tests(pyargus): add tests for parsing expressions
This commit is contained in:
Anand Balakrishnan
parent
019797f344
commit
5da441db42
9 changed files with 231 additions and 122 deletions
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@ -8,6 +8,7 @@ classifiers = [
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]
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dependencies = ["typing-extensions"]
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dynamic = ["version"]
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[project.optional-dependencies]
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@ -25,7 +26,7 @@ dev = [
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"black",
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]
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test = ["pytest", "pytest-cov", "hypothesis"]
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test = ["pytest", "pytest-cov", "hypothesis[lark]"]
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[build-system]
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requires = ["maturin>=1.0,<2.0"]
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0
pyargus/tests/__init__.py
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0
pyargus/tests/__init__.py
Normal file
16
pyargus/tests/test_expr.py
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16
pyargus/tests/test_expr.py
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@ -0,0 +1,16 @@
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import logging
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from hypothesis import given
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import argus
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from .utils.expr_gen import argus_expr
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@given(spec=argus_expr())
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def test_correct_expr(spec: str) -> None:
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try:
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_ = argus.parse_expr(spec)
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except ValueError as e:
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logging.critical(f"unable to parse expr: {spec}")
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raise e
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@ -1,118 +1,18 @@
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import typing
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from typing import List, Tuple, Type, Union
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import pytest
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from hypothesis import assume, given
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from hypothesis import strategies as st
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from hypothesis.strategies import SearchStrategy, composite
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import argus
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from argus import AllowedDtype, dtype
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def gen_element_fn(dtype_: Union[Type[AllowedDtype], dtype]) -> SearchStrategy[AllowedDtype]:
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new_dtype = dtype.convert(dtype_)
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if new_dtype == dtype.bool_:
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return st.booleans()
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elif new_dtype == dtype.int64:
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size = 2**64
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return st.integers(min_value=(-size // 2), max_value=((size - 1) // 2))
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elif new_dtype == dtype.uint64:
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size = 2**64
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return st.integers(min_value=0, max_value=(size - 1))
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elif new_dtype == dtype.float64:
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return st.floats(
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width=64,
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allow_nan=False,
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allow_infinity=False,
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allow_subnormal=False,
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)
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else:
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raise ValueError(f"invalid dtype {dtype_}")
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@composite
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def gen_samples(
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draw: st.DrawFn, min_size: int, max_size: int, dtype_: Union[Type[AllowedDtype], dtype]
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) -> List[Tuple[float, AllowedDtype]]:
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"""
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Generate arbitrary samples for a signal where the time stamps are strictly
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monