Introduction To Python FunctionsIn today’s fast-paced IT world, it is always an advantage to have an edge over the others in terms of in-depth knowledge of a certain technology. Python is a widely used language and provides ‘n’ number of opportunities to enthusiastic learners. Learning to use the functions in Python in the right way is a notable skill for any Python Developer. Show
In this Python Functions blog, the goal is to get you the expertise required to get started and work with functions using Python. I will be covering the following topics in this Python Functions blog:
Python Functions Tutorial | Working With Functions In Python | Edureka This video covers all the important aspects of
functions in Python right from the introduction to what functions are, all the way till checking out the major functions and using the code-first approach to understand them better. Let us begin this Python Functions blog by first checking out why we need Python Functions. Why We Need Python Functions?Functions manage the inputs and outputs in computer programs. Python Programming languages are designed to work on data and functions are an effective way to manage and transform this data. The modifications are generally done to drive outcomes like performing tasks and finding results. And, the set of operations or instructions required to do so comes from logically functional blocks of code that can be reused independently from the main program. In fact, the main code is also a function, just a very important one at that. Every other function is logically aligned and maintained to functionally execute from your main code. But, if the function has not been defined previously, you’ll just have to define one yourself before using it. This is because the definition lists the steps of its operation. Would you rather write a single piece of code 10 times or just once and use it 10 times? So, functions are nothing but tasks that a user wants to perform. But, defining it once with a name will let you reuse that functionality without making your main programs look too scary. This drastically reduces lines of code and even make debugging easier. We’ll be getting into that shortly, but the first reason behind why use a function is because of its reusability. The fact that even complex operations could be put together as singular tasks that would run with just a call by its name is what has made computer codes of today so much clearer as well. Every programming language lets you create and use these functions to perform various tasks with just a call. And, you could call it any number of times without having to worry about logically structuring its code into your main code every single time. Let’s try and understand their need to us through a simple example first. Say, you have a television that stores many channels on it, receives their digital radio broadcasts, converts them into what we watch, while also giving us additional options for a variety of other features as well.But that doesn’t mean there is someone logically scripting the lines of codes for what you watch every time you turn on your tv or flip a channel. Rather, functions for each task in its working have been logically defined once and keep getting reused time and again according to the features you try to use. All of it happens by calling its different functions as many times as needed from the main function that is running. So, even if you’re turning the volume up or down, its defined function is being called repeatedly. And, having a system operating the main code to keep calling these functions as and when needed has also made designing and innovating upon it all the easier. The important thing to note is that whenever this function is called, it executes its tasks depending on the instructions specified in it. That’s how machines can have different functions. A calculator is probably the most common example of this. It has the provision of addition, subtraction, multiplication, division, and other functions. All its functions have been clearly predefined into it, but it only performs those that you choose to call by pressing its respective button. Programmers reduce coding time and debugging time, thereby reducing overall development time, by using functions. Next up on this Python Functions blog, let us look at what the Python Functions actually are. What Are Python Functions?The functions in Python are a classic example of such reusability. So, to serve a wide range of applications from GUI and mathematical computing to web development and testing, Python’s interpreter already comes equipped with numerous functions that are always available for use. And, you could also bring in other libraries or modules to your program that contain pre-defined functions readily available for use. All you’ll really have to do is download required packages that according to their documentation and freely avail all its useful functionalities by just importing them over to your code. So, once defined, a function can be used any number of times at any point in any of your codes. Now, this is because Python falls in-line with the DRY principle of software engineering, which aims to replace any repetition of software patterns or codes with abstractions to avoid redundancy and ensure that they can be used freely without revealing any inner details on their implementations. DRY expands to Don’t Repeat Yourself and this concept of having re-usable blocks of codes is very crucial for achieving abstraction in Python. Thus, in order to use a function all that you’ll really need is its name, its purpose, its arguments if it takes any and its result’s type if it returns any. It’s almost like using an automobile or a telephone, where you don’t necessarily need to understand the working of its components to use them. Rather, they’ve been already built to serve common purposes that you can just use directly to achieve your goals and devote your precious time to implementing all the innovative aspects of your application program. And, nobody really wants to know how a function in your program works on the inside, as long as it does the job. So, with Python, unless you must write a new function or change how an existing one works, you won’t even need to understand anything about what goes on inside till it works the way you need it to. It’s just like with a vehicle or a phone again, where you’ll need to know how it works in order to build or fix one. And, similarly, once you’ve written a working function, you can use it repeatedly without having to look at the contents inside it ever again. A function can be called as a section of a program that is written once and can be executed whenever required in the program, thus making code reusability. The function is a subprogram that works on data and produces some output. To define a Python function, you’d have to use the ‘def’ keyword before the name of your function and add parentheses to its end, followed by a colon(:). Python uses indentation to indicate blocks instead of brackets to make codes more readable. A function in Python may contain any number of parameters or none. So, for times when you need your function to operate on variables from other blocks of code or from your main program, it could take any number of parameters and produce results. A Python function could also optionally return a value. This value could be a result produced from your function’s execution or even be an expression or value that you specify after the keyword ‘return’. And, after a return statement is executed, the program flow goes back to the state next to your function call and gets executed from there. So, to call a Python function at any place in your code, you’ll only have to use its name and pass arguments in its parentheses, if any. The rules for naming a function are the same as naming a variable. It begins with either letter from A-Z, a-z in both upper & lower cases or an underscore(_). The rest of its name can contain underscores(_), digits(0-9), any letters in upper or lower case.
