I recently wrote an article for freeCodeCamp titled "How to Install Python on a Mac", which provides a clear guide to installing Python on macOS.

As a follow-up, I will discuss errors you may encounter when installing Python on macOS and how to fix them in this article.

Contents

Here's what we'll cover here:

• How to Fix the "command not found: python" Error
• Using an Out-of-date Python
• Using the System Python
• Using the Homebrew Python
• Missing Pip
• Pip Package Installation Errors
• More on Mac Python
• Conclusion

How to Fix the "command not found: python" Error

You may encounter this error:

$ python ...
zsh: command not found: python

You'll see this when trying to run Python commands in the terminal. This mostly happens because Python is yet to be installed. However, it is also possible, and more frustrating, that the Python installation is not in the Mac PATH.

If you only need to install and run a Python application, you can use Homebrew to install Pipx. This will install Python as a dependency. Pipx is a tool that allows you to install and run Python applications as standalone executables, avoiding dependency conflicts that can occur when using the standard Python package manager Pip.

If you're going to work on a programming project in Python, install Python with Pyenv, the standard Python version manager. Better yet, install Python with Rye, an all-in-one tool for Python installation, virtual environment management, and package installation.

If you're seeing the zsh: command not found: python error, and are certain you have already installed Python, you may need to update the Mac Python PATH. You'll need to find where Python is installed on your system, which takes some sleuthing because there are multiple ways to install Python on macOS.

Here are the most common locations for Python on a Mac:

1. /usr/bin/python3 is the system Python installed with Xcode Command Line Tools. This is an alias; the actual location is /Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/bin.
2. /opt/homebrew/opt/python@3.12/libexec/bin/python is the Homebrew Python.
3. /Library/Frameworks/Python.framework/Versions/3.12/bin/python3 is the Python installed with the official Python website installer.
4. /Users/username/.pyenv/shims/python is the Python installed with Pyenv.
5. /Users/username/.rye/shims/python is the Python installed with Rye.

Enter the full pathname followed by python --version and see if you get a version number. If you do, you'll need to update your PATH by adding the Python installation path to your .zprofile file. For more information, see Mac PATH.

The article Command not found: python goes into more detail if you need more help.

Using an Out-of-date Python Version

The current Python version is 3.12, as of October 2023. New releases of Python come yearly, typically released in October. The next version, Python 3.13, is expected in October 2024. The newest Python version is listed on the Python website.

Check your Mac Python version:

$ python --version
Python 3.12.4

You should see Python 3.12.4 or a later version. You may not notice issues with an older Python version but it's a good idea to start any project with the newest version. The article about updating Python on Mac explains how to update Python on macOS.

Using the System Python

Macs no longer come with Python pre-installed. But you may have installed Xcode Command Line Tools which includes Python 3.9.6, an older Python version that supports Apple development utilities.

Try python3 --version and which -a python3 to check if Python was installed with Xcode Command Line Tools.

$ python3 --version
Python 3.9.6
$ which -a python3
/usr/bin/python3

If you have Python 3.9.6 installed at /usr/bin/python3, you'll likely have the system Python installed by Xcode Command Line Tools. You can confirm this with xcode-select -p which will show if Xcode Command Line Tools is installed.

$  xcode-select -p
/Library/Developer/CommandLineTools

It's possible to alias python3 to python but I would not recommend using the system Python for development. The system Python is intended for Apple utilities, not for you, so you should install Python on macOS separately if you want to run Python programs or develop in Python.

See my freeCodeCamp article How to Install Python on a Mac to install Python for development.

Using the Homebrew Python

If you use Homebrew as a software package manager, you can easily install Python with brew install python. Homebrew-installed Python is suitable for running scripts but it has drawbacks for installing Python applications or Python software development, when packages are installed.

• Homebrew's automatic updates. Homebrew automatically updates its Python as a dependency for other packages, potentially breaking your projects.
• Multiple projects may need different Python versions. Homebrew-installed Python is a single version and you may need to switch among different versions for different projects.
• Problems with environment isolation. Homebrew provides a single Python environment, which can cause conflicts between projects. Pip, the Python package manager, will block installation of packages unless you first create a virtual environment.

You can check if Python is installed with Homebrew:

$ brew list | grep python
python@3.12

For running applications, it's best to install Pipx and use pipx install instead of pip install to install programs. For Python development, it's best to install Pyenv or install Rye for Python version management and virtual environments.

Missing Pip

READMEs and tutorials often assume users are familiar with Python development tools and instruct them to install Python packages using Pip, the Python package manager. If you've followed instructions that start with pip install <package>, you may have run into the zsh: command not found: pip error.

This is the error you'll see:

$ pip install <package>
zsh: command not found: pip

Pip is installed automatically with Python, so it's unusual to run the python command successfully and then pip and see the error. If you have Python installed, you should be able to use the pip command. You can try a special command that installs Pip:

$ python -m ensurepip --upgrade

If Pip is not already installed, this command will install it. Otherwise, nothing will happen. With this error, it's more likely that you have a Python installation that is not in your Mac Python PATH. See the article Command not found: pip for more details.

Pip Package Installation Errors

You will need to use Pip to install Python packages, unless you are using Rye as an all-in-one tool. However, Pip has some drawbacks.

By default, the pip install <package> command installs the package "globally." This means that the package is added to the global Python site-packages directory, which may result in conflicts if different projects require different versions of the same package.

For example, if project A requires package==1.0 and project B requires package==2.0, installing both packages globally may result in conflicts and dependency hell. Without proper isolation, installing one project's dependencies can cause problems for another. To avoid these conflicts, create a Python virtual environment for each project.

There are two Python tools for creating virtual environments and using different versions of packages. Venv is a built-in Python package. Virtualenv is a more powerful tool with additional features. These tools allow pip to install Python packages into a virtual environment that has its own installation directories and does not share libraries with other virtual environments. Pip must be used in conjunction with either Venv or Virtualenv to successfully install packages.

When you try to install a package with Pip, you may see:

$ pip install <package>
error: externally-managed-environment

Recent versions of pip implement PEP 668 to prevent attempts to install packages globally, which results in the message error: externally-managed-environment. This error occurs when attempting to install a package globally without using a virtual environment. To resolve this error, create a virtual environment using Venv or Virtualenv and install the package within it.

More on Mac Python

You'll need to do more than install Python to begin a programming project, so I've also written a longer article about Mac Python that explains the fundamentals of version management, virtual environments, and package management, as well as comparing various installation options.

Conclusion

A variety of competing development tools means that it can be difficult to get started with Python compared to other programming languages such as JavaScript, Rust, or Ruby. Python is moving towards standardization of tools, and there's rapid innovation as the community seeks to improve the developer experience.

For now, developing Python skills requires some knowledge of the Python ecosystem, the various tools, and how to use them. Still, Python is popular and powerful, and the tutorials on freeCodeCamp will help you learn the language and become a better developer.

Like most newbies, I went to Google to find some inspiration. As I scrolled through the internet, I stumbled upon Skillcrush’s list of HTML and CSS projects for beginners.

Number 5 piqued my interest, so I googled some images on how HTML forms should look. I thought “Oh I can do this. This looks easy!” But this project turned out to be a bit harder than I thought.

In this article, I will show you three things I have learned in surviving, I mean making HTML forms error-free. Let’s get started! 😀

Tip #1: Make Sure the Labels and Inputs Match.

When I first started creating HTML forms, I would often use the following methods for creating email input fields:

<label id="text"> Your Email</label>
<input type="text" id="text" name="text">

I would often use text as the label and id's attribute because I thought it was the correct method.

This all changed when I started using WAVE’s accessibility checker to learn how to make my code more accessible. When I ran my form through the checker, it pointed out that the email input did not have a properly associated label, and that can cause screen readers to have difficulty presenting it to users with disabilities.

So, I googled a few sources and found ”HTML Inputs and Labels: A Love Story” by Amber Wilson. Through reading this article, I learned that it’s best to use specific names in the id attribute.

With a new feeling of confidence, I started using this approach. Here’s an example:

In the code snippet above, I used email as the label and input’s id attribute. When I ran it through the accessibility checker, there were no red Xs.

While this victory was sweet, I wanted to learn more ways to ensure that labels and inputs were accessible. So I went to Google and found this HTML Forms attributes article. Through reading, I learned that you can add other attributes like placeholder, which demonstrates how the user should present their contact information.

Through these experiences, I realized that creating harmonious labels and inputs for a form is like constructing a sandwich. You want to make sure that your flavors work well together and use the best features of your oven (or whatever appliance you use) to make your sandwich nice and toasty.

Now before we start getting hungry, let’s move on to my next tip. :)

Tip #2: Be More Semantic When Creating a Button

Formatting your form’s buttons is crucial to the efficiency of your HTML form. Buttons are the main way that your user’s information is sent to your desired destination.

When I first started creating HTML forms, I used to create buttons like this:

<input type="submit">

Like the labels and inputs, I would get a red x on WAVE’s accessibility checker. In the results, it mentioned that a value attribute was missing, which makes it difficult for the screen reader to detect the button.

With that in mind, I decided to do what most beginners do when creating this feature:

<button> Submit</button>

When I ran the code in the WAVE accessibility checker again, it passed a few tests. But something inside me told me that my previous solution was ok too and that I just needed to find a way to add a value attribute to it.

With a new thirst for knowledge, I went to Google and found this article on how to create accessible form components. In the section about buttons, they recommend using the following methods to make this element semantic:

<input type="Submit" value="Submit">
<button type="Submit">Submit</button>

When I ran the first snippet into the accessibility checker, I received no red Xs. The same result occurred when I ran the second code snippet through the accessibility checker.

At first, I didn't know which one to pick because both approaches made the form accessible. But something inside me told to go with what I truly wanted. So, I took a deep breath and chose the following code line:

I decided to go with the second code snippet because it's more explicitly labeled, which makes it easier for screen readers to scan. It's also easier to remember, and is the method that I often use for creating buttons.

Think of it as deciding to go with the brand of bread you’ve always used for your sandwiches instead of picking a different one. As cliché as this saying sounds, sometimes simplicity is best.

Before you start getting hungry again, there is just one more suggestion for making your HTML forms error-free.

Tip #3: Pick the Best CSS Framework Based on Your Needs

When I first started creating the style for my forms, I used to force myself to use CSS frameworks like Flexbox. At the time, my feelings of imposter syndrome were at an all-time high due to seeing other people creating great forms with those frameworks. I felt that if I started using them too, I would get those same designs.

At first, I was happy with using Flexbox as it made things like centering content easier as shown in the snippet below:

Unfortunately, I still wasn't satisfied in the end. I found that the design did not come to fruition as I envisioned.

To combat this feeling, I went to Google to find something to help me solve my dilemma. When I was about to give up, I stumbled upon the article, “How to style forms with CSS: A beginner’s guide” by Supun Kavinda.

My heart leaped with joy when it pointed out that you can use vanilla CSS to create beautiful designs. For example, to make the texts’ input fields look more presentable, I could do this:

input[type=text]{
padding: 10px;
}

With newfound confidence, I gave vanilla CSS another chance, and I can honestly say I was so happy with this decision. Here’s the final result:

I wanted to keep my design simple, so I used basic elements like text-align property to center my form's content.

If I had to pick something that exemplifies this experience, it would be like a sandwich cut into two triangle slices. Simple yet effective.

Overall, sometimes, it’s best to go back to the basics before moving on to something more challenging.

Conclusion

There it is folks, my three tips on how to make your HTML forms error-free.

I know creating HTML forms can be frightening in the beginning. But with these tips, confidence, and some imagination, you can HTML forms that wow your viewers. Now go forth and be great! :)

This particular error indicates that there is a problem with importing the force text method from the django.utils.encoding module. The missing method is used for converting input data into a consistent text string format.

Perhaps you might wonder, what exactly caused this error even though you seem to have done everything right, well here is what might have happened:

• Outdated package
• Incorrect import statement

So, we know the cause but how do we solve the error? Below are a couple of steps to solve it:

Step 1: Update Packages and Django

In most cases, the error message will contain information about the package that caused the error. After confirming which one it is, follow the necessary steps to update it.

In most cases, to update a package in Python, you can use pip install <packagename> --upgrade, replacing the packagename with your desired package.

Another cause for an outdated package is if you are using an older version of Django. Previous versions of Django used the force_text method which changed to force_str in the newer version. So updating Django might also solve the problem.

Step 2: Update Import Statement

Next you'll need to confirm that the import statement is correct. The correct import statement should look like this:

from django.utils.encoding import force_text

For Django 3.0 and above, it looks like this:

from django.utils.encoding import force_str

Generally when working with Django, understanding the possible cause of an error will bring you one step closer to solving it.

Be sure to read through the error message carefully, as in most cases it points you to the correct area and how to solve the error you may encounter.

This error can occur on both the YouTube website and the mobile apps for Android and iPhone. In the case of the mobile apps, you might get the error "You're offline. Watch downloads without a connection."

That's because you have videos downloaded on that mobile app. If you don’t have downloaded videos, the error message is the same as you'd see on the web version of YouTube.

In this article, I'll show you how to fix the error on both PC and mobile phones so you can start watching your favorite videos on YouTube once again. But before that, let's look at what causes the error.

What We'll Cover

• What Causes the "You're offline. Check your Connection." YouTube Error?
• How to Fix the "You're offline. Check your Connection." YouTube Error
• How to Fix the "You're offline. Check your Connection." YouTube Error on a Computer
  • Disable your Ad Blocker
  • Disable your Virtual Private Network (VPN)
  • Flush your Computer's DNS in the Command Line
• How to Fix the "You're offline. Check your Connection." YouTube Error on a Mobile Phone
  • Update the YouTube Mobile App
  • Force Stop and Clear your Mobile App's Cache Data
• Conclusion

What Causes the "You're offline. Check your Connection." YouTube Error?

Most errors you encounter online will contain error messages that tell you what went wrong and how to fix them.

In the case of this error, it is related to your internet connection. That's why a part of the error message says "You're offline". Therefore, the causes include:

• A poor or unstable network.
• A faulty Wi-Fi adapter connection.
• An outdated YouTube app or browser.
• Corrupted cache data.

The other part of the error message says "Check your connection". So make sure your internet connection is stable.

But your internet connection may not be the only reason for this error. Read on to see other solutions you can use to fix the error.

How to Fix the "You're offline. Check your Connection." YouTube Error

Since the error is network-related, some quick fixes you can try include:

• Make sure your internet connection is good.
• Refresh the YouTube website or tap retry in the YouTube mobile app.
• Refresh the YouTube mobile app.
• Restart the YouTube mobile app.
• Clear your browser cache.
• Make sure your PC or mobile phone is not in airplane mode.

If all of the quick fixes above fail to work, then keep reading to see other solutions you can use to fix the error on both PC and mobile.

How to Fix the "You're offline. Check your Connection." YouTube Error on a Computer

Disable your Ad Blocker

Ad blockers are software programs that prevent adverts from appearing on websites. They work by blocking the code that displays ads, such as images or videos, before they can be loaded in the browser.

While ad blockers can improve the user experience by removing annoying and intrusive ads, they can also interfere with some website functionalities, including YouTube.

So, disabling the ad blocker(s) on your computer might be enough to get YouTube working again.

Disable your Virtual Private Network (VPN)

A Virtual Private Network (VPN) can interfere with websites like YouTube and cause them not to work properly due to restrictions in the virtual server's location, configuration issues, network congestion, and so on.

So, just like disabling ad blockers, disabling your VPN can be a solution to the error.

Flush your Computer's DNS in the Command Line

Sometimes, clearing your browser's cache might not be enough to get rid of corrupted cache data because the cache might be on your computer itself.

In that case, you need to clear your computer's cache too. And flushing your DNS gets rid of it for you.

To flush your PC's DNS, open CMD and run the following commands one by one:

• ipconfig /flushdns
• ipconfig /release
• ipconfig /renew

How to Fix the "You're offline. Check your Connection." YouTube Error on a Mobile Phone

Update the YouTube Mobile App

If you use an Android device, head over to the Play Store and update the YouTube app if updates are available. And if you use an iPhone, you can download the latest version of the YouTube app on the iOS App Store.

But sometimes, the error occurs even if your mobile app is up to date. In that case, the next solution might fix it for you.

Force Stop and Clear your Mobile App's Cache Data

On an Android phone, long-tap the YouTube app and select "App info":

Tap on "Force stop":

After that, select "Storage & Cache":

Tap on "Clear cache":

If that fails to work, select "Clear storage" or reinstall the YouTube app.

