The “typeerror response object is not subscriptable” is an error message that is raised if you are trying to access a key or index that doesn’t exist in the “response” object.
If you’re not familiar with and struggling to troubleshoot this error, worry no more as we are going to hand you the solution for this ‘response’ object is not subscriptable.
In this article, we’ll discuss in detail the solutions to “typeerror response object is not subscriptable“ so that you’ll understand this error thoroughly.
If you want to get the solution, continue reading until the end of this discussion.
What is “typeerror: ‘response’ object is not subscriptable” error message?
The “typeerror: ‘response’ object is not subscriptable” error message occurs when you’re trying to access a specific element of an object. That isn’t subscriptable or doesn’t support indexing, such as a response object from a web request.
In this particular case, this error indicates that you are trying to access a specific element of a “response” object in your code. Using indexing syntax, such as response[0], but the ‘response’ object is not a list or a tuple that can be indexed.
Note: In order to solve the error, you just have to convert the object to a subscriptable object.
The following are the subscriptable objects in Python:
- string
- tuple
- dictionary
- list
How to fix the “typeerror: ‘response’ object is not subscriptable” error

To fix this error, you should ensure that the ‘response’ object you are working with is actually a list or a tuple. If it is not, you should use the appropriate methods to extract the data you need from the “response” object.
1. Use the json() method
For instance, if you are trying to access a JSON object in the response object, you should use the json() method to extract the data as follows:
data = res.json()Here’s the full example code:
import requests
def make_request():
res = requests.post(
'https://reqres.in/api/users',
data={'Website': 'Itsourcecode', 'Offer': 'Free sourcecode and tutorials'}
)
data = res.json()
print(data)
print(data['Website'])
print(data['Offer'])
print(data['id'])
make_request()
Output:
{'Website': 'Itsourcecode', 'Offer': 'Free sourcecode and tutorials', 'id': '825', 'createdAt': '2023-03-29T08:50:51.308Z'}
Itsourcecode
Free sourcecode and tutorials
8252. Accessing header value in a response object
If the response object contains a header with the name ‘header_name’, the code will print the value of that header to the console.
For example:
import requests
response = requests.get('https://itsourcecode.com')
value = response.headers.get('header_name')
print(value)Output:
NoneIf the response object does not contain a header with that name, the value variable will be set to None.
3. Converting response object to string
import requests
response = requests.get('https://itsourcecode.com')
data = response.text
print(data)
If the response object contains text data, the code will print that data to the console. If the response object does not contain any text data, the data variable will be set to an empty string.
Conclusion
By executing the different solutions that this article has given, you can easily fix the “typeerror: ‘response’ object is not subscriptable” error message in Python.
We are hoping that this article provides you with sufficient solutions; if yes, we would love to hear some thoughts from you.
You could also check out other “typeerror” articles that may help you in the future if you encounter them.
- Typeerror: ‘str’ object cannot be interpreted as an integer
- Typeerror: minicssextractplugin is not a constructor
- Typeerror: ‘required’ is an invalid argument for positionals
Thank you very much for reading to the end of this article. Just in case you have more questions or inquiries, feel free to comment, and you can also visit our official website for additional information.
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.
