typeerror 'nonetype' object does not support item assignment python

TypeError: NoneType object does not support item assignment

Last updated: Apr 8, 2024 Reading time · 3 min

# TypeError: NoneType object does not support item assignment

The Python "TypeError: NoneType object does not support item assignment" occurs when we try to perform an item assignment on a None value.

To solve the error, figure out where the variable got assigned a None value and correct the assignment.

Here is an example of how the error occurs.

We tried to assign a value to a variable that stores None .

# Checking if the variable doesn't store None

Use an if statement if you need to check if a variable doesn't store a None value before the assignment.

The if block is only run if the variable doesn't store a None value, otherwise, the else block runs.

# Setting a fallback value if the variable stores None

Alternatively, you can set a fallback value if the variable stores None .

If the variable stores a None value, we set it to an empty dictionary.

# Track down where the variable got assigned a None value

You have to figure out where the variable got assigned a None value in your code and correct the assignment to a list or a dictionary.

The most common sources of None values are:

• Having a function that doesn't return anything (returns None implicitly).
• Explicitly setting a variable to None .
• Assigning a variable to the result of calling a built-in function that doesn't return anything.
• Having a function that only returns a value if a certain condition is met.

# Functions that don't return a value return None

Functions that don't explicitly return a value return None .

You can use the return statement to return a value from a function.

The function now returns a list, so we can safely change the value of a list element using square brackets.

# Many built-in functions return None

Note that there are many built-in functions (e.g. sort() ) that mutate the original object in place and return None .

The sort() method mutates the list in place and returns None , so we shouldn't store the result of calling it into a variable.

To solve the error, remove the assignment.

# A function that returns a value only if a condition is met

Another common cause of the error is having a function that returns a value only if a condition is met.

The if statement in the get_list function is only run if the passed-in argument has a length greater than 3 .

To solve the error, you either have to check if the function didn't return None or return a default value if the condition is not met.

Now the function is guaranteed to return a value regardless of whether the condition is met.

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

• How to Return a default value if None in Python
• Why does my function print None in Python [Solved]
• Check if a Variable is or is not None in Python
• Convert None to Empty string or an Integer in Python
• How to Convert JSON NULL values to None using Python
• Join multiple Strings with possibly None values in Python
• Why does list.reverse() return None in Python

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Web Developer

Copyright © 2024 Borislav Hadzhiev

Typeerror: nonetype object does not support item assignment

When working with Python projects, we may come across an error that reads “Typeerror: nonetype object does not support item assignment” .

At first glance, this error message can seem cryptic and frustrating. However, it’s actually a helpful clue that points toward the root of the problem.

In this guide, we’ll explore the causes of this error as well as provide practical examples of how to resolve it.

By the end of this guide, we’ll have a better understanding of how to prevent and fix this error in Python.

What is Typeerror: nonetype object does not support item assignment?

The Python error TypeError: ‘NoneType’ object does not support item assignment occurs means that we are trying to assign a value to an object that has a value of None (or null in other programming languages).

Moreover, None is a special value that represents the absence of a value.

Thus it is often used as a default value for function arguments or to indicate that a variable has not been initialized.

Take a look at the next section on how this error occurs…

How to reproduce Typeerror: nonetype object does not support item assignment

Here’s an example code snippet that could produce this error:

In this code, we have a variable x that has not been assigned a value. Its value will be None by default.

Therefore if we try to assign a value to x[0] , you will get a TypeError because you cannot assign a value to an index of None.

Now let’s find the possible factors why and when we can get this error. Hence you might consider in finding solutions.

When do we get this error?

These are the common possible causes when we got the TypeError: ‘NoneType’ object does not support item assignment.

• Trying to assign a value to a variable that has not been initialized or is set to None.
• Using the wrong data type in an operation that requires a mutable object, such as a list or dictionary.
• Calling a function that returns None and trying to perform an item assignment on the result.
• Accessing an object that does not exist, which results in None.
• Overwriting a variable with a function that returns None, causing the variable to become None.
• Using the wrong variable name or referencing the wrong object in a function call.

This time let’s figure out what are the solutions to this error…

How to fix nonetype object does not support item assignment

Here are the possible solutions you can try in fixing the error nonetype object does not support item assignment .

Solution 1: Verify why the variable is assigned to the value None

The first way to fix the error is to ensure why the variable is assigned to None.

Meanwhile, if we assigned a mutable collection of objects (list, set, array, etc.) in a variable it will definitely fix the error.

For example:

[10, 20, 30]

Solution 2: Skip assigning the value using the index if variable is None

In this solution, we should avoid assigning the value using the index, when the variable is assigned to None.

