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Python Tutorials - Elevate You…
1. Introduction to Python
2. Features of Python
3. How to install python in windows
4. How to Install Python on macOS
5. Install Python on Linux
6. Hello World Program in Python
7. Python Variables
8. Global Variable in Python
9. Python Keywords and Identifiers
10. Assert Keyword in Python
11. Comments in Python
12. Escape Sequence in Python
13. Print In Python
14. Python-if-else-statement
15. Python for Loop
16. Nested for loop in Python
17. While Loop in Python
18. Python’s do-while Loop
19. Break in Python
20. Break Pass and Continue Statement in Python
21. Python Try Except
22. Data Types in Python
23. Float in Python
24. String Methods Python
25. List in Python
26. List Methods in Python
27. Tuples in Python
28. Dictionary in Python
29. Set in Python
30. Operators in Python
31. Boolean Operators in Python
32. Arithmetic Operators in Python
33. Assignment Operator in Python
34. Bitwise operators in Python
35. Identity Operator in Python
36. Operator Precedence in Python
37. Functions in Python
38. Lambda and Anonymous Function in Python
39. Range Function in Python
40. len() Function in Python
41. How to Use Lambda Functions in Python?
42. Random Function in Python
43. Python __init__() Function
44. String Split function in Python
45. Round function in Python
46. Find Function in Python
47. How to Call a Function in Python?
48. Python Functions Scope
49. Method Overloading in Python
50. Method Overriding in Python
51. Static Method in Python
52. Python List Index Method
53. Python Modules
54. Math Module in Python
55. Module and Package in Python
56. OS module in Python
57. Python Packages
58. OOPs Concepts in Python
59. Class in Python
60. Abstract Class in Python
61. Object in Python
62. Constructor in Python
63. Inheritance in Python
64. Multiple Inheritance in Python
65. Encapsulation in Python
66. Data Abstraction in Python
67. Opening and closing files in Python
68. How to open JSON file in Python
69. Read CSV Files in Python
70. How to Read a File in Python
71. How to Open a File in Python?
72. Python Write to File
73. JSON Python
74. Python JSON – How to Convert a String to JSON
75. Python JSON Encoding and Decoding
76. Exception Handling in Python
77. Recursion in Python
78. Python Decorators
79. Python Threading
80. Multithreading in Python
81. Multiprocеssing in Python
82. Python Regular Expressions
83. Enumerate() in Python
84. Map in Python
85. Filter in Python
86. Eval in Python
87. Difference Between List, Tuple, Set, and Dictionary in Python
88. List to String in Python
89. Linked List in Python
90. Length of list in Python
91. Python List remove() Method
92. How to Add Elements in a List in Python
93. How to Reverse a List in Python?
94. Difference Between List and Tuple in Python
95. List Slicing in Python
96. Sort in Python
97. Merge Sort in Python
98. Selection Sort in Python
99. Sort Array in Python
100. Sort Dictionary by Value in Python
101. Datetime Python
102. Random Number in Python
103. 2D Array in Python
104. Abs in Python
105. Advantages of Python
106. Anagram Program in Python
107. Append in Python
108. Applications of Python
109. Armstrong Number in Python
110. Assert in Python
111. Binary Search in Python
112. Binary to Decimal in Python
113. Bool in Python
114. Calculator Program in Python
115. chr in Python
116. Control Flow Statements in Python
117. Convert String to Datetime Python
118. Count in python
119. Counter in Python
120. Data Visualization in Python
121. Datetime in Python
122. Extend in Python
123. F-string in Python
124. Fibonacci Series in Python
125. Format in Python
126. GCD of Two Numbers in Python
127. How to Become a Python Developer
128. How to Run Python Program
129. In Which Year Was the Python Language Developed?
130. Indentation in Python
131. Index in Python
132. Interface in Python
133. Is Python Case Sensitive?
134. Isalpha in Python
135. Isinstance() in Python
136. Iterator in Python
137. Join in Python
138. Leap Year Program in Python
139. Lexicographical Order in Python
140. Literals in Python
141. Matplotlib
142. Matrix Multiplication in Python
143. Memory Management in Python
144. Modulus in Python
145. Mutable and Immutable in Python
146. Namespace and Scope in Python
147. OpenCV Python
148. Operator Overloading in Python
149. ord in Python
150. Palindrome in Python
151. Pass in Python
152. Pattern Program in Python
153. Perfect Number in Python
154. Permutation and Combination in Python
155. Prime Number Program in Python
156. Python Arrays
157. Python Automation Projects Ideas
158. Python Frameworks
159. Python Graphical User Interface GUI
160. Python IDE
161. Python input and output
Now Reading
162. Python Installation on Windows
163. Python Object-Oriented Programming
164. Python PIP
165. Python Seaborn
166. Python Slicing
167. type() function in Python
