Adventures in Machine Learning

Creating Robust Programs: Handling Invalid Input with Python

Validating Integer Input with Python

Have you ever encountered an error message while writing a Python program that says “invalid literal for int() with base 10”? This usually happens when you try to convert a non-integer string to an integer.

Fortunately, Python provides a built-in function that allows you to get user input from the command line. This is known as the input() function.

Using Python’s input() function

The input() function allows you to get a user’s response to a prompt. Let’s say we want to ask the user to enter their age.

We can do this by using the input() function as follows:

“`

age = input(“Enter your age: “)

print(“Your age is:”, age)

“`

This code will prompt the user to enter their age and store their response in a variable called age. We can then print out their age using the print() function.

Converting string value to integer

However, input() function always returns a string, even if the user enters a number. To perform arithmetic operations, we need to convert the string to an integer data type using the int() function.

Let’s see an example:

“`

age = input(“Enter your age: “)

age = int(age)

print(“In ten years, you will be”, age + 10, “years old.”)

“`

In this case, we have to convert age to an integer before we can perform arithmetic operations.

Handling errors for invalid input

But what happens if the user enters a non-numeric input such as “twenty”? The int() function will throw a ValueError exception, causing our program to crash.

To handle this error, we can use a try/except block as shown below:

“`

try:

age = input(“Enter your age: “)

age = int(age)

print(“In ten years, you will be”, age + 10, “years old.”)

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

“`

This code will catch any ValueError exceptions and print an error message to the console.

Filtering input for valid integers using

EAFP approach

Another way to handle invalid input is to use the Easier to Ask for Forgiveness than Permission (

EAFP) approach. This involves assuming that the input is valid and attempting to convert it to an integer.

If the conversion fails, we catch the exception and ask the user to enter a valid input as shown below:

“`

while True:

try:

age = int(input(“Enter your age: “))

break

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

print(“In ten years, you will be”, age + 10, “years old.”)

“`

This code loops indefinitely until a valid input is entered.

It uses a try/except block to catch any ValueError exceptions. The break statement is used to exit the loop once a valid input is entered.

Creating a reusable utility function for valid integer input

We can simplify the code by creating a reusable utility function that handles all the error checking and conversion to an integer as shown below:

“`

def get_valid_integer(prompt):

while True:

try:

value = int(input(prompt))

return value

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

age = get_valid_integer(“Enter your age: “)

print(“In ten years, you will be”, age + 10, “years old.”)

“`

This code defines a function called get_valid_integer() that takes a prompt as an argument and returns a valid integer value.

The function loops indefinitely until a valid input is entered. It uses a try/except block to catch any ValueError exceptions.

Importance of Python 3 for input() Function

If you’re using Python 2, the input() function works the same way as in Python 3, with one key difference: it evaluates the user input as a Python expression rather than returning it as a string. This means that it is possible to execute malicious code by entering certain inputs.

Python 3 has resolved this issue by renaming the input() function to input(), and creating a new function called raw_input() which behaves like input() in Python 2. In conclusion, the input() function is a useful feature in Python that allows you to get user input from the command line.

However, it is important to handle error checking and conversion to integer data type to avoid program crashes. By using the try/except block, the

EAFP approach, and creating a reusable utility function, you can write more robust code that is capable of handling user input more effectively.

Additionally, it is important to use Python 3 to avoid security risks associated with Python 2’s input() function.

Dealing with Invalid Input

One of the most common challenges that programmers face is dealing with invalid input. Invalid input could cause a program to crash or produce incorrect output.

It is important to implement defensive coding techniques to handle invalid input. Defensive coding involves adding extra code to a program to handle unexpected events.

These include unexpected user input, network failures or bugs in other parts of the program. Let’s take a look at some strategies that we can use to handle invalid input and write more robust code.

Error Checking

One of the first strategies for dealing with invalid inputs is to perform error checking. This involves checking whether the input meets the required criteria.

For instance, if we are expecting a number as input, we can check whether the input is indeed numeric. We can then handle any exceptions that arise.

Here is an example:

“`

try:

x = int(input(“Enter a number: “))

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

“`

In this code, we use a try/except block to catch the ValueError exception that is raised if the input is not numeric.

If the exception is caught, we print an error message to the console. This helps to avoid a program crash and prompts the user to enter a valid input.

Filtering Input for Valid Integers

Another way to handle invalid input is to filter input for valid integers. This involves checking the input at the time of input rather than trying to catch exceptions later on.

There are two main approaches to filtering input;

LBYL (Look Before You Leap) and

EAFP (Easier to Ask for Forgiveness than Permission).

LBYL

With the

LBYL approach, we check the input before performing any action on it. If the input is not valid, we return an error message or prompt the user to enter a valid input.