In short, accessing value with an index is pointless.

We should do this way instead:

Solution 3: Create a list with a value assigned to None

Create a list with values assigned to when a variable is assigned to None needs to store values in the variable.

Moreover, the index should be available in the list. Wherein the list assigned to the value None is changeable by adding values to the index.

[5, None, None, None, None, None, None, None, None, None]

Anyway, we also have a solution for Typeerror series objects are mutable thus they cannot be hashed errors, you might encounter.

To conclude, Typeerror: nonetype object does not support item assignment occurs when we are trying to assign a value to an object which has a value of None.

To fix this error, we need to make sure that the variable we are trying to access has a valid value before trying to assign an item to it.

I think that’s all for this guide. We hope you have learned and we helped you fix your error.

Thank you for reading! 😊

TypeError: 'NoneType' object does not support item assignment

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OpenCV: Resolving NoneType errors

by Adrian Rosebrock on December 26, 2016

Each week I receive and respond to at least 2-3 emails and 3-4 blog post comments regarding NoneType errors in OpenCV and Python.

For beginners, these errors can be hard to diagnose — by definition they aren’t very informative.

Since this question is getting asked so often I decided to dedicate an entire blog post to the topic.

While NoneType errors can be caused for a nearly unlimited number of reasons, in my experience, both as a computer vision developer and chatting with other programmers here on PyImageSearch, in over 95% of the cases, NoneType errors in OpenCV are caused by either:

• An invalid image path passed to cv2.imread .
• A problem reading a frame from a video stream/video file via cv2.VideoCapture and the associated .read method.

To learn more about NoneType errors in OpenCV (and how to avoid them), just keep reading .

Looking for the source code to this post?

In the first part of this blog post I’ll discuss exactly what NoneType errors are in the Python programming language.

I’ll then discuss the two primary reasons you’ll run into NoneType errors when using OpenCV and Python together.

Finally, I’ll put together an actual example that not only causes a NoneType error, but also resolves it as well.

What is a NoneType error?

When using the Python programming language you’ll inevitably run into an error that looks like this:

Where something can be replaced by whatever the name of the actual attribute is.

We see these errors when we think we are working with an instance of a particular Class or Object, but in reality we have the Python built-in type None .

As the name suggests, None represents the absence of a value, such as when a function call returns an unexpected result or fails entirely.

Here is an example of generating a NoneType error from the Python shell:

Here I create a variable named foo and set it to None .

I then try to set the bar attribute of foo to True , but since foo is a NoneType object, Python will not allow this — hence the error message.

Two reasons for 95% of OpenCV NoneType errors

When using OpenCV and Python bindings, you’re bound to come across NoneType errors at some point.

In my experience, over 95% of the time these NoneType errors can be traced back to either an issue with cv2.imread or cv2.VideoCapture .

I have provided details for each of the cases below.

Case #1: cv2.imread

If you are receiving a NoneType error and your code is calling cv2.imread , then the likely cause of the error is an invalid file path supplied to cv2.imread .

The cv2.imread function does not explicitly throw an error message if you give it an invalid file path (i.e., a path to a nonexistent file). Instead, cv2.imread will simply return None .

Anytime you try to access an attribute of a None image loaded from disk via cv2.imread you’ll get a NoneType error.

Here is an example of trying to load a nonexistent image from disk:

As you can see, cv2.imread gladly accepts the image path (even though it doesn’t exist), realizes the image path is invalid, and returns None . This is especially confusing for Python programmers who are used to these types of functions throwing exceptions.

As an added bonus, I’ll also mention the AssertionFailed exception.

If you try to pass an invalid image (i.e., NoneType image) into another OpenCV function , Python + OpenCV will complain that the image doesn’t have any width, height, or depth information — and how could it, the “image” is a None object after all!

Here is an example of an error message you might see when loading a nonexistent image from disk and followed by immediately calling an OpenCV function on it:

These types of errors can be harder to debug since there are many reasons why an AssertionError could be thrown. But in most cases, your first step should be be ensuring that your image was correctly loaded from disk.

A final, more rare problem you may encounter with cv2.imread is that your image does exist on disk, but you didn’t compile OpenCV with the given image I/O libraries installed.

For example, let’s say you have a .JPEG file on disk and you knew you had the correct path to it.

You then try to load the JPEG file via cv2.imread and notice a NoneType or AssertionError .

How can this be?

The file exists!

In this case, you likely forgot to compile OpenCV with JPEG file support enabled.

In Debian/Ubuntu systems, this is caused by a lack of libjpeg being installed.

For macOS systems, you likely forgot to install the jpeg library via Homebrew.

To resolve this problem, regardless of operating system, you’ll need to re-compile and re-install OpenCV. Please see this page for more details on how to compile and install OpenCV on your particular system.

Case #2: cv2.VideoCapture and .read

Just like we see NoneType errors and AssertionError exceptions when using cv2.imread , you’ll also see these errors when working with video streams/video files as well.

To access a video stream, OpenCV uses the cv2.VideoCapture which accepts a single argument, either:

• A string representing the path to a video file on disk.
• An integer representing the index of a webcam on your computer.

Working with video streams and video files with OpenCV is more complex than simply loading an image via cv2.imread , but the same rules apply.

If you try to call the .read method of an instantiated cv2.VideoCapture (regardless if it’s a video file or webcam stream) and notice a NoneType error or AssertionError , then you likely have a problem with either:

• The path to your input video file (it’s probably incorrect).
• Not having the proper video codecs installed, in which case you’ll need to install the codecs, followed by re-compiling and re-installing OpenCV (see this page for a complete list of tutorials).
• Your webcam not being accessible via OpenCV. This could be for any number of reasons, including missing drivers, an incorrect index passed to cv2.VideoCapture , or simply your webcam is not properly attached to your system.

Again, working with video files is more complex than working with simple image files, so make sure you’re systematic in resolving the issue.

First, try to access your webcam via a separate piece of software than OpenCV.

Or, try to load your video file in a movie player.

If both of those work, you likely have a problem with your OpenCV install.

Otherwise, it’s most likely a codec or driver issue.

An example of creating and resolving an OpenCV NoneType error

To demonstrate a NoneType error in action I decided to create a highly simplified Python + OpenCV script that represents what you might see elsewhere on the PyImageSearch blog.

Open up a new file, name it display_image.py , and insert the following code:

All this script does is:

• Parse command line arguments.
• (Attempts to) load an image from disk.
• Prints the width, height, and depth of the image to the terminal.
• Displays the image to our screen.

For most Python developers who are familiar with the command line, this script won’t give you any trouble.

But if you’re new to the command line and are unfamiliar/uncomfortable with command line arguments, you can easily run into a NoneType error if you’re not careful.

How, you might say?

The answer lies in not properly using/understanding command line arguments.

Over the past few years of running this blog, I’ve seen many emails and blog post comments from readers who are trying to modify the .add_argument function to supply the path to their image file.

DON’T DO THIS — you don’t have to change a single line of argument parsing code.

Instead, what you should do is spend the next 10 minutes reading through this excellent article that explains what command line arguments are and how to use them in Python:

https://pyimagesearch.com/2018/03/12/python-argparse-command-line-arguments/

This is required reading if you expect to follow tutorials here on the PyImageSearch blog.

Working with the command line, and therefore command line arguments, are a big part of what it means to be a computer scientist — a lack of command line skills is only going to harm you . You’ll thank me later.

Going back to the example, let’s check the contents of my local directory:

As we can see, I have two files:

• display_image.py : My Python script that I’ll be executing shortly.
• jemma.png : The photo I’ll be loading from disk.

If I execute the following command I’ll see the jemma.png image displayed to my screen, along with information on the dimensions of the image:

However, let’s try to load an image path that does not exist:

Sure enough, there is our NoneType   error.

In this case, it was caused because I did not supply a valid image path to cv2.imread  .

What's next? We recommend PyImageSearch University .

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In this blog post I discussed NoneType   errors and AssertionError   exceptions in OpenCV and Python.

In the vast majority of these situations, these errors can be attributed to either the cv2.imread   or cv2.VideoCapture   methods.

Whenever you encounter one of these errors,  make sure you can load your image/read your frame before continuing. In over 95% of circumstances, your image/frame was not properly read.

Otherwise, if you are using command line arguments and are unfamiliar with them, there is a chance that you aren’t using them properly. In that case, make sure you educate yourself by reading this tutorial on command line arguments — you’ll thank me later.

Anyway, I hope this tutorial has helped you in your journey to OpenCV mastery!

If you’re just getting started studying computer vision and OpenCV, I would highly encourage you to take a look at my book,  Practical Python and OpenCV , which will help you grasp the fundamentals.

Otherwise, make sure you enter your email address in the form below to be notified when future blog posts and tutorials are published!

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About the Author

Hi there, I’m Adrian Rosebrock, PhD. All too often I see developers, students, and researchers wasting their time, studying the wrong things, and generally struggling to get started with Computer Vision, Deep Learning, and OpenCV. I created this website to show you what I believe is the best possible way to get your start.

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TypeError: Type object does not support item assignment: How to fix it?

TypeError: Type object does not support item assignment

Have you ever tried to assign a value to a property of a type object and received a TypeError? If so, you’re not alone. This error is a common one, and it can be frustrating to figure out what went wrong.

In this article, we’ll take a look at what a type object is, why you can’t assign values to its properties, and how to avoid this error. We’ll also provide some examples of how to work with type objects correctly.

So, if you’re ready to learn more about TypeErrors and type objects, read on!

What is a type object?

A type object is a special kind of object that represents a data type. For example, the `int` type object represents the integer data type, and the `str` type object represents the string data type.

Type objects are created when you use the `type()` function. For example, the following code creates a type object for the integer data type:

python int_type = type(1)

Type objects have a number of properties that you can use to get information about them. For example, the `__name__` property returns the name of the type, and the `__bases__` property returns a list of the type’s base classes.

Why can’t you assign values to type objects?

Type objects are immutable, which means that their values cannot be changed. This is because type objects are used to represent the abstract concept of a data type, and their values are not meant to be changed.

If you try to assign a value to a property of a type object, you’ll receive a TypeError. For example, the following code will raise a TypeError:

python int_type.name = “New name”

How to avoid TypeErrors

To avoid TypeErrors, you should never try to assign values to properties of type objects. If you need to change the value of a property, you should create a new object with the desired value.

For example, the following code correctly changes the value of the `name` property of an integer object:

python new_int = int(1) new_int.name = “New name”

TypeErrors can be frustrating, but they can usually be avoided by understanding what type objects are and how they work. By following the tips in this article, you can avoid these errors and write more robust code.

| Header 1 | Header 2 | Header 3 | |—|—|—| | TypeError: type object does not support item assignment | Definition | Cause | | An error that occurs when you try to assign a value to an element of a type object that does not support item assignment. | The type object is immutable, which means that its values cannot be changed. | Trying to assign a value to an element of a type object will result in a TypeError. |

A TypeError is a type of error that occurs when an operation or function is applied to an object of an inappropriate type. For example, trying to assign a value to an attribute of a type object will result in a TypeError.

TypeErrors can be difficult to debug, because they can occur in a variety of situations. However, by understanding what causes a TypeError, you can be better equipped to avoid them.

What causes a TypeError?

There are a few different things that can cause a TypeError:

• Using an incompatible data type: One of the most common causes of a TypeError is using an incompatible data type. For example, trying to add a string to a number will result in a TypeError.
• Using an invalid operator: Another common cause of a TypeError is using an invalid operator. For example, trying to divide a number by zero will result in a TypeError.
• Calling a method on an object that doesn’t support it: Finally, trying to call a method on an object that doesn’t support it can also result in a TypeError. For example, trying to call the `.sort()` method on a string will result in a TypeError.

There are a few things you can do to avoid TypeErrors:

• Be careful about the data types you use: Make sure that you are using the correct data types for your operations. For example, if you are adding two numbers, make sure that both numbers are numbers.
• Use the correct operators: Make sure that you are using the correct operators for your operations. For example, if you are dividing two numbers, use the `/` operator.
• Read the documentation: If you are not sure whether a method is supported by an object, read the documentation to find out.

By following these tips, you can help to avoid TypeErrors in your code.

TypeErrors can be a frustrating experience, but they can also be a learning opportunity. By understanding what causes a TypeError, you can be better equipped to avoid them. And by following the tips in this article, you can help to reduce the number of TypeErrors in your code.

Additional resources

• [Python TypeError documentation](https://docs.python.org/3/library/exceptions.htmlTypeError)
• [Stack Overflow: TypeError questions](https://stackoverflow.com/questions/tagged/typeerror)
• [Real Python: How to avoid TypeErrors in Python](https://realpython.com/python-typeerror/)

3. How to fix a TypeError?

To fix a TypeError, you need to identify the cause of the error and then take steps to correct it. Some common fixes include:

Using the correct data type

Using the correct operator

Calling the correct method on the object

Let’s take a look at some examples of how to fix each of these types of errors.

