We Keep Coding

I want build a alert for ema indicator crypto in a special list

First one:
### configuration details
TELEGRAM_TOKEN = '' # telegram bot token
TELEGRAM_CHANNEL ='' # channel id
INTERVAL = '1m' # binance time interval
SHORT_EMA = 7 # short interval for ema
LONG_EMA = 21 # long interval for ema
Here is my second code:
import requests
import talib
import time
import numpy as np
import websocket
from config import TELEGRAM_TOKEN, TELEGRAM_CHANNEL , INTERVAL, SHORT_EMA , LONG_EMA
def streamKline(currency, interval):
websocket.enableTrace(False)
socket = f'wss://stream.binance.com:9443/ws/{currency}#kline_{interval}'
ws = websocket.WebSocketApp(socket)
ws.run_forever()
#SYMBOLS TO LOOK FOR ALERTS
SYMBOLS = [
"ETHUSDT",
"BTCUSDT",
"ATOMUSDT",
"BNBUSDT",
"FTMBUSD",
"ENJUSDT",
"WAXPUSDT"
]
#sending alerts to telegram
def send_message(message):
url = "https://api.telegram.org/bot{}/sendMessage?chat_id={}&text={}&parse_mode=markdown".format(TELEGRAM_TOKEN,TELEGRAM_CHANNEL,message)
res = requests.get(url);print(url);
return res
# getting klines data to process
def streamKline(symbol):
data = socket.streamKline(symbol=symbol,interval=INTERVAL,limit=300) # more data means more precision but at the trade off between speed and time
return_data = []
# taking closing data for each kline
for each in data:
return_data.append(float(each[4])) # 4 is the index of the closing data in each kline
return np.array(return_data) # returning as numpy array for better precision and performance
def main():
# making a infinite loop that keeps checking for condition
while True:
#looping through each coin
for each in SYMBOLS:
data = streamKline(each)
ema_short = talib.EMA(data,int(SHORT_EMA))
ema_long = talib.EMA(data,int(LONG_EMA))
last_ema_short = ema_short[-2]
last_ema_long = ema_long[-2]
ema_short = ema_short[-1]
ema_long = ema_long[-1]
# conditions for alerts
if(ema_short > ema_long and last_ema_short < last_ema_long):
message = each + "bullcoming "+ str(SHORT_EMA) + " over "+str(LONG_EMA);print(each ,"alert came");
send_message(message);
time.sleep(0.5);
# calling the function
if __name__ == "__main__":
main()
The part of config is all settle done, just second for the kline data, the error mention lot like this.
data = socket.streamKline(symbol=symbol,interval=INTERVAL,limit=300) # more data means more precision but at the
trade off between speed and time
NameError: name 'socket' is not defined
I just don't know how to do it, I want build a ema alert that can give me a message when I am not watching chart, through this way seems not work, I have tried many times, and also find many video but still, I am just an beginner, nothing improving at all.

Read multiple DS18B20 temperature sensors faster using Raspberry Pi

My custom sensor dashboard requests new readings every second.
This worked well, until I hooked up 3 DS18B20 temperature sensors (1-wire protocol, so all on 1 pin), which each take 750ms to provide new data.
This is the class I currently use to read the temperature of each sensor:
# ds18b20.py
# written by Roger Woollett
import os
import glob
import time
class DS18B20:
# much of this code is lifted from Adafruit web site
# This class can be used to access one or more DS18B20 temperature sensors
# It uses OS supplied drivers and one wire support must be enabled
# To do this add the line
# dtoverlay=w1-gpio
# to the end of /boot/config.txt
#
# The DS18B20 has three pins, looking at the flat side with the pins pointing
# down pin 1 is on the left
# connect pin 1 to GPIO ground
# connect pin 2 to GPIO 4 *and* GPIO 3.3V via a 4k8 (4800 ohm) pullup resistor
# connect pin 3 to GPIO 3.3V
# You can connect more than one sensor to the same set of pins
# Only one pullup resistor is required
def __init__(self):
# Load required kernel modules
os.system('modprobe w1-gpio')
os.system('modprobe w1-therm')
# Find file names for the sensor(s)
base_dir = '/sys/bus/w1/devices/'
device_folder = glob.glob(base_dir + '28*')
self._num_devices = len(device_folder)
self._device_file = list()
i = 0
while i < self._num_devices:
self._device_file.append(device_folder[i] + '/w1_slave')
i += 1
def _read_temp(self, index):
# Issue one read to one sensor
# You should not call this directly
# First check if this index exists
if index >= len(self._device_file):
return False
f = open(self._device_file[index], 'r')
data = f.read()
f.close()
return data
def tempC(self, index=0):
# Call this to get the temperature in degrees C
# detected by a sensor
data = self._read_temp(index)
retries = 0
# Check for error
if data == False:
return None
while (not "YES" in data) and (retries > 0):
# Read failed so try again
time.sleep(0.1)
#print('Read Failed', retries)
data = self._read_temp(index)
retries -= 1
if (retries == 0) and (not "YES" in data):
return None
(discard, sep, reading) = data.partition(' t=')
if reading == 85000:
# 85ºC is the boot temperature of the sensor, so ignore that value
return None
temperature = float(reading) / 1000.0
return temperature
def device_count(self):
# Call this to see how many sensors have been detected
return self._num_devices
I already tried to return the previous temperature reading if the current one isn't finished yet, however this didn't reduce the time it took to read a sensor, so I guess the only way is to do things asynchronously.
I could reduce the precision to reduce the time it takes per reading, but ideally I would read all of the sensors simultaneously on separate threads.
How can I best implement this? Or are there other ways to improve the reading speed of multiple DS18B20 sensors?
Thanks for any insights!

