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dosangyoon
2022-05-25 13:13:36 +09:00
parent b199d683de
commit 74aaa33285
2 changed files with 16 additions and 23 deletions
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35
hts/BuySellChecker.py
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@@ -363,30 +363,23 @@ class BuySellChecker:
def analyze(self, result):
window = 5
open = result["open"]
close = result["close"]
high = result["high"]
low = result["low"]
vol = result["vol"]
open_list = open[:-window+1]
close_list = close[window-1:]
high_list = [max(high[i + window - 1:i + 2 * window - 1]) for i in range(len(high) - window + 1)]
low_list = [min(low[i + window - 1:i + 2 * window - 1]) for i in range(len(low) - window + 1)]
vol_list = [sum(vol[i + window - 1:i + 2 * window - 1]) for i in range(len(vol) - window + 1)]
close_df = pd.DataFrame(close_list)
avg5_list = close_df.rolling(window=5).mean().fillna(close_list[0]).values.tolist()
close_df = pd.DataFrame(close)
avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
avg5 = [item[0] for item in avg5_list]
avg10_list = close_df.rolling(window=10).mean().fillna(close_list[0]).values.tolist()
avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
avg10 = [item[0] for item in avg10_list]
avg30_list = close_df.rolling(window=30).mean().fillna(close_list[0]).values.tolist()
avg30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
avg30 = [item[0] for item in avg30_list]
avg60_list = close_df.rolling(window=60).mean().fillna(close_list[0]).values.tolist()
avg60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
avg60 = [item[0] for item in avg60_list]
df = pd.DataFrame(close_list)
df = pd.DataFrame(close)
max20 = df.rolling(window=10).mean()
stddev20 = df.rolling(window=10).std()
upper_df = max20 + (stddev20 * 2) # 상단 볼린저 밴드
@@ -394,9 +387,9 @@ class BuySellChecker:
upper, lower = [], []
for i in range(len(upper_df)):
if i < window:
upper.append(upper_df.values[window - 1][0])
lower.append(lower_df.values[window - 1][0])
if i < 10:
upper.append(upper_df.values[0][0])
lower.append(lower_df.values[0][0])
else:
upper.append(upper_df.values[i][0])
lower.append(lower_df.values[i][0])
@@ -404,8 +397,8 @@ class BuySellChecker:
point_temp = result["time"]
STOCK = []
for i in range(len(open_list)):
STOCK.append({'volume': vol_list[i], 'close': close_list[i], 'open': open_list[i], 'high': high_list[i], 'low': low_list[i],
for i in range(len(open)):
STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
'avg5': avg5[i],'avg10': avg10[i],'avg30': avg30[i],'avg60': avg60[i]})
# stochastic 계산
@@ -421,12 +414,12 @@ class BuySellChecker:
rsi = rsi_df['rsi'].values.tolist()
rsis = rsi_df['rsis'].values.tolist()
temp = {"date": point_temp[window-1:],
"open": open_list, "high": high_list, "low": low_list, "close": close_list, "volume": vol_list, "upper": upper, "lower": lower,
temp = {"date": point_temp,
"open": open, "high": high, "low": low, "close": close, "volume": vol, "upper": upper, "lower": lower,
"avg5": avg5, "avg10": avg10, "avg30": avg30, "avg60": avg60,
"fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d, "rsi": rsi, "rsis": rsis}
data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp[window-1:])
df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time
return data

4
stockpredictor/crawler/sQLite/Crawler.py
View File

@@ -44,9 +44,9 @@ metaCrawler.crawl_meterials(stockFileName)
print("\n[종목 다운로드]")
stockCrawler = StockCrawler(START_DATE)
#stockCrawler.crawl_etf_stocks(stockFileName)
#stockCrawler.crawl_stocks(stockFileName)
stockCrawler.crawl_us_stocks(stockFileName)
stockCrawler.crawl_etf_stocks(stockFileName)
stockCrawler.crawl_stocks(stockFileName)
print("\n[종목 분석]")