On an iPhone, you can delete and reinstall the YouTube app and the cache data will go away.

Conclusion

This article showed you how to fix the YouTube error, "You're offline. Check your Connection." error on both the web version of YouTube and the mobile apps.

Some of the quick fixes might be enough to fix the error. But sometimes, fixing the error goes beyond those quick fixes. That's why I discussed other advanced fixes for the error.

Thank you for reading. If you found the article helpful, don’t hesitate to share it with your family and friends.

Errors are an inevitable part of programming, and every programmer will encounter them at some point in their career.

Errors in programming can take various forms, including syntax errors, logic errors, and runtime errors, and they can have a significant impact on the functioning of a program.

Understanding the different types of errors in programming and learning how to identify and fix them is essential for writing robust and reliable code.

In this regard, various tools, such as debuggers, profilers, and automated testing frameworks can help you detect and fix errors more efficiently.

In this quick tutorial, we'll look at a specific Python error – the "ModuleNotFoundError: no module named 'requests'" error – to see what causes it and how to fix it.

What is the ModuleNotFoundError: no module named 'requests' Python Error?

The ModuleNotFoundError: no module named 'requests' error occurs when you try to import the requests module in your Python code but the module is not installed or not available in the current environment.

This error is commonly encountered when using Python Django because the requests module is often used for making HTTP requests in Django applications.

How to Fix the ModuleNotFoundError: no module named 'requests' Error in Python

To solve this error, you can follow these steps:

First, check if the requests module is installed. Open a terminal or command prompt and enter the following command:

pip freeze | grep requests

This command will search for the requests module in your environment and print its version number if it is installed. If nothing is printed, it means that the module is not installed.

If the requests module is not installed, you can install it by running the following command in your terminal or command prompt:

pip install requests

This command will download and install the requests module and all its dependencies.

Then you'll need to check if the requests module was imported correctly. Once the requests module is installed, you can import it in your Python code using the following statement:

import requests

Make sure that this statement is placed at the top of your Python file before any other statements that use the requests module.

Finally, if you are using the requests module in a Python Django application, you may need to restart your server after installing the module to ensure that the changes take effect.

Wrapping Up

By following these steps, you should be able to solve the ModuleNotFoundError: no module named 'requests' error and use the requests module in your Python Django application.

And that is it!

Feel free to connect with me on Twitter and on LinkedIn. You can also subscribe to my YouTube channel.

Happy Coding!

In this tutorial, we'll cover some of the most common errors in Python and how to fix them.

Syntax Errors in Python

Syntax errors occur when you have a typo or other mistake in your code that causes it to be invalid syntax. These errors are usually caught by Python's interpreter when you try to run the code.

Here are some tips for avoiding syntax errors:

• Double-check your code for typos or other mistakes before running it.

• Use a code editor that supports syntax highlighting to help you catch syntax errors.

• Read the error message carefully to determine the location of the error.

Example:

if x = 10:
    print("x is equal to 10")

In this example, we are trying to assign the value 10 to the variable x using the assignment operator (=) inside an if statement.

But the correct syntax for comparing values in an if statement is to use the comparison operator (==).

So here's how you fix this one:

if x == 10:
    print("x is equal to 10")

Indentation Errors in Python

One of the most common errors in Python is indentation errors. Unlike many other programming languages, Python uses whitespace to indicate blocks of code, so proper indentation is critical.

Here are a few rules to keep in mind when it comes to indentation in Python:

• Use four spaces for each level of indentation.

• Don't mix tabs and spaces for indentation.

• Make sure your indentation is consistent throughout your code.

To avoid indentation errors, it's a good idea to use a code editor that supports automatic indentation, such as PyCharm or Visual Studio Code.

Example:

for i in range(10):
print(i)

In this example, the code inside the for loop is not indented correctly.

Fix:

for i in range(10):
    print(i)

Name Errors in Python

Name errors occur when you try to use a variable or function that hasn't been defined. For example, if you try to print the value of a variable that hasn't been assigned a value yet, you'll get a name error.

Here are some tips for avoiding name errors:

• Make sure you've defined all variables and functions before using them.

• Double-check the spelling and capitalization of your variable and function names.

• Use Python's built-in debugging tools, such as print statements, to help you track down name errors.

Example:

my_variable = 5
print(my_vairable)

In this example, we misspelled the variable name my_variable as my_vairable.

Fix:

my_variable = 5
print(my_variable)

Type Errors in Python

Another common error in Python is type errors. Type errors occur when you try to perform an operation on data of the wrong type. For example, you might try to add a string and a number, or you might try to access an attribute of an object that doesn't exist.

Here are some tips for avoiding type errors:

• Use type annotations in your code to make it clear what types of data you expect.

• Use Python's built-in type-checking tools, such as the typing module and the mypy tool.

• Write unit tests to ensure that your code handles different types of data correctly.

Example:

x = "5"
y = 10
result = x + y

In this example, we are trying to concatenate a string and an integer, which is not possible.

Fix:

x = "5"
y = 10
result = int(x) + y

Here, we convert the string to an integer using the int() function before performing the addition.

Index Errors in Python

Index errors occur when you try to access an item in a list or other sequence using an index that is out of range. For example, if you try to access the fifth item in a list that only has four items, you'll get an index error.

Here are some tips for avoiding index errors:

• Make sure you're using the correct index values for your sequence.

• Use Python's built-in functions, such as len, to determine the length of your sequence before trying to access items in it.

• Use exception handling, such as try and except blocks, to handle index errors gracefully.

Example:

my_list = [1, 2, 3, 4]
print(my_list[5])

In this example, we are trying to access an item at index 5, which is outside the range of the list.

Fix:

my_list = [1, 2, 3, 4]
print(my_list[3])

Here, we access the item at index 3, which is within the range of the list.

Key Errors in Python

Key errors occur when you try to access a dictionary using a key that doesn't exist. For example, if you try to access the value associated with a key that hasn't been defined in a dictionary, you'll get a key error.

Here are some tips for avoiding key errors:

• Make sure you're using the correct keys for your dictionary.

• Use Python's built-in in operator to check whether a key exists in a dictionary before trying to access it.

• Use exception handling, such as try and except blocks, to handle key errors gracefully.

Example:

my_dict = {"name": "John", "age": 25}
print(my_dict["gender"])

In this example, we are trying to access the value for the key "gender", which does not exist in the dictionary.

Fix:

my_dict = {"name": "John", "age": 25}
print(my_dict.get("gender", "Key not found"))

Here, we use the get() method to access the value for the key "gender". The second argument of the get() method specifies the default value to return if the key does not exist.

Attribute Errors in Python

Attribute errors occur when you try to access an attribute of an object that doesn't exist, or when you try to access an attribute in the wrong way.

There are several different types of attributes in Python:

• Instance attributes: These are attributes that belong to a specific instance of a class.

• Class attributes: These are attributes that belong to a class rather than an instance.

• Static attributes: These are attributes that belong to a class, but can be accessed without creating an instance of the class.

To avoid attribute errors, it's important to understand the different types of attributes and how they work. You should also make sure that you're accessing attributes in the correct way, and that you're not trying to access attributes that don't exist.

Example:

my_list = [1, 2, 3, 4]
my_list.append(5)
my_list.add(6)

In this example, we are trying to add an item to the list using the add() method, which does not exist for lists.

Fix:

my_list = [1, 2, 3, 4]
my_list.append(5)

Here, we use the append() method to add an item to the list.

General Tips

Here are a few general tips for avoiding common errors in Python:

• Use good coding practices, such as commenting your code and following the DRY (Don't Repeat Yourself) principle.

• Write unit tests to catch errors before they make it into your production code.

• Read the documentation for the modules and functions you're using to make sure you're using them correctly.

Conclusion

Python is a powerful language with many features, but like any programming language, it can be prone to errors.

In this article, we covered some of the most common errors in Python and how to fix them. By understanding these errors and how to fix them, you can become a more confident and effective Python programmer.

Let’s connect on Twitter and LinkedIn.

Have you ever encountered a "circular reference" error when working with JSON?

In this tutorial, I'll explain what this error means as well as how to fix it.

This error, in my experience, occurs when you try to convert an object with circular references to JSON. You may have experienced this error while doing this or something else.

