Can you name ten built-in functions in Python and explain each in brief?
Assesses fundamental understanding of Python conventions, runtime behavior, and memory/performance considerations.
Hiring managers look for precision, avoidance of ambiguous jargon, and ability to explain trade-offs under real production conditions.
Ten Built-in Functions, you say? Okay, here you go.
complex()- Creates a complex number.
>>> complex(3.5,4)
(3.5+4j)
eval()- Parses a string as an expression.
>>> eval('print(max(22,22.0)-min(2,3))')
20
filter()- Filters in items for which the condition is true.
>>> list(filter(lambda x:x%2==0,[1,2,0,False]))
[2, 0, False]
format()- Lets us format a string.
>>> print("a={0} but b={1}".format(a,b))
a=2 but b=3
hash()- Returns the hash value of an object.
>>> hash(3.7)
644245917
hex()- Converts an integer to a hexadecimal.
>>> hex(14)
'0xe'
input()- Reads and return s a line of string.
>>> input('Enter a number')
Enter a number7
'7'
len()- Returns the length of an object.
>>> len('Ayushi')
6
locals()- Returns a dictionary of the current local symbol table.
>>> locals()
{'__name__': '__main__', '__doc__': None, '__package__': None, '__loader__': <class '_frozen_importlib.BuiltinImporter'>, '__spec__': None, '__annotations__': {}, '__builtins__': <module 'builtins' (built-in)>, 'a': 2, 'b': 3}
open()- Opens a file.
>>> file=open('tabs.txt')
Candidate Response Strategy & Interview Tips
- Start with a concise one-sentence summary: Deliver a direct, confident answer first before expanding into nuances.
- Demonstrate real-world trade-offs: Discuss where this approach excels and when you would avoid it in production systems.
- Discuss complexity & edge cases: Proactively explain time/space complexity or boundary conditions (null values, scale limits).
- Prepare for interviewer follow-ups: Technical hiring panels frequently probe deeper into concurrency, backward compatibility, or alternative libraries.