init
This commit is contained in:
dsyoon
29
monitor.py
29
monitor.py
@@ -151,6 +151,29 @@ class Monitor:
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# ------------- Strategy -------------
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def buy_ticker(self, symbol: str, data: pd.DataFrame) -> bool:
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try:
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check_5_week_lowest = False
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# 5주봉이 20주봉이나 40주봉보다 아래에 있는지 체크
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try:
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# Convert hourly data to week-based rolling periods (5, 20, 40 weeks)
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hours_in_week = 24 * 7 # 168 hours
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period_5w = 5 * hours_in_week # 840 hours
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period_20w = 20 * hours_in_week # 3,360 hours
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period_40w = 40 * hours_in_week # 6,720 hours
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if len(data) >= period_40w:
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wma5 = data['Close'].rolling(window=period_5w).mean().iloc[-1]
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wma20 = data['Close'].rolling(window=period_20w).mean().iloc[-1]
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wma40 = data['Close'].rolling(window=period_40w).mean().iloc[-1]
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# 5-week MA is the lowest among 5, 20, 40 week MAs
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if (wma5 < wma20) and (wma5 < wma40):
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check_5_week_lowest = True
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except Exception:
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# Ignore errors in MA calculation so as not to block trading logic
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pass
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current_time = datetime.now()
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if data['buy_signal'].iloc[-1] == 'fall_6p':
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if data['Close'].iloc[-1] > 100:
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@@ -184,6 +207,10 @@ class Monitor:
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else:
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buy_amount = 50000
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if data['buy_signal'].iloc[-1] in ['movingaverage', 'deviation40', 'deviation240', 'deviation1440']:
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if check_5_week_lowest:
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buy_amount *= 2
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_ = self.hts.buyCoinMarket(symbol, buy_amount)
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if self.cooldown_file is not None:
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@@ -390,7 +417,7 @@ class Monitor:
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cursor.execute(
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"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
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+ symbol
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+ " order by ymdhms desc limit 5000) subquery order by datetime"
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+ " order by ymdhms desc limit 7000) subquery order by datetime"
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)
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result = cursor.fetchall()
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conn.commit()
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118
monitor_coin.py
118
monitor_coin.py
@@ -1,10 +1,5 @@
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import pandas as pd
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from dateutil.relativedelta import relativedelta
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from datetime import datetime
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import sqlite3
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import time
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import requests
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import json
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from config import *
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from monitor import Monitor
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@@ -15,119 +10,6 @@ class MonitorCoin (Monitor):
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def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
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super().__init__(cooldown_file)
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# ------------- Data fetch -------------
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def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
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for attempt in range(retries):
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try:
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if to is None:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
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else:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
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headers = {"accept": "application/json"}
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response = requests.get(url, headers=headers)
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json_data = json.loads(response.text)
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df_temp = pd.DataFrame(json_data)
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df_temp = df_temp.sort_index(ascending=False)
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if 'candle_date_time_kst' not in df_temp:
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return None
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data = pd.DataFrame()
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data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
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data['Open'] = df_temp['opening_price']
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data['Close'] = df_temp['trade_price']
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data['High'] = df_temp['high_price']
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data['Low'] = df_temp['low_price']
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data['Volume'] = df_temp['candle_acc_trade_volume']
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data = data.set_index('datetime')
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data = data.astype(float)
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data["datetime"] = data.index
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if not data.empty:
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return data
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print(f"No data received for {symbol}, attempt {attempt + 1}")
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time.sleep(0.5)
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except Exception as e:
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print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
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if attempt < retries - 1:
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time.sleep(5)
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continue
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return None
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def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
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to = datetime.now()
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data: pd.DataFrame | None = None
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while data is None or len(data) < bong_count:
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if data is None:
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data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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else:
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previous_count = len(data)
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df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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data = pd.concat([data, df], ignore_index=True)
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if previous_count == len(data):
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break
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time.sleep(0.3)
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to = to - relativedelta(minutes=interval * 200)
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data = data.set_index('datetime')
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
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data["datetime"] = data.index
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return data
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def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
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conn = sqlite3.connect('coins.db')
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cursor = conn.cursor()
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for i in range(1, len(data)):
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cursor.execute(
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"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
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(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
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)
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arr = cursor.fetchone()
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if not arr:
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cursor.execute(
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"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
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(
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interval,
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symbol,
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KR_COINS[symbol],
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data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
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data['datetime'].iloc[-i].strftime('%Y%m%d'),
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data['datetime'].iloc[-i].strftime('%H%M%S'),
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data['Close'].iloc[-i],
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data['Open'].iloc[-i],
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data['High'].iloc[-i],
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data['Low'].iloc[-i],
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data['Volume'].iloc[-i],
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),
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)
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else:
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break
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cursor.execute(
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"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
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+ symbol
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+ " order by ymdhms desc limit 5000) subquery order by datetime"
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)
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result = cursor.fetchall()
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conn.commit()
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cursor.close()
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conn.close()
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df = pd.DataFrame(result)