First, let's understand what a circular reference is in JavaScript.

What is a Circular Reference in JS?

An object in JavaScript can have different data types for properties. Here's an example of an object:

const obj = {
  name: "Dillion",
  isDev: true,
  hobbies: ["singing", "writing"],
  age: 100,
}

This object has properties containing values of the string, boolean, array, and number data type.

In objects, you can also have a nested object. Here's what I mean:

obj.languages = {
  first: "javascript",
  second: "java",
}

console.log(obj)
// {
//   name: "Dillion",
//   isDev: true,
//   hobbies: ["singing", "writing"],
//   age: 100,
//   languages: {
//     first: "javascript",
//     second: "java"
//   }
// }

Here, we add a languages property, which holds an object value containing the first and second properties.

To access the properties of the nested object, you can use the dot notation (or bracket notation) like this:

obj.languages.first
obj.languages.second

I have a video version of this topic you can also check out.

Now, what if we have a nested object that points to the original object? Take a look at this example:

obj.itself = obj

Here, we add an itself property, and assign it an object reference, which is obj. This is a circular reference. I'll show you why it is called a circular reference.

Let's try to print obj to the console:

// {
//   name: "Dillion",
//   isDev: true,
//   hobbies: ["singing", "writing"],
//   age: 100,
//   languages: {
//     first: "javascript",
//     second: "java"
//   },
//   itself: [Circular *1]
// }

In the console, the value of the itself property shows [Circular *1]. This is a notation that the property points back to the object, and trying to log the value of that property will result in an endlessly nested object.

This means that the itself property will look like this:

{
  name: "Dillion",
  isDev: true,
  hobbies: ["singing", "writing"],
  age: 100,
  languages: {
    first: "javascript",
    second: "java"
  },
  itself: {
    name: "Dillion",
    isDev: true,
    hobbies: ["singing", "writing"],
    age: 100,
    languages: {
      first: "javascript",
      second: "java"
    },
    itself: {
      name: "Dillion",
      // ...
    }
  }
}

Here's a graphical illustration of this:

Graphical illustration of a cyclic reference

As you can see in this object, the itself property has all the properties of the object, including itself, which again has all the properties of the object, including itself and it keeps going on and on without any end.

With this circular reference of the property to the object, we can access the first property like this:

obj.itself.itself.itself.itself.itself.itself.first

This many itselfs still work due to circular reference.

We can also access the name property in obj like this:

obj.itself.itself.itself.itself.name

Since itself has a reference to obj, we can access the name property from any of the nested itselfs.

Now let's see how this circular reference pattern applies to JSON.

JSON's Issue with Circular References

Let's look at our initial object again:

const obj = {
  name: "Dillion",
  isDev: true,
  hobbies: ["singing", "writing"],
  age: 100,
}

When you stringify this object to fit the JSON structure, here's the result:

const stringified = JSON.stringify(obj)

console.log(stringified)
// {
//   "name":"Dillion",
//   "isDev":true,
//   "hobbies":["singing","writing"],"age":100
// }

JSON stringify goes through the properties from the first one being "name" to the last one being "hobbies".

What if we had our nested languages object stringified?

obj.languages = {
  first: "javascript",
  second: "java",
}

const stringified = JSON.stringify(obj)

console.log(stringified)
// {
//   "name":"Dillion",
//   "isDev":true,
//   "hobbies":["singing","writing"],"age":100,
//   "languages":{
//     "first":"javascript",
//     "second":"java"
//   }
// }

As you see here, the stringify method goes through the properties from the first one being "name" to the last one being "languages". When it gets to languages, it goes through the properties of the object which are first and second.

Now let's introduce a circular reference and see what happens:

obj.itself = obj

const stringified = JSON.stringify(obj)

console.log(stringified)
// TypeError: Converting circular structure to JSON

Now we get an error: TypeError: Converting circular structure to JSON.

What's the problem here?

By stringifying an object with a circular reference, that's an infinite stringification process.

Let's say JSON stringify tried to go through this object, here's what happens: the stringify method goes from the first property in obj which is name to the last property itself. When it gets to itself, it stringifies the properties of this object. The value of the itself object is the obj object, so stringify goes through from name to itself again. By coming across itself, it has to go through again.

Here's an illustration explaining what happens:

As you see here, this results in an infinite loop because stringify doesn't know when to stop. Everytime it comes across itself, it has to go through this object that has itself. It will keep stringifying forever.

This is basically impossible. So when the stringify method comes across a circular reference in an object, it just throws an error immediately. There's no need to waste its time 😅

So if you come across this error when building applications, how do you solve it?

How to Solve the Circular Reference Error

There are a couple of ways you can solve this problem. You can use libraries or implement a solution yourself.

One major way to solve this is by using serialization. This process involves serializing the object to remove some properties from an object before converting it to JSON.

In this process, you can remove properties you are not interested in, or in our case, properties that can cause errors.

Here's a simple solution:

obj.itself = obj

function replacer(key, value) {
  if(key === 'itself') {
    return null
  }

  return value
}

const stringified = JSON.stringify(obj, replacer)

console.log(stringified)
// {
//   "name":"Dillion",
//   "isDev":true,
//   "hobbies":["singing","writing"],"age":100,
//   "languages":{
//     "first":"javascript",
//     "second":"java"
//   },
//   "itself":null
// }

What we've done here is use the replacer argument of JSON.stringify to modify the itself property.

In the replacer function, we check for the key itself, and return the value null for that key. This way, JSON.stringify replaces the circular reference value with null during stringifying, thereby avoiding infinite stringification.

Wrapping Up

If you build applications with JavaScript, you may have come across this cyclic reference error one way or the other.

In this article, I've explained what this error is, and why it exists when converting an object to JSON.

If you enjoyed this article, please share it with others 🙏🏾

In this article, we'll look at two ways to validate and/or apply conditional formatting to a sample order form to prevent errors and speed up fulfillment.

gif of man saying, "there is no room for error"

You can find the Excel sheet we're using for this tutorial here.

You may download a local copy to tinker with by selecting File, Save As, Download a Copy:

Download a copy of Excel Workbook

You can find a Google Sheets version of the same thing here.

You may download or make a copy online by selecting File, Download or File, Make a copy.

Download or make a copy of Google Sheet

I'll discuss the Excel version from here on, making reference when something differs in Google Sheets.

Video Walkthrough

Oh, and here's an enjoyable video walkthrough should you feel so inclined. 😁😁

Setup

I've created a three column order form where a store may inventory their product and enter an amount to order. The third column is used by the warehouse to enter how many were actually delivered. This is a real world setup that we'll use in simplified form for this tutorial.

Sample order form in Excel

It can be difficult for fulfillment if there are zeros entered into the order column. Instead of allowing this, we'll use a couple tools to show how to control values in a cell. No matter how clear the directions are, someone will always forget and enter a zero.

Conditional Formatting

By applying conditional formatting, we can effectively white-out the cells that contain zeros (or any negative values).

From the Home Ribbon in Excel and the Format menu in Google Sheets, select Conditional Formatting.

If you don't see the conditional formatting as an option, it'll be over in the styles dropdown or in the far right in a three-dotted dropdown, depending on whether you've got the classic or the new style of ribbon displayed.

Conditional formatting menu in Excel Ribbons

If you want to change your ribbon's layout, select this dropdown arrow at the far right of the ribbon:

Change Excel Ribbon layout

Once you're in the conditional format menu, click Manage Rules. This will let you specify the formatting depending on a ton of options.

Manage conditional formatting rules in Excel

This is where Microsoft Excel does have a leg up on Google Sheets. Excel has more options laid out in a more intuitive way. You can do the same things in each program, but Excel has organized theirs a little better in my opinion.

Conditional formatting menu organization in Excel

We are going to select the Order column as our range and then highlight cells with cell values of less than or equals to zero.

At other times, you'll be using conditional formatting to make data visualization using colors and color scales, but in our case, we want to blot out the zero value.

To do this, I've simply selected a white fill color and a white text color. 🤔

Conditional formatting menu

And now, voilà! If a zero amount is entered, it will simply white out to not distract from the fulfillment center:

Zero value entered and conditional formatting applied

Data Validation

The second option at our disposal is data validation. You can find this on the data tab in the ribbon, and if you're not seeing it, you can find it by exploring the same ribbon options I detailed above.