Here’s an example:

“`

value = input(“Enter a number: “)

if value.isdigit():

x = int(value)

else:

print(“Invalid input. Please enter a numeric value.”)

“`

In this code, we use the in-built method isdigit() to check whether the input is numeric.

If it returns True, we proceed with the conversion to integer. Otherwise, we print an error message to the console.

EAFP

With the

EAFP approach, we assume that the input is valid and try to perform the operation. If the operation fails, we handle the exception.

In other words, we are “eager to ask for forgiveness rather than permission.”

Here’s an example:

“`

while True:

try:

value = input(“Enter a number: “)

x = int(value)

break

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

“`

In this code, we use a while loop to keep prompting the user until a valid input is entered.

We then use a try/except block to catch any ValueError exception. If the input is not valid, the user is prompted to try again.

Using while loop and try/except for retrying invalid inputs

Another way to filter input for valid integers is to use a while loop and try/except block. This approach keeps prompting the user to enter input until a valid integer is entered.

Here’s an example:

“`

while True:

try:

value = int(input(“Enter a number: “))

break

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

print(“Your number is:”, value)

“`

In this code, we use a while loop to keep prompting the user until a valid input is entered.

We then use a try/except block to catch any ValueError exception. If the input is not valid, the user is prompted to try again.

Conclusion

In conclusion, dealing with invalid input is an important skill for any programmer. It is essential to implement defensive coding techniques to handle unexpected events.

We can perform error checking, filter input for valid integers using the

LBYL and

EAFP approaches or retry invalid inputs using a while loop and try/except block. By taking these steps, we can write more robust code that avoids crashing or producing incorrect output and provides a more user-friendly experience.

Creating a Reusable Utility Function for Valid Integer Input

As we have already seen, it is important to handle invalid input in our programs. One way to make our code more robust is by creating a reusable utility function for valid integer input.

In this section, we will explore how to write such a function. Functions are a useful tool for structuring our code and making it more reusable.

A function is a block of code that we define once and can be called multiple times. By defining a function for valid integer input, we can encapsulate all the error checking and filtering logic in one place and use it repeatedly throughout our program.

Here’s an example of a reusable utility function for valid integer input:

“`

def get_valid_int(prompt):

while True:

try:

value = int(input(prompt))

return value

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

“`

In this function, we use a while loop to keep prompting the user until a valid input is entered.

We then use a try/except block to catch any ValueError exception. If the input is not valid, the user is prompted to try again.

Once a valid input is entered, we return the value. We can now use this function in our code like this:

“`

age = get_valid_int(“Enter your age: “)

print(“In ten years, you will be”, age + 10, “years old.”)

“`

This code prompts the user to enter their age, validates the input using the get_valid_int() function, and performs arithmetic operations on the input.

Reusable code is an essential concept in programming. It saves time and effort by reducing the amount of code that needs to be written and tested.

It also makes the code more modular and easier to maintain. We can use functions to create reusable code blocks that can be used repeatedly throughout our program.

Module Creation

In addition to functions, we can also create modules, which are collections of functions that can be used to perform a specific task. Modules are useful for situations where we need many functions that are related to a specific task or domain.

Creating a module involves defining a collection of functions in a separate file, which can then be imported and used in our program. Let’s say we want to create a module for handling valid integer input.

We can create a new file called “input_helper.py” and define our get_valid_int() function in it like this:

“`

def get_valid_int(prompt):

while True:

try:

value = int(input(prompt))

return value

except ValueError:

print(“Invalid input. Please enter a numeric value.”)

“`

We can then use this module in our main program by importing it like this:

“`

import input_helper

age = input_helper.get_valid_int(“Enter your age: “)

print(“In ten years, you will be”, age + 10, “years old.”)

“`

In this code, we import the input_helper module and then use the get_valid_int() function from the module to handle the user input.

Conclusion and Next Steps

In conclusion, input validation is an essential part of writing reliable code. By handling invalid input using error checking, filtering, and retrying, we can create robust programs that produce correct output and provide a positive user experience.

Creating a reusable utility function for valid integer input can save time and effort by encapsulating all the error checking and filtering in one place and allowing us to use it repeatedly throughout our program. Furthermore, creating modules can help us create more complex programs with more reusable code blocks.

If you want to take your input validation skills to the next level, consider contributing to open-source projects that rely heavily on user input. These projects often require robust error checking and filtering to ensure the safety and reliability of their software.

By contributing to such projects, you can develop your validation skills and contribute to a valuable resource for the developer community. In conclusion, input validation is essential in creating reliable code.

Handling invalid input using error checking, filtering, and retrying can make your code more robust and user-friendly.

Creating a reusable utility function for valid integer input and modules can save time and effort.

Additionally, contributing to open-source projects that rely heavily on user input can help you develop your validation skills and contribute to a valuable resource for the developer community. Remember, taking care of input validation can make a huge difference!

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