168. Queue in Python
169. Replace in Python
170. Reverse a Number in Python
171. Reverse a string in Python
172. Reverse String in Python
173. Stack in Python
174. scikit-learn
175. Selenium with Python
176. Self in Python
177. Sleep in Python
178. Speech Recognition in Python
179. Split in Python
180. Square Root in Python
181. String Comparison in Python
182. String Formatting in Python
183. String Slicing in Python
184. Strip in Python
185. Subprocess in Python
186. Substring in Python
187. Sum of Digits of a Number in Python
188. Sum of n Natural Numbers in Python
189. Sum of Prime Numbers in Python
190. Switch Case in Python
191. Python Program to Transpose a Matrix
192. Type Casting in Python
193. What are Lists in Python?
194. Ways to Define a Block of Code
195. What is Pygame
196. Why Python is Interpreted Language?
197. XOR in Python
198. Yield in Python
199. Zip in Python
In programming, the ability to effectively handle Python input and output operations is paramount for crafting efficient applications. As we navigate through the digital era, professionals often encounter situations where mastering these basic functionalities of Python proves indispensable. This tutorial aims to give the reader in-depth insights into Python's input/output dynamics, ensuring a holistic understanding.
The Python input and output ecosystem is vast, encompassing not only simple interactions but also complex file operations. This tutorial offers a structured exploration, from the foundational input() and print() functions to advanced file handling techniques, ensuring a comprehensive grasp of Python's I/O functionalities.
In Python, you can take input from the user using the input() function. The input() function reads a line of text entered by the user and returns it as a string. Here's how you can use it:
Code:
user_input = input("Enter something: ") # Display a prompt and wait for user input
print("You entered:", user_input) # Display the user's input
In this example:
The input() always returns a string. If you want to work with numerical values, you'll need to convert the string to the appropriate data type (e.g., int or float) using functions like int() or float():
Code:
user_input = input("Enter a number: ")
number = int(user_input) # Convert the user's input to an integer
print("You entered:", number)
In Python, you can get user input with a message by using the input() function along with a string that serves as the input prompt or message. Here's how you can do it:
Code:
user_input = input("Please enter your name: ")
print("Hello,", user_input)
In this example:
You can replace "Please enter your name: " with any custom message or prompt that you want to show to the user. Just make sure to enclose the message in double or single quotes within the input() function.
To receive an integer input from the user in Python, you can use the input() function to collect a string from the user and then convert it to an integer using the int() function. Here's an example:
Code:
user_input = input("Enter an integer: ") # Get user input as a string
try:
integer_value = int(user_input) # Convert the string to an integer
print("You entered:", integer_value)
except ValueError:
print("Invalid input. Please enter a valid integer.")
In this example:
This code ensures that the user provides a valid integer input and handles cases where the input is not a valid integer.
In Python, you can use the map() function to apply a given function to each element of one or more iterable objects (such as lists) and get the result as a map object. If you want to take multiple inputs from the user using the map() method, you can follow these steps:
Here's an example of how to take multiple integer inputs from the user using the map() method:
Code:
# Step 1: Take a single string input containing integers separated by space
input_string = input("Enter multiple integers separated by space: ")
# Step 2: Split the input string into individual values using space as the delimiter
input_values = input_string.split()
# Step 3: Use the map() function to convert the values to integers
integer_values = list(map(int, input_values))
# Display the result
print("You entered the following integers:", integer_values)
Here's an example of how to take multiple float inputs using the same approach:
Code:
# Step 1: Take a single string input containing floats separated by space
input_string = input("Enter multiple floats separated by space: ")
# Step 2: Split the input string into individual values using space as the delimiter
input_values = input_string.split()
# Step 3: Use the map() function to convert the values to floats
float_values = list(map(float, input_values))
# Display the result
print("You entered the following floats:", float_values)
This code allows you to take multiple inputs from the user and convert them to the desired data type using the map() function.