Data validation menu in ribbon

This will give us a host of options to select to validate the data going into a specified range. There are many options to choose from for our data.

In our case, we want to make sure they are whole numbers greater than zero. Sort of the opposite of the conditional formatting we did above.

Data validation

Another nice Excel feature that's missing at the time of this writing in Google Sheets is the ability to put an Input Message into the data validation.

Input message in data validation

Now, whenever you are on cell in the data validation range, a friendly box will pop up with directions reminding you to not order a zero amount. 😀

Example of input text in spreadsheet

Data validation in Excel defaults to blocking any input that doesn't adhere to the defined conditions.

So, you'll receive an ugly pop up preventing you from entering a zero.

data validation warning

We can improve upon this by setting a custom message here too, though. And we can select whether to block it outright or to allow a zero to be entered after the warning pops up. Effectively allowing the warning to be ignored in the event that there's a reason to do this.

data validation custom warning message

And finally, we can couple any of these options with our conditional formatting so that if we do only warn against the entry, we still blot it out with the white text and white fill color.

The accompanying Excel Sheet and Google Sheet contain four columns of each of the above examples for you to see in action.

I hope this has been helpful for you!

Please come see my video tutorials on YouTube. I'd appreciate a like and subscribe as I'm growing my tech education channel there!

Have a great one!

Some examples of these undefined operations are:

• The square root of a negative number (√-2).
• A divisor with a value of zero (20/0).

The "ValueError: math domain error" error in Python occurs when you carry out a math operation that falls outside the domain of the operation.

To put it simply, this error occurs in Python when you perform a math operation with mathematically undefined values.

In this article, you'll learn how to fix the "ValueError: math domain error" error in Python.

You'll start by learning what the keywords found in the error message mean. You'll then see some practical code examples that raise the error and a fix for each example.

Let's get started!

How to Fix the "ValueError: math domain error" Error in Python

A valueError is raised when a function or operation receives a parameter with an invalid value.

A domain in math is the range of all possible values a function can accept. All values that fall outside the domain are considered "undefined" by the function.

So the math domain error message simply means that you're using a value that falls outside the accepted domain of a function.

Here are some examples:

Example #1 – Python Math Domain Error With math.sqrt

import math

print(math.sqrt(-1))
# ValueError: math domain error

In the code above, we're making use of the sqrt method from the math module to get the square root of a number.

We're getting the "ValueError: math domain error" returned because -1 falls outside the range of numbers whose square root can be obtained mathematically.

Solution #1 – Python Math Domain Error With math.sqrt

To fix this error, simply use an if statement to check if the number is negative before proceeding to find the square root.

If the number is greater than or equal to zero, then the code can be executed. Otherwise, a message would be printed out to notify the user that a negative number can't be used.

Here's a code example:

import math

number = float(input('Enter number: '))

if number >= 0:
    print(f'The square root of {number} is {math.sqrt(number)}')
else: 
    print('Cannot find the square root of a negative number')

Example #2 – Python Math Domain Error With math.log

You use the math.log method to get the logarithm of a number. Just like the sqrt method, you can't get the log of a negative number.

Also, you can't get the log of the number 0. So we have to modify the condition of the if statement to check for that.

Here's an example that raises the error:

import math

print(math.log(0))
# ValueError: math domain error

Solution #2 – Python Math Domain Error With math.log

import math

number = float(input('Enter number: '))

if number > 0:
    print(f'The log of {number} is {math.log(number)}')
else: 
    print('Cannot find the log of 0 or a negative number')

In the code above, we're using the condition of the if statement to make sure the number inputted by the user is neither zero nor a negative number (the number must be greater than zero).

Example #3 – Python Math Domain Error With math.acos

You use the math.acos method to find the arc cosine value of a number.

The domain of the acos method is from -1 to 1, so any value that falls outside that range will raise the "ValueError: math domain error" error.

Here's an example:

import math

print(math.acos(2))
# ValueError: math domain error

Solution #3 – Python Math Domain Error With math.acos

import math

number = float(input('Enter number: '))

if -1 <= number <= 1:
    print(f'The arc cosine of {number} is {math.acos(number)}')
else:
    print('Please enter a number between -1 and 1.')

Just like the solution in other examples, we're using an if statement to make sure the number inputted by the user doesn't exceed a certain range.

That is, any value that falls outside the range of -1 to 1 will prompt the user to input a correct value.

Summary

In this article, we talked about the "ValueError: math domain error" error in Python.

We had a look at some code examples that raised the error, and how to check for and fix them using an if statement.

Happy coding!

Have you ever tried reading about the error type specified by the interpreter before solving these errors? If not, you should, since knowing about these errors can help you solve your problems.

For example, when you encounter an error, you probably Google it. You copy and paste the whole error and try to find out the solution, by visiting various websites and forums. It's a trial and error method of finding and solving bugs.

But what if you already knew why the error generally occurs? This would save you time you'd otherwise spend searching for solutions online. Instead, you could start looking for solutions on your own just by looking at the error type.

In this guide, you will learn about the two mostly encountered error types, which are type error and reference error. You'll learn why they occur, the difference between them, and how to avoid getting these errors.

Note: There are other types of errors in JavaScript like syntax errors, internal errors, range errors, and eval errors. But the scope of this article is limited to the two most commonly occurring errors.

What is a Type Error?

Type errors occur when you use something that is not intended to be used in that particular way. For example, using a screwdriver to hammer in a nail, instead of using a hammer.

Let's understand this using an example:

let a = 1
console.log(a()) 

//output
Uncaught TypeError: a is not a function

Here a is a variable initialized with a value. You encountered an error because you tried to call a function with the variable name. A variable cannot be called as a function. Functions and variables work differently. So in this case, you got a type error. You used the let variable differently from its type.

This gives us a type error.

Solution: To resolve this error, you must refer to the variable in the console, as it is intended to be used. In this case, you pass a as a variable instead of a function.

let a = 1
console.log(a)

//output
1

Let's take another example:

const a = 1
a = 2 // you reassign a const type variable again

//output
TypeError: Assignment to constant variable.

Here, we reassigned the const type variable a to a new value. But you can't change const variables like this, so in this case you get a type error

Solution: never reassign a const type variable once you've defined it.

const a = 1
const b = 2
console.log(a, b)

//output
1 2

Here's another example using an array:

const myArray = [1,2,3,4]
myArray = myArray.push(5) // reassign array

//output
TypeError: Assignment to constant variable.

In this case, we reassigned the const type myArray. This gives us a type error because again, this kind of reassignment is against the properties of const.

Solution:

const myArray = [1,2,3,4]
myArray.push(5) // you can push new values

//output
[1,2,3,4,5]

You can easily push new values to the array without reassigning it. This will not give you any error. Pushing values into an array is allowed. This way you can avoid getting the error.

How to avoid getting a type error

The easiest way to prevent type errors is to avoid using the same names for different variables and functions.

If you use different names, you will not get confused or replace one with another, and you can easily avoid getting this error.

Another way is to make sure you use variables as they're intended to be used. Instead of using const when you need to reassign a value, use let (which allows this kind of change).

What is a Reference Error?

Reference errors occur when you are trying to refer to or use something that does not exist. For example, looking for a screwdriver in your toolbox, but it's not there.

Let's understand this using an example:

let a = 1
console.log(b) // undefined variable used

//output
Uncaught ReferenceError: b is not defined

Here, a is a variable initialized with a value. We encountered an error because we tried to console log the variable b that does not exist. We hadn't yet declared any such variable, so we got a reference error here.

Solution: only use a variable that you've declared to avoid getting an error.

let a = 1
console.log(a) // used defined variable

//output
1

Here's another example:

if(true){
    let a = 1
}

console.log(a)

//output
ReferenceError: a is not defined

In this example, we're trying to access the a variable of type let outside its block. The interpreter cannot find it outside the block. This gives us an error.

Solution:

if(true){
    let a = 1
    console.log(a)
}


//output
1

Using the variable inside its block or scope will not give you any error.

Let's take one more example, but this one can be difficult to understand.

if(true){
    console.log(a)
    let a = 1
}


//output
ReferenceError: Cannot access 'a' before initialization

a is still inside its scope. But we get an error. Why? Because we're trying to use the variable before we've defined it. This is not allowed and goes against the properties of the let variable.

