Python Functions and Data Structures PDF

Functions, Scoping and Abstraction Unit-2 Content- Declaring, Defining and Invoking a Function, Function Specification, Function arguments: keyword, default, positional, variable-length Local v/s Global variables Types of functions in python- There are three types of functions...

Functions, Scoping and Abstraction Unit-2 Content- Declaring, Defining and Invoking a Function, Function Specification, Function arguments: keyword, default, positional, variable-length Local v/s Global variables Types of functions in python- There are three types of functions in Python: Built-in functions, such as help() to ask for help, min() to get the minimum value, print() to print an object to the terminal etc. User-Defined Functions (UDFs), which are functions that users create to help them out; Anonymous functions, which are also called lambda functions because they are not declared with the standard def keyword. Declaring, Defining and Invoking a Function- The four steps to defining a function in Python are the following: Use the keyword def to declare the function and follow this up with the function name. Add parameters to the function: they should be within the parentheses of the function. End your line with a colon. Add statements that the functions should execute. End your function with a return statement if the function should output something. Without the return statement, your function will return an object None. Continue.. Syntax of Python Function def name_of_function( parameters ): ""“Python Programming""" # code block Declaring and defining a user-defined function- We will define a function that when called will return the square of the number passed to it as an argument. def square( num ): """This function computes the square of the number. """ return num**2 ans= square(9) print( "The square of the number is: ", ans) Calling a Function A function is defined by using the def keyword and giving it a name, specifying the arguments that must be passed to the function, and structuring the code block. After a function's fundamental framework is complete, we can call it from anywhere in the program. Example- # Defining a function def a_function( string ): "This prints the value of length of string" return len(string) # Calling the function we defined print( "Length of the string Functions is: ", a_function( "Functions" ) ) print( "Length of the string Python is: ", a_function( "Python" ) ) Function Arguments The following are the types of arguments that we can use to call a function: Default arguments Keyword arguments Required arguments Variable-length arguments Default Arguments A default argument is a kind of parameter that takes as input a default value if no value is supplied for the argument when the function is called. Default arguments are demonstrated in the following instance. # defining a function def function( num1, num2 = 40 ): print("num1 is: ", num1) print("num2 is: ", num2) # Calling the function and passing only one argument print( "Passing one argument" ) function(10)  Continue.. # Now giving two arguments to the function print( "Passing two arguments" ) function(10,30) Output- Passing one argument num1 is: 10 num2 is: 40 Passing two arguments num1 is: 10 num2 is: 30 Keyword Arguments The arguments in a function called are connected to keyword arguments. If we provide keyword arguments while calling a function, the user uses the parameter label to identify which parameters value it is. # Defining a function def function( num1, num2 ): print("num1 is: ", num1) print("num2 is: ", num2) # Calling function and passing arguments without using keyword print( "Without using keyword" ) function( 50, 30) # Calling function and passing arguments using keyword print( "With using keyword" ) function( num2 = 50, num1 = 30) Continue.. Output: Without using keyword num1 is: 50 num2 is: 30 With using keyword num1 is: 30 num2 is: 50 Required Arguments The arguments given to a function while calling in a pre-defined positional sequence are required arguments. The count of required arguments in the method call must be equal to the count of arguments provided while defining the function. We must send two arguments to the function function() in the correct order, or it will return a syntax error, as seen below. Example- # Function definition is here def printme( str ): "This prints a passed string into this function" print str return; # Now you can call printme function printme() Output-TypeError: printme() takes exactly 1 argument (0 given) Variable-Length Arguments We can use special characters in Python functions to pass as many arguments as we want in a function. There are two types of characters that we can use for this purpose: *args -These are Non-Keyword Arguments below is example- def func(*args): # # here is the body of the function # **kwargs - These are Keyword Arguments. Example- def sum(*args): resultfinal = 0 #beginning of for loop for arg in args: resultfinal = resultfinal + arg return resultfinal #printing the values print(sum(10, 20)) # 30 print(sum(10, 20, 30)) # 60 print(sum(10, 20, 2)) # 32 Lamda Function- Lambda Functions in Python are anonymous functions, implying they don't have a name. The def keyword is needed to create a typical function in Python, as we already know. We can also use the lambda keyword in Python to define an unnamed function. Syntax of Python Lambda Function lambda arguments: expression Example of Lambda Function in Python add = lambda num: num + 4 print( add(6) ) The lambda function is "lambda num: num+4" in the given programme. The parameter is num, and the computed and returned equation is num +4. There is no label for this function. It generates a function object associated with the "add" identifier. We can now refer to it as a standard function. Local and Global variables- Global variables are those which are not defined inside any function and have a global scope whereas local variables are those which are defined inside a function and its scope is limited to that function only. In other words, we can say that local variables are accessible only inside the function in which it was initialized whereas the global variables are accessible throughout the program and inside every function. Example (local Variable)- def f(): # local variable s = “Python Programming" print(s) # Driver code f() Example (global Variable)- # This function uses global variable s def f(): print("Inside Function", s) # Global scope s = “Python Programming" f() print("Outside Function", s) Python Datatype- Immutable data structure- These datatypes cannot be changed once declared. They consist of Numbers, Strings, Tuples. Numbers Python has four types of literals: Integer, Long Integer, Floating number and Complex. Even Python does not require the datatype to the variable in the declaration. Python will automatically convert one type to another datatype. Example- Let’s see with an example Immutable data structure- Immutable