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from scalene import scalene_json
from hypothesis import given
from hypothesis.strategies import floats, lists
from typing import Any, List
class TestScaleneJSON:
# Define strategies for the input variables
size_in_mb = floats(min_value=0.0, allow_nan=False, allow_infinity=False)
time_in_ms = floats(min_value=0.0, allow_nan=False, allow_infinity=False)
max_footprint = floats(
min_value=0.0, allow_nan=False, allow_infinity=False
)
samples = lists(
elements=floats(min_value=0.0, allow_nan=False, allow_infinity=False),
min_size=0,
)
@given(size_in_mb)
def test_memory_consumed_str(self, size_in_mb: int) -> None:
formatted = scalene_json.ScaleneJSON().memory_consumed_str(size_in_mb)
assert isinstance(formatted, str)
if size_in_mb < 1024:
assert formatted.endswith("MB")
elif size_in_mb < 1024 * 1024:
assert formatted.endswith("GB")
else:
assert formatted.endswith("TB")
@given(time_in_ms)
def test_time_consumed_str(self, time_in_ms: int) -> None:
formatted = scalene_json.ScaleneJSON().time_consumed_str(time_in_ms)
assert isinstance(formatted, str)
if time_in_ms < 1000:
assert formatted.endswith("ms")
elif time_in_ms < 60 * 1000:
assert formatted.endswith("s")
elif time_in_ms < 60 * 60 * 1000:
assert formatted.endswith("s")
else:
assert formatted.endswith("s")
assert not formatted.startswith("0")
@given(samples, max_footprint)
def test_compress_samples(self, samples : List[Any], max_footprint: int) -> None:
compressed = scalene_json.ScaleneJSON().compress_samples(
samples, max_footprint
)
assert isinstance(compressed, list)
assert all(isinstance(x, float) for x in compressed)
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