Solution: use the let variable only after defining it.

if(true){
    let a = 1
    console.log(a)

}

//output
1

How to avoid getting a reference error

The easiest way to avoid getting reference errors is to refer to or access only defined variables. Only use variables that exist.

You can also use conditional statements and error handling to avoid running code if a variable or a function does not exist.

Conclusion

You can easily debug your code when you already know how to resolve your errors. It's good to know commonly occurring errors and how to avoid them. This will save you time searching for solutions online and wasting hours trying to find a solution when a little bit of knowledge and awareness about these things can help.

Even more specifically, one amazing thing about the Internet is its ability to handle errors.

What do I mean by errors? When a packet or a frame is received by a machine, we say it contains an error if the data that had been sent is not the data that was received. For instance, a single 1 was mistakenly received as a 0 after its transmission.

This can happen due to many different reasons. Perhaps there was some disturbance in the wire where the data was transmitted – say, a child rode her bicycle over the wire. Perhaps there was some collision in the air as many people transmitted at once. Maybe it was a device's error.

Regardless of the specific reason, you still get valid data on the Internet. Without handling errors, you may read the last sentence and instead of errors read errbbb. Weird, isn't it? So how does the Internet handle errors?

There are two main approaches for handling errors – detection, and correction. We shall start by describing detection, and then talk about correction.

What is Error Detection?

When dealing with error detection, we are looking for a boolean result – True, or False. Is the frame/packet valid, or not. That is all. We don’t want to know where the error occurred. If the frame is invalid, we will simply drop it.

So when the receiver receives a frame, they will determine whether an error has occurred. If the frame is valid, they will read it. If the frame contains errors - the receiver will drop it.

_Error Detection: we only want to know if the frame/packet is valid or not. (Source: Brief)_

One method for error detection is using a checksum. A common implementation of a checksum is called CRC – Cyclic Redundancy Check.

In this post we will not trouble ourselves with the mathematical implementation of CRCs in the real world (if you're interested, check out Wikipedia). Rather, we'll simply try to understand the concept. To do so, let’s implement a very simple checksum mechanism ourselves.

Consider a protocol for transmitting 10-digit phone numbers between endpoints. This protocol is extremely simple: each packet includes exactly 10 bytes, each one representing a digit. For example, a packet might include the following digits:

5551234567

_A packet with a payload of 10 digits (Source: Brief)_

For simplicity's sake, we will omit the headers of the packet and focus solely on the payload.

Now, we will add a checksum. Say that we add all the digits. So in this example, we would calculate 5 + 5 +5 +1+… all the way through 7. We would get 43. This would be our checksum value.

Now, the sender won’t only send the phone number, but also the checksum value right after it. In this example, the sender would send:

_The packet's data is followed by a checksum. (Source: Brief)_

Now, as the receiver, you can do the same thing. You will read the phone number, and calculate the checksum. You will add the digits, and get 43.

Since you've received the correct result (that is, your calculation based on the data matches the checksum value sent in the packet), you can assume that the frame is valid.

_The sender compares their calculated checksum value and the checksum in the packet. If the values match, the packet is assumed to be valid (Source: Brief)_

What happens in case of an error? 🤔

Let’s say, for instance, that the digit 2 was replaced by an 8. Now, even though the sender sent the same stream as before ( 555123456743 ), you, as the receiver, see something a bit different:

_A packet containing an error (Source: Brief)_

Now, you are calculating the checksum, adding all the digits. You get 49. Since this value is different from the checksum value specified in the original frame, 43, the frame is considered to be invalid and you drop it.

_The sender compares their calculated checksum value and the checksum in the packet. If the values don't match, the packet is assumed to be invalid (Source: Brief)_

Are there problems with this method? 🤔

Yes, there are. Consider, for example, what happens if there are two errors – and instead of the original stream ( 555123456743 ), you receive the following:

_A packet received with two errors, resulting in the stream 456123456743 (Source: Brief)_

What happens when you add the digits?

Even though the digits are not the same as the original packet, the checksum will remain correct, and the frame will be regarded as valid.

_Despite the errors, the checksum value happens to be correct, resulting in a false assumption that the packet is valid (Source: Brief)_

Real checksum functions, such as CRCs, are of course much better implemented than the one in our example – but in extremely rare cases, such problems may occur.

Notice that using this kind of method, error detection, we don’t know where the problem occurred, but only whether the frame is valid or not. If the checksum value is invalid, we assume that the frame is invalid and drop it.

What is Error Correction?

As mentioned earlier, detection is not the only way to handle errors. Another approach might be to find the error and correct it. How can we do that?

An extremely simple way would be to transmit the data many times – let’s say, three times. For example, the stream 5551234567 would be transmitted as follows:

_Sending the same data multiple times (Source: Brief)_

So we basically sent the data three times.

Now, in case of an error in one digit, the receiver can look at the other two digits, and choose the one that appears two times out of three.

So, for instance, if we had a problem and 2 was replaced with an 8, the receiver would get this stream:

_An error in one of the occurrences of the data (Source: Brief)_

Now, as a receiver, you can say: “I have 2, 8, 2… so it was probably 2 in the original message”.

Is this problematic? Well, in some rare cases, we might get the same error twice. So it is possible, even though unlikely, that two of the original twos have been received as eights.

So while the sender sent this stream:

_Sending the same data multiple times (Source: Brief)_

The first 2 was mistakenly read as an 8, and also the second 2 was received as an 8:

_Two identical errors; Rare, but possible (Source: Brief)_

Now, it looks as if the original message included an 8, and not a 2.

What can you do in order to lower the probability of such scenario?

The most simple solution would be to simply send the data even more times. Let’s say, five times. So now we duplicate all the data, and send it 5 times in total…

_Sending the data five(!) times (Source: Brief)_

Now, say that two errors occurred, and again two of the 2 digits were replaced with 8s.

_Two identical errors; Rare, but possible (Source: Brief)_

Clearly, it is very unlikely to get the same error twice, but even in this case, we still get 2 three times, so as the receiver you can tell, with a high probability, that the original message contained a 2, rather than an 8.

What's the Overhead?

Now would be a good time to introduce the term overhead. When we say overhead, we basically mean data or time needed to convey the actual message. Let’s first understand what this term means in general, and then consider it in the context of handling errors.

Let’s say that I have a lesson to teach in my university. My goal is to teach the lesson itself, which is also called the payload in that context – that is, the actual data or message I would like to convey.

In order to teach the lesson, or to convey the payload, I first have to physically get to the university – so I get out of my home, walk to the bus station, wait for the bus, take the bus, get off the bus, walk to the building, wait for the lesson to start – and only then do I actually get to teach the lesson.

This entire process is overhead that I have to pay in order to deliver the payload, in this case – to teach the lesson.

_Overhead and Payload are two extremely important terms in Computer Networks (Source: Brief)_

The same applies in computer networks. Our payload is the data, and there is always some overhead associated with sending it.

Back to Handling Errors

In the context here – sending the data three times, as suggested earlier, means that for every byte of payload we have two bytes of overhead. If we send the data five times, then for every byte of payload, we have four bytes of overhead. That’s a LOT!

Consider error detection, on the other hand. In our example protocol for sending phone numbers, how much overhead did we have?

Recall that for every ten-digit phone number, that is ten bytes, we included a two-digit checksum value. In other words, we had two bytes of overhead for ten bytes of payload. It is clear that in our example, error detection yields much smaller overhead in comparison to error correction.

_In the sample protocol, for every ten-digit phone number (ten bytes of payload), we included a two-digit checksum value (two bytes of overhead) (Source: Brief)_

There are better ways to achieve error correction with high accuracy than to simply send the data so many times, but they are more complicated and out of scope for this post. Even with very complicated error correction techniques, they still require lots of overhead when compared to error detection.

Also, notice that except for the bytes sent as overhead in case of error correction, error detection is much simpler.

Error Correction vs Error Detection – Which is Better?

We already concluded that error detection is simpler, and with a smaller payload compared to error correction.

So, when would we prefer error correction?

One case might be when we have a one-way link. That is, a network where we can only transfer data in one direction.

For example, say you have a secret agent that you need to send a message to. The agent knows that they need to look up to the sky at exactly midnight, and they will see a series of flashes indicating the secret message.

The secret agent cannot reply, or their location and identity will be revealed. In addition, you don’t want to send the message over and over again, as not to draw much attention, and to make it harder for someone to intercept the message.

