] < int(data['low'][i - 1] * 0.7):
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gap_state = True
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gap_interval -= 1
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continue
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if gap_state:
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if gap_interval <= 0:
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gap_state = False
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gap_interval = 60
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else:
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gap_interval -= 1
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continue
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if data['disparity'][i] < 2:
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check = True
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for l in range(i - 3, i):
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if (
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data['gradients_avg60'][l - 1] > data['gradients_avg60'][l] or
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data['gradients_avg20'][l - 1] > data['gradients_avg20'][l] or
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data['gradients_low'][l - 1] > data['gradients_low'][l] or
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data['disparity_avg5'][l - 1] > data['disparity_avg5'][l] or
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data['disparity'][l - 1] < data['disparity'][l]
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):
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check = False
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break
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if check and 99 < sum(data['disparity_avg5'][i - 4:i + 1]) / 5 < 100 and 99 < sum(
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data['disparity_avg60'][i - 4:i + 1]) / 5 < 100:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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check = True
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for l in range(i - 2, i):
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if (
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data['gradients_avg60'][l - 1] > data['gradients_avg60'][l] or
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data['gradients_low'][l - 1] > data['gradients_low'][l]
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):
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check = False
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break
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if (
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check and
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-0.0011 < data['gradients_low'][i] < 0 and -0.007 < data['gradients_avg5'][i] < 0.001 and
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-0.0012 < data['gradients_avg60'][i] < 0 and
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98.90 < data['disparity_avg5'][i] < 101
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):
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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check = True
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for l in range(i - 6, i):
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if (
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data['gradients_avg60'][l - 1] < data['gradients_avg60'][l] or
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data['gradients_avg20'][l - 1] < data['gradients_avg20'][l] or
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data['gradients_low'][l - 1] < data['gradients_low'][l] or
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-0.039 < data['gradients_low'][l - 1] < -0.35 or
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-0.05 < data['gradients_avg20'][l - 1] < -0.30 or
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-0.40 < data['gradients_avg60'][l - 1] < -0.30
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):
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check = False
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break
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if check and 99 < min(data['disparity_avg5'][i - 6:i]) < max(data['disparity_avg5'][i - 6:i]) < 101:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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check = True
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for l in range(i - 3, i):
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if (
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data['gradients_low'][l - 1] < data['gradients_low'][l] or
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data['gradients_avg60'][l - 1] < data['gradients_avg60'][l] or
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data['gradients_avg20'][l - 1] < data['gradients_avg20'][l] or
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0.01 < data['gradients_low'][l - 1] < 0.21 or
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-0.09 < data['gradients_avg20'][l - 1] < -0.002 or
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0.01 < data['gradients_avg60'][l - 1] < 0.021
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):
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check = False
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break
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if check:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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if (data['disparity'][i] < 5 and 99.0 < data['disparity_avg60'][i] < 99.1 and
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-0.009 < data['gradients_avg60'][i] < -0.008 and 0.015 < data['gradients_avg20'][i] < 0.016 and
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-0.006 < data['gradients_avg5'][i] < -0.005 and -0.009 < data['gradients_low'][i] < -0.008):
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check = True
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for l in range(i - 5, i):
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if (
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data['gradients_avg60'][l - 1] > data['gradients_avg60'][l] or
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data['gradients_low'][l - 1] > data['gradients_low'][l] or
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data['disparity'][l - 1] < data['disparity'][l]
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):
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check = False
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break
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if check:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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if data['macd'][i] < -4000:
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if data['macd'][i - 1] < data['macd'][i]:
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if not self.notBuy(data, i) and data['slow_k'][i] < 30:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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# macd 이전에 없던 바닥인 경우 상승할 찰나 매수
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if data['macds'][i - 1] < min(data['macds'][:i - 1]):
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if data['macds'][i - 1] < data['macds'][i]:
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if not self.notBuy(data, i) and data['slow_k'][i] < 30:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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if (
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98 < data['disparity_avg5'][i] < 100 and data['disparity_avg20'][i] < 93.5 and
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data['disparity_avg60'][i] < 89 and
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-0.014 < data['gradients_avg60'][i] < -0.013 and -0.03 < data['gradients_avg20'][
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i] < -0.02 and -0.014 < data['gradients_low'][i] < -0.013 and
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data['slow_k'][i] < 11
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):
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if not self.notBuy(data, i):
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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if data['slow_k'][i] < 20 and data['slow_k'][i - 1] < data['slow_d'][i - 1] and data['slow_d'][i] < \
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data['slow_k'][i]:
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buy = data['low'][i]
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data['buy'][i] = buy
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bsLine['buy'][i] = buy
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bsLine['buy_weight'][i] = 30
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return bsLine, data
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def buyRealTime(self, ticker, isRealTime=False):
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stock = {"CODE": ticker, "NAME": ticker, "PRICE": []}
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@@ -441,16 +618,16 @@ class Bithumb(HTS):
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# 분석일 데이터만 활용한다 (이전 데이터는 제거)
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data.drop(data.index[:len(data) - analyzed_day], inplace=True)
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bsLine, data = self.buySellChecker.checkWithEnvelope(data, analyzed_day, isRealTime=isRealTime)
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bsLine, data = self.checkWithEnvelope(data, analyzed_day, isRealTime=isRealTime)
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# 그래프를 그린다.
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if len(data.index) > 10:
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today = datetime.today().strftime('%Y%m%d')
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log_filename = os.path.join(RESOURCE_PATH, 'analysis', 'bithumb', today + '.log')
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if not isRealTime and not self.exist_buy(ticker, log_filename):
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if isRealTime and not self.exist_buy(ticker, log_filename):
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if max(bsLine['buy'][len(bsLine['buy']) - 2:]) > 100:
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balance = self.getBalance(ticker)
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count = int(balance * (bsLine['buy_weight'][len(bsLine['buy_weight'])-1]/100))
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count = round((balance * (bsLine['buy_weight'][len(bsLine['buy_weight'])-1]/100)) / bsLine['buy'][len(bsLine['buy'])-1], 2)
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order = self.bithumb.buy_limit_order(ticker, bsLine['buy'][len(bsLine['buy'])-1], count)
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# order: ('bid', 'BTC', 'C0101000000322993432', 'KRW')
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@@ -477,7 +654,13 @@ if __name__ == "__main__":
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bithumb = Bithumb(RESOURCE_PATH)
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tickers = ['XRP', 'BTC', 'SOL']
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while True:
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isRealTime = False
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if isRealTime:
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while True:
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for ticker in tickers:
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print(ticker, datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
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bithumb.buyRealTime(ticker, isRealTime)
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else:
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for ticker in tickers:
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print(ticker, datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
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bithumb.buyRealTime(ticker, isRealTime=False)
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bithumb.buyRealTime(ticker, isRealTime)
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