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df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
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df = df.set_index('datetime')
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df = df.sort_index()
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df['datetime'] = df.index
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return df
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def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
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data = self.get_coin_data(symbol, interval)
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data_1 = self.get_coin_data(symbol, interval=1)
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data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
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saved_data = self.get_coin_saved_data(symbol, interval, data)
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data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
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data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
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data = data.set_index('datetime')
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
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data["datetime"] = data.index
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return data
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def monitor_coins(self) -> None:
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print("[{}] KRW COINs: {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), ','.join(KR_COINS.keys())))
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for symbol in KR_COINS:
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@@ -1,10 +1,5 @@
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import pandas as pd
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from dateutil.relativedelta import relativedelta
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from datetime import datetime
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import sqlite3
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import time
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import requests
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import json
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from config import *
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from monitor import Monitor
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@@ -15,119 +10,6 @@ class MonitorCoin (Monitor):
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def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
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super().__init__(cooldown_file)
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# ------------- Data fetch -------------
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def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
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for attempt in range(retries):
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try:
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if to is None:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
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else:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
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headers = {"accept": "application/json"}
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response = requests.get(url, headers=headers)
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json_data = json.loads(response.text)
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df_temp = pd.DataFrame(json_data)
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df_temp = df_temp.sort_index(ascending=False)
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if 'candle_date_time_kst' not in df_temp:
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return None
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data = pd.DataFrame()
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data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
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data['Open'] = df_temp['opening_price']
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data['Close'] = df_temp['trade_price']
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data['High'] = df_temp['high_price']
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data['Low'] = df_temp['low_price']
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data['Volume'] = df_temp['candle_acc_trade_volume']
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data = data.set_index('datetime')
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data = data.astype(float)
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data["datetime"] = data.index
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if not data.empty:
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return data
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print(f"No data received for {symbol}, attempt {attempt + 1}")
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time.sleep(0.5)
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except Exception as e:
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print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
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if attempt < retries - 1:
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time.sleep(5)
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continue
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return None
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def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
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to = datetime.now()
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data: pd.DataFrame | None = None
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while data is None or len(data) < bong_count:
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if data is None:
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data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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else:
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previous_count = len(data)
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df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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data = pd.concat([data, df], ignore_index=True)
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if previous_count == len(data):
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break
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time.sleep(0.3)
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to = to - relativedelta(minutes=interval * 200)
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data = data.set_index('datetime')
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
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data["datetime"] = data.index
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return data
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def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
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conn = sqlite3.connect('coins.db')
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cursor = conn.cursor()
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for i in range(1, len(data)):
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cursor.execute(
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"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
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(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
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)
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arr = cursor.fetchone()
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if not arr:
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cursor.execute(
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"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
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(
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interval,
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symbol,
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KR_COINS_1[symbol],
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data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
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data['datetime'].iloc[-i].strftime('%Y%m%d'),
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data['datetime'].iloc[-i].strftime('%H%M%S'),
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data['Close'].iloc[-i],
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data['Open'].iloc[-i],
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data['High'].iloc[-i],
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data['Low'].iloc[-i],
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data['Volume'].iloc[-i],
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),
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)
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else:
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break
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cursor.execute(
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"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
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+ symbol
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+ " order by ymdhms desc limit 5000) subquery order by datetime"
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)
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result = cursor.fetchall()
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conn.commit()
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cursor.close()
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conn.close()
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df = pd.DataFrame(result)
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df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
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df = df.set_index('datetime')
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df = df.sort_index()
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df['datetime'] = df.index
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return df
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def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
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data = self.get_coin_data(symbol, interval)
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data_1 = self.get_coin_data(symbol, interval=1)
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data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
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saved_data = self.get_coin_saved_data(symbol, interval, data)
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data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
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data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
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data = data.set_index('datetime')
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
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data["datetime"] = data.index
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return data
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def monitor_coins(self) -> None:
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for symbol in KR_COINS_1:
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print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
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@@ -1,10 +1,5 @@
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import pandas as pd
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from dateutil.relativedelta import relativedelta
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from datetime import datetime