data types e.g tuples and string are the data types that cannot be further changed or modified once executed in the program. Immutable data structures are very handy when you want to prevent multiple people from modifying a piece of data in parallel programming at the same time. Tuples in python Tuples are the collection of python objects separated by commas. Tuples are similar to the list in terms of indexing, repetition, and nested objects. But here, the list is mutable and can be changed further according to the need of the programmer. Example- Python program to change the value inside the tuple # Python contains the immutable tuple t = ( 0, 1, 2, 3, 4, 5 ) print(t) t=3 print(t) Output-TypeError: 'tuple' object does not support item assignment. Example- Python program to delete the value inside the tuple # Python contains the immutable tuples t=(12, 13, 15, 2, 7, 9) print(type(t)) print(t) del t print(t) Output-TypeError: 'tuple' object doesn't support item deletion. Example- Python program to delete the whole tuple t=(12, 13, 15, 2, 7, 9) print(type(t)) print(t) del t print(t) Example- Immutable data Structure- String in Python- Python string is the collection of the characters surrounded by single quotes, double quotes, or triple quotes. The computer does not understand the characters; internally, it stores manipulated character as the combination of the 0's and 1's. Each character is encoded in the ASCII or Unicode character. So we can say that Python strings are also called the collection of Unicode characters. In Python, strings can be created by enclosing the character or the sequence of characters in the quotes. Python allows us to use single quotes, double quotes, or triple quotes to create the string. Example- str = "Hi Python !" Here, if we check the type of the variable str using a Python script print(type(str)), then it will print a string (str). Example- #Using single quotes str1 = 'Hello Python' print(str1) #Using double quotes str2 = "Hello Python" print(str2) #Using triple quotes str3 = '''''Triple quotes are generally used for represent the multiline or docstring''' print(str3) Output: Hello Python Hello Python Triple quotes are generally used for represent the multiline or docstring Example- In Python, the slice operator [] is used to access the individual characters of the string. However, we can use the : (colon) operator in Python to access the substring from the given string. Consider the following example. Example- Example- Reassigning Strings A string can only be replaced with new string since its content cannot be partially replaced. Strings are immutable in Python. str = "HELLO" str = "h" print(str) TypeError: 'str' object does not support item assignment Example- str = "HELLO" print(str) str = "hello" print(str) Output: HELLO hello Deleting the String str1 = “Python" del str1 print(str1) Output: NameError: name 'str1' is not defined String Operators Operator Description + It is known as concatenation operator used to join the strings given either side of the operator. * It is known as repetition operator. It concatenates the multiple copies of the same string. [] It is known as slice operator. It is used to access the sub-strings of a particular string. [:] It is known as range slice operator. It is used to access the characters from the specified range. in It is known as membership operator. It returns if a particular sub-string is present in the specified string. not in It is also a membership operator and does the exact reverse of in. It returns true if a particular substring is not present in the specified string. r/R It is used to specify the raw string. Raw strings are used in the cases where we need to print the actual meaning of escape characters such as "C://python". To define any string as a raw string, the character r or R is followed by the string. % It is used to perform string formatting. It makes use of the format specifiers used in C programming like %d or %f to map their values in python. We will discuss how formatting is done in python. Python String functions- Mutable Data Structure- These data types can be changed anytime. They consist of Lists, Dictionary, and Sets. Lists in python- A list is a mutable Python data type that is defined within the []-square brackets. This group of values can be easily changed. First, we will define a list variable having multiple datatypes of values in it. Check-in In. There are also some operations applied on the list, Python List functions- There are also some operations applied on the list, Concatenation Used to add two or more lists/elements together, as we learned in tuples. Repetition It’s used to duplicate a list a given number of times. Slicing Same as tuples, if you want the specific set of the list mentioned the starting index number and ending number+1, and it will return the sliced list Python List functions- Append For adding value to a list. Extend It’s another function as concatenation. Insert By using the index value you can specify any value in between the list. Example- Example- Mutable Data Structure- Dictionary in python- Python Dictionary is a group of values within a {} -curly braces. While defining a value, there are two elements: Key, and its Value, or we can say like we define an index for each element. Dictionary Functions- emptyDictionary There is no value inside the dictionary. Integer key Key values in the dictionary are integer only. Mixed key There are mixed types of keys used in the Dictionary. Pairing This is a sequence where each item has a pair. Continue.. Accessing dictionary You can access the dictionary by directly using a key. len() If I want to find the Length of the Dictionary, I will use this function. It will return the output in numeric as the number of elements is there in Dictionary. value() Returns all the values inside the dictionary. key() If I want to find the key to my dictionary, then I will choose this function. Example- Example- Mutable data structure- Sets Sets- Sets are the unordered collection of items within the curly braces {}. Every element in the set is unique and we don’t need to define the key-value to that element. For example, pySet={1,2,3}: All the elements are different and they don’t consist of any key-value. It’s the only difference between set and dictionary. Sets Functions- Creating a set Union When we create two sets, it returns a common value from both sets. Intersection Returns the common element from both sets. Difference Omits all common values from both sets. It will return only that value which is unique and written in the first set. Example- Variable length keyword arguments #program to demonstrate **kwargs in python def my_func(**kwargs): for k,v in kwargs.items(): print("%s=%s"%(k,v)) #passing the parameters in function my_func(a_key="Let",b_key="us",c_key="study",d_key="Data Science",e_key="and",f_key="Blockchain") Output: a_key=Let b_key=us c_key=study d_key=Data Science e_key=and f_key=Blockchain