You're facing some limitations introduced by the Linux kernel driver. If you were interacting with the OneWire protocol directly, you would only have a single 750ms read cycle for all three sensors, rather than (3 * 750ms). When speaking the 1-wire protocol directly, you can issue a single "convert temperature" command to all devices on the bus, as described here, and then read all the sensors.
The Linux driver explicitly doesn't support this mode of operation:
If none of the devices are parasite powered it would be possible to convert all the devices at the same time and then go back to read individual sensors. That isn’t currently supported. The driver also doesn’t support reduced precision (which would also reduce the conversion time) when reading values.
That means you're stuck with a 750ms per device read cycle. Your best option is probably placing the sensor reading code in a separate thread, e.g.:
import glob
import threading
import time
# Note that we're inheriting from threading.Thread here;
# see https://docs.python.org/3/library/threading.html
# for more information.
class DS18B20(threading.Thread):
default_base_dir = "/sys/bus/w1/devices/"
def __init__(self, base_dir=None):
super().__init__()
self._base_dir = base_dir if base_dir else self.default_base_dir
self.daemon = True
self.discover()
def discover(self):
device_folder = glob.glob(self._base_dir + "28*")
self._num_devices = len(device_folder)
self._device_file: list[str] = []
for i in range(self._num_devices):
self._device_file.append(device_folder[i] + "/w1_slave")
self._values: list[float | None] = [None] * self._num_devices
self._times: list[float] = [0.0] * self._num_devices
def run(self):
"""Thread entrypoint: read sensors in a loop.
Calling DS18B20.start() will cause this method to run in
a separate thread.
"""
while True:
for dev in range(self._num_devices):
self._read_temp(dev)
# Adjust this value as you see fit, noting that you will never
# read actual sensor values more often than 750ms * self._num_devices.
time.sleep(1)
def _read_temp(self, index):
for i in range(3):
with open(self._device_file[index], "r") as f:
data = f.read()
if "YES" not in data:
time.sleep(0.1)
continue
disacard, sep, reading = data.partition(" t=")
temp = float(reading) / 1000.0
self._values[index] = temp
self._times[index] = time.time()
break
else:
print(f"failed to read device {index}")
def tempC(self, index=0):
return self._values[index]
def device_count(self):
"""Return the number of discovered devices"""
return self._num_devices
Because this is a thread, you need to .start() it first, so your
code would look something like:
d = DS18B20()
d.start()
while True:
for i in range(d.device_count()):
print(f'dev {i}: {d.tempC(i)}')
time.sleep(0.5)
You can call the tempC method as often as you want, because it's
just return a value from the _values array. The actual update
frequency is controlled by the loop in the run method (and the
minimum cycle time imposed by the sensors).