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import sqlite3
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import time
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import requests
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import json
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from config import *
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from monitor import Monitor
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@@ -15,119 +10,6 @@ class MonitorCoin (Monitor):
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def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
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super().__init__(cooldown_file)
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# ------------- Data fetch -------------
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def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
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for attempt in range(retries):
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try:
|
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if to is None:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
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else:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
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headers = {"accept": "application/json"}
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response = requests.get(url, headers=headers)
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json_data = json.loads(response.text)
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df_temp = pd.DataFrame(json_data)
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df_temp = df_temp.sort_index(ascending=False)
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if 'candle_date_time_kst' not in df_temp:
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return None
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data = pd.DataFrame()
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data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
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data['Open'] = df_temp['opening_price']
|
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data['Close'] = df_temp['trade_price']
|
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data['High'] = df_temp['high_price']
|
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data['Low'] = df_temp['low_price']
|
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data['Volume'] = df_temp['candle_acc_trade_volume']
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data = data.set_index('datetime')
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data = data.astype(float)
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data["datetime"] = data.index
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if not data.empty:
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return data
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print(f"No data received for {symbol}, attempt {attempt + 1}")
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time.sleep(0.5)
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except Exception as e:
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print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
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if attempt < retries - 1:
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time.sleep(5)
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continue
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return None
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|
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def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
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to = datetime.now()
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data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
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if data is None:
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data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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else:
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previous_count = len(data)
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df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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data = pd.concat([data, df], ignore_index=True)
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if previous_count == len(data):
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break
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time.sleep(0.3)
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to = to - relativedelta(minutes=interval * 200)
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data = data.set_index('datetime')
|
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
|
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data["datetime"] = data.index
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return data
|
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|
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def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
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conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
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interval,
|
||||
symbol,
|
||||
KR_COINS_2[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self) -> None:
|
||||
for symbol in KR_COINS_2:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
@@ -1,10 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
@@ -15,119 +10,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS_3[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self) -> None:
|
||||
for symbol in KR_COINS_3:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
@@ -1,10 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
@@ -15,119 +10,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS_4[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self) -> None:
|
||||
for symbol in KR_COINS_4:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -15,119 +15,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
import pandas as pd
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime
|
||||
import sqlite3
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
from config import *
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
@@ -15,119 +9,6 @@ class MonitorCoin (Monitor):
|
||||
def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
|
||||
super().__init__(cooldown_file)
|
||||
|
||||
# ------------- Data fetch -------------
|
||||
def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
data = pd.DataFrame()
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
if not data.empty:
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
|
||||
to = datetime.now()
|
||||
data: pd.DataFrame | None = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
previous_count = len(data)
|
||||
df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if previous_count == len(data):
|
||||
break
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
|
||||
conn = sqlite3.connect('coins.db')
|
||||
cursor = conn.cursor()
|
||||
for i in range(1, len(data)):
|
||||
cursor.execute(
|
||||
"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
|
||||
(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
|
||||
)
|
||||
arr = cursor.fetchone()
|
||||
if not arr:
|
||||
cursor.execute(
|
||||
"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
|
||||
(
|
||||
interval,
|
||||
symbol,
|
||||
KR_COINS[symbol],
|
||||
data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
|
||||
data['datetime'].iloc[-i].strftime('%Y%m%d'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
|
||||
data['Close'].iloc[-i],
|
||||
data['Open'].iloc[-i],
|
||||
data['High'].iloc[-i],
|
||||
data['Low'].iloc[-i],
|
||||
data['Volume'].iloc[-i],
|
||||
),
|
||||
)
|
||||
else:
|
||||
break
|
||||
cursor.execute(
|
||||
"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
|
||||
+ symbol
|
||||
+ " order by ymdhms desc limit 5000) subquery order by datetime"
|
||||
)
|
||||
result = cursor.fetchall()
|
||||
conn.commit()
|
||||
cursor.close()
|
||||
conn.close()
|
||||
df = pd.DataFrame(result)
|
||||
df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
|
||||
df = df.set_index('datetime')
|
||||
df = df.sort_index()
|
||||
df['datetime'] = df.index
|
||||
return df
|
||||
|
||||
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
|
||||
data = self.get_coin_data(symbol, interval)
|
||||
data_1 = self.get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
saved_data = self.get_coin_saved_data(symbol, interval, data)
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
return data
|
||||
|
||||
def monitor_coins(self, symbol) -> None:
|
||||
print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))
|
||||
|
||||
|
||||
@@ -1,535 +0,0 @@
|
||||
import yfinance as yf
|
||||
import pandas as pd
|
||||
from datetime import datetime, timedelta
|
||||
import telegram
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
import asyncio
|
||||
from multiprocessing import Pool
|
||||
import schedule
|
||||
from config import *
|
||||
import FinanceDataReader as fdr
|
||||
|
||||
|
||||
def send_coin_msg(text):
|
||||
coin_client = telegram.Bot(token=COIN_TELEGRAM_BOT_TOKEN)
|
||||
asyncio.run(coin_client.send_message(chat_id=COIN_TELEGRAM_CHAT_ID, text=text))
|
||||
return
|
||||
|
||||
|
||||
def send_coin_telegram_message(message_list, header):
|
||||
pStr = header + "\n"
|
||||
for i, message in enumerate(message_list):
|
||||
pStr += message
|
||||
|
||||
if i + 1 % 20 == 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, [pStr])
|
||||
pStr = ''
|
||||
|
||||
if len(message_list) % 20 != 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, [pStr])
|
||||
|
||||
return
|
||||
|
||||
|
||||
def send_stock_msg(text):
|
||||
stock_client = telegram.Bot(token=STOCK_TELEGRAM_BOT_TOKEN)
|
||||
asyncio.run(stock_client.send_message(chat_id=STOCK_TELEGRAM_CHAT_ID, text=text))
|
||||
return
|
||||
|
||||
|
||||
def send_stock_telegram_message(message_list, header):
|
||||
pStr = header + "\n"
|
||||
for i, message in enumerate(message_list):
|
||||
pStr += message
|
||||
|
||||
if i + 1 % 20 == 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_stock_msg, [pStr])
|
||||
pStr = ''
|
||||
|
||||
if len(message_list) % 20 != 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_stock_msg, [pStr])
|
||||
|
||||
return
|
||||
|
||||
|
||||
def calculate_bollinger_bands(data):
|
||||
data['MA'] = data['Close'].rolling(window=BOLLINGER_PERIOD).mean()
|
||||
data['STD'] = data['Close'].rolling(window=BOLLINGER_PERIOD).std()
|
||||
data['Upper'] = data['MA'] + (BOLLINGER_STD * data['STD'])
|
||||
data['Lower'] = data['MA'] - (BOLLINGER_STD * data['STD'])
|
||||
return data
|
||||
|
||||
|
||||
def calculate_technical_indicators(data):
|
||||
# 볼린저 밴드 계산
|
||||
data = calculate_bollinger_bands(data)
|
||||
|
||||
# RSI 계산 (14일 기준)
|
||||
delta = data['Close'].diff()
|
||||
gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
|
||||
loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
|
||||
rs = gain / loss
|
||||
data['RSI'] = 100 - (100 / (1 + rs))
|
||||
|
||||
# MACD 계산
|
||||
exp1 = data['Close'].ewm(span=12, adjust=False).mean()
|
||||
exp2 = data['Close'].ewm(span=26, adjust=False).mean()
|
||||
data['MACD'] = exp1 - exp2
|
||||
data['Signal'] = data['MACD'].ewm(span=9, adjust=False).mean()
|
||||
|
||||
# 이동평균선
|
||||
data['MA5'] = data['Close'].rolling(window=5).mean()
|
||||
data['MA20'] = data['Close'].rolling(window=20).mean()
|
||||
data['MA40'] = data['Close'].rolling(window=40).mean()
|
||||
data['MA60'] = data['Close'].rolling(window=60).mean()
|
||||
|
||||
# 거래량 이동평균
|
||||
data['Volume_MA5'] = data['Volume'].rolling(window=5).mean()
|
||||
|
||||
return data
|
||||
|
||||
|
||||
def check_ma_alert(symbol, data, interval=0):
|
||||
"""1시간봉 기준 이동평균선 조건 알림
|
||||
- 5봉 이동평균(MA5) 상승
|
||||
- 20봉 이동평균(MA20) 상승
|
||||
- 40봉 이동평균(MA40)이 하락세에서 상승세로 전환되는 시점 (직전 기울기 < 0 and 현재 기울기 ≥ 0)
|
||||
"""
