Tutorial Playlist
200 Lessons1. 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
Now Reading
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. Reverse a List in Python
92. Python List remove() Method
93. How to Add Elements in a List in Python
94. How to Reverse a List in Python?
95. Difference Between List and Tuple in Python
96. List Slicing in Python
97. Sort in Python
98. Merge Sort in Python
99. Selection Sort in Python
100. Sort Array in Python
101. Sort Dictionary by Value in Python
102. Datetime Python
103. Random Number in Python
104. 2D Array in Python
105. Abs in Python
106. Advantages of Python
107. Anagram Program in Python
108. Append in Python
109. Applications of Python
110. Armstrong Number in Python
111. Assert in Python
112. Binary Search in Python
113. Binary to Decimal in Python
114. Bool in Python
115. Calculator Program in Python
116. chr in Python
117. Control Flow Statements in Python
118. Convert String to Datetime Python
119. Count in python
120. Counter in Python
121. Data Visualization in Python
122. Datetime in Python
123. Extend in Python
124. F-string in Python
125. Fibonacci Series in Python
126. Format in Python
127. GCD of Two Numbers in Python
128. How to Become a Python Developer
129. How to Run Python Program
130. In Which Year Was the Python Language Developed?
131. Indentation in Python
132. Index in Python
133. Interface in Python
134. Is Python Case Sensitive?
135. Isalpha in Python
136. Isinstance() in Python
137. Iterator in Python
138. Join in Python
139. Leap Year Program in Python
140. Lexicographical Order in Python
141. Literals in Python
142. Matplotlib
143. Matrix Multiplication in Python
144. Memory Management in Python
145. Modulus in Python
146. Mutable and Immutable in Python
147. Namespace and Scope in Python
148. OpenCV Python
149. Operator Overloading in Python
150. ord in Python
151. Palindrome in Python
152. Pass in Python
153. Pattern Program in Python
154. Perfect Number in Python
155. Permutation and Combination in Python
156. Prime Number Program in Python
157. Python Arrays
158. Python Automation Projects Ideas
159. Python Frameworks
160. Python Graphical User Interface GUI
161. Python IDE
162. Python input and output
163. Python Installation on Windows
164. Python Object-Oriented Programming
165. Python PIP
166. Python Seaborn
167. Python Slicing
168. type() function in Python
169. Queue in Python
170. Replace in Python
171. Reverse a Number in Python
172. Reverse a string in Python
173. Reverse String in Python
174. Stack in Python
175. scikit-learn
176. Selenium with Python
177. Self in Python
178. Sleep in Python
179. Speech Recognition in Python
180. Split in Python
181. Square Root in Python
182. String Comparison in Python
183. String Formatting in Python
184. String Slicing in Python
185. Strip in Python
186. Subprocess in Python
187. Substring in Python
188. Sum of Digits of a Number in Python
189. Sum of n Natural Numbers in Python
190. Sum of Prime Numbers in Python
191. Switch Case in Python
192. Python Program to Transpose a Matrix
193. Type Casting in Python
194. What are Lists in Python?
195. Ways to Define a Block of Code
196. What is Pygame
197. Why Python is Interpreted Language?
198. XOR in Python
199. Yield in Python
200. Zip in Python
In the programming world, especially in Python, challenges often emerge in the form of unexpected errors. The power of Python lies not just in its vast capabilities but also in how it allows developers to handle these unforeseen errors. This tutorial will guide professionals through the labyrinth of exception handling in Python, ensuring that your applications run seamlessly, even when they encounter unexpected bumps.
Exception handling is the process by which Python allows a programmer to handle these aforementioned "bumps" or errors. Beyond just managing errors, exception handling in Python ensures that your application's user experience remains unhindered. As we navigate this tutorial, we'll uncover the essence of exceptions, their types, and the advantages and disadvantages of managing them in Python.
In programming, errors are akin to unforeseen obstacles on a well-planned road trip. These aren’t just trivial disruptions; they can potentially halt our journey, demanding immediate attention. As seasoned developers, we recognize that no matter how meticulous our code is or how well we chart our path, these errors remain an inevitable part of the journey.
In the context of Python—a language celebrated for its simplicity and power—an "exception" stands as a testament to this unpredictability. Specifically, an exception in Python is an event that arises unexpectedly during the execution phase of a program, causing a disruption in the expected flow of the program's instructions. Imagine crafting a sequence of actions, only to have an unanticipated event render a portion of it unworkable. That's precisely the scenario exceptions present.
The try and except statement is used for handling exceptions or errors that may occur during the execution of your code. It allows us to gracefully handle errors without crashing the program.
Here is the syntax:
try:
# Code that may raise an exception
except ExceptionType:
# Code to handle the exception
In the above syntax,
Here is an example of catching a division by zero exception:
try:
result = 10 / 0 # For raising a ZeroDivisionError
except ZeroDivisionError:
print("Division by zero is not allowed.")
In the above code, the try block tries dividing 10 by 0, raising a ZeroDivisionError. This specific exception is caught by the except block and it prints a message.
You can raise an exception manually using the raise statement. This is useful when you want to signal an error condition explicitly.
Here is the syntax:
raise ExceptionType("Optional error message")
In the above syntax,
Here is an example of raising a custom exception:
def divide(a, b):
if b == 0:
raise ValueError("Division by zero is not allowed")
return a / b
try:
result = divide(10, 0)
except ValueError as e:
print("Error:", str(e))
In this example, the divide function raises a custom ValueError exception with a specific error message when attempting to divide by zero.
Assertions are used for debugging and testing purposes. They allow you to check whether a condition holds true and raise an exception if it does not.