It is good practice to name a Python function according to what it does. use a docstring right under the first line of a function declaration. This is a documentation string, and it explains what the function does. Next up in this Python Functions blog, let us check out the types of Functions available in Python. There are many types of Python Functions. And each of them is very vital in its own way. The following are the different types of Python Functions:
Let us check out these functions in detail. Beginning with Built-in functions as they are very easy to understand and implement. Python Built-in Functions:The Python interpreter has a number of functions that are always available for use. These functions are called built-in functions. For example, print() function prints the given object to the standard output device (screen) or to the text stream file. In Python 3.6, there are 68 built-in functions. But for the sake of simplicity let us consider the majorly used functions and we can build on from there. Python abs() Function:Definition The abs() method returns the absolute value of the given number. If the number is a complex number, abs() returns its magnitude. Syntax The syntax of abs() method is: abs(num) Parameters The abs() method takes a single argument:
Example # random integer integer = -20 print('Absolute value of -20 is:', abs(integer)) #random floating number floating = -30.33 print('Absolute value of -30.33 is:', abs(floating)) Output Absolute value of -20 is: 20 Absolute value of -30.33 is: 30.33 Python all() Function:Definition The all() method returns True when all elements in the given iterable are true. If not, it returns False. Syntax The syntax of all() method is: all(iterable) Parameters The all() method takes a single parameter:
Example # all values true l = [1, 3, 4, 5] print(all(l)) # all values false l = [0, False] print(all(l)) # one false value l = [1, 3, 4, 0] print(all(l)) # one true value l = [0, False, 5] print(all(l)) # empty iterable l = [] print(all(l)) Output True False False False True Python ascii() Function:Definition The ascii() method returns a string containing a printable representation of an object. It escapes the non-ASCII characters in the string using x, u or U escapes. Syntax The syntax of ascii() method is: ascii(object) Parameters The ascii() method takes an object (like strings, list etc). Example normalText = 'Python is interesting' print(ascii(normalText)) otherText = 'Pythön is interesting' print(ascii(otherText)) print('Pythn is interesting') Output 'Python is interesting' 'Pythn is interesting' Pythön is interesting Python bin() Function:Definition The bin() method converts and returns the binary equivalent string of a given integer. If the parameter isn’t an integer, it has to implement __index__() method to return an integer. Syntax The syntax of bin() method is: bin(num) Parameters The bin() method takes a single parameter:
Example number = 5 print('The binary equivalent of 5 is:', bin(number)) Output The binary equivalent of 5 is: 0b101 Python compile() Function:Definition The compile() method returns a Python code object from the source (normal string, a byte string, or an AST object). Syntax The syntax of compile() method is: compile(source, filename, mode, flags=0, dont_inherit=False, optimize=-1) Parameters
Example codeInString = 'a = 5 b=6 sum=a+b print("sum =",sum)' codeObejct = compile(codeInString, 'sumstring', 'exec') exec(codeObejct) Output sum = 11 Python dict() Function:Definition The dict() constructor creates a dictionary in Python. Different forms of dict() constructors are: class dict(**kwarg) class dict(mapping, **kwarg) class dict(iterable, **kwarg) Example numbers = dict(x=5, y=0) print('numbers = ',numbers) print(type(numbers)) empty = dict() print('empty = ',empty) print(type(empty)) Output empty = dict() print('empty = ',empty) print(type(empty)) Python enumerate() Function:Definition The enumerate() method adds counter to an iterable and returns it (the enumerate object). Syntax The syntax of enumerate() method is: enumerate(iterable, start=0) Parameters The enumerate() method takes two parameters:
