# Understanding and Utilizing Function Signatures in Python

A signature is like an identification mark, it is unique to every person in this world. It serves as a crucial authorizing agent for important documents due to its unique properties. Graphologists say that a signature can reveal a lot about a person. And just like that, a function signature in Python reveals a lot about the properties about that particular function.

In Python, a function signature provides crucial information about the types of parameters that a function can accept and the type of data it returns. The signature() function from the inspect module is used to determine the function signature, helping developers to ensure they are passing the correct types of arguments to their functions. This function can be particularly useful in large programs where a small mistake can lead to significant issues.

A function signature typically informs us about the types of parameters that a function can accept as arguments and the type of data or result it returns.

There is an inbuilt function that is used to determine the signature of a function. It assists in predetermining whether a function accepts a specific type of argument.

In this tutorial, we will first look at what functions are and how they are structured, and how to easily determine the function signature in Python using the signature attribute. Let’s get started!

## Exploring Python Functions

In programming, a function is a reusable piece of code designed to perform a specific task. These are blocks of code that are predefined by the system or the user, and they execute when called upon.

Similar to functions in mathematics, functions in programming have specified uses. Different functions have different responsibilities.

Each function has specific arguments or parameters that a particular action is performed on, and they have a specific syntax as well. A function returns a specific result which can be of any data type available. Functions are not limited to Python, they are available in all programming languages.

Let’s look at how you can create a function. The function when first defined with what task it has to perform is written with the def keyword. Let’s create a function called addition where we will take two integer inputs and return their sum.

```def addition(a:int, b:int):
ans= a + b
return ans
```

A function can take up any number of arguments or parameters. But if your function has been designed to take up 2 parameters but you provide 3 at the time of calling it, it will raise an error. You can pass variables as well as keyword arguments in your functions.

When you are unsure about the number of parameters that are going to be passed during runtime, you can use the *args and **kwargs keywords to take up any arbitrary number of parameters.

When calling a function, you need to use a pair of parentheses at the end of the function name containing your variables. So to call our addition function to add two given numbers we will write the following:

```>>print("The answer is =",addition(3,5))
8
```

## Identifying the Signature of a Python Function

In lengthy programs where even a small mistake can make your code crumble, it is essential to know the type of arguments that you need to pass to your functions. The signature of a function tells you what are the types of inputs required by your function along with annotations, and also the type of information that the function returns. The signature() function in Python, is used to find the signature of a function.

Let’s look at how we can use it in our code.

You need to import the inspect module before using the signature() function. The syntax of the function is as follows:

```inspect.signtaure(your_function)
```

Let’s determine the signature of our function addition from the previous section.

```from inspect import signature
#defining our function
ans= a + b
return ans
#calling our function
#printing the input parameters of the function
print(sig)
#printing type of a
print(sig.parameters['a'])
#printing annotation of b
print(sig.parameters['b'].annotation)
```

The output would be:

```The answer is = 8
(a: int, b: int)
a: int
<class 'int'>
```

This function will raise a TypeError if the class of the object or the object type is invalid.

## Final words

In this tutorial, we’ve explored how to create functions in Python and determine their signatures using the signature() function from the inspect module. Understanding function signatures can greatly enhance your Python programming efficiency by ensuring you’re passing the correct types of arguments to your functions. Now, how might you apply this knowledge in your next Python project?

References

Official documentation