How to Parameterize in Python

In this tutorial, we will be discussing parameterization in Python. Parameterization, in simplest terms, refers to the process where the parameters of a program are modified for different scenarios. This method is essential, particularly in testing, where different data sets are used to determine code effectiveness and efficiency.

Getting Started with Parameterization in Python

First, we need to understand what a parameter in Python is. A parameter is a variable listed inside the parentheses in the function definition.

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def function_name(parameter_1, parameter_2):
  # code block

Parameters are essentially the ‘input’ that the function works with, and they become variables inside the function.

Parameter Types in Python

Python offers two types of parameters:

  1. Positional Parameters: These are parameters that need to be passed in the correct positional order. Here, the number of arguments in the function call should match exactly with the function definition.
  2. Keyword Parameters: These are related to the function calls. When you use keyword parameters in a function call, Python identifies the arguments by the parameter name.

Using Parameterization in code

Let’s consider the following code:

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def print_info(name, age):
   print("Name: ", name)
   print("Age ", age)

So, our function print_info accepts two parameters: name and age.

Now we will call this function with different parameters:

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print_info(age=30, name="John")

Even though we changed the order of parameters while calling the function, Python understands it correctly because we used keyword parameters. The output will be:

Name: John
Age: 30

Full Python Code

Here is the full code used in this tutorial:

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def print_info(name, age):
   print("Name: ", name)
   print("Age ", age)
 
print_info(age=30, name="John")

Conclusion

In conclusion, using parameters in Python makes your code more flexible and re-usable. It allows for variation, which is an important aspect of testing and coding. It’s a crucial way to feed different values into your functions – making Python even more versatile and efficient.