Meaning
Verifies that a floating-point computation is approximately equal to an expected value within a tolerance, using pytest's approx helper. This avoids false test failures due to floating-point rounding errors.
Primary Function
Testing
Communicative Purpose
Checks numeric results with tolerance for floating-point imprecision.
Pattern
assert ; == pytest.approx(;)
Core Structure
assert ; == pytest.approx(;)
Função primária
Testing
Propósito comunicativo
Checks numeric results with tolerance for floating-point imprecision.
Situações de gatilho
Writing unit tests for numerical algorithms; comparing results of floating-point arithmetic; validating scientific computations.
Contextos
Python test suites that use pytest; scientific computing libraries; any code requiring approximate equality in tests.
Padrão
assert ; == pytest.approx(;)
Estrutura central
assert ; == pytest.approx(;)
Slots de substituição
expression: any numeric expression (e.g., 0.1 + 0.2); expected: float or numeric literal representing the anticipated value
Colocados típicos
- pytest fixture
- test function
- assert statement
- approx tolerance parameters (rel
- abs)
Substituições comuns
- Using math.isclose
- using numpy.allclose
- using round equality with a fixed number of decimal places
Erros comuns
Forgetting to import pytest.approx; using == directly causing flaky tests; placing approx on the left side of the equality
Similar / contraste
assert math.isclose(a, b, rel_tol=1e-9) – offers explicit tolerance control; assert round(a, 7) == round(b, 7) – less flexible and can hide issues
Interferências
Coming from languages with exact numeric equality (e.g., Java integer comparison): may expect == to work for floats; need to remember floating-point imprecision.
Família do chunk
- pytest assertions
- floating-point comparison
Nuance
pytest.approx defaults to relative tolerance 1e-6 and absolute tolerance 1e-12; can be adjusted with rel and abs arguments; not suitable for comparing NaNs or complex numbers without extra handling.
Efeito pragmático
Makes test assertions robust to floating-point rounding errors, reducing false negatives.
Dica de memória
Think 'approx' when you see floating point equality in tests.
Nota
pytest.approx defaults to relative tolerance 1e-6 and absolute tolerance 1e-12; can be adjusted with rel and abs arguments; not suitable for NaNs or complex numbers without extra handling.
Upgrade path
Using explicit tolerance with math.isclose for more control, or numpy.allclose for array comparisons.
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