|
||||
# 40 이동평균선의 기울기를 계산하기 위해 최소 41개 캔들이 필요합니다.
|
||||
if len(data) < 41:
|
||||
return None
|
||||
|
||||
# 이동평균선 값 추출
|
||||
ma5_current, ma5_prev = data['MA5'].iloc[-1], data['MA5'].iloc[-2]
|
||||
ma20_current, ma20_prev = data['MA20'].iloc[-1], data['MA20'].iloc[-2]
|
||||
ma40_current = data['MA40'].iloc[-1]
|
||||
ma40_prev1, ma40_prev2 = data['MA40'].iloc[-2], data['MA40'].iloc[-3]
|
||||
|
||||
# 조건 계산
|
||||
up5 = ma5_current > ma5_prev
|
||||
up20 = ma20_current > ma20_prev
|
||||
slope_prev = ma40_prev1 - ma40_prev2 # 직전 기울기 (음수: 하락)
|
||||
slope_now = ma40_current - ma40_prev1 # 현재 기울기
|
||||
turning = (slope_prev < 0) and (slope_now >= 0)
|
||||
|
||||
alert = up5 and up20 and turning
|
||||
|
||||
return {
|
||||
'symbol': symbol,
|
||||
'price': data['Close'].iloc[-1],
|
||||
'alert': alert,
|
||||
'details': {
|
||||
'interval': interval,
|
||||
'up5': up5,
|
||||
'up20': up20,
|
||||
'ma40_turning': turning
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
def check_buy_signals(symbol, data):
|
||||
if len(data) < 60: # 최소 60일치 데이터 필요
|
||||
return None
|
||||
|
||||
latest = data.iloc[-1]
|
||||
prev = data.iloc[-2]
|
||||
|
||||
# 볼린저 밴드 신호
|
||||
bb_signal = False
|
||||
if isinstance(latest['Upper'], float):
|
||||
upper_band = latest['Upper']
|
||||
lower_band = latest['Lower']
|
||||
current_price = latest['Close']
|
||||
else:
|
||||
upper_band = latest['Upper'].iloc[0]
|
||||
lower_band = latest['Lower'].iloc[0]
|
||||
current_price = latest['Close'].iloc[0]
|
||||
|
||||
distance = (current_price - lower_band) / (upper_band - lower_band)
|
||||
bb_signal = distance < BOLLINGER_THRESHOLD
|
||||
|
||||
# U자 반등 후 이전 고점 돌파 여부 계산 (BREAKOUT)
|
||||
breakout_signal = False
|
||||
if len(data) >= max(BREAKOUT_LOOKBACK, BREAKOUT_WEEK_LOOKBACK) + 1:
|
||||
# ① U자 형태 확인
|
||||
window_close = data['Close'].iloc[-BREAKOUT_LOOKBACK - 1:-1]
|
||||
prev_high = window_close.max()
|
||||
prev_low = window_close.min()
|
||||
|
||||
# ② 1주일(42캔들) 전 가격 대비 5% 이상 상승하지 않았는지 체크
|
||||
price_week_ago = data['Close'].iloc[-BREAKOUT_WEEK_LOOKBACK - 1]
|
||||
if price_week_ago > 0:
|
||||
week_change = (current_price - price_week_ago) / price_week_ago
|
||||
else:
|
||||
week_change = 1 # 값이 0이면 조건 불충족 처리
|
||||
|
||||
# ③ 조건 종합: U자+돌파 && 주간 상승률 ≤ 5%
|
||||
if (
|
||||
prev_high > 0 and (prev_high - prev_low) / prev_high > BUY_THRESHOLD and current_price > prev_high
|
||||
and week_change <= BREAKOUT_WEEK_LIMIT
|
||||
):
|
||||
breakout_signal = True
|
||||
|
||||
# 장기간 저항선 돌파 여부 계산 (LONG RESISTANCE BREAKOUT)
|
||||
long_breakout_signal = False
|
||||
if len(data) >= RESISTANCE_LOOKBACK + 1:
|
||||
resistance_level = data['Close'].iloc[-RESISTANCE_LOOKBACK - 1:-1].max()
|
||||
previous_closes = data['Close'].iloc[-RESISTANCE_LOOKBACK - 1:-1]
|
||||
# 과거 구간에서 저항선 이상으로 종가가 한번도 올라가지 않은 경우 + 현재 가격이 저항선 돌파
|
||||
if (previous_closes <= resistance_level * (1 + RESISTANCE_BREAK_THRESHOLD)).all() and \
|
||||
current_price > resistance_level * (1 + RESISTANCE_BREAK_THRESHOLD):
|
||||
long_breakout_signal = True
|
||||
|
||||
# RSI 과매도 신호 (RSI < 30)
|
||||
if not isinstance(latest['Upper'], float):
|
||||
rsi_signal = latest['RSI'].iloc[0] < 30
|
||||
|
||||
# MACD 신호 (MACD가 시그널 라인을 상향 돌파)
|
||||
macd_signal = (prev['MACD'].iloc[0] < prev['Signal'].iloc[0]) and (
|
||||
latest['MACD'].iloc[0] > latest['Signal'].iloc[0])
|
||||
|
||||
# 이동평균선 골든크로스 임박 또는 발생
|
||||
ma_signal = (prev['MA5'].iloc[0] < prev['MA20'].iloc[0]) and (latest['MA5'].iloc[0] >= latest['MA20'].iloc[0])
|
||||
|
||||
# 거래량 증가 신호 (5일 평균 대비 150% 이상)
|
||||
volume_signal = latest['Volume'].iloc[0] > (latest['Volume_MA5'].iloc[0] * 1.5)
|
||||
|
||||
# 종합 신호
|
||||
buy_signals = {
|
||||
'bb_signal': bb_signal,
|
||||
'rsi_signal': rsi_signal,
|
||||
'macd_signal': macd_signal,
|
||||
'ma_signal': ma_signal,
|
||||
'volume_signal': volume_signal,
|
||||
'breakout_signal': breakout_signal,
|
||||
'long_breakout_signal': long_breakout_signal
|
||||
}
|
||||
|
||||
# 최소 3개 이상의 신호가 동시에 발생할 때 매수 신호로 간주
|
||||
signal_count = sum(1 for signal in buy_signals.values() if signal)
|
||||
|
||||
return {
|
||||
'symbol': symbol,
|
||||
'price': current_price,
|
||||
'lower_band': lower_band,
|
||||
'distance': distance,
|
||||
'rsi': latest['RSI'].iloc[0],
|
||||
'macd': latest['MACD'].iloc[0],
|
||||
'signal_line': latest['Signal'].iloc[0],
|
||||
'buy_signals': buy_signals,
|
||||
'signal_count': signal_count,
|
||||
'buy': long_breakout_signal or breakout_signal or (
|
||||
(bb_signal and rsi_signal) or (signal_count >= 2 and (bb_signal or rsi_signal)))
|
||||
}
|
||||
else:
|
||||
rsi_signal = latest['RSI'] < 30
|
||||
|
||||
# MACD 신호 (MACD가 시그널 라인을 상향 돌파)
|
||||
macd_signal = (prev['MACD'] < prev['Signal']) and (latest['MACD'] > latest['Signal'])
|
||||
|
||||
# 이동평균선 골든크로스 임박 또는 발생
|
||||
ma_signal = (prev['MA5'] < prev['MA20']) and (latest['MA5'] >= latest['MA20'])
|
||||
|
||||
# 거래량 증가 신호 (5일 평균 대비 150% 이상)
|
||||
volume_signal = latest['Volume'] > (latest['Volume_MA5'] * 1.5)
|
||||
|
||||
# 종합 신호
|
||||
buy_signals = {
|
||||
'bb_signal': bb_signal,
|
||||
'rsi_signal': rsi_signal,
|
||||
'macd_signal': macd_signal,
|
||||
'ma_signal': ma_signal,
|
||||
'volume_signal': volume_signal,
|
||||
'breakout_signal': breakout_signal,
|
||||
'long_breakout_signal': long_breakout_signal
|
||||
}
|
||||
|
||||
# 최소 3개 이상의 신호가 동시에 발생할 때 매수 신호로 간주
|
||||
signal_count = sum(1 for signal in buy_signals.values() if signal)
|
||||
|
||||
return {
|
||||
'symbol': symbol,
|
||||
'price': current_price,
|
||||
'lower_band': lower_band,
|
||||
'distance': distance,
|
||||
'rsi': latest['RSI'],
|
||||
'macd': latest['MACD'],
|
||||
