89 lines
3.2 KiB
Markdown
89 lines
3.2 KiB
Markdown
|
---
|
||
|
|
title: Lambda Expressions
|
||
|
|
---
|
||
|
|
## Lambda Expressions
|
||
|
|
|
||
|
|
Lambda Expressions are ideally used when we have something simple to be done an we are more interested in quickly getting the job done rather than formally naming the function. Lambda expressions also known as anonymous functions.
|
||
|
|
<a href='https://github.com/freecodecamp/guides/tree/master/src/pages/python/lambda-expressions/index.md' target='_blank' rel='nofollow'>Help our community expand it</a>.
|
||
|
|
|
||
|
|
Lambda Expressions in Python are a short way to declare small and anonymous functions (it is not necessary to provide a name for lambda functions). Lambda functions behave just like regular functions declared with the `def` keyword. They come in handy when you want to define a small function in a concise way. They can contain only one expression, so they are not best suited for functions with control-flow statements.
|
||
|
|
master
|
||
|
|
|
||
|
|
#### Syntax of Lambda Function
|
||
|
|
`lambda arguments: expression`
|
||
|
|
|
||
|
|
Lambda functions can have any number of arguments but only one expression
|
||
|
|
|
||
|
|
#### Example code
|
||
|
|
```py
|
||
|
|
# Lambda function to calculate square of a number
|
||
|
|
square = lambda x: x ** 2
|
||
|
|
print(square(3)) # Output: 9
|
||
|
|
|
||
|
|
# Traditional function to calculate square of a number
|
||
|
|
def square1(num):
|
||
|
|
return num ** 2
|
||
|
|
print(square(5)) # Output: 25
|
||
|
|
|
||
|
|
```
|
||
|
|
In the above lambda example `lambda x: x ** 2` yields an anonymous function object which can be associated with any name.
|
||
|
|
So, we associated the function object with `square` and hence from now on we can call the `square` object like any traditional function. e.g. `square(10)`
|
||
|
|
|
||
|
|
## Examples
|
||
|
|
|
||
|
|
### Beginner
|
||
|
|
```py
|
||
|
|
lambda_func = lambda x: x**2 # Function that takes an integer and returns its square
|
||
|
|
lambda_func(3) # Returns 9
|
||
|
|
```
|
||
|
|
### Intermediate
|
||
|
|
```py
|
||
|
|
lambda_func = lambda x: True if x**2 >= 10 else False
|
||
|
|
lambda_func(3) # Returns False
|
||
|
|
lambda_func(4) # Returns True
|
||
|
|
```
|
||
|
|
### Complex
|
||
|
|
```py
|
||
|
|
my_dict = {"A": 1, "B": 2, "C": 3}
|
||
|
|
sorted(my_dict, key=lambda x: my_dict[x]%3) # Returns ['C', 'A', 'B']
|
||
|
|
```
|
||
|
|
### Use-case
|
||
|
|
|
||
|
|
Let's say you want to filter out odd numbers from a `list`. You could use a `for` loop:
|
||
|
|
|
||
|
|
```python
|
||
|
|
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
|
||
|
|
filtered = []
|
||
|
|
|
||
|
|
for num in my_list:
|
||
|
|
if num % 2 != 0:
|
||
|
|
filtered.append(num)
|
||
|
|
|
||
|
|
print(filtered) # Python 2: print filtered
|
||
|
|
# [1, 3, 5, 7, 9]
|
||
|
|
```
|
||
|
|
|
||
|
|
You could write this as a one liner with list-comprehensions
|
||
|
|
|
||
|
|
```python
|
||
|
|
filtered = [x for x in [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] if x % 2 != 0]
|
||
|
|
```
|
||
|
|
|
||
|
|
But you might be tempted to use the built-in `filter` function. Why? The first example is a bit to verbose, the one-liner can be harder to understand, where as `filter` offers the best of both words. What is more, the built-in functions are usually faster.
|
||
|
|
|
||
|
|
```python
|
||
|
|
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
|
||
|
|
|
||
|
|
filtered = filter(lambda x: x % 2 != 0, my_list)
|
||
|
|
|
||
|
|
list(filtered)
|
||
|
|
# [1, 3, 5, 7, 9]
|
||
|
|
```
|
||
|
|
NOTE: in Python 3 built in function return generator objects, so you have to call `list`, while in Python 2 they return a `list`, `tuple`or `string`.
|
||
|
|
|
||
|
|
What happened? You told `filter` to take each element in `my_list` and apply the lambda expressions. The values that return `False` are filtered out.
|
||
|
|
|
||
|
|
#### More Information:
|
||
|
|
- [Official Doc](https://docs.python.org/3/reference/expressions.html#lambda)
|
||
|
|
- [Further Read](https://dbader.org/blog/python-lambda-functions)
|