Example grocery = ['bread', 'milk', 'butter'] enumerateGrocery = enumerate(grocery) print(type(enumerateGrocery)) # converting to list print(list(enumerateGrocery)) # changing the default counter enumerateGrocery = enumerate(grocery, 10) print(list(enumerateGrocery)) Output <class 'enumerate'> [(0, 'bread'), (1, 'milk'), (2, 'butter')] [(10, 'bread'), (11, 'milk'), (12, 'butter')] Python eval() Function:Definition The eval() method parses the expression passed to this method and runs python expression (code) within the program. Syntax The syntax of eval() method is: eval(expression, globals=None, locals=None) Parameters The eval() takes three parameters:
Example x = 1 print(eval('x + 1')) Output sum = 11 Python filter() Function:Definition The filter() method constructs an iterator from elements of an iterable for which a function returns true. Syntax The syntax of filter() method is: filter(function, iterable) Parameters The filter() method takes two parameters:
Example # list of alphabets alphabets = ['a', 'b', 'd', 'e', 'i', 'j', 'o'] # function that filters vowels def filterVowels(alphabet): vowels = ['a', 'e', 'i', 'o', 'u'] if(alphabet in vowels): return True else: return False filteredVowels = filter(filterVowels, alphabets) print('The filtered vowels are:') for vowel in filteredVowels: print(vowel) Output The filtered vowels are: a e i o Python getattr() Function:Definition The getattr() method returns the value of the named attribute of an object. If not found, it returns the default value provided to the function. Syntax The syntax of getattr() method is: getattr(object, name[, default]) Parameters The getattr() method takes multiple parameters:
Example class Person: age = 23 name = "Adam" person = Person() print('The age is:', getattr(person, "age")) print('The age is:', person.age) Output The age is: 23 The age is: 23 Python help() Function:Definition The help() method calls the built-in Python help system. Syntax The syntax of help() method is: help(object) Parameters The help() method takes the maximum of one parameter.
Example
Python id() Function:Definition The id() function returns identity (unique integer) of an object. Syntax The syntax of id() method is: id(object) Parameters The id() function takes a single parameter object. Example class Foo: b = 5 dummyFoo = Foo() print('id of dummyFoo =',id(dummyFoo)) Output id of dummyFoo = 140343867415240 Python len() Function:Definition The len() function returns the number of items (length) in an object. Syntax The syntax of len() method is: len(s) Parameters s – a sequence (string, bytes, tuple, list, or range) or a collection (dictionary, set or frozen set) Example testList = [] print(testList, 'length is', len(testList)) testList = [1, 2, 3] print(testList, 'length is', len(testList)) testTuple = (1, 2, 3) print(testTuple, 'length is', len(testTuple)) testRange = range(1, 10) print('Length of', testRange, 'is', len(testRange)) Output [] length is 0 [1, 2, 3] length is 3 (1, 2, 3) length is 3 Length of range(1, 10) is 9 Python max() Function:Definition The max() method returns the largest element in an iterable or largest of two or more parameters. Syntax The syntax of max() method is: max(iterable, *iterables[,key, default]) max(arg1, arg2, *args[, key]) Parameters max() has two forms of arguments it can work with.
Example # using max(arg1, arg2, *args) print('Maximum is:', max(1, 3, 2, 5, 4)) # using max(iterable) num = [1, 3, 2, 8, 5, 10, 6] print('Maximum is:', max(num)) Output Maximum is: 5 Maximum is: 10 Python min() Function:Definition The min() method returns the smallest element in an iterable or smallest of two or more parameters. The syntax of min() method is: min(iterable, *iterables[,key, default]) min(arg1, arg2, *args[, key]) Parameters min() has two forms of arguments it can work with.