Optimize output of a script by varying input parameters

I have a written a script that uses the code below and I would like to optimize rsi_high and rsi_low to get the best sharpe_ratio:
#
import numpy
import talib as ta
global rsi_high, rsi_low
rsi_high = 63
rsi_low = 41
def myTradingSystem(DATE, OPEN, HIGH, LOW, CLOSE, VOL, exposure, equity, settings):
''' This system uses trend following techniques to allocate capital into the desired equities'''
nMarkets = CLOSE.shape[1] # SHAPE OF NUMPY ARRAY
result, rsi_pos = numpy.apply_along_axis(rsicalc, axis=0, arr=CLOSE)
pos = numpy.asarray(rsi_pos, dtype=numpy.float64)
return pos, settings
def rsicalc(num):
# print rsi_high
try:
rsival = ta.RSI(numpy.array(num,dtype='f8'),timeperiod=14)
if rsival[14] > rsi_high: pos_rsi = 1
elif rsival[14] < rsi_low: pos_rsi = -1
else: pos_rsi = 0
except:
rsival = 0
pos_rsi = 0
return rsival, pos_rsi
def mySettings():
''' Define your trading system settings here '''
settings = {}
# Futures Contracts
settings['markets'] = ['CASH','F_AD', 'F_BO', 'F_BP', 'F_C', 'F_CC', 'F_CD',
'F_CL', 'F_CT', 'F_DX', 'F_EC', 'F_ED', 'F_ES', 'F_FC', 'F_FV', 'F_GC',
'F_HG', 'F_HO', 'F_JY', 'F_KC', 'F_LB', 'F_LC', 'F_LN', 'F_MD', 'F_MP',
'F_NG', 'F_NQ', 'F_NR', 'F_O', 'F_OJ', 'F_PA', 'F_PL', 'F_RB', 'F_RU',
'F_S', 'F_SB', 'F_SF', 'F_SI', 'F_SM', 'F_TU', 'F_TY', 'F_US', 'F_W',
'F_XX', 'F_YM']
settings['slippage'] = 0.05
settings['budget'] = 1000000
settings['beginInSample'] = '19900101'
settings['endInSample'] = '19931231'
settings['lookback'] = 504
return settings
# Evaluate trading system defined in current file.
if __name__ == '__main__':
import quantiacsToolbox
results = quantiacsToolbox.runts(__file__, plotEquity=False)
sharpe_ratio = results['stats']['sharpe']
I suspect that using something like scipy minimize function would do the trick, but I am having trouble understanding how to package my script so that it can be in a usable form.
I have tried putting everything in a function and then running all the code through a number of loops, each time incrementing values but there must be a more elegant way of doing this.
Apologies for posting all my code but I thought it would help if the responder wanted to reproduce my setup and for anyone who is new to quantiacs to see a real example who is faced with the same issue.
Thanks for your help in advance!

How to simulate game controller key input?

I am currently working on a program that acts as a USB game controller but I am having trouble finding a way to simulate keypress and stick movement...
I am hoping to work with python but anything will work.

Have a look into pyvjoy, it allows you to simulate controllers when the emulator x360ce is installed.
Have a look at this rocket league bot framework where the code allows you to simulate input.
Example:
import pyvjoy
class PlayHelper:
def __init__(self, player_index):
self.device = pyvjoy.VJoyDevice(player_index + 1)
def update_controller(self, output):
self.device.data.wAxisX = output[0]
self.device.data.wAxisY = output[1]
self.device.data.wAxisZRot = output[2]
self.device.data.wAxisZ = output[3]
self.device.data.lButtons = (1 * output[4]) + (2 * output[5]) + (4 * output[6])
self.device.data.wAxisXRot = 16383
self.device.data.wAxisYRot = 16383
self.device.update() # Send data to vJoy device
Source: https://github.com/drssoccer55/RLBot

python run a scapy function as a background process

I would like to know in any way that i can run a function as a background process.
I have gone through reading threading but i am still unclear on how to implement it.
In my system , the scapy detection script run when i click on the Button.But then the system will be hang as the scapy function is running.
What i want to achieve is that when i click on the button that initiate the scapy detection script , i would like to be able to do other function in the same system.(general idea was to prevent the system from hang)
def startMonitor(self,event):
selectedInterface = self.interfaces_cblist.GetValue()
#selectInterfaceStr = str(selectedInterface)
if len(selectedInterface) == 0:
noInterfaceSelected = wx.MessageDialog(None,"Please select an interface","",wx.ICON_ERROR)
noInterfaceSelected.ShowModal()
else:
#confirmMonitor = wx.MessageDialog(None,"Monitoring Start on %s interface"%selectedInterface,"",wx.OK)
#confirmMonitor.ShowModal()
x = selectedInterface
thread.start_new_thread(self.camtableDetection(x))
def camtableDetection(self,a):
global interface
interface = str(a)
THRESH=(254/4)
START = 5
def monitorPackets(p):
if p.haslayer(IP):
hwSrc = p.getlayer(Ether).src
if hwSrc not in hwList:
hwList.append(hwSrc)
delta = datetime.datetime.now() - start
if((delta.seconds > START) and ((len(hwList)/delta.seconds) > THRESH)):
camAttackDetected = wx.MessageDialog(None,"Cam Attack Detected","",wx.ICON_ERROR)
camAttackDetected.ShowModal()
hwList = []
start = datetime.datetime.now()
sniff(iface=interface,prn=monitorPackets)