Typeerror unsupported operand type s for dict and dict [SOLVED]

In this article, you’ll get the solution for the “typeerror: unsupported operand type s for dict and dict” error message in Python.

If this error gives you a headache, then keep on reading to finally resolve this error message.

Today, you’ll understand thoroughly why this error keeps bothering you and what this error is all about.

But the most important thing is that we provide different ways for you to resolve this “typeerror: unsupported operand type(s) for +: ‘dict’ and ‘dict'” error.

What is “typeerror unsupported operand type s for dict and dict”?

The “type error: unsupported operand type(s) for dict and dict” is an error message that occurs when you’re attempting to perform an unsupported operation between two dictionaries.

Such as:

→ adding

→ subtracting

→ multiplying

In other words, you are trying to perform arithmetic or comparison operations directly on dictionaries, which Python doesn’t support.

For example:

sampledict1 = {'a': 1, 'b': 2}
sampledict2 = {'c': 3, 'd': 4}
result = sampledict1 + sampledict2
print(result)

As a result, it will throw an error message:

TypeError: unsupported operand type(s) for +: 'dict' and 'dict'

Why does this error “typeerror: unsupported operand type(s) for +: ‘dict’ and ‘dict'” occur?

The root cause of this error is that dictionaries are not designed to be used with arithmetic operators.

Python does not support these operations because dictionaries are not ordered collections.

While you can use operators like + and * with strings or lists, they don’t work with dictionaries.

Therefore, it’s not clear how to perform arithmetic or comparison operations between two dictionaries.

What are dictionaries, and how do they work?

If you are asking about dictionaries, as we mentioned above, here it is.

Dictionaries are defined using curly braces {} in Python. It consist of key-value pairs separated by a colon.

The keys and values can be of any data type, and the keys must be unique.

Here’s an example of a dictionary:

my_dict = {'name': 'Caren', 'age': 25, 'address': 'Korea'}

To access values in a dictionary, you can use the key as an index.

For instance, to retrieve caren’s name, age, and address from the dictionary above, you can use:

name = my_dict['name']
age = my_dict['age']
location = my_dict['location']

How to fix the “typeerror unsupported operand type s for dict and dict”

Now that you fully understand this error, let’s dive into the different solutions that will help you fix the error in no time.

1.Use update() method

You can easily merge two dictionaries by using the update() method of one dictionary to add the keys and values of another dictionary to it.

sampledict1 = {'a': 1, 'b': 2}
sampledict2 = {'c': 3, 'd': 4}
sampledict1.update(sampledict2)
print(sampledict1)

Output:

{'a': 1, 'b': 2, 'c': 3, 'd': 4}

2. Use dictionary unpacking

Using the unpacking operator **, you can easily merge two dictionaries into a new dictionary.

sampledict1 = {'a': 1, 'b': 2}
sampledict2 = {'c': 3, 'd': 4}
sampledict3 = {**sampledict1, **sampledict2}
print(sampledict3)

Output:

{'a': 1, 'b': 2, 'c': 3, 'd': 4}

3. Use dictionary comprehension

Using a dictionary comprehension, you can easily merge two dictionaries by creating a new dictionary. That iterates over the keys and values of both dictionaries.

sampledict1 = {'a': 1, 'b': 2}
sampledict2 = {'c': 3, 'd': 4}
sampledict3 = {k: sampledict1.get(k, 0) + sampledict2.get(k, 0) for k in set(sampledict1) | set(sampledict2)}
print(sampledict3)

Output:

{'a': 1, 'b': 2, 'c': 3, 'd': 4}

4. Use collections.ChainMap

Using collections.ChainMap class, you can easily merge two or more dictionaries.

This class creates a view of multiple dictionaries as a single dictionary.

from collections import ChainMap

sampledict1 = {'a': 1, 'b': 2}
sampledict2 = {'c': 3, 'd': 4}
sampledict3 = ChainMap(sampledict1, sampledict2)
print(sampledict3)

Output:

ChainMap({'a': 1, 'b': 2}, {'c': 3, 'd': 4})

Conclusion

By executing the different solutions that this article has already given, you can easily fix the “typeerror unsupported operand type s for dict and dict” error message while working with Python.

We are hoping that this article provides you with sufficient solutions.

You could also check out other “typeerror” articles that may help you in the future if you encounter them.

Thank you very much for reading to the end of this article.

Frequently Asked Questions

What is Python TypeError and what causes it?

TypeError is raised when an operation is applied to an object of the wrong type. Common patterns: calling a non-callable object, adding incompatible types (str + int), passing the wrong number of arguments, or accessing attributes on a NoneType. Each TypeError message names the operation and expected vs actual types, the fix is almost always to convert types explicitly (int(), str()) or fix the wrong variable assignment.

How do I quickly debug a Python TypeError?

Three steps: (1) Read the full error message, it names the exact operation and types involved. (2) Print the type of every variable in that line: print(type(var1), type(var2)). (3) Check what the function expected vs what you passed. Most TypeError fixes are 1-line type casts or fixing a variable that became None unexpectedly.

Should I catch TypeError or let it propagate?

For internal code, let TypeError propagate, it’s almost always a real bug (wrong type passed). For boundary code (parsing user input, third-party API responses), catch TypeError + ValueError together: try: parsed = int(value) except (TypeError, ValueError): parsed = 0. Catching internal TypeErrors hides bugs.

How do I prevent TypeError in production?

Three patterns: (1) Use type hints (def add(a: int, b: int) -> int) and check with mypy / pyright in CI. (2) Validate inputs at boundaries (Pydantic for FastAPI, DRF serializers for Django). (3) Default values that match expected types (return 0 not None for numeric functions). Static typing catches 80% of TypeErrors before runtime.

Where can I find more TypeError fixes?

Browse the TypeError reference hub for 220+ specific TypeError fixes. For broader Python debugging, see the Python Tutorial hub. For related error types, see ValueError and AttributeError guides.

Caren Bautista

Technical Writer at PIES IT Solution

Responsible for crafting clear, well-structured, and beginner-friendly content across the platform. Handles the writing, proofreading, and editorial review of tutorials, guides, and documentation to ensure every article is accurate, readable, and easy to follow.

Expertise: Technical Writing · Content Creation · Documentation · Editorial Writing · JavaScript · TypeScript · Python · Python Errors · HTTP Errors · MS Excel  · View all posts by Caren Bautista →

Leave a Comment