'signal_line': latest['Signal'],
|
||||
'buy_signals': buy_signals,
|
||||
'signal_count': signal_count,
|
||||
'buy': long_breakout_signal or breakout_signal or (
|
||||
(bb_signal and rsi_signal) or (signal_count >= 2 and (bb_signal or rsi_signal)))
|
||||
}
|
||||
|
||||
|
||||
def format_message(info, market_type):
|
||||
message = ""
|
||||
if info['buy']:
|
||||
message += '🛒 '
|
||||
|
||||
message += f"[{market_type}] {info['name']} ({info['symbol']}) "
|
||||
message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.2f}, "
|
||||
|
||||
# 매수 신호 상세 정보
|
||||
count = 0
|
||||
if any(info['buy_signals'].values()):
|
||||
message += "📊신호 ({count}):"
|
||||
if info['buy_signals']['bb_signal']:
|
||||
message += "- 볼린저 밴드 하단 근접 (근접도: {:.1f}%),".format(info['distance'] * 100)
|
||||
count += 1
|
||||
if info['buy_signals']['rsi_signal']:
|
||||
message += f"- RSI 과매도 구간 (RSI: {info['rsi']:.1f}),"
|
||||
count += 1
|
||||
if info['buy_signals']['macd_signal']:
|
||||
message += "- MACD 골든크로스,"
|
||||
count += 1
|
||||
if info['buy_signals']['ma_signal']:
|
||||
message += "- 이동평균선 골든크로스,"
|
||||
count += 1
|
||||
if info['buy_signals']['volume_signal']:
|
||||
message += "- 거래량 급증"
|
||||
count += 1
|
||||
if info['buy_signals'].get('breakout_signal'):
|
||||
message += "- U자 반등 돌파"
|
||||
count += 1
|
||||
if info['buy_signals'].get('long_breakout_signal'):
|
||||
message += "- 장기 저항 돌파"
|
||||
count += 1
|
||||
message += "\n"
|
||||
message = message.replace("{count}", str(count))
|
||||
return message
|
||||
|
||||
|
||||
def format_ma_message(info, market_type):
|
||||
"""MA 알림 메시지 생성"""
|
||||
prefix = '📈 ' if info.get('alert') else ''
|
||||
message = prefix + f"[{market_type}] {info['name']} ({info['symbol']}) "
|
||||
message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.2f} \n"
|
||||
return message
|
||||
|
||||
|
||||
def get_coin_data(symbol, interval=240, retries=3):
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
url = "https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=3000".format(interval, symbol)
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
|
||||
data = pd.DataFrame()
|
||||
# data.columns = ['datetime', 'open', 'close', 'high', 'low', 'volume']
|
||||
# data['datetime'] = pd.to_datetime(data_temp['candle_date_time_kst'])
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
|
||||
if not data.empty:
|
||||
return data
|
||||
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
|
||||
def get_kr_stock_data(symbol, retries=3):
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
end = datetime.now()
|
||||
start = end - timedelta(days=300)
|
||||
|
||||
# FinanceDataReader를 사용하여 한국 주식 데이터 가져오기
|
||||
data = fdr.DataReader(symbol, start.strftime('%Y-%m-%d'), end.strftime('%Y-%m-%d'))
|
||||
|
||||
if not data.empty:
|
||||
# FinanceDataReader의 컬럼명을 yfinance 형식으로 변환
|
||||
data = data.rename(columns={
|
||||
'Open': 'Open',
|
||||
'High': 'High',
|
||||
'Low': 'Low',
|
||||
'Close': 'Close',
|
||||
'Volume': 'Volume'
|
||||
})
|
||||
return data
|
||||
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(2)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
|
||||
def monitor_us_stocks():
|
||||
message_list = []
|
||||
print("US Stocks {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in US_STOCKS:
|
||||
data = get_kr_stock_data(symbol)
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
info = check_ma_alert(symbol, data, 0)
|
||||
if info is None:
|
||||
continue
|
||||
info['name'] = US_STOCKS[symbol]
|
||||
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']}")
|
||||
|
||||
if info['alert']:
|
||||
message_list.append(format_ma_message(info, 'US'))
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
time.sleep(0.5)
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_stock_telegram_message(message_list, header="[US-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def monitor_kr_stocks():
|
||||
message_list = []
|
||||
print("KR ETFs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in KR_ETFS:
|
||||
try:
|
||||
# .KS 접미사 제거
|
||||
clean_symbol = symbol.replace('.KS', '')
|
||||
data = get_kr_stock_data(clean_symbol)
|
||||
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
info = check_ma_alert(symbol, data, 0)
|
||||
if info is None:
|
||||
continue
|
||||
info['name'] = KR_ETFS[symbol]
|
||||
print(f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']}")
|
||||
|
||||
if info['alert']:
|
||||
message_list.append(format_ma_message(info, 'KR'))
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
else:
|
||||
print(f"Data for {symbol} is empty or None.")
|
||||
|
||||
# 각 심볼 처리 후 1초 대기
|
||||
time.sleep(1)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Unexpected error processing {symbol}: {str(e)}")
|
||||
continue
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_stock_telegram_message(message_list, header="[KR-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def monitor_coins():
|
||||
message_list = []
|
||||
print("KRW COINs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in KR_COINS:
|
||||
# 1시간
|
||||
interval = 60
|
||||
data = get_coin_data(symbol, interval=interval)
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
info = check_ma_alert(symbol, data, interval)
|
||||
if info is None:
|
||||
continue
|
||||
info['name'] = KR_COINS[symbol]
|
||||
print(
|
||||
f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']} ({info['details']['interval']})")
|
||||
|
||||
if info['alert']:
|
||||
message_list.append(format_ma_message(info, 'KR'))
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
else:
|
||||
print(f"Data for {symbol} is empty or None.")
