Python_lambda_trading.py

# Lambda construct with a single argument
x = [23,34,55]
func = lambda x: max(x)
print (func(x))

# Lambda construct with multiple arguments
price,volume = 60,20
func = lambda price,volume: price/volume
print(func(price,volume))

# Lambda construct with logical operators
signal = "SELL"
func = lambda x: x>50 and signal == "BUY"
func(65)

# Lambda construct with conditional expressions like the if..else statement and comparison operators
func = lambda x: "BUY" if x > 45 else "SELL"
signal = func(65)
print(signal)

# We can also construct lambda with multiple if..else statements in the following manner
func = lambda x: "BUY" if x <=  30 else "SELL" if x>= 70 else "None"
signal = func(65)
print(signal)

# The filter function is used to extract each element in the iterable object
# for which the function returns True. In this case, we will define the function
# using the lambda construct and apply the filter function

Signal = ['Buy','Sell', None, 'Sell', 'Sell', 'Sell']
list(filter(lambda x: x == 'Buy' or x == 'Sell', Signal))

# The reduce function is a unique function which reduces the input list to a single value
# by calling the function provided as part of the argument.  The reduce function by default
# starts from the first value of the list and passes the current output along the next item
# from the list.

from functools import reduce
reduce((lambda x,y: x+y),[2,1.35,-2.4,3])