Example # using min(arg1, arg2, *args) print('Minimum is:', min(1, 3, 2, 5, 4)) # using min(iterable) num = [3, 2, 8, 5, 10, 6] print('Minimum is:', min(num)) Output Minimum is: 1 Minimum is: 2 Python oct() Function:Definition The oct() method takes an integer number and returns its octal representation. If the given number is an int, it must implement __index__() method to return an integer. The syntax of oct() method is: oct(x) Parameters The oct() method takes a single parameter x. This parameter could be:
Example # decimal number print('oct(10) is:', oct(10)) # binary number print('oct(0b101) is:', oct(0b101)) # hexadecimal number print('oct(0XA) is:', oct(0XA)) Output oct(10) is: 0o12 oct(0b101) is: 0o5 oct(0XA) is: 0o12 Python pow() Function:Definition The pow() method returns x to the power of y. If the third argument (z) is given, it returns x to the power of y modulus z, i.e. pow(x, y) % z. The syntax of pow() method is: pow(x, y[, z]) Parameters The pow() method takes three parameters:
Example # positive x, positive y (x**y) print(pow(2, 2)) # negative x, positive y print(pow(-2, 2)) # positive x, negative y (x**-y) print(pow(2, -2)) # negative x, negative y print(pow(-2, -2)) Output 4 4 0.25 0.25 Python reversed() Function:Definition The reversed() method returns the reversed iterator of the given sequence. The syntax of reversed() method is: reversed(seq) Parameters The reversed() method takes a single parameter:
Example # for string seqString = 'Python' print(list(reversed(seqString))) # for tuple seqTuple = ('P', 'y', 't', 'h', 'o', 'n') print(list(reversed(seqTuple))) # for range seqRange = range(5, 9) print(list(reversed(seqRange))) # for list seqList = [1, 2, 4, 3, 5] print(list(reversed(seqList))) Output ['n', 'o', 'h', 't', 'y', 'P'] ['n', 'o', 'h', 't', 'y', 'P'] [8, 7, 6, 5] [5, 3, 4, 2, 1] Python sum() Function:Definition The sum() method returns the reversed iterator of the given sequence. The syntax of sum() method is: sum(iterable, start) Parameters
Example numbers = [2.5, 3, 4, -5] # start parameter is not provided numbersSum = sum(numbers) print(numbersSum) # start = 10 numbersSum = sum(numbers, 10) print(numbersSum) Output 4.5 14.5 Python type() Function:Definition If a single argument (object) is passed to type() built-in, it returns the type of the given object. If three arguments (name, bases, and dict) are passed, it returns a new type object. The syntax of type() method is: type(object) type(name, bases, dict) Parameters
Example numberList = [1, 2] print(type(numberList)) numberDict = {1: 'one', 2: 'two'} print(type(numberDict)) class Foo: a = 0 InstanceOfFoo = Foo() print(type(InstanceOfFoo)) Output <class 'dict'> <class 'Foo'> Next up on this Python Functions blog, let us check out the Recursive Function in Python. Python Recursive FunctionsWhat is recursion in Python?Recursion is the process of defining something in terms of itself. A physical world example would be to place two parallel mirrors facing each other. Any object in between them would be reflected recursively. Python Recursive FunctionWe know that in Python, a function can call other functions. It is even possible for the function to call itself. These type of construct are termed as recursive functions. Following is an example of a recursive function to find the factorial of an integer. Factorial of a number is the product of all the integers from 1 to that number. For example, the factorial of 5 (denoted as 5!) is 1*2*3*4*5 = 120. Example: # An example of a recursive function to # find the factorial of a number def calc_factorial(x): <em>"""This is a recursive function to find the factorial of an integer""" </em>if x == 1: return 1 else: return (x * calc_factorial(x-1)) num = 4 print("The factorial of", num, "is", calc_factorial(num)) In the above example, calc_factorial() is a recursive function as it calls itself. When we call this function with a positive integer, it will recursively call itself by decreasing the number. Each function call multiples the number with the factorial of number 1 until the number is equal to one. Our recursion ends when the number reduces to 1. This is called the base condition. Every recursive function must have a base condition that stops the recursion or else the function calls itself infinitely. Advantages of Recursion
Disadvantages of Recursion