|
||||
time.sleep(0.5)
|
||||
|
||||
# 4시간
|
||||
interval = 240
|
||||
data = get_coin_data(symbol, interval=interval)
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
info = check_ma_alert(symbol, data, interval)
|
||||
if info is None:
|
||||
continue
|
||||
info['name'] = KR_COINS[symbol]
|
||||
print(
|
||||
f" - {info['name']} ({symbol}): {info['price']:.2f} -> {info['alert']} ({info['details']['interval']})")
|
||||
|
||||
if info['alert']:
|
||||
message_list.append(format_ma_message(info, 'KR'))
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
else:
|
||||
print(f"Data for {symbol} is empty or None.")
|
||||
time.sleep(0.5)
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_coin_telegram_message(message_list, header="[KRW-COIN]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def run_schedule():
|
||||
# 코인 모니터링 스케줄 (매시간 1분, 11분, 21분, 31분, 41분, 51분)
|
||||
for minute in [4, 14, 24, 34, 44, 54]:
|
||||
schedule.every().hour.at(f":{minute:02d}").do(monitor_coins)
|
||||
|
||||
# 미국 주식 모니터링 스케줄 (매일 저녁 5시 20분)
|
||||
schedule.every().day.at("16:30").do(monitor_us_stocks)
|
||||
schedule.every().day.at("23:30").do(monitor_us_stocks)
|
||||
schedule.every().day.at("05:10").do(monitor_us_stocks)
|
||||
|
||||
# 한국 ETF 모니터링 스케줄 (매일 오전 8시)
|
||||
schedule.every().day.at("18:20").do(monitor_kr_stocks)
|
||||
schedule.every().day.at("07:10").do(monitor_kr_stocks)
|
||||
|
||||
print("Scheduler started. Monitoring will run at specified times.")
|
||||
while True:
|
||||
schedule.run_pending()
|
||||
time.sleep(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_schedule()
|
||||
@@ -1,460 +0,0 @@
|
||||
import pandas as pd
|
||||
from HTS2 import HTS
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime, timedelta
|
||||
import telegram
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
import asyncio
|
||||
from multiprocessing import Pool
|
||||
import schedule
|
||||
from config import *
|
||||
import FinanceDataReader as fdr
|
||||
import numpy as np
|
||||
|
||||
hts = HTS()
|
||||
|
||||
def send_coin_msg(text):
|
||||
coin_client = telegram.Bot(token=COIN_TELEGRAM_BOT_TOKEN)
|
||||
asyncio.run(coin_client.send_message(chat_id=COIN_TELEGRAM_CHAT_ID, text=text))
|
||||
return
|
||||
|
||||
|
||||
def send_coin_telegram_message(message_list, header):
|
||||
pStr = header + "\n"
|
||||
for i, message in enumerate(message_list):
|
||||
pStr += message
|
||||
|
||||
if i + 1 % 20 == 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, [pStr])
|
||||
pStr = ''
|
||||
|
||||
if len(message_list) % 20 != 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, [pStr])
|
||||
|
||||
return
|
||||
|
||||
def buy_ticker(symbole, data):
|
||||
try:
|
||||
BUY_AMOUNT = 5000
|
||||
|
||||
if data['buy_signal'].iloc[-1] == 'movingaverage':
|
||||
BUY_AMOUNT = 50000
|
||||
elif data['buy_signal'].iloc[-1] == 'deviation40':
|
||||
BUY_AMOUNT = 6000
|
||||
elif data['buy_signal'].iloc[-1] == 'deviation240':
|
||||
BUY_AMOUNT = 5000
|
||||
|
||||
_ = hts.buyCoinMarket(symbole, BUY_AMOUNT)
|
||||
except Exception as e:
|
||||
print(f"Error buying {symbole}: {str(e)}")
|
||||
return
|
||||
|
||||
|
||||
|
||||
def send_stock_msg(text):
|
||||
stock_client = telegram.Bot(token=STOCK_TELEGRAM_BOT_TOKEN)
|
||||
asyncio.run(stock_client.send_message(chat_id=STOCK_TELEGRAM_CHAT_ID, text=text))
|
||||
return
|
||||
|
||||
|
||||
def send_stock_telegram_message(message_list, header):
|
||||
pStr = header + "\n"
|
||||
for i, message in enumerate(message_list):
|
||||
pStr += message
|
||||
|
||||
if i + 1 % 20 == 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_stock_msg, [pStr])
|
||||
pStr = ''
|
||||
|
||||
if len(message_list) % 20 != 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_stock_msg, [pStr])
|
||||
|
||||
return
|
||||
|
||||
|
||||
def normalize_data(data):
|
||||
"""데이터 정규화 함수 - 모든 코인에 동일하게 적용"""
|
||||
# Min-Max 정규화를 위한 컬럼
|
||||
columns_to_normalize = ['Open', 'High', 'Low', 'Close', 'Volume']
|
||||
|
||||
normalized_data = data.copy()
|
||||
|
||||
# 각 컬럼별 정규화 (20일 롤링 윈도우 사용)
|
||||
for column in columns_to_normalize:
|
||||
min_val = data[column].rolling(window=20).min()
|
||||
max_val = data[column].rolling(window=20).max()
|
||||
# 0으로 나누기 방지
|
||||
denominator = max_val - min_val
|
||||
normalized_data[f'{column}_Norm'] = np.where(
|
||||
denominator != 0,
|
||||
(data[column] - min_val) / denominator,
|
||||
0.5 # 기본값 설정
|
||||
)
|
||||
|
||||
return normalized_data
|
||||
|
||||
def calculate_technical_indicators(data):
|
||||
"""기술적 지표 계산 - 모든 코인에 동일하게 적용"""
|
||||
# 데이터 정규화
|
||||
data = normalize_data(data)
|
||||
|
||||
# 이동평균선 계산
|
||||
data['MA5'] = data['Close'].rolling(window=5).mean()
|
||||
data['MA20'] = data['Close'].rolling(window=20).mean()
|
||||
data['MA40'] = data['Close'].rolling(window=40).mean()
|
||||
data['MA120'] = data['Close'].rolling(window=120).mean()
|
||||
data['MA200'] = data['Close'].rolling(window=200).mean()
|
||||
data['MA240'] = data['Close'].rolling(window=240).mean()
|
||||
data['MA720'] = data['Close'].rolling(window=720).mean()
|
||||
data['MA1440'] = data['Close'].rolling(window=1440).mean()
|
||||
|
||||
# --- 이격도(Deviation) 계산 ---
|
||||
data['Deviation5'] = (data['Close'] / data['MA5']) * 100
|
||||
data['Deviation20'] = (data['Close'] / data['MA20']) * 100
|
||||
data['Deviation40'] = (data['Close'] / data['MA40']) * 100
|
||||
data['Deviation120'] = (data['Close'] / data['MA120']) * 100
