If you have an already written code and want to reuse the same instead of rewriting the entire code, then you can do so by keeping the existing code within the defined function and later it can be called as and when required. A defined function is a code which only runs when it is called later. It avoids repetition and makes the code reusable any number of times.
Python Code: Call Defined Function
The defined function begins with the keyword "def" followed by the function name defined by the programmer and ends with the open and close parenthesis. To call a function, we simply type the function name defined earlier with the open and close parenthesis.
def callfunction():
print ("welcome to bucketscene.com")
callfunction()
Python Code: Call Defined Function with Changes
The defined function begins with the keyword "def" followed by the function name defined by the programmer and ends with the open and close parenthesis having a parameter in-between. Such parameter is the key to the call function. To call a function, we simply type the function name defined earlier and instead of that parameter used in-between the open and close parenthesis, we define the parameter to play with in the defined function code.
In our example, we have "x" as a parameter and instead of calling with 'callfunction(x)', we define the parameter as 'hello, ' to include this with the print command. So now the Python will replace the 'x' used in print command with 'hello, ' to concatenate with the existing.
def callfunction(x):
print (x + "welcome to bucketscene.com")
callfunction("hello, ")
Defined Function Name "callfunction" can be replaced. It can be 'function()' or 'callmeagain()' or anything you want.
Similarly, the parameter "x" can be replaced. It can be 'name' or 'placeholder' or anything you want.
Disclaimer: We, in our example, only cover how to perform such functions and less focusing on the type of example we take. Our motive is to deliver the exact solution to the queries on "How To" in the most simplest way. Of course, the application of these function can be seen in our advanced modules with more complex examples and datasets.
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