One of the most common causes of TypeErrors is using the wrong data type. For example, if you try to add a string to an integer, you will get a TypeError because strings and integers are different data types. To fix this error, you need to convert the string to an integer or the integer to a string.

x = ‘123’ y = 456

This will raise a TypeError because you cannot add a string to an integer z = x + y

To fix this error, you can convert the string to an integer z = int(x) + y

Another common cause of TypeErrors is using the wrong operator. For example, if you try to divide an integer by a string, you will get a TypeError because you cannot divide an integer by a string. To fix this error, you need to use the correct operator.

x = 123 y = ‘456’

This will raise a TypeError because you cannot divide an integer by a string z = x / y

To fix this error, you can use the `str()` function to convert the string to an integer z = x / int(y)

Finally, another common cause of TypeErrors is calling the wrong method on an object. For example, if you try to call the `len()` method on a string, you will get a TypeError because the `len()` method is not defined for strings. To fix this error, you need to call the correct method on the object.

x = ‘hello’

This will raise a TypeError because the `len()` method is not defined for strings y = len(x)

To fix this error, you can use the `str()` function to convert the string to an integer y = len(str(x))

By following these tips, you can help to avoid TypeErrors in your Python code.

4. Examples of TypeErrors

Here are some examples of TypeErrors:

x = ‘hello’ x[0] = ‘a’

This will result in a TypeError because strings are immutable and cannot be changed.

print(int(‘123’))

This will also result in a TypeError because the string ‘123’ cannot be converted to an integer.

class MyClass: def __init__(self, name): self.name = name

my_class = MyClass(‘John’) my_class.name = ‘Jane’

This will also result in a TypeError because the method `name` is not defined on the `MyClass` object.

TypeErrors are a common problem in Python, but they can be easily avoided by following the tips in this article. By using the correct data types, operators, and methods, you can help to ensure that your Python code is free of errors.

Q: What does the error “TypeError: type object does not support item assignment” mean?

A: This error occurs when you try to assign a value to a property of a type object. For example, the following code will raise an error:

>>> type = type(‘MyType’, (object,), {}) >>> type.name = ‘MyType’ Traceback (most recent call last): File “ “, line 1, in TypeError: type object does not support item assignment

The reason for this error is that type objects are immutable, which means that their properties cannot be changed after they are created. If you need to change the value of a property of a type object, you can create a new type object with the desired value.

Q: How can I fix the error “TypeError: type object does not support item assignment”?

A: There are two ways to fix this error. The first way is to create a new type object with the desired value. For example, the following code will fix the error in the example above:

>>> type = type(‘MyType’, (object,), {‘name’: ‘MyType’}) >>> type.name ‘MyType’

The second way to fix this error is to use a dictionary to store the properties of the type object. For example, the following code will also fix the error in the example above:

>>> type = type(‘MyType’, (object,), {}) >>> type.__dict__[‘name’] = ‘MyType’ >>> type.name ‘MyType’

Q: What are some common causes of the error “TypeError: type object does not support item assignment”?

A: There are a few common causes of this error. The first is trying to assign a value to a property of a type object that does not exist. For example, the following code will raise an error:

>>> type = type(‘MyType’, (object,), {}) >>> type.foo = ‘bar’ Traceback (most recent call last): File “ “, line 1, in AttributeError: type object has no attribute ‘foo’

The second is trying to assign a value to a property of a type object that is read-only. For example, the following code will also raise an error:

>>> type = type(‘MyType’, (object,), {}) >>> type.name = ‘MyType’ Traceback (most recent call last): File “ “, line 1, in TypeError: can’t set attribute ‘name’ of type object

The third is trying to assign a value to a property of a type object that is not a valid type. For example, the following code will also raise an error:

>>> type = type(‘MyType’, (object,), {}) >>> type.name = 123 Traceback (most recent call last): File “ “, line 1, in TypeError: can’t assign int to str object

Q: How can I avoid the error “TypeError: type object does not support item assignment”?

A: There are a few things you can do to avoid this error. First, make sure that you are trying to assign a value to a property of a type object that exists. Second, make sure that you are not trying to assign a value to a property of a type object that is read-only. Third, make sure that you are not trying to assign a value to a property of a type object that is not a valid type.

Here are some specific examples of how to avoid this error:

• Instead of trying to assign a value to the `name` property of a type object, you can create a new type object with the desired value. For example:

>>> type = type(‘MyType’, (object,), {‘name’: ‘MyType’})

• Instead of trying to assign a value to the `name` property of a type object, you can use a dictionary to store the properties of the type object. For example:

>>> type = type(‘MyType’, (object,), {}) >>> type.__dict__[‘name’] = ‘MyType’

• Instead of trying to assign a value to the `name` property of a type object, you can use a getter and setter method to access the property. For example:

In this blog post, we discussed the TypeError: type object does not support item assignment error. We first explained what the error is and then provided several ways to fix it. We also discussed some common causes of the error and how to avoid them.

We hope that this blog post has been helpful and that you now have a better understanding of the TypeError: type object does not support item assignment error. If you have any other questions or comments, please feel free to leave them below.

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How to Fix: ‘numpy.float64’ object does not support item assignment

One common error you may encounter when using Python is:

This error usually occurs when you attempt to use brackets to assign a new value to a NumPy variable that has a type of float64 .

The following example shows how to resolve this error in practice.

How to Reproduce the Error

Suppose we create some NumPy variable that has a value of 15.22 and we attempt to use brackets to assign it a new value of 13.7 :

We receive the error that ‘numpy.float64’ object does not support item assignment .

We received this error because one_float is a scalar but we attempted to treat it like an array where we could use brackets to change the value in index position 0.

Since one_float is not an array, we can’t use brackets when attempting to change its value.

How to Fix the Error

The way to resolve this error is to simply not use brackets when assigning a new value to the float:

We’re able to successfully change the value from 15.22 to 13.7 because we didn’t use brackets.

Note that it’s fine to use brackets to change values in specific index positions as long as you’re working with an array.

For example, the following code shows how to change the first element in a NumPy array from 15.22 to 13.7 by using bracket notation:

This time we don’t receive an error either because we’re working with a NumPy array so it makes sense to use brackets.

Additional Resources

The following tutorials explain how to fix other common errors in Python:

How to Fix in Python: ‘numpy.ndarray’ object is not callable How to Fix: TypeError: ‘numpy.float64’ object is not callable How to Fix: Typeerror: expected string or bytes-like object

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Hey there. My name is Zach Bobbitt. I have a Masters of Science degree in Applied Statistics and I’ve worked on machine learning algorithms for professional businesses in both healthcare and retail. I’m passionate about statistics, machine learning, and data visualization and I created Statology to be a resource for both students and teachers alike.  My goal with this site is to help you learn statistics through using simple terms, plenty of real-world examples, and helpful illustrations.

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• Python »
• 3.14.0a0 Documentation »
• The Python Tutorial »
• 3. An Informal Introduction to Python
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3. An Informal Introduction to Python ¶

In the following examples, input and output are distinguished by the presence or absence of prompts ( >>> and … ): to repeat the example, you must type everything after the prompt, when the prompt appears; lines that do not begin with a prompt are output from the interpreter. Note that a secondary prompt on a line by itself in an example means you must type a blank line; this is used to end a multi-line command.

You can toggle the display of prompts and output by clicking on >>> in the upper-right corner of an example box. If you hide the prompts and output for an example, then you can easily copy and paste the input lines into your interpreter.

Many of the examples in this manual, even those entered at the interactive prompt, include comments. Comments in Python start with the hash character, # , and extend to the end of the physical line. A comment may appear at the start of a line or following whitespace or code, but not within a string literal. A hash character within a string literal is just a hash character. Since comments are to clarify code and are not interpreted by Python, they may be omitted when typing in examples.

Some examples:

3.1. Using Python as a Calculator ¶

Let’s try some simple Python commands. Start the interpreter and wait for the primary prompt, >>> . (It shouldn’t take long.)

3.1.1. Numbers ¶

The interpreter acts as a simple calculator: you can type an expression at it and it will write the value. Expression syntax is straightforward: the operators + , - , * and / can be used to perform arithmetic; parentheses ( () ) can be used for grouping. For example:

The integer numbers (e.g. 2 , 4 , 20 ) have type int , the ones with a fractional part (e.g. 5.0 , 1.6 ) have type float . We will see more about numeric types later in the tutorial.

Division ( / ) always returns a float. To do floor division and get an integer result you can use the // operator; to calculate the remainder you can use % :

With Python, it is possible to use the ** operator to calculate powers [ 1 ] :

The equal sign ( = ) is used to assign a value to a variable. Afterwards, no result is displayed before the next interactive prompt:

If a variable is not “defined” (assigned a value), trying to use it will give you an error:

There is full support for floating point; operators with mixed type operands convert the integer operand to floating point:

In interactive mode, the last printed expression is assigned to the variable _ . This means that when you are using Python as a desk calculator, it is somewhat easier to continue calculations, for example:

This variable should be treated as read-only by the user. Don’t explicitly assign a value to it — you would create an independent local variable with the same name masking the built-in variable with its magic behavior.

In addition to int and float , Python supports other types of numbers, such as Decimal and Fraction . Python also has built-in support for complex numbers , and uses the j or J suffix to indicate the imaginary part (e.g. 3+5j ).