|
||||
data['Deviation200'] = (data['Close'] / data['MA200']) * 100
|
||||
data['Deviation240'] = (data['Close'] / data['MA240']) * 100
|
||||
data['Deviation720'] = (data['Close'] / data['MA720']) * 100
|
||||
data['Deviation1440'] = (data['Close'] / data['MA1440']) * 100
|
||||
|
||||
# 매수 타이밍을 이동평균선으로 결정
|
||||
# 골든크로스: 단기 이동평균선이 장기 이동평균선을 상향 돌파할 때 매수
|
||||
data['golden_cross'] = (data['MA5'] > data['MA20']) & (data['MA5'].shift(1) <= data['MA20'].shift(1))
|
||||
|
||||
# 볼린저 밴드 계산
|
||||
data['MA'] = data['Close'].rolling(window=20).mean()
|
||||
data['STD'] = data['Close'].rolling(window=20).std()
|
||||
data['Upper'] = data['MA'] + (2 * data['STD'])
|
||||
data['Lower'] = data['MA'] - (2 * data['STD'])
|
||||
|
||||
return data
|
||||
|
||||
def check_buy_point(data, simulation=None):
|
||||
|
||||
"""
|
||||
# 매수 포인트 탐지 및 표시
|
||||
if simulation:
|
||||
recent_data = data
|
||||
else:
|
||||
# recent_data의 복사본 생성
|
||||
recent_data = data.tail(10).copy()
|
||||
|
||||
# 'buy_point' 열 초기화
|
||||
recent_data['buy_point'] = 0
|
||||
|
||||
# FutureWarning 해결
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
# 코드 계속
|
||||
for i in range(1, len(recent_data)):
|
||||
if all(recent_data[f'MA{n}'].iloc[i] < recent_data['MA720'].iloc[i] for n in [5, 20, 40, 120, 200, 240]) and \
|
||||
all(recent_data[f'MA{n}'].iloc[i] > recent_data[f'MA{n}'].iloc[i-1] for n in [5, 20, 40, 120, 200, 240]) and \
|
||||
recent_data['MA720'].iloc[i] < recent_data['MA1440'].iloc[i]:
|
||||
recent_data.at[recent_data.index[i], 'buy_point'] = 1
|
||||
|
||||
if not simulation:
|
||||
if recent_data['buy_point'][-10:-1].sum() > 0:
|
||||
recent_data.at[recent_data.index[-1], 'buy_point'] = 1
|
||||
|
||||
return recent_data
|
||||
"""
|
||||
|
||||
# 매수 포인트 탐지 및 표시
|
||||
# 'buy_point' 열 초기화
|
||||
data['buy_signal'] = ''
|
||||
data['buy_point'] = 0
|
||||
|
||||
# FutureWarning 해결
|
||||
if data['buy_point'].iloc[-1] != 1:
|
||||
# 코드 계속
|
||||
for i in range(1, len(data)):
|
||||
# 이동평균선 기반 매수 조건
|
||||
if all(data[f'MA{n}'].iloc[i] < data['MA720'].iloc[i] for n in [5, 20, 40, 120, 200, 240]) and \
|
||||
all(data[f'MA{n}'].iloc[i] > data[f'MA{n}'].iloc[i - 1] for n in [5, 20, 40, 120, 200, 240]) and \
|
||||
data['MA720'].iloc[i] < data['MA1440'].iloc[i]:
|
||||
data.at[data.index[i], 'buy_signal'] = 'movingaverage'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-10:-1].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'movingaverage'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
# Deviation40(이격도 40) 기반 매수 조건: 90 이하에서 상승 전환
|
||||
if data['Deviation40'].iloc[i - 1] < data['Deviation40'].iloc[i] and data['Deviation40'].iloc[i - 1] <= 90:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation40'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-10:-1].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation40'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
# Deviation240(이격도 240) 기반 매수 조건: 90 이하에서 상승 전환
|
||||
if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 90:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation240'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-10:-1].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation240'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
return data
|
||||
|
||||
def format_message(market_type, symbol, symbol_name, close, buy_signal):
|
||||
message = f"매수 [{market_type}] {symbol_name} ({symbol}): {buy_signal} "
|
||||
message += f"현재가: {'$' if market_type == 'US' else '₩'}{close:.2f}, "
|
||||
return message
|
||||
|
||||
|
||||
def format_ma_message(info, market_type):
|
||||
"""MA 알림 메시지 생성"""
|
||||
prefix = '상승 ' if info.get('alert') else ''
|
||||
message = prefix + f"[{market_type}] {info['name']} ({info['symbol']}) "
|
||||
message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.2f} \n"
|
||||
return message
|
||||
|
||||
|
||||
def get_coin_data(symbol, interval=240, to=None, retries=3):
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
#url = "https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=3000".format(interval, symbol)
|
||||
if to is None:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
|
||||
else:
|
||||
url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
|
||||
|
||||
|
||||
#url = 'https://api.bithumb.com/v1/candles/minutes/60?market=KRW-ADA&count=200'
|
||||
#url = 'https://api.bithumb.com/v1/candles/minutes/minutes/60?market=KRW-ADA&count=200&to=2025-08-06 10:38:38'
|
||||
headers = {"accept": "application/json"}
|
||||
response = requests.get(url, headers=headers)
|
||||
json_data = json.loads(response.text)
|
||||
df_temp = pd.DataFrame(json_data)
|
||||
df_temp = df_temp.sort_index(ascending=False)
|
||||
if 'candle_date_time_kst' not in df_temp:
|
||||
return None
|
||||
|
||||
data = pd.DataFrame()
|
||||
# data.columns = ['datetime', 'open', 'close', 'high', 'low', 'volume']
|
||||
# data['datetime'] = pd.to_datetime(data_temp['candle_date_time_kst'])
|
||||
data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
|
||||
data['Open'] = df_temp['opening_price']
|
||||
data['Close'] = df_temp['trade_price']
|
||||
data['High'] = df_temp['high_price']
|
||||
data['Low'] = df_temp['low_price']
|
||||
data['Volume'] = df_temp['candle_acc_trade_volume']
|
||||
data = data.set_index('datetime')
|
||||
data = data.astype(float)
|
||||
data["datetime"] = data.index
|
||||
|
||||
if not data.empty:
|
||||
return data
|
||||
