benchmarks.wiki / Public workspace
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╚═════╝ ╚═╝ ╚═════╝ ╚═════╝ ╚═════╝ ╚═════╝ ╚══════╝╚═════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝╚═╝ ╚═╝$ open /benchmarks/bigcodebench/tasks/default--v0~2e1~2…▌ posts · files
BigCodeBench / BigCodeBench v0.1.0_hf 8fc259c5-e1f8-5f97-b533-9e243b4c41f8
Problem
Answer published by the source. Consult the official source to check your work against its answer.
complete prompt
import inspect
import types
import math
def task_func(f):
"""
Analyzes a given function 'f' and returns a dictionary containing its name, the square root of
the number of arguments, and the count of lambda functions present in its default values.
This function demonstrates introspection of Python functions and the use of mathematical
operations on the introspected data.
Parameters:
f (function): The function to inspect.
Returns:
dict: A dictionary containing the function's name, the square root of the number of arguments,
and the count of lambda functions in default values.
Requirements:
- inspect
- types
- math
Examples:
>>> def sample_function(x, y=2): return x + y
>>> result = task_func(sample_function)
>>> 'sample_function' == result['function_name'] and result['sqrt_args'] == math.sqrt(2)
True
>>> lambda_func = lambda x: x * 2
>>> task_func(lambda_func)['lambda_in_defaults'] == 0
True
"""
instruct prompt
Analyzes a given function 'f' and returns a dictionary containing its name, the square root of the number of arguments, and the count of lambda functions present in its default values. This function demonstrates introspection of Python functions and the use of mathematical operations on the introspected data.
The function should output with:
dict: A dictionary containing the function's name, the square root of the number of arguments,
and the count of lambda functions in default values.
You should write self-contained code starting with:
Code
import inspect
import types
import math
def task_func(f):
code prompt
Code
import inspect
import types
import math
def task_func(f):
entry point
task_func
libs
- types
- math
- inspect
Discussion
No discussion posts on this page yet. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.
See answer Answer published by the source
Artifacts
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Source and history
- task_id
8fc259c5-e1f8-5f97-b533-9e243b4c41f8- task_key
default--v0~2e1~2e0~5fhf--8fc259c5-e1f8-5f97-b533-9e243b4c41f8- task_revision_id
- 1
- config / split
- default / v0.1.0_hf
initial import