Taking List/Set Elements With the append() and add() methods
Taking inputs for a list using append():
Code:
# Initialize an empty list
my_list = []
# Define the number of elements you want to add
num_elements = int(input("Enter the number of elements in the list: "))
# Loop to take inputs and add them to the list
for i in range(num_elements):
element = input(f"Enter element {i + 1}: ")
my_list.append(element)
# Display the list
print("List:", my_list)
Taking inputs for a set using add():
Code:
# Initialize an empty set
my_set = set()
# Define the number of elements you want to add
num_elements = int(input("Enter the number of elements in the set: "))
# Loop to take inputs and add them to the set
for i in range(num_elements):
element = input(f"Enter element {i + 1}: ")
my_set.add(element)
# Display the set
print("Set:", my_set)
Taking inputs for a tuple:
Code:
# Initialize an empty list to store elements temporarily
temp_list = []
# Define the number of elements you want to add
num_elements = int(input("Enter the number of elements in the tuple: "))
# Loop to take inputs and add them to the temporary list
for i in range(num_elements):
element = input(f"Enter element {i + 1}: ")
temp_list.append(element)
# Convert the temporary list to a tuple
my_tuple = tuple(temp_list)
# Display the tuple
print("Tuple:", my_tuple)
Taking Inputs for a List Using map() and list():
Code:
# Define the number of elements you want to add
num_elements = int(input("Enter the number of elements in the list: "))
# Use map() and list() to take inputs and create a list
my_list = list(map(str, input("Enter elements separated by space: ").split()[:num_elements]))
# Display the list
print("List:", my_list)
Taking inputs for a set using map() and set():
Code:
# Define the number of elements you want to add
num_elements = int(input("Enter the number of elements in the set: "))
# Use map() and set() to take inputs and create a set
my_set = set(map(str, input("Enter elements separated by space: ").split()[:num_elements]))
# Display the set
print("Set:", my_set)
Taking inputs for a tuple directly:
Code:
# Define the number of elements you want to add
num_elements = int(input("Enter the number of elements in the tuple: "))
# Use a generator expression to create a tuple
my_tuple = tuple(input(f"Enter element {i + 1}: ") for i in range(num_elements))
# Display the tuple
print("Tuple:", my_tuple)
Code:
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
print(fruit)
Code:
fruits = ["apple", "banana", "cherry"]
print("Fruits:", *fruits, sep=", ", end="!\n")
Formatted String Literals, often referred to as f-strings, provide a powerful and convenient way to format strings in Python. Introduced in Python 3.6, f-strings offer a concise and readable syntax for embedding expressions and variables within string literals. Here's a breakdown of the theory behind f-strings:
1. Syntax:
2. Embedding Expressions:
3. Embedding Variables:
4. Formatting Options:
Here is an example:
Code:
name = "Alice"
age = 30
price = 19.99
# Basic string formatting
formatted_string = f"Name: {name}, Age: {age}"
print (formatted_string)
# Number formatting
formatted_price = f"Price: ${price:.2f}"
print (formatted_price)
# Combining variables and expressions
total_years = age + 10
combined_output = f"Name: {name}, Age in 10 years: {total_years}"
print (combined_output)
# Advanced formatting
formatted_number = f"Number: {7:03d}" # Padded with zeros
print(formatted_number)
5. Advantages:
6. Compatibility:
F-strings have become the preferred way to format strings in Python due to their clarity, simplicity, and ability to handle a wide range of formatting tasks. They are especially useful when creating strings with dynamic content or when dealing with complex formatting requirements.
Code:
name = "Alice"
age = 30
print(f"Name: {name}, Age: {age}")
Formatting output using the format() method is a powerful and flexible way to create formatted strings in Python. This method is available for string objects and allows you to replace placeholders in a string with values or expressions. Here's the theory behind using format() for string formatting:
Code:
name = "Alice"
age = 30
price = 19.99
# Basic string formatting
formatted_string = "Name: {}, Age: {}".format(name, age)
print(formatted_string)
# Number formatting
formatted_price = "Price: {:.2f}".format(price)
print(formatted_price)
# Combining positional and named arguments
formatted_output = "Name: {0}, Age: {1}, Price: {price:.2f}".format(name, age, price=price)
print(formatted_output)
# Advanced formatting with field names and specifiers
formatted_number = "Number: {:03d}".format(7)
print(formatted_number)
Formatting output using the % operator in Python is a traditional approach that allows you to create formatted strings by inserting values into placeholders within a string. Here's an example where we use the % operator for string formatting:
Code:
name = "Alice"
age = 30
formatted_string = "Name: %s, Age: %d" % (name, age)
print(formatted_string)
Navigating the complexities of Python input and output operations is an invaluable skill for today's professionals, especially as Python continues to dominate various industry sectors. Throughout this tutorial, we've unveiled the tools and techniques that transform these operations from mere tasks to powerful functionalities. With a clearer understanding, you're well-equipped to leverage these skills in real-world applications. For those committed to further refining their expertise, upGrad offers a diverse range of courses tailored to the ever-evolving landscape of Python programming.
Professionals often grapple with file-related operations, converting input data types, and customizing outputs.
A Python code output generator can predict a given code's output. Ensure your code is correct and enter the segment.
The principal output statement in Python is the print() function, allowing data display on the console.
Python's input() always returns a string, unlike some languages where the input type varies based on entered data.
Python offers advanced I/O libraries such as os, shutil, and sys for varied functionalities.
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