import time from iqoptionapi.stable_api import IQ_Option class AutoTradingBot: """ Class to handle the auto trading bot for IQ Option using moving average EMA 9 and EMA 15. Attributes: - username: str The username for the IQ Option account. - password: str The password for the IQ Option account. - api: IQ_Option The instance of the IQ Option API. """ def __init__(self, username: str, password: str): """ Constructor to instantiate the AutoTradingBot class. Parameters: - username: str The username for the IQ Option account. - password: str The password for the IQ Option account. """ # Initializing the IQ Option API with the provided credentials. self.username = [email protected] self.password = Ss&150795 self.api = IQ_Option(self.username, self.password) def login(self): """ Logs in to the IQ Option account using the provided credentials. Returns: - bool: Returns True if the login is successful, False otherwise. """ # Connecting to the IQ Option API. self.api.connect() # Checking if the login is successful. if self.api.check_connect(): print("Login successful.") return True else: print("Login failed.") return False def moving_average_strategy(self): """ Implements the moving average strategy using EMA 9 and EMA 15. This strategy involves placing trades automatically when EMA 9 and EMA 15 intersect. Returns: - bool: Returns True if the strategy is executed successfully, False otherwise. """ # Subscribing to the EMA 9 and EMA 15 indicators. self.api.start_candles_stream("EURUSD", 60, 100) # Loop to continuously check for EMA 9 and EMA 15 intersection. while True: # Getting the EMA 9 and EMA 15 values. ema9 = self.api.get_technical_indicators("EURUSD", 9, "EMA", 60) ema15 = self.api.get_technical_indicators("EURUSD", 15, "EMA", 60) # Checking if EMA 9 and EMA 15 intersect. if ema9 and ema15 and ema9[-1] > ema15[-1] and ema9[-2] < ema15[-2]: # Placing trade automatically if EMA 9 and EMA 15 intersect. self.place_trade() # Delaying the loop execution for 1 second. time.sleep(1) def place_trade(self): """ Places a trade automatically based on the moving average strategy. This function will place a trade above 80% payout and in multiple assets at the same time. """ # Checking the available assets for trading. assets = self.api.get_all_open_time() # Looping through the assets and placing trades above 80% payout. for asset in assets: if assets[asset]["open"]: # Placing trade above 80% payout. self.api.buy(1, asset, "call", 1) def run_bot(self): """ Runs the auto trading bot. This function will handle the login and execute the moving average strategy. """ # Logging in to the IQ Option account. if self.login(): # Executing the moving average strategy. self.moving_average_strategy() # Example of using the AutoTradingBot class: # Initializing and running the auto trading bot bot = AutoTradingBot("your_username", "your_password") bot.run_bot()
Write, Run & Share Python code online using OneCompiler's Python online compiler for free. It's one of the robust, feature-rich online compilers for python language, supporting both the versions which are Python 3 and Python 2.7. Getting started with the OneCompiler's Python editor is easy and fast. The editor shows sample boilerplate code when you choose language as Python or Python2 and start coding.
OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.
import sys
name = sys.stdin.readline()
print("Hello "+ name)
Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.
When ever you want to perform a set of operations based on a condition IF-ELSE is used.
if conditional-expression
#code
elif conditional-expression
#code
else:
#code
Indentation is very important in Python, make sure the indentation is followed correctly
For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.
mylist=("Iphone","Pixel","Samsung")
for i in mylist:
print(i)
While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.
while condition
#code
There are four types of collections in Python.
List is a collection which is ordered and can be changed. Lists are specified in square brackets.
mylist=["iPhone","Pixel","Samsung"]
print(mylist)
Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.
myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
Below throws an error if you assign another value to tuple again.
myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)
Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.
myset = {"iPhone","Pixel","Samsung"}
print(myset)
Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.
mydict = {
"brand" :"iPhone",
"model": "iPhone 11"
}
print(mydict)
Following are the libraries supported by OneCompiler's Python compiler
Name | Description |
---|---|
NumPy | NumPy python library helps users to work on arrays with ease |
SciPy | SciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation |
SKLearn/Scikit-learn | Scikit-learn or Scikit-learn is the most useful library for machine learning in Python |
Pandas | Pandas is the most efficient Python library for data manipulation and analysis |
DOcplex | DOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling |