In programming, a function is a label or name assigned to a piece of code. You can call that code any number of times by using the name. It is quite easy to define a function in Python using the “def” keyword. Before we get into the details of creating functions, first understand a little more about them.<\/p>\n\n\n\n
What is a Function in Programming?<\/h3>\n\n\n\n
A function in Python is an independent and reusable block of code that you can call any number of times from any place in a program. It is an essential tool for programmers to split<\/a> a big project into smaller modules. Here are some key points to consider.<\/p>\n\n\n\n 1.<\/strong> They are the core building blocks of any programming language that a programmer must learn to use. Python provides several built-in methods for direct use and also allows you to define your custom functions.<\/p>\n\n\n\n 2.<\/strong> A function in Python is a logical unit of code containing a sequence of statements indented under a name given using the “def” keyword.<\/p>\n\n\n\n 3.<\/strong> Functions allow you to create a logical division of a big project into smaller modules. They make your code more manageable and extensible.<\/p>\n\n\n\n 4.<\/strong> While programming, a function prevents you from adding duplicate code and promotes reusability.<\/p>\n\n\n\n Let’s now quickly see what else are we going to learn from this tutorial.<\/p>\n\n\n\n The syntax of a Python function is as follows.<\/p>\n\n\n\n Single line function:<\/strong><\/p>\n\n\n\n Python function with docstring:<\/strong><\/p>\n\n\n\n Nested Python function:<\/strong><\/p>\n\n\n\n Please read the below notes to understand the purpose of the “def” keyword in Python.<\/p>\n\n\n\n Example :<\/strong><\/p>\n\n\n\n By using the def keyword, you learned to create the blueprint of a function that has a name, parameters to pass, and a body with valid Python statements<\/a>.<\/p>\n\n\n\n The next step is to execute it. You can do so by calling it from the Python script, inside a function, or directly from the Python shell.<\/p>\n\n\n\n To call a function, you need to specify the function name with relevant parameters, and that’s it.<\/p>\n\n\n\n Follow the below example to learn how to call a function in Python.<\/p>\n\n\n It’s a simple example where a function “typeOfNum()” has nested functions to decide if a number is either odd or even.<\/p>\n\n\n\n In Python, function polymorphism is possible as we don’t specify the argument types while creating functions.<\/p>\n\n\n\n Example :<\/strong><\/p>\n\n\n\n The above example clarifies that we can pass any two objects to the product() function which supports the ‘*’ operator.<\/p>\n\n\n\n The concept above we’ve explained is known as polymorphism. Some points which you should remember are as follows.<\/p>\n\n\n\n We often use the terms parameters and arguments<\/strong> interchangeably. However, there is a slight difference between them<\/strong>.<\/p>\n\n\n\n Parameters<\/strong> are the variables used in the function definition whereas arguments<\/strong> are the values we pass to the function parameters.<\/p>\n\n\n\n Python supports different variations of passing parameters to a function. Before we discuss each of them, you should read the following notes.<\/p>\n\n\n\n After execution, the above code prints the following.<\/p>\n\n\n\n After execution, the above code prints the following.<\/p>\n\n\n\n The standard arguments are those that you pass as specified in a Python function definition. It means without changing their order and without skipping any of them.<\/p>\n\n\n\n Executing the above code throws the below error as we’ve not passed the single argument required.<\/p>\n\n\n\n When you assign a value to the parameter (such as param=value) and pass it to the function (like fn(param=value)), then it turns into a keyword argument.<\/p>\n\n\n\n If you pass the keyword arguments to a function, then Python determines it through the parameter name used in the assignment.<\/p>\n\n\n\n See the below example.<\/p>\n\n\n\n While using keyword arguments, you should make sure that the name in the assignment should match the one in the function definition. Otherwise, Python throws the TypeError as shown below.<\/p>\n\n\n\n The above function call causes the following error.<\/p>\n\n\n\n Python functions allow setting the default values for parameters in the function definition. We refer to them as the default arguments.<\/p>\n\n\n\n The callee uses these default values when the caller doesn’t pass them in the function call.<\/p>\n\n\n\n The below example will help you clearly understand the concept of default arguments.<\/p>\n\n\n\n Here, the parameter “is_leap_year” is working as a default argument. If you don’t pass any value, it assumes the False default.<\/p>\n\n\n\n The output of the above code is:<\/p>\n\n\n\n You may encounter situations when you have to pass additional arguments to a Python function. We refer to them as variable-length arguments.<\/p>\n\n\n\n Python’s print()<\/a> is itself an example of such a function that supports variable arguments.<\/p>\n\n\n\n To define a function with variable arguments, you need to prefix the parameter with an asterisk (*) sign. Follow the below syntax.<\/p>\n\n\n\n Check out the below example for better clarity.<\/p>\n\n\n\n The output of the above code goes like this.<\/p>\n\n\n\n Please note that you can choose to have a formal argument or not in the function definition along with the variable arguments.<\/p>\n\n\n\n You may choose to skip the variable arguments while calling the function. In such a case, the tuple<\/a> would remain empty.<\/p>\n\n\n\n Two types of variables can exist in a Python function. Let’s check out.<\/p>\n\n\n\n A local variable has visibility only inside a code block such as the function def. They are available only while the function is executing. Check out the below example of using local variables.<\/p>\n\n\n\n In this example, we try to access local variables outside the function body which results in the NameError.<\/p>\n\n\n\n The function\u2019s local variables don’t retain values between calls. The names used inside a def do not conflict with variables outside the def, even if you’ve used the same names elsewhere.<\/p>\n\n\n\n In Python, the variables assignment can occur at three different places.<\/p>\n\n\n\n The global keyword is a statement in Python. It enables variables (names) to retain changes that live outside a def, at the top level of a module file.<\/p>\n\n\n\n In a single global statement, you can specify one or more names separated by commas.<\/p>\n\n\n\n All the listed names are attached to the enclosing module\u2019s scope when assigned or referenced within the function body.<\/p>\n\n\n\n Check the below example.<\/p>\n\n\n\n In the above code, ‘x’ is a global variable that will retain any change in its value made in the function. Another variable ‘y’ has local scope and won’t carry forward the change.<\/p>\n\n\n\n Let’s now see how a globally declared name behaves in two different Python functions.<\/p>\n\n\n\n In the next example, let’s see how global behaves with the import statement.<\/p>\n\n\n\n Here, we have the following three scripts:<\/p>\n\n\n\n While creating and calling the functions, you should know about the following rules.<\/p>\n\n\n\n It is essential to understand how name resolution works in case of a def statement.<\/p>\n\n\n\n Here are a few points you should keep in mind.<\/p>\n\n\n\n To gain more understanding, run through the below example.<\/p>\n\n\n\n After uncommenting the first “var” assignment, the output is:<\/p>\n\n\n\n Next, after uncommenting the second “var” assignment as well, the output is:<\/p>\n\n\n\n Finally, if we uncomment the last “var” assignment, then the result is as follows.<\/p>\n\n\n\n Python functions can access names in all available enclosing def statements.<\/p>\n\n\n\n Check the below example.<\/p>\n\n\n\n The scope lookup remains in action even if the enclosing function has already returned.<\/p>\n\n\n\n The output is as follows.<\/p>\n\n\n\n In Python functions, you can add the “return” statement to return a value.<\/p>\n\n\n\n Usually, the functions return a single value. But if required, Python allows returning multiple values by using the collection types such as using a tuple or list<\/a>.<\/p>\n\n\n\n This feature works like the call-by-reference by returning tuples and assigning the results back to the original argument names in the caller.<\/p>\n\n\n\n The above code gives the following output.<\/p>\n\n\n\n We have compiled a few distinct Python function examples. Check these and try to practice with them.<\/p>\n\n\n\n Check out a general function call example.<\/strong><\/p>\n\n\n\n The output is as follows.<\/p>\n\n\n\n Next is an example of the recursive function.<\/strong><\/p>\n\n\n\n The output is as follows.<\/p>\n\n\n\n Also Read: Higher Order Functions in Python<\/a><\/p>\n\n\n\n Yes, Python treats everything as an object and functions are no different.<\/p>\n\n\n\n You can assign a function object to any other name.<\/strong><\/p>\n\n\n\n The output is:<\/p>\n\n\n\n You can even pass the function object to other functions.<\/strong><\/p>\n\n\n\n The output is:<\/p>\n\n\n\n You can also embed a function object in data structures.<\/strong><\/p>\n\n\n\n The output is:<\/p>\n\n\n\n You can return a function object from another function.<\/strong><\/p>\n\n\n\n The output is:<\/p>\n\n\n\n Python functions also have attributes.<\/p>\n\n\n\n The output is:<\/p>\n\n\n\n You can utilize the function attributes to archive state information instead of using any of the globals or nonlocal names. Unlike the nonlocals, attributes are accessible anywhere the function itself is, even from outside its code.<\/p>\n\n\n\n We’ve covered the essential concept of a Python function in this tutorial. You should now try to use these concepts in your routine programming tasks.<\/p>\n\n\n\n Before you leave. share this post on social media (Linkedin<\/a>\/Twitter<\/a>). It would help us run this site free for our users.<\/p>\n\n\n\n Enjoy coding, This tutorial walks you through the concept of a Python function. You\u2019ll learn how to create your own functions and use them to write modular code in Python Simple Steps to Create a Python Function In programming, a function is a label or name assigned to a piece of code. You can call that code […]<\/p>\n","protected":false},"author":321,"featured_media":6782,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","jetpack_post_was_ever_published":false},"categories":[92],"tags":[],"class_list":{"0":"post-6780","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-python-programming-tutorials"},"jetpack_featured_media_url":"https:\/\/techbeamers.com\/wp-content\/uploads\/2018\/09\/Python-Function-A-Complete-Overview.png","_links":{"self":[{"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/posts\/6780","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/users\/321"}],"replies":[{"embeddable":true,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/comments?post=6780"}],"version-history":[{"count":1,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/posts\/6780\/revisions"}],"predecessor-version":[{"id":23565,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/posts\/6780\/revisions\/23565"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/media\/6782"}],"wp:attachment":[{"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/media?parent=6780"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/categories?post=6780"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techbeamers.com\/wp-json\/wp\/v2\/tags?post=6780"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Create a Python Function – Syntax<\/h3>\n\n\n\n
def single_line(): statement<\/pre>\n\n\n\n
def fn(arg1, arg2,...):\n \"\"\"docstring\"\"\"\n statement1\n statement2<\/pre>\n\n\n\n
def fn(arg1, arg2,...):\n \"\"\"docstring\"\"\"\n statement1\n statement2\n def fn_new(arg1, arg2,...):\n statement1\n statement2\n ...\n ...<\/pre>\n\n\n\n
<\/a>Why is the ‘def’ Statement Used in a Python Function?<\/h4>\n\n\n\n
\n
if test:\n def test(): # First definition\n ...\n else:\n def test(): # Alternate definition\n ...\n ...<\/pre>\n\n\n\n
<\/a>How to Call a Function in Python?<\/h4>\n\n\n\n
![\"Python](\"https:\/\/techbeamers.com\/wp-content\/uploads\/2018\/09\/Python-function-for-modular-programming.png\")
<\/a><\/figure>\n<\/div>\n\n\n<\/a>Example of a Function Call<\/h4>\n\n\n\n
def typeOfNum(num): # Function header\n # Function body\n if num % 2 == 0:\n def message():\n print(\"You entered an even number.\")\n else:\n def message():\n print(\"You entered an odd number.\")\n message()\n# End of function\n\ntypeOfNum(2) # call the function\ntypeOfNum(3) # call the function again<\/pre>\n\n\n\n
<\/a>Polymorphism in Python<\/h3>\n\n\n\n
\n
def product(x, y) : return x * y\nprint(product(4, 9)) # function returns 36\nprint(product('Python!', 2)) # function returns\n # Python!Python!\nprint(product('Python 2 or 3?', '3')) # TypeError occurs<\/pre>\n\n\n\n\n
<\/a>Parameters in a Function<\/h3>\n\n\n\n
\n
<\/a>Example: Immutable vs. Mutable<\/h4>\n\n\n\n
def test1(a, b) :\n a = 'Garbage' # 'a' receives an immutable object\n b[0] = 'Python' # 'b' receives a list object\n # list is mutable\n # it can undergo an in place change\ndef test2(a, b) :\n a = 'Garbage 2'\n b = 'Python 3' # 'b' now is made to refer to new\n # object and therefore argument 'y'\n # is not changed\n\narg1 = 10\narg2 = [1, 2, 3, 4]\ntest1(arg1, arg2)\nprint(\"After executing test 1 =>\", arg1, arg2)\ntest2(arg1, arg2)\nprint(\"After executing test 2 =>\", arg1, arg2)<\/pre>\n\n\n\n
After executing test 1 => 10 ['Python', 2, 3, 4]\nAfter executing test 2 => 10 ['Python', 2, 3, 4]<\/pre>\n\n\n\n
Example: Mutable Arguments<\/h4>\n\n\n\n
def test1(a, b) :\n a = 'Garbage'\n b[0] = 'Python'\n\narg1 = 10\narg2 = [1, 2, 3, 4]\n\nprint(\"Before test 1 =>\", arg1, arg2)\ntest1(arg1, arg2[:]) # Create an explicit copy of mutable object\n # 'y' in the function.\n # Now 'b' in test1() refers to a\n # different object which was initially a\n # copy of 'arg2'\n \nprint(\"After test 1 =>\", arg1, arg2)<\/pre>\n\n\n\n
Before test 1 => 10 [1, 2, 3, 4]\nAfter test 1 => 10 [1, 2, 3, 4]<\/pre>\n\n\n\n
<\/a>Standard Arguments<\/h4>\n\n\n\n
def fn(value):\n print(value)\n return\n\nfn()<\/pre>\n\n\n\n
TypeError: fn() missing 1 required positional argument: 'value'<\/pre>\n\n\n\n
<\/a>Keyword-based Arguments<\/h4>\n\n\n\n
def fn(value):\n print(value)\n return\n\nfn(value=123) # output => 123\nfn(value=\"Python!\") # output => Python!<\/pre>\n\n\n\n
fn(value1=\"Python!\") # wrong name used in the keyword argument<\/pre>\n\n\n\n
TypeError: fn() got an unexpected keyword argument 'value1'<\/pre>\n\n\n\n
<\/a>Arguments with Default Values<\/h4>\n\n\n\n
def daysInYear(is_leap_year=False):\n if not is_leap_year:\n print(\"365 days\")\n else:\n print(\"366 days\")\n return\n\ndaysInYear()\ndaysInYear(True)<\/pre>\n\n\n\n
365 days\n366 days<\/pre>\n\n\n\n
<\/a>Variable Arguments<\/h4>\n\n\n\n
def fn([std_args,] *var_args_tuple ):\n \"\"\"docstring\"\"\"\n function_body\n return_statement<\/pre>\n\n\n\n
def inventory(category, *items):\n print(\"%s [items=%d]:\" % (category, len(items)), items)\n for item in items:\n print(\"-\", item)\n return\n\ninventory('Electronics', 'tv', 'lcd', 'ac', 'refrigerator', 'heater')\ninventory('Books', 'python', 'java', 'c', 'c++')<\/pre>\n\n\n\nElectronics [items=5]: ('tv', 'lcd', 'ac', 'refrigerator', 'heater')\n- tv\n- lcd\n- ac\n- refrigerator\n- heater\nBooks [items=4]: ('python', 'java', 'c', 'c++')\n- python\n- java\n- c\n- c++<\/pre>\n\n\n\nUse Variables in Functions<\/h3>\n\n\n\n
<\/a>Local Variables Inside a Function<\/h4>\n\n\n\n
def fn(a, b) : \n temp = 1\n for iter in range(b) :\n temp = temp*a\n return temp\n\nprint(fn(2, 4))\n\nprint(temp) # error : can not access 'temp' out of scope of function 'fn'\nprint(iter) # error : can not access 'iter' out of scope of function 'fn'<\/pre>\n\n\n\n
\n
<\/a>Global Variables in a Function<\/h4>\n\n\n\n
