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intro-to-python
  • An Introduction to Programming in Python (for Business Students)
  • exercises
    • Data Flow Diagramming Exercise
    • Developer Collaboration Exercise
    • README
    • "Web App" Exercise
      • checkpoints
        • Checkpoint 5: Bootstrap Layout
        • Checkpoint 4: Submitting Data from Web Forms
        • Checkpoint 3: Rendering HTML Pages
        • Checkpoint 1: Routing
        • Checkpoint 2: Modular Organization
      • "Web App" Exercise - Further Exploration
    • hello-world
      • "Hello World (Local)" Exercise
      • "Hello World (Local w/ Version Control)" Exercise
      • "Hello World (Colab)" Exercise
    • "Interface Capabilities" Exercise
    • "Continuous Integration 1, 2, 3" Exercise
    • "Web Service" Exercise
      • "Web Service" Exercise - Further Exploration
    • "Testing 1, 2, 3" Exercise
    • "Command-line Computing" Exercise
      • "Command-line Computing" Exercise
      • Professor Rossetti's Mac Terminal Configuration
      • Command-line Computing Exercise
    • "Codebase Cleanup" Assignment
    • "List Comprehensions" Exercise
    • "Groceries" Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
    • "Rock, Paper, Scissors" Exercise
      • "Rock, Paper, Scissors" Exercise
    • README
    • "Monthly Sales Predictions" Exercise
    • Setting up your Local Development Environment
    • "Chart Gallery" Exercise
    • "Run the App" Exercise
    • "Web Requests" Exercise
    • "API Client" Exercise
    • "Custom Functions" Exercise
    • Process Diagramming Exercise
  • notes
    • python
      • packages
        • The bigquery Package
        • The PySimpleGUI Package
        • The dotenv Package
        • The matplotlib Package
        • The requests Package
        • The altair Package
        • The gspread Package
        • The PyMySQL Package
        • The psycopg2 Package
        • The selenium Package
        • The seaborn Package
        • The pytest Package
        • The SpeechRecognition Package
        • The flask Package
        • The pandas Package
        • The spotipy Package
        • The pipenv Package
        • The nltk Package
        • The sqlalchemy Package
        • The pymongo Package
        • The plotly Package
        • The BeautifulSoup Package
        • The sendgrid Package
        • The fpdf Package
        • The autopep8 Package
        • The tweepy Package
        • The twilio Package
        • The tkinter Package
      • Python Datatypes Overview
        • Numbers
        • Classes
        • Dates and Times
        • Strings
        • None
        • Dictionaries
        • Booleans
        • Lists
        • Class Inheritance
      • Control Flow
      • Python Modules
        • The webbrowser Module
        • The time Module
        • The csv Module
        • The sqlite3 Module
        • The itertools Module
        • The json Module
        • The math Module
        • The os Module
        • The statistics Module
        • The random Module
        • The pprint Module
        • The datetime Module
        • The collections Module
      • Printing and Logging
      • Comments
      • Syntax and Style
      • Functions
      • Variables
      • Errors
      • Docstrings
      • File Management
      • User Inputs
      • Debugging
    • clis
      • The git Utility
      • Heroku, and the heroku Utility
      • Anaconda
      • The chromedriver Utility
      • The brew Utility (Mac OS)
      • The pdftotext Utility
      • The python Utility
      • The pip Utility
    • Software
      • Software Licensing
      • Software Documentation
      • Software Ethics
      • Software Testing Overview
      • Application Programming Interfaces (APIs)
      • Software Version Control
      • Software Refactoring Overview
    • devtools
      • The VS Code Text Editor
      • Code Climate
      • Travis CI
      • GitHub Desktop Software
      • Git Bash
      • Google Colab
    • Information Systems
      • Computer Networks
      • Processes
      • Datastores
      • Information Security and Privacy
      • People
    • Technology Project Management
      • Project Management Tools and Techniques
      • The Systems Development Lifecycle (SDLC)
    • hardware
      • Servers
    • Environment Variables
  • projects
    • "Executive Dashboard" Project
      • testing
      • "Exec Dash" Further Exploration Challenges
    • The Self-Directed (a.k.a "Freestyle") Project
      • "Freestyle" Project - Demonstration
      • "Freestyle" Project - Implementation (TECH 2335 Version)
      • "Freestyle" Project - Implementation
      • "Freestyle" Project Proposal
      • plan
    • "Robo Advisor" Project
      • Robo Advisor Project - Automated Testing Challenges
      • "Robo Advisor" Further Exploration Challenges
    • "Shopping Cart" Project
      • "Shopping Cart" Project - Automated Testing Challenges
      • "Shopping Cart" Further Exploration Challenges
      • "Shopping Cart" Project Checkpoints
  • License
  • Exam Prep
  • units
    • Unit 4B: User Interfaces and Experiences (Bonus Material)
    • Unit 5b: Databases and Datastores
    • Module 1 Review
    • Unit 7b: Processing Data from the Internet (Bonus Material)
    • Unit 9: Software Products and Services
    • Unit 8: Software Maintenance and Quality Control
    • Unit 7: Processing Data from the Internet
    • Unit 6: Data Visualization
    • Unit 5: Processing CSV Data
    • Unit 4: User Interfaces and Experiences
    • Unit 3: Python Datatypes
    • Unit 12: Project Presentations
    • Unit 2: Python Language Overview
    • Unit 11: Project Implementation Sprint
    • Unit 1: The Python Development Environment
    • Unit 10: Software Planning, Analysis, and Design
    • Unit 0: Onboarding
    • Unit 5B: Advanced Data Analytics
  • Contributor's Guide
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On this page
  • Handling Errors
  • Raising Errors
  • Defining and Raising Custom Errors

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Errors

PreviousVariablesNextDocstrings

Last updated 4 years ago

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Reference:

Handling Errors

Sometimes our programs will encounter errors. In Python, we can use a try... except block to handle these errors.

After running into an error for the first time, we should observe what type of error we are experiencing (e.g. KeyError, IndexError, DivisionByZeroError, etc.).

Once we know what type of error we need to handle, we should wrap the problematic code inside the try clause, and specify the known error type in the except clause:

try:
  empty_list = []
  matching_item = empty_list[0] # triggers an IndexError (list index out of range)
  print("EVERYTHING IS GOING FINE") # this never gets reached
except IndexError:
  print("OOPS - MY ERROR")

#> OOPS - MY ERROR
try:
  100 / 0 # triggers a DivisionByZeroError
  print("EVERYTHING IS GOING FINE") # this never gets reached
except DivisionByZeroError:
  print("OOPS - MY ERROR")

#> OOPS - MY ERROR

If we're not yet sure what type of error we're experiencing, we can temporarily catch all error classes that inherit from the base error class (Exception), and once caught, we print the specific error's datatype to learn how to handle it:

try:
    do_something() # some hypothetical problematic code
except Exception as err:
    print(type(err)) #> this will tell you the error type
    print(err) #> the error message

Raising Errors

If we find the need to trigger our own errors to stop program execution (less common), we can use the raise keyword followed by the type of error (e.g. ValueError):

options = ["rock", "paper", "scissors"]

choice = input("Please choose either 'rock', 'paper', or 'scissors': ")

if choice in options:
    print("YOU CHOSE", choice)
else:
    raise ValueError("OOPS - Please type 'rock', or 'paper', or 'scissors'.")

Defining and Raising Custom Errors

We can define our own errors if that's helpful, by inheriting a class from the base Exception class (or preferably a more specific one):

class MyCustomError(Exception):
   pass

raise MyCustomError("My custom message")
https://docs.python.org/3/library/exceptions.html#bltin-exceptions
https://docs.python.org/3/tutorial/errors.html