3.1.2. Text ¶

Python can manipulate text (represented by type str , so-called “strings”) as well as numbers. This includes characters “ ! ”, words “ rabbit ”, names “ Paris ”, sentences “ Got your back. ”, etc. “ Yay! :) ”. They can be enclosed in single quotes ( '...' ) or double quotes ( "..." ) with the same result [ 2 ] .

To quote a quote, we need to “escape” it, by preceding it with \ . Alternatively, we can use the other type of quotation marks:

In the Python shell, the string definition and output string can look different. The print() function produces a more readable output, by omitting the enclosing quotes and by printing escaped and special characters:

If you don’t want characters prefaced by \ to be interpreted as special characters, you can use raw strings by adding an r before the first quote:

There is one subtle aspect to raw strings: a raw string may not end in an odd number of \ characters; see the FAQ entry for more information and workarounds.

String literals can span multiple lines. One way is using triple-quotes: """...""" or '''...''' . End of lines are automatically included in the string, but it’s possible to prevent this by adding a \ at the end of the line. The following example:

produces the following output (note that the initial newline is not included):

Strings can be concatenated (glued together) with the + operator, and repeated with * :

Two or more string literals (i.e. the ones enclosed between quotes) next to each other are automatically concatenated.

This feature is particularly useful when you want to break long strings:

This only works with two literals though, not with variables or expressions:

If you want to concatenate variables or a variable and a literal, use + :

Strings can be indexed (subscripted), with the first character having index 0. There is no separate character type; a character is simply a string of size one:

Indices may also be negative numbers, to start counting from the right:

Note that since -0 is the same as 0, negative indices start from -1.

In addition to indexing, slicing is also supported. While indexing is used to obtain individual characters, slicing allows you to obtain a substring:

Slice indices have useful defaults; an omitted first index defaults to zero, an omitted second index defaults to the size of the string being sliced.

Note how the start is always included, and the end always excluded. This makes sure that s[:i] + s[i:] is always equal to s :

One way to remember how slices work is to think of the indices as pointing between characters, with the left edge of the first character numbered 0. Then the right edge of the last character of a string of n characters has index n , for example:

The first row of numbers gives the position of the indices 0…6 in the string; the second row gives the corresponding negative indices. The slice from i to j consists of all characters between the edges labeled i and j , respectively.

For non-negative indices, the length of a slice is the difference of the indices, if both are within bounds. For example, the length of word[1:3] is 2.

Attempting to use an index that is too large will result in an error:

However, out of range slice indexes are handled gracefully when used for slicing:

Python strings cannot be changed — they are immutable . Therefore, assigning to an indexed position in the string results in an error:

If you need a different string, you should create a new one:

The built-in function len() returns the length of a string:

Strings are examples of sequence types , and support the common operations supported by such types.

Strings support a large number of methods for basic transformations and searching.

String literals that have embedded expressions.

Information about string formatting with str.format() .

The old formatting operations invoked when strings are the left operand of the % operator are described in more detail here.

3.1.3. Lists ¶

Python knows a number of compound data types, used to group together other values. The most versatile is the list , which can be written as a list of comma-separated values (items) between square brackets. Lists might contain items of different types, but usually the items all have the same type.

Like strings (and all other built-in sequence types), lists can be indexed and sliced:

Lists also support operations like concatenation:

Unlike strings, which are immutable , lists are a mutable type, i.e. it is possible to change their content:

You can also add new items at the end of the list, by using the list.append() method (we will see more about methods later):

Simple assignment in Python never copies data. When you assign a list to a variable, the variable refers to the existing list . Any changes you make to the list through one variable will be seen through all other variables that refer to it.:

All slice operations return a new list containing the requested elements. This means that the following slice returns a shallow copy of the list:

Assignment to slices is also possible, and this can even change the size of the list or clear it entirely:

The built-in function len() also applies to lists:

It is possible to nest lists (create lists containing other lists), for example:

3.2. First Steps Towards Programming ¶

Of course, we can use Python for more complicated tasks than adding two and two together. For instance, we can write an initial sub-sequence of the Fibonacci series as follows:

This example introduces several new features.

The first line contains a multiple assignment : the variables a and b simultaneously get the new values 0 and 1. On the last line this is used again, demonstrating that the expressions on the right-hand side are all evaluated first before any of the assignments take place. The right-hand side expressions are evaluated from the left to the right.