x = 5\ny = 55\ndef fn() :\n global x\n x = [3, 7]\n y = [1, 33, 55]\n # a local 'y' is assigned and created here\n # whereas, 'x' refers to the global name\nfn()\nprint(x, y)<\/pre>\n\n\n\n
foo = 99\n\ndef fn1() :\n foo = 'new' # new local foo created\n\ndef fn2() :\n global foo\n foo = 'update' # value of global foo changes<\/pre>\n\n\n\n
\n
# mod_global.py\ndef fn1() :\n global x\t\n x = [1,2] ; y = [20, 200]\n # a local 'y' is created \u2013 availableonly within 'f1'\n # 'x' can be accessed anywhere after a call to 'f1'\nfn1()\ntry :\n print(x, y) # name 'y' is not defined \u2013 error\nexcept Exception as ex:\n print('y ->', ex)\n print('x ->', x)<\/pre>\n\n\n\n# test1.py\nimport mod_global\nprint('test1 ->', mod_global.x)<\/pre>\n\n\n\n# test2.py\nfrom mod_global import *\nprint('test2 ->', x)<\/pre>\n\n\n\nGeneral Function Rules<\/h3>\n\n\n\n
<\/a>Name Resolution in a Python Function<\/h4>\n\n\n\n
\n
\n
#var = 5\ndef fn1() :\n #var = [3, 5, 7, 9]\n def fn2() :\n #var = (21, 31, 41)\n print(var)\n fn2()\nfn1()\t# uncomment var assignments one-by-one and check the output\nprint(var)<\/pre>\n\n\n\n
5\n5<\/pre>\n\n\n\n
[3, 5, 7, 9]\n5<\/pre>\n\n\n\n
(21, 31, 41)\n5<\/pre>\n\n\n\n
<\/a>Variable Scope in Functions<\/h4>\n\n\n\n
X = 101 # global scope name - unused\ndef fn1():\n X = 102 # Enclosing def local\n def fn2():\n print(X) # Reference made in nested def\n fn2() # Prints 102: enclosing def local\nfn1()<\/pre>\n\n\n\n
def fn1():\n print('In fn1')\n X = 100\n def fn2(): \n print('In fn2')\n print(X) # Remembers X in enclosing def scope\n return fn2 # Return fn2 but don't call it\naction = fn1() # Make, return function\naction() # Call fn2() now: prints 100<\/pre>\n\n\n\nIn fn1\nIn fn2\n100<\/pre>\n\n\n\n
<\/a>Return Values from a Python Function<\/h4>\n\n\n\n
def returnDemo(val1, val2) :\n val1 = 'Windows'\n val2 = 'OS X'\n return val1, val2 # return multiple values in a tuple\n\nvar1 = 4\nvar2 = [2, 4, 6, 8]\n\nprint(\"before return =>\", var1, var2)\nvar1, var2 = returnDemo(var1, var2)\nprint(\"after return =>\", var1, var2)<\/pre>\n\n\n\n
before return => 4 [2, 4, 6, 8]\nafter return => Windows OS X<\/pre>\n\n\n\n
<\/a>Python Function Examples<\/h3>\n\n\n\n
def getMin(*varArgs) :\n min = varArgs[0]\n for i in varArgs[1:] :\n if i < min :\n min = i\n return min\n\nmin = getMin(21, -11, 17, -23, 6, 5, -89, 4, 9)\nprint(min)<\/pre>\n\n\n\n
-89<\/pre>\n\n\n\n
def calcFact(num) :\n if(num != 1) :\n return num * calcFact(num-1)\n else :\n return 1\n\nprint(calcFact(4))<\/pre>\n\n\n\n
24<\/pre>\n\n\n\n
<\/a>Python Functions as Objects<\/h3>\n\n\n\n
def testFunc(a, b) : print('testFunc called')\nfn = testFunc\nfn(22, 'bb')<\/pre>\n\n\n\ntestFunc called<\/pre>\n\n\n\n
def fn1(a, b) : print('fn1 called')\ndef fn2(fun, x, y) : fun(x, y)\nfn2(fn1, 22, 'bb')<\/pre>\n\n\n\nfn1 called<\/pre>\n\n\n\n
def fn1(a) : print('fn1', a)\ndef fn2(a) : print('fn2', a)\n\nlistOfFuncs = [(fn1, \"First function\"), (fn2, \"Second function\")]\nfor (f, arg) in listOfFuncs : f(arg)<\/pre>\n\n\n\nfn1 First function\nfn2 Second function<\/pre>\n\n\n\n
def FuncLair(produce) : \n def fn1() : print('fn1 called')\n def fn2() : print('fn2 called')\n def fn3() : print('fn3 called')\n if produce == 1 : return fn1\n elif produce == 2 : return fn2\n else : return fn3\n\nf = FuncLair(2) ; f()<\/pre>\n\n\n\nfn2 called<\/pre>\n\n\n\n
<\/a>Function Attributes<\/h3>\n\n\n\n
\n
def testFunc():\n print(\"I'm just a test function.\")\n\ntestFunc.attr1 = \"Hello\"\ntestFunc.attr2 = 5\ntestFunc()\nprint(dir(testFunc))<\/pre>\n\n\n\n
I'm just a test function.\n['__annotations__', '__call__', '__class__', '__closure__', '__code__', '__defaults__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__get__', '__getattribute__', '__globals__', '__gt__', '__hash__', '__init__', '__kwdefaults__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__qualname__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', 'attr1', 'attr2']<\/pre>\n\n\n\n
TechBeamers.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"