In this case, you definitely want your agent to receive the exact message that you’ve sent. Consider a case where you want to send them the message “do not place the bomb”.

_A sensitive message for a secret agent (Source: Brief)_

Of course, you don’t want to risk the unfortunate scenario of the agent reading the message as “do now place the bomb”, due to an error.

_An error may change the meaning of the message substantially (Source: Brief)_

If you use error detection, the agent might be aware that the message they received is invalid in case of an error, but they won’t be able to tell you that they need you to send the message again. As you want the agent to be able to read your message correctly and without sending any data back to us, error correction is preferred.

So, one-way link is one case where we prefer error correction. What about other cases?

Sometimes you just can’t send the data again, perhaps because it has been erased from the memory of your machine. That is, the data is deleted right after it has been sent. In this case, you'd clearly prefer error correction, as sending the data again, as we would do with error detection, is just impossible.

Also, if sending the data again is possible, but extremely expensive, error correction may be preferable.

For example, if you send a message to the moon, say, with a spaceship – it might be really expensive to send it over again in case of an error. Using error correction, you send the data only once and the receiver should be able to deal with it, even if an error occurred.

_Cases where correction is preferred (Source: Brief)_

In general, we prefer error correction when retransmitting the data is costly or impossible.

When would we prefer error detection?

Well, in case we can retransmit the data, we usually prefer error detection since it comes with very little overhead compared to error correction. Especially, when sending the data is relatively cheap.

For example, on the Internet, if an error occurs when you send a frame, no problem – you can simply send it again!

For example, when I covered the Ethernet protocol in a previous post, I mentioned that Ethernet protocol uses change detection, namely CRC32 – that is, 32 bits (or 4 bytes) of a checksum for every frame.

Note that it doesn’t mean that error detection is simply better. It just better fits the Internet than error correction. As mentioned before, error correction is preferable in other cases.

Wrapping Up

In this tutorial, we discussed various methods for handling errors. We looked at error detection, where we only know whether a frame is valid or not. We also considered error correction, where the receiver can restore the correct value of an erroneous frame. We also introduced the term overhead.

We then understood why we use error detection on the Internet, rather than error correction. Stay tuned for more posts in this series about Computer Networks 💪🏻

About the Author

Omer Rosenbaum is Swimm’s Chief Technology Officer. He's the author of the Brief YouTube Channel. He's also a cyber training expert and founder of Checkpoint Security Academy. He's the author of Computer Networks (in Hebrew). You can find him on Twitter.

Additional Resources

• Computer Networks Playlist - on my Brief channel
• CRC - Wikipedia
• The Complete Guide to Ethernet Protocol

I wondered if it was an M1 issue or because I had yet to shut the machine down. I shut down, and the problem persisted. And I couldn't find anything online indicating that it was an issue with M1. So how could I fix it?

In this tutorial, you'll learn:

• Why does the Error 504 occur?
• What is Laravel Valet and how does it work?
• Valet commands you should know
• How to fix the 504 error and speed up performance in Valet

Why does the Error 504 occur?

Error 504 Nginx

Error 504, also known as "Gateway timeout", is an error that occurs when a server takes longer than usual to respond to an HTTP request. This makes it unable to complete the request cycle.

The Gateway timeout is a server-side error caused by several things. It can result from network connectivity issues when the server exceeds the default limit of 256M or an execution time of 60 seconds, an overloaded server, firewall, and so on.

This error happens with local servers, too, such as XAMPP, WAMP and Valet, during the local development lifecycle.

This article will help you fix this problem on Valet by adding some configurations to speed up the server request lifecycle.

What is Laravel Valet and How Does It Work?

Laravel Valet is a development environment for macOS, Windows, and other operating systems. Once installed, Valet runs Nginx processes in the background when your laptop comes on.

Unlike other development environments like XAMPP and WAMP, you'll have to manually start your server each time you set out to work. Valet then uses DnsMasq to proxy all parked applications to a .test domain.

So, for instance, you would access on XAMPP server http://localhost/application but on valet, you would do http://application.test, and it will point to where the application is installed.

Working with Valet means you don't have to put all applications in an htdocs or www directory. Instead, any random directory you create will work just perfectly in Valet.

Helpful Valet Commands You Should Know:

• valet park: Registers all applications/sites in a directory and exposes them with the .test domain.

cd ~/project_directory
valet park

• valet parked: Gives a tabular breakdown of all registered sites. Information like site name, SSL, URL, and path is available.

cd ~/project_directory
valet parked

• valet secure: Secures your application with an SSL certificate and makes the site accessible over HTTPS.

cd ~/project_directory/site
valet secure

• valet unsecure: Use this command to unsecure your site and revert to serving over HTTP.

cd ~/project_directory/site
valet unsecure

• valet isolate: Isolates a particular site and makes it run on a different PHP version that's not the globally installed version. You can run php -v on the terminal to see the version. But if some of your applications want to downgrade or upgrade, you should use the isolate command and specify the version you need. The isolate command below, enforce the site to use PHP version 7.4:

cd ~/project_directory/site
valet isolate @php7.4

• valet unisolate: Reverts a site back to the globally installed PHP version.

cd ~/project_directory/site
valet unisolate

• valet restart: The restart command ensures all valet services are restarted. It's useful when configurations are modified, updated, and installed.

cd ~/project_directory/site
valet restart

• valet -v: This command helps check the the current Valet version. Not only that, but the command also shows a list of all available commands and descriptions of what they do in Valet.

~/project_directory/site
valet -v

Valet available commands

How to Speed Up Performance in Valet

Over in the terminal, we will need to create a file www.conf in a directory and then add the configuration settings we need.

Get your PHP global version and copy it like this:

php -v

Navigate to the directory and replace the 7.4 with the PHP version you copied earlier.

cd /opt/homebrew/etc/php/7.4/php-fpm.d

Create a www.conf file like this:

touch www.conf

Open the file so you can add the valet configuration settings:

open -a TextEdit www.conf

The command opens up the www.conf file in your text editor and you can update the file with these settings:

pm.max_children = 200
pm.start_servers = 20
pm.min_spare_servers = 10
pm.max_spare_servers = 20
pm.process_idle_timeout = 10s
pm.max_requests = 500

Save and close the file from the text editor.

Let's go through each line we added to the www.conf file:

• pm is an acronym for process manager, and the setting will impact how the process manager controls every child process. The possible values available to us include static, on-demand, and dynamic.
• pm.max_children is a static option, indicating the maximum number of the child processes, which we have set to 200.
• pm.start_servers, pm.max_spare_servers and pm.min_spare_servers: These are dynamic values, and the child processes are set dynamically based on the server directives – that is, start_servers = 20, min_spare_servers = 10 and max_spare_servers = 20.
• pm.process_idle_timeout: the total time taken for an idle request not processed to be killed/terminated is set to a default value of 10 seconds (s). Other units can be estimated in minutes (m), hours (h) or days (d).
• pm.max_requests: This refers to the maximum number of requests a child process can handle at a given time before it's killed/terminated. If the request executes the maximum, it becomes idle, and the pm gets rid of it.

Finally, restart all services from the terminal using the sudo brew command. Notice again the 7.4 – that's because of my global PHP version.

sudo brew services restart php@7.4

You can now say bye-bye to the 504 error and slow Valet performance in your local environment.

Wrapping up

In this article, you have learned about working with Laravel Valet and how to get all Valet configurations set up. You also learned how to ensure a fast development environment and get rid of persistent 504 gateway timeout errors.

Keep learning and Happy Coding!

You can find me on LinkedIn and Twitter.

The Python error, "TypeError: can't multiply sequence by non-int of type float" is no exception to that.

I have prepared this article to show you why this error occurs and how you can fix it. Read on.

Why the "TypeError: can't multiply sequence by non-int of type float" Error Occurs

To understand why you get the error "TypeError: can't multiply sequence by non-int of type float", let's look at the keywords in the error: Typeerror, multiply, sequence, and type float.

• Typeerror is an exception thrown when you put together inappropriate data types in an operation
• multiply in the error means you're trying to perform a multiplication
• sequence is an ordered set in Python. It could be strings, lists, or tuples.
• type float means there's a decimal number in the operation you're trying to perform, for example, 2.4 or 5.40

So, if you're getting this error, it means you're multiplying any of those sequences (usually a string and a tuple) with a floating point number (decimal number).

