As I was drafting this article on the little confusing and less used Python’s lambda function, exciting tweet dropped on my twitter timeline. It mentioned that Microsoft is exploring the idea of adding Python as one of the official Excel scripting languages. I am sure thousands of Python enthusiasts would be elated on knowing this. Yes! One of the powerful and popular programming languages in recent years, Python will be made available inside Excel if Microsoft decides to implement it.
This will make Python super popular which already has wide application in the areas of finance, data science, research, web development, robotics, software development, education and many other fields.
Our Executive Programme in Algorithmic Trading (EPAT™) includes a special module called “Algorithmic Trading Platform” in which EPAT™ participants learn the basics of Python and get a practical and hands-on training to backtest and automated their algorithmic trading strategies. You can learn more about the EPAT™ program here.
Lambda FunctionNow let’s come to our main topic for this post, the short anonymous lambda function. Many python learners might not be aware of its existence. Lambda is used to construct a python function; it is an in-line function, unlike the conventional def function which allows constructing in blocks. Let’s us compare the syntax of the conventional function construct with the lambda function syntax to make things clear.
One can have any number of statements in the conventional def function, and it starts by giving a name to the function. On the other hand, the lambda is an anonymous function. You need not provide any name to the lambda construct. Let us take simple examples to illustrate their usage.
The lambda construct is more used for its convenience rather than the range of operations that can be performed using lambda. Remember the following points when you need to construct a lambda function.
- Lambda is an expression and not a statement. It does not support a block of expressions.
- Lambda is defined at the point where we need to use it and need not be named
- Lambda does not require a return statement. It always returns something after evaluation.
Lambda construct with a single argument.
Lambda construct with multiple arguments.
Lambda construct with logical operators
Lambda construct with conditional expressions like the if..else statement and comparison operators.
We can also construct lambda with multiple if..else statements in the following manner.
Using Lambda with Map, Filter, and Reduce functionsLambda functions are usually used in conjunction with the functions like map(), filter(), and reduce(). Let us illustrate their usage.
The map function is used to pass a function to each item in an iterable object and it returns a list containing all the results from the function call. The map function takes the following syntax.
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.
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.
These were some of the ways in which we can use the lambda construct. We will continue posting more such informative articles on Python and its usage in algorithmic trading. You can read our last post on basic operations in Python here. If you are interested in Python algorithmic trading strategies, we have many posts in our “Trading Strategies” category. Keep reading and sharing our articles. Cheers!
Next StepIf you are interested in exploring algorithmic trading using Python then do check our EPAT™ program. It covers training modules like Algorithmic & Quantitative Trading, Financial Computing, Technology, Statistics, and Econometrics. EPAT™ equips you with the required skill sets to be a successful algorithmic trader. Enroll now!
Disclaimer: All investments and trading in the stock market involve risk. Any decisions to place trades in the financial markets, including trading in stock or options or other financial instruments is a personal decision that should only be made after thorough research, including a personal risk and financial assessment and the engagement of professional assistance to the extent you believe necessary. The trading strategies or related information mentioned in this article is for informational purposes only.
Download Python Code
- Python Learning Lambda Function - Python Code