Here is the syntax:
assert condition, "Optional error message"
In the above syntax,
Here is an example of using assert for debugging:
def divide(a, b):
assert b != 0, "Division by zero is not allowed"
return a / b
result = divide(10, 0)
In this example, the assert statement is used to check that b is not equal to zero before performing the division. If the condition is False, an AssertionError is raised with the specified error message.
As we discussed before, we can use the try and except statement to catch specific exceptions by specifying the exception type(s) you want to handle. This allows us to handle different exceptions differently based on their types.
Let us try catching a ValueError exception:
try:
age = int(input("Enter your age: "))
except ValueError:
print("Invalid input. Please enter a valid age.")
In this example, we catch a ValueError exception that occurs when trying to convert user input to an integer.
You can use the else clause in conjunction with the try and except statement. The code in the else block gets executed if no exceptions are raised in the try block.
Here is the syntax:
try:
# Code that may raise an exception
except ExceptionType:
# Code to handle the exception
else:
# Code to execute if no exception occurs
Here is an example of using: Using try with else Clause:
try:
result = 10 / 0
except ZeroDivisionError:
print("Division by zero is not allowed.")
else:
print("Result:", result)
In this example, if no ZeroDivisionError occurs, the code in the else block will execute and print the result.
The finally keyword is used to define a block of code that will be executed regardless of whether an exception occurs or not. This is useful for tasks like resource cleanup.
Here is the syntax:
try:
# Code that may raise an exception
except ExceptionType:
# Code to handle the exception
finally:
# Code that always executes, regardless of exceptions
Example of using try with finally clause:
try:
file = open("example.txt", "r")
# Code that may raise an exception while working with the file
except FileNotFoundError:
print("File not found.")
finally:
file.close() # Ensure the file is always closed, even if an exception occurs
In this example, the finally block ensures that the file is closed, whether or not an exception occurs.
Here is a list of some common built-in exceptions in Python:
BaseException: The base class for all built-in exceptions.
SystemExit: Raised when Python interpreter is quitting.
KeyboardInterrupt: Raised when the user interrupts program execution, typically by pressing Ctrl+C.
Exception: The base class for all built-in exceptions except SystemExit, KeyboardInterrupt, and GeneratorExit.
StopIteration: Raised when an iterator is exhausted. This is typically caught implicitly in for loops and other iteration constructs.
GeneratorExit: Raised when a generator is closed.
ArithmeticError: The base class for numeric errors like ZeroDivisionError and OverflowError.
OverflowError: Raised when an arithmetic operation exceeds the limits of its numeric type.
FloatingPointError: Raised when a floating-point operation fails.
ZeroDivisionError: Raised when division or modulo operation is performed with zero as the divisor.
AssertionError: Raised when an assert statement fails.
AttributeError: Raised when an attribute reference or assignment fails.
BufferError: Raised when a buffer-related operation cannot be performed.
EOFError: Raised when the input() function hits an end-of-file condition (Ctrl+D on UNIX, Ctrl+Z on Windows).
ImportError: Raised when an import statement fails to find the module or name being imported.
ModuleNotFoundError: A subclass of ImportError, raised when a module could not be found.
LookupError: The base class for lookup errors (e.g., IndexError and KeyError).
IndexError: Raised when trying to access an index that doesn't exist in a sequence (e.g., list or tuple).
KeyError: Raised when trying to access a dictionary key that doesn't exist.
NameError: Raised when an identifier is not found in the local or global namespace.
UnboundLocalError: Raised when trying to access a local variable before it has been assigned a value.
TypeError: Raised when an operation or function is applied to an object of inappropriate type.
ValueError: Raised when an operation or function receives an argument of the correct type but an inappropriate value.
UnicodeError: The base class for all Unicode-related errors (e.g., UnicodeEncodeError and UnicodeDecodeError).
UnicodeEncodeError: Raised when encoding a Unicode string fails.
UnicodeDecodeError: Raised when decoding a Unicode string fails.
UnicodeTranslateError: Raised when translating a Unicode string fails.
AssertionError: Raised when an assert statement fails.
IndentationError: The base class for indentation-related errors (e.g., TabError and IndentationError).
TabError: Raised when inconsistent use of tabs and spaces in indentation is detected.
EnvironmentError: The base class for exceptions that can occur outside the Python system (e.g., IOError and OSError).
IOError: Raised when an I/O operation (e.g., file operations) fails.
OSError: Raised for operating system-related errors.
FileNotFoundError: A subclass of OSError, raised when a file or directory is not found.
Navigating the complexities of Python's exception handling elucidates its indispensable role in modern-day programming. Adeptly leveraging this feature ensures software robustness and user satisfaction. For professionals eager to delve deeper into Python's vast landscape, upGrad's extensive upskilling courses stand as invaluable resources.
1. How is the Python raise exception employed?
The raise statement allows developers to forcefully generate a specified exception, facilitating testing of exception handling routines.
2. What does Python try-except: print error accomplish?
This structure captures exceptions and prints the corresponding error message, offering clarity on the nature of the issue.
3. Can you explain the user-defined exception in Python?
Python allows developers to define bespoke exceptions to cater to specific application needs, enhancing error detection and handling efficiency.
4. What encompasses a Python exception message?
It's a descriptive text tied to an exception, shedding light on the anomaly for developers and users.
5. Could you explain the exception hierarchy in Python?
Python's exceptions are structured hierarchically, with a base class at the summit. This hierarchy enables systematic handling based on exception specificity.
PAVAN VADAPALLI
Director of Engineering
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upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...