import time
import hmac
import hashlib
import base64
import urllib.parse
import requests
import json
import numpy as np
import pandas as pd
from datetime import datetime
def send_dingtalk_message(webhook, secret, message):
timestamp = str(round(time.time() * 1000))
secret_enc = secret.encode('utf-8')
string_to_sign = '{}\n{}'.format(timestamp, secret)
string_to_sign_enc = string_to_sign.encode('utf-8')
hmac_code = hmac.new(secret_enc, string_to_sign_enc, digestmod=hashlib.sha256).digest()
sign = urllib.parse.quote_plus(base64.b64encode(hmac_code))
webhook = '{}×tamp={}&sign={}'.format(webhook, timestamp, sign)
headers = {'Content-Type': 'application/json'}
data = {"msgtype": "text", "text": {"content": message}}
response = requests.post(url=webhook, headers=headers, data=json.dumps(data))
print(response.text)
def read_events_from_file(filename="events.txt"):
try:
with open(filename, "r") as file:
return [line.strip() for line in file.readlines()]
except FileNotFoundError:
return []
def save_events_to_file(events, filename="events.txt"):
with open(filename, "w") as file:
for event in events:
file.write(str(event) + "\n")
def get_klines(symbol, interval, limit=100):
url = "https://fapi.binance.com/fapi/v1/klines"
params = {'symbol': symbol, 'interval': interval, 'limit': limit}
response = requests.get(url, params=params)
return response.json()
def calculate_ema(prices, period):
return pd.Series(prices).ewm(span=period, adjust=False).mean().tolist()
def calculate_macd(prices, fast_period, slow_period, signal_period):
ema_fast = calculate_ema(prices, fast_period)
ema_slow = calculate_ema(prices, slow_period)
macd = np.subtract(ema_fast[-len(ema_slow):], ema_slow)
signal = calculate_ema(macd, signal_period)
return macd, signal
def find_crossovers(macd, signal, times, prices, ema5, ema30):
crosses = []
min_length = min(len(macd), len(signal))
last_valid_time = datetime.min
for i in range(1, min_length):
closing_price = prices[i]
ema5_price = ema5[i]
ema30_price = ema30[i]
current_time = times[i]
cross_time = datetime.utcfromtimestamp(current_time / 1000 + 8*3600)
time_diff = (cross_time - last_valid_time).total_seconds() / 60
confidence_msg = ""
if macd[i-1] < signal[i-1] and macd[i] > signal[i] and closing_price > ema5_price:
if time_diff >= 30 or last_valid_time == datetime.min:
if closing_price > ema5_price and closing_price > ema30_price:
confidence_msg = "放心做吧"
crosses.append((i, 'Gold', cross_time.strftime('%Y-%m-%d %H:%M:%S'), '有效', confidence_msg))
last_valid_time = cross_time
else:
crosses.append((i, 'Gold', cross_time.strftime('%Y-%m-%d %H:%M:%S'), '无效', ""))
elif macd[i-1] > signal[i-1] and macd[i] < signal[i] and closing_price < ema5_price:
if time_diff >= 30 or last_valid_time == datetime.min:
if closing_price < ema5_price and closing_price < ema30_price:
confidence_msg = "放心做吧"
crosses.append((i, 'Dead', cross_time.strftime('%Y-%m-%d %H:%M:%S'), '有效', confidence_msg))
last_valid_time = cross_time
else:
crosses.append((i, 'Dead', cross_time.strftime('%Y-%m-%d %H:%M:%S'), '无效', ""))
return crosses
def main():
symbol = 'BTCUSDT'
interval = '5m'
limit = 500
klines = get_klines(symbol, interval, limit)
prices = [float(kline[4]) for kline in klines]
times = [int(kline[0]) for kline in klines]
ema5 = calculate_ema(prices, 5)
ema30 = calculate_ema(prices, 30)
macd, signal = calculate_macd(prices, 6, 7, 4)
crossovers = find_crossovers(macd, signal, times, prices, ema5, ema30)
# 这一段是新增的,用来处理事件的存储和钉钉消息发送
existing_events = read_events_from_file("events.txt")
new_events = [event for event in crossovers if str(event) not in existing_events]
webhook_url = "https://oapi.dingtalk.com/robot/send?access_token=8a6ddcf98d3b47c63333580bfe9d0bad55b17272eea05cc9c0af7f7be4de070d"
secret = "你的秘钥"
if new_events:
save_events_to_file(crossovers, "events.txt") # 保存所有当前识别的事件,而不仅仅是新事件
for event in new_events:
message = " 穿越".join(map(str, event))
send_dingtalk_message(webhook_url, secret, message) # 确保替换 YOUR_WEBHOOK_URL 和 YOUR_SECRET
if __name__ == '__main__':
while True:
main()
time.sleep(5)
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