How to Handle Python Exceptions in Robotics

When programming in Python for Robotics, it is important to be aware of potential errors that could occur in your code. These errors, known as exceptions, can be handled in a number of ways in order to prevent your program from crashing. In this article, we will explore some of the most common exception types and how to deal with them.

What Are Python Exceptions in Robotics?

Python exceptions in robotics refer to errors that occur when a Python program is executed. This can happen for a variety of reasons, such as when the program is syntactically incorrect or when it is unable to access required data. When an exception occurs, the program will typically terminate, and an error message will be displayed.

There are a variety of ways to handle exceptions in Python, such as using try-except blocks or using the logging module. Which approach you take will depend on your specific needs. However, understanding how exceptions work is important for anyone who wants to use Python for robotics.

Why Do We Need to Deal With Exceptions in Robotics?

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Exceptions are times when the expected order of things is disrupted. In robotics, we need to deal with exceptions because they can cause our robots to malfunction or even break.

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Exceptions can occur for a number of reasons, but the most common cause is when a robot’s sensors detect something that is not expected. For example, if a robot is designed to only operate in a certain type of environment, it may malfunction if it encounter an unexpected type of terrain. Exceptions can also occur due to human error, such as when a robot is given an incorrect command.

Dealing with exceptions is an important part of designing and building robots. By anticipating and accounting for exceptions, we can build stronger and more reliable robots.

This page is a part of the larger guide on How to use Python for Robotics as a Beginner!

Types of Python Exceptions in Robotics

There are a number of different exception types that you may encounter when programming in Python. Some of the most common include:

  • SyntaxError – This exception is raised when there is a syntax error in your code. For example, if you forget to close a bracket or parenthesis, you will see a Syntax Error.
  • NameError – This exception occurs when you try to use a variable that has not been defined.
  • TypeError – This exception is raised when you try to perform an operation on a variable of the wrong type. For example, if you try to add a string and an integer, you will see a TypeError.
  • ValueError – This exception is raised when you pass an invalid value to a function. For example, if you try to convert a string to an integer but the string does not contain a valid number, you will see a ValueError.
  • IndexError – This exception occurs when you try to access a list or dictionary index that does not exist.
  • KeyError – This exception is raised when you try to access a dictionary key that does not exist.

Handling Python Exceptions in Robotics

One of the challenges of using Python in robotics is dealing with exceptions. When an exception occurs, it can disrupt the normal flow of execution and cause unexpected results. There are many ways to handle exceptions in Python, we will cover 3 of those ways.

Try/Except Block

In Python, the try except block is used to handle exceptions. Exceptions are errors that occur during the execution of a program. When an exception occurs, the program will stop running and an error message will be displayed. The try except block can be used to catch exceptions and handle them accordingly.

The basic syntax of the try except block is as follows:

try:
code block
except Exception1:
handle Exception1
except Exception2:
handle Exception2
else:
code block if no exceptions occur

Once you have written the try/except block, you can then test it by running your program and see what happens. If an exception occurs, the program will stop and an error message will be displayed. If no exceptions occur, the code in the else block will be executed.

Logging Module

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Python’s logging module is a powerful tool that can help you troubleshoot errors in your code. When an error occurs, the logging module can automatically log the traceback, which can be very helpful in debugging. The logging module also provides a variety of other features, such as the ability to log to a file or send an email notification when an error occurs.

The logging module is part of the standard Python library, so you do not need to install it. To use the logging module, you first need to import it:

import logging

Once you have imported the logging module, you can use the following methods to log messages:

  • logging.debug(): Logs a message with the DEBUG level.
  • logging.info(): Logs a message with the INFO level.
  • logging.warning(): Logs a message with the WARNING level.
  • logging.error(): Logs a message with the ERROR level.
  • logging.critical(): Logs a message with the CRITICAL level.

To log a message, you need to use the appropriate method and pass in the message you want to log. For example, to log a debug message, you would use the following code:

logging.debug(‘This is a debug message.’)

The logging module has many other features, such as the ability to format messages or log to a file instead of the console. For more information about the logging module, see the Python documentation.

Custom Exceptions

Finally, it is also possible to raise custom exceptions. This can be useful if there is some specific condition that needs to be handled in a particular way. By raising a custom exception, you can ensure that the code handles the situation correctly. The example below shows a custom exception that is raised when the input value is not valid::

def validate_input(inp):
if inp <= 0:
raise ValueError(“Invalid input!”)

In the example above, the program will raise a ValueError exception if the input is <= 0. Generally, it is not recommended to use custom exceptions too frequently. Custom exceptions are best used when you have a specific condition that needs special handling and there is no standard Python exception that can be used.

When to Use Which Type of Exception Handling in Python for Robotics?

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For the three types of error handling in Python that we covered: the try block, the logging module, and custom exception handling they each have their own advantages and disadvantages. Due to that, it’s important to know when to use each one.

The try block is the simplest form of error handling. It simply tells the Python interpreter to try running a certain piece of code, and if an error occurs, to skip over that code and continue running the rest of the program. This is useful for simple programs where errors are not likely to occur.

The logging module is a more powerful error-handling tool. It allows you to log errors and track them over time. This is useful for more complex programs where errors are more likely to occur.

Custom exception handling is the most powerful error-handling tool. It allows you to write custom error-handling code for your program. This is useful for programs where errors are very likely to occur and you need more control over how they are handled.

Each one of the exception-handling types above can be used at different times and in different ways. Whatever type of exception you are experiencing will determine which exception handling type you should use.

Some final thoughts

As you can see, there are a number of ways to deal with Python exceptions in robotics. The most important thing is to ensure that your code is robust and able to handle any potential errors. You can do this by using try/except blocks, testing your code thoroughly, and using robust libraries.

In the next section of the guide, we will focus on Python’s objects and classes. You can learn more about them here: Python Objects and Classes in Robotics.



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