Next up on this Python Functions blog, let us check out the Lambda Function in Python. Python Lambda FunctionsWhat Are Lambda functions?In Python, an anonymous function is a function that is defined without a name. While normal functions are defined using the Hence, anonymous functions are also called lambda functions. How To Use Lambda Functions In Python?A Lambda function in python has the following syntax: lambda arguments: expression Lambda functions can have any number of arguments but only one expression. The expression is evaluated and returned. Lambda functions can be used wherever function objects are required. Example # Program to show the use of lambda functions double = lambda x: x * 2 # Output: 10 print(double(5)) Output 10 In [1]: In the above program, This function has no name. It returns a function object which is assigned to the identifier double = lambda x: x * 2 is nearly the same as def double(x): return x * 2 Next up on this Python Functions blog, let us check out the how we can make use of User-defined functions in Python Python User-Defined FunctionsWhat Are User-Defined Functions In Python?Functions that we define ourselves to do the certain specific task are referred to as user-defined functions. The way in which we define and call functions in Python are already discussed. Functions that readily come with Python are called built-in functions. If we use functions written by others in the form of the library, it can be termed as library functions. All the other functions that we write on our own fall under user-defined functions. So, our user-defined function could be a library function to someone else. Advantages of user-defined functions
Syntax def function_name(argument1, argument2, ...) : statement_1 statement_2 .... Example # Program to illustrate # the use of user-defined functions def add_numbers(x,y): sum = x + y return sum num1 = 5 num2 = 6 print("The sum is", add_numbers(num1, num2)) Output Enter a number: 2.4 Enter another number: 6.5 The sum is 8.9 Next up on this Python Functions blog, let us check out how we can create a simple application using Python. Python Program To Create A Simple Calculator ApplicationIn this example, you will learn to create a simple calculator that can add, subtract, multiply or divide depending upon the input from the user. Code # Program make a simple calculator that can add, subtract, multiply and divide using functions # This function adds two numbers def add(x, y): return x + y # This function subtracts two numbers def subtract(x, y): return x - y # This function multiplies two numbers def multiply(x, y): return x * y # This function divides two numbers def divide(x, y): return x / y print("Select operation.") print("1.Add") print("2.Subtract") print("3.Multiply") print("4.Divide") # Take input from the user choice = input("Enter choice(1/2/3/4):") num1 = int(input("Enter first number: ")) num2 = int(input("Enter second number: ")) if choice == '1': print(num1,"+",num2,"=", add(num1,num2)) elif choice == '2': print(num1,"-",num2,"=", subtract(num1,num2)) elif choice == '3': print(num1,"*",num2,"=", multiply(num1,num2)) elif choice == '4': print(num1,"/",num2,"=", divide(num1,num2)) else: print("Invalid input") Output Select operation. 1.Add 2.Subtract 3.Multiply 4.Divide Enter choice(1/2/3/4): 3 Enter first number: 15 Enter second number: 14 15 * 14 = 210 In this program, we ask the user to choose the desired operation. Options 1, 2, 3 and 4 are
valid. Two numbers are taken and an ConclusionThe concepts discussed in this tutorial should help you build your own functions using Python by adding functionality and operability to the same. This will be very handy when you are trying to create an application by making the process easy and makes it suited for your personal needs. Now, you should also be able to use these Python functions to develop applications easily with the help of Python directly. After reading this blog on Python Functions, I am pretty sure you want to know more about Python. To know more about Python you can refer the following blogs:
To get in-depth knowledge on Python along with its various applications, you can enroll now for live Python course training with 24/7 support and lifetime access. I hope you have enjoyed this post on Python Functions. If you have any questions regarding this tutorial, please let me know in the comments. What are 4 types of function in Python?Types Of Python Functions
Python Built-in Functions. Python Recursion Functions. Python Lambda Functions. Python User-defined Functions.
What are the 3 different function in Python?There are three functions in python that provide vast practicality and usefulness when programming. These three functions, which provide a functional programming style within the object-oriented python language, are the map(), filter(), and reduce() functions.
What are two types of functions in Python?Python function types
There are two basic types of functions: built-in functions and user defined functions. The built-in functions are part of the Python language; for instance dir , len , or abs . The user defined functions are functions created with the def keyword.
What are the different functions in Python?Python Built-in Functions. print( ) function.. type( ) function.. input( ) function.. abs( ) function.. pow( ) function.. dir( ) function.. sorted( ) function.. max( ) function.. |