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(0.5)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
def get_coin_more_data(symbol, interval, bong_count=3000):
|
||||
# 코인 데이터 1500개 봉 가져오기
|
||||
to = datetime.now()
|
||||
data = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
df = get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
time.sleep(0.3)
|
||||
to = to - relativedelta(minutes=interval * 200)
|
||||
|
||||
data = data.set_index('datetime')
|
||||
data = data.sort_index()
|
||||
data = data.drop_duplicates(keep='first')
|
||||
data["datetime"] = data.index
|
||||
# 코인 데이터 1500개 봉 가져오기
|
||||
|
||||
return data
|
||||
|
||||
|
||||
def get_kr_stock_data(symbol, retries=3):
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
end = datetime.now()
|
||||
start = end - timedelta(days=300)
|
||||
|
||||
# FinanceDataReader를 사용하여 한국 주식 데이터 가져오기
|
||||
data = fdr.DataReader(symbol, start.strftime('%Y-%m-%d'), end.strftime('%Y-%m-%d'))
|
||||
|
||||
if not data.empty:
|
||||
# FinanceDataReader의 컬럼명을 yfinance 형식으로 변환
|
||||
data = data.rename(columns={
|
||||
'Open': 'Open',
|
||||
'High': 'High',
|
||||
'Low': 'Low',
|
||||
'Close': 'Close',
|
||||
'Volume': 'Volume'
|
||||
})
|
||||
return data
|
||||
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(2)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
|
||||
def monitor_us_stocks():
|
||||
message_list = []
|
||||
print("US Stocks {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in US_STOCKS:
|
||||
data = get_kr_stock_data(symbol)
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
recent_data = check_buy_point(data) # Changed to check_buy_point
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
continue
|
||||
print(f" - {US_STOCKS[symbol]} ({symbol}): {recent_data['Close'][-1]:.2f}")
|
||||
message_list.append(format_message('US', symbol, US_STOCKS[symbol], recent_data['Close'][-1], recent_data['buy_signal'][-1]))
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
time.sleep(0.5)
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_stock_telegram_message(message_list, header="[US-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def monitor_kr_stocks():
|
||||
message_list = []
|
||||
print("KR ETFs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in KR_ETFS:
|
||||
try:
|
||||
# .KS 접미사 제거
|
||||
clean_symbol = symbol.replace('.KS', '')
|
||||
data = get_kr_stock_data(clean_symbol)
|
||||
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
recent_data = check_buy_point(data) # Changed to check_buy_point
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
continue
|
||||
print(f" - {KR_ETFS[symbol]} ({symbol}): {recent_data['Close'][-1]:.2f}")
|
||||
message_list.append(format_message('KR', symbol, US_STOCKS[symbol], recent_data['Close'][-1]))
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
else:
|
||||
print(f"Data for {symbol} is empty or None.")
|
||||
|
||||
# 각 심볼 처리 후 1초 대기
|
||||
time.sleep(1)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Unexpected error processing {symbol}: {str(e)}")
|
||||
continue
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_stock_telegram_message(message_list, header="[KR-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def monitor_coins():
|
||||
message_list = []
|
||||
print("KRW COINs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in KR_COINS:
|
||||
|
||||
# 1시간
|
||||
interval = 60
|
||||
data = get_coin_more_data(symbol, interval)
|
||||
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
recent_data = check_buy_point(data) # Changed to check_buy_point
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
continue
|
||||
print(f" - {KR_ETFS[symbol]} ({symbol}): {recent_data['Close'][-1]:.2f}")
|
||||
message_list.append(format_message('COIN', symbol, US_STOCKS[symbol], recent_data['Close'][-1], recent_data['buy_signal'][-1]))
|
||||
|
||||
# buy
|
||||
buy_ticker(symbol, recent_data)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
else:
|
||||
print(f"Data for {symbol} is empty or None.")
|
||||
time.sleep(0.5)
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
# send message
|
||||
send_coin_telegram_message(message_list, header="[KRW-COIN]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
# ----------------------
|
||||
# Turnaround Detector v6
|
||||
# ----------------------
|
||||
|
||||
def detect_turnaround_signal(symbol, data, interval=0, params=None):
|
||||
if len(data) < 7:
|
||||
return None
|
||||
|
||||
# 이동평균을 기반으로 매수 신호 결정
|
||||
cur = data.iloc[-1]
|
||||
prev = data.iloc[-2]
|
||||
|
||||
return None
|
||||
|
||||
def run_schedule():
|
||||
|
||||
# 코인 모니터링 스케줄 (매시간 1분, 11분, 21분, 31분, 41분, 51분)
|
||||
for minute in [4, 14, 24, 34, 44, 54]:
|
||||
schedule.every().hour.at(f":{minute:02d}").do(monitor_coins)
|
||||
|
||||
# 미국 주식 모니터링 스케줄 (매일 저녁 5시 20분)
|
||||
schedule.every().day.at("16:30").do(monitor_us_stocks)
|
||||
schedule.every().day.at("23:30").do(monitor_us_stocks)
|
||||
schedule.every().day.at("05:10").do(monitor_us_stocks)
|
||||
|
||||
# 한국 ETF 모니터링 스케줄 (매일 오전 8시)
|
||||
schedule.every().day.at("18:20").do(monitor_kr_stocks)
|
||||
schedule.every().day.at("07:10").do(monitor_kr_stocks)
|
||||
|
||||
print("Scheduler started. Monitoring will run at specified times.")
|
||||
while True:
|
||||
schedule.run_pending()
|
||||
time.sleep(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_schedule()
|
||||
#monitor_coins()
|
||||
Reference in New Issue
Block a user