Indeed, you can multiply a sequence with a number and Python will do the work properly:

site_name = 'freeCodeCamp '

print(site_name * 2)
# freeCodeCamp freeCodeCamp 

print(site_name * 3)
# freeCodeCamp freeCodeCamp freeCodeCamp

stringfied_num = '10 '

print(stringfied_num * 3)
# 10 10 10

Same thing also works for tuples:

myTuple = (4, 3, 4)
print(myTuple * 2)

# (4, 3, 4, 4, 3, 4)

But if you try to do the multiplication with a decimal point number, you get the error "TypeError: can't multiply sequence by non-int of type float":

site_name = 'freeCodeCamp '

print(site_name * 2.5)
# Traceback (most recent call last):  
#   File "seq.py", line 3, in <module>
#     print(site_name * 2.5)
# TypeError: can't multiply sequence by non-int of type 'float'

myTuple = (4, 3, 4)
print(myTuple * 2.2)

# Traceback (most recent call last):   
#   File "seq.py", line 11, in <module>
#     print(myTuple * 2.2)
# TypeError: can't multiply sequence by non-int of type 'float'

How to Fix the "TypeError: can't multiply sequence by non-int of type 'float'" Error

To fix the error "TypeError: can't multiply sequence by non-int of type 'float'", make sure you're not multiplying the string or tuple with a decimal point number.

So instead of multiplying the string or tuple with a floating point number, use an integer. For instance "freeCodeCamp" * 5 instead of "freeCodeCamp" * 5.6:

site_name = 'freeCodeCamp '
print(site_name * 5)

# freeCodeCamp freeCodeCamp freeCodeCamp freeCodeCamp freeCodeCamp

If you're dealing with a number in strings, for example, "10", you can convert the string to an integer with the int() method and to float with the float() method:

stringfied_num = '10 '

print(int(stringfied_num) * 3)
# 30

stringfied_num = '10 '

print(float(stringfied_num) * 3)
# 30

If you're dealing with a user input, you can also find a way to convert the floating-point number to an integer. In fact, you should handle the possibility of the user entering a decimal point number instead of a straight integer:

# declare a string variable
site_name = 'freeCodeCamp '

# Get the user input and convert it to a decimal number
user_input = float(input("Enter a number: "))

# Round the number entered by the user to the nearest whole number
rounded_input = round(user_input)

# Multiply the site_name variable by the user input
result = rounded_input * site_name

# Print the result to the console
print(result)

# I entered 3.6 and the result was: freeCodeCamp freeCodeCamp freeCodeCamp freeCodeCamp

Conclusion

You cannot multiply a sequence by a floating point number. What you get if you do that is the error, TypeError: can't multiply sequence by non-int of type 'float'. That's why this article was dedicated to letting you know how to fix the error.

The takeaway from this article is that if you're using any string as a number, you should make sure they are converted with the float() method – especially if they are used in a calculation.

This error might be raised when using either JavaScript or TypeScript in the back-end. So you could be working on the client side with React, Vue, and so on, and still run into this error.

You can also encounter this error when working with JavaScript on the client side.

In this article, you'll learn how to fix the SyntaxError: Cannot use import statement outside a module error when using TypeScript or JavaScript with Node.

You'll also learn how to fix the error when working with JavaScript on the client side.

How to Fix the TypeScript SyntaxError: Cannot use import statement outside a module Error

In this section, we'll work with a basic Node server using Express.

Note that if you're using the latest version of TypeScript for your Node app, the tsconfig.json file has default rules that prevent the SyntaxError: Cannot use import statement outside a module error from being raised.

So you're most likely not going to encounter the SyntaxError: Cannot use import statement outside a module error if you:

• Install the latest version of TypeScript, and are using the default tsconfig.json file that is generated when you run tsc init with the latest version.
• Setup TypeScript correctly for Node and install the necessary packages.

But let's assume you're not using the latest tsconfig.json file configurations.

Here's an Express server that listens on port 3000 and logs "Hello World!" to the console:

import express from "express"

const app = express()

app.listen("3000", (): void => {
    console.log("Hello World!")
    // SyntaxError: Cannot use import statement outside a module
})

The code above looks as though it should run perfectly but the SyntaxError: Cannot use import statement outside a module is raised.

This is happening because we used the import keyword to import a module: import express from "express".

To fix this, head over to the tsconfig.json file and scroll to the modules section.

You should see a particular rule like this under the modules section:

/* Modules */
"module": "esnext"

To fix the problem, change the value "esnext" to "commonjs".

That is:

/* Modules */
"module": "commonjs"

How to Fix the JavaScript SyntaxError: Cannot use import statement outside a module Error

Fixing the SyntaxError: Cannot use import statement outside a module error when using vanilla JS is a bit different from TypeScript.

Here's our server:

import express from "express";

const app = express();

app.listen(3000, () => {
    console.log("Hello World!");
    // SyntaxError: Cannot use import statement outside a module
});

We're getting the SyntaxError: Cannot use import statement outside a module error for the same reason — we used the import keyword to import a module.

To fix this, go to the package.json file and add "type": "module",. That is:

{
  "name": "js",
  "version": "1.0.0",
  "description": "",
  "main": "app.js",
  "type": "module",
  "scripts": {
    "test": "echo \"Error: no test specified\" && exit 1"
  },
  "keywords": [],
  "author": "",
  "license": "ISC",
  "dependencies": {
    "express": "^4.18.2"
  }
}

Now you can use the import keyword without getting an error.

To fix this error when working with JavaScript on the client side (without any frameworks), simply add the attribute type="module" to the script tag of the file you want to import as a module. That is:

<script type="module" src="./add.js"></script>

Summary

In this article, we talked about the SyntaxError: Cannot use import statement outside a module error in TypeScript and JavaScript.

This error mainly occurs when you use the import keyword to import a module in Node.js. Or when you omit the type="module" attribute in a script tag.

We saw code examples that raised the error and how to fix them when working with TypeScript and JavaScript.

Happy coding!

You’re not alone, because I’m currently getting it too:

The React app indeed failed to start:

In this article, you’ll learn how to fix this error in 3 ways. But first, let’s discuss what causes the error.

What Causes the "0308010c:digital envelope routines::unsupported" Error?

You are likely getting this error because of 2 main reasons:

• you’re not using the LTS (long term support) version of Node JS. You can see I’m using Node 17.0.0, which is not an LTS version of Node.
• you’re using react-script with a version less than 5

The error can also occur because you’re using Node 17.

How to Fix the "0308010c:digital envelope routines::unsupported" Error

There are at least 3 ways by which you can fix this error. We are going to look at them one by one. Any of them should work for you.

Pass --openssl-legacy-provider to Webpack or the CLI Tool

In a React app, for instance, you can pass --openssl-legacy-provider to the start script like this "react-scripts --openssl-legacy-provider start".

That should do it. But if this fails to fix the error, then proceed to the next fix. On many occasions, it works.

Use an LTS Version of Node JS

Consider downgrading your Node version to 16.16.0 or other LTS versions.

Currently, 18.12.1 is the latest LTS version of Node. You can download it from the Node JS official website or use NVM to install it.

Upgrade React Script to Version 5+

If you’re working with React and this still fails to fix the error for you, then it’s likely an issue with your React script.

If you’re using a React script version less than 5, then you should upgrade it to version 5+.

In my case, I’m currently using react-scripts 3.4.3:

To upgrade react-scripts to 5+, you can do it in two ways:

• Uninstall and reinstall react-scripts

  • open the terminal and run npm uninstall react-scripts
  • run npm install react-scripts

• Manually change the react script version

  • go to your package.json and change the react-script version to 5.0.2
  • delete the node_modules folder by running rm –rf node_modules
  • delete the package.lock.json file by running rm –rf package.lock.json
  • run npm install or yarn add, depending on the package manager you’re using

After upgrading the version of react-scripts to 5+, my React app is now working fine:

Conclusion

As already pointed out in this article, if you are getting the "0308010c:digital envelope routines::unsupported" error, then it could happen you’re not using an LTS version of Node JS, or you’re using react-scripts version <5.

Hopefully the fixes we discussed in this tutorial help you fix this error. If any of the fixes fail to work for you, then you should try the others. In my case, upgrading react-scripts to 5+ was what worked for me.

Thank you for reading.