'str' object is not callable for grouped df

I am trying to build a dictionary based on entity

df = pd.DataFrame({
    'entity': ['foo', 'bar', 'baz', 'buzz', 'bar', 'buzz', 'foo', 'foo'],
    'value': [4, 3, 2, 1, 9, 8, 7, 4]
})
out = dict(df.groupby('entity'))

But I get the following error

   out = dict(df.groupby('entity'))
TypeError: 'str' object is not callable

What’s wrong???

This is my pandas and python version

print(pd.__version__)
print(sys.version)

pandas == 1.5.3
sys == 3.10.9 

>Solution :

In old version of pandas need convert groupby object to iterator or tuples:

out = dict(iter(df.groupby('entity')))

Or:

out = dict(tuple(df.groupby('entity')))

print (out)
{'bar':   entity  value
1    bar      3
4    bar      9, 'baz':   entity  value
2    baz      2, 'buzz':   entity  value
3   buzz      1
5   buzz      8, 'foo':   entity  value
0    foo      4
6    foo      7
7    foo      4}

Better explanation by @tdelaney from commnents:

A dict prefers initialization by a "Mapping" to an iterable. I don’t know exactly where a "Mapping" is defined, but the groupby object as a .keys parameter that holds the columns you use to group. In your case, its the string "entity". The dict constructor sees a .keys attribute and tries to call it, assuming its a function that lists the mapping’s keys. But its a string, so boom. had you groupby([‘entity’, ‘value’]), you’d get a ‘list’ object is not callable instead.