The while loop executes as long as the condition (here: a < 10 ) remains true. In Python, like in C, any non-zero integer value is true; zero is false. The condition may also be a string or list value, in fact any sequence; anything with a non-zero length is true, empty sequences are false. The test used in the example is a simple comparison. The standard comparison operators are written the same as in C: < (less than), > (greater than), == (equal to), <= (less than or equal to), >= (greater than or equal to) and != (not equal to).

The body of the loop is indented : indentation is Python’s way of grouping statements. At the interactive prompt, you have to type a tab or space(s) for each indented line. In practice you will prepare more complicated input for Python with a text editor; all decent text editors have an auto-indent facility. When a compound statement is entered interactively, it must be followed by a blank line to indicate completion (since the parser cannot guess when you have typed the last line). Note that each line within a basic block must be indented by the same amount.

The print() function writes the value of the argument(s) it is given. It differs from just writing the expression you want to write (as we did earlier in the calculator examples) in the way it handles multiple arguments, floating point quantities, and strings. Strings are printed without quotes, and a space is inserted between items, so you can format things nicely, like this:

The keyword argument end can be used to avoid the newline after the output, or end the output with a different string:

Table of Contents

• 3.1.1. Numbers
• 3.1.2. Text
• 3.1.3. Lists
• 3.2. First Steps Towards Programming

Previous topic

2. Using the Python Interpreter

4. More Control Flow Tools

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【Python】TypeError: ‘NoneType’のエラー原因と対処法まとめ（初心者向け・実例でわかりやすく解説）

再帰関数などを使って処理を記述している場合に、次のようなエラーが発生することがあります。

なお、この記事の内容は、上記以外でも「NoneTpye」を含むエラー全般の発生原因と対処法にもなっています。

エラーが発生する状況例

対処法（returnの設置）, returnの設置場所の注意点.

最初に結論を述べると、主な原因は次の２つです。

①戻り値(return)のない関数の実行結果は「値None, タイプNoneType」になる。

②関数を変数に代入する場合は、その関数にreturnがあること。 　└ printではだめ。（実行結果ではなく、実行途中のいち処理のため） 　└ returnは関数の最終出力となっていること。 　└ 関数内のどこかにreturnが1個あればいいというわけではない。

以下で実例を踏まえて原因と対処法について解説しています。

例えば、次のように多次元配列からintを抜き出そうとしたときに、’NoneType’ object is not iterableのエラーが発生します。

‘NoneType’のオブジェクトをいじろうとしていることが原因です。

▼もう少し細かく 「res = number(brr)」で変数に関数number()代入しているが、この関数自体に戻り値(return)がないため、変数にはNoneが格納され、タイプがNoneTypeとなっている。

「result += res」このNoneTypeの変数resと、list型の変数resultを結合しようとしたため、

resはイテラブルじゃないから結合できないと言われている。

関数にデフォルト引数が渡されなかった場合に発生するエラー。値はNoneのみとのこと。

(python公式)Noneとは 型 NoneType の唯一の値です。 None は、関数にデフォルト引数が渡されなかったときなどに、値の非存在を表すのに頻繁に用いられます。 None への代入は不正で、SyntaxError を送出します。

▼簡単にするとこんな感じ 関数の実行結果が空とき、その結果自体がNoneTypeになる。

なので、実行結果が空の関数を変数に代入するとNoneTypeになる。

printの場合もNoneTypeになる

「こんにちは」が出力されているが、関数の実行過程で表示されたもので、関数自体と置き換わるものではない。

NoneTypeとしないために、returnで関数に実態をもたせる。 　└ 戻り値(return)は関数を実行した結果を関数自身と置き換える。

xが文字列「こんにちは」に置き換わっている。

関数の中にreturnがあればいいというわけではありません。実行した最終結果としてreturnを経由する必要があります。

▼returnが記述されているがNoneTypeになる例

1 < 2　のため、関数の出力結果は空になっている。この原因は、returnの処理を経由しないためです。

▼実行結果がreturnを経由する場合はOK

▼関数自体はのタイプはfunction

▼関数自体を変数に代入する場合はカッコ不要, ▼変数（関数を代入）の実行例.

hello()=x()となっている。

冒頭に記述したエラーコードを修正すると以下のようになります。

ポイントは、 変数に代入する値が関数にならないよう、returnを適切に設置する。

以上で無事に処理が動きます。

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TypeError: 'NoneType' object does not support item assignment #706

Quentin-C0mps0n commented Nov 22, 2021

zhupr commented Nov 22, 2021

Sorry, something went wrong.

Quentin-C0mps0n commented Nov 22, 2021 • edited

Zhupr commented nov 23, 2021, quentin-c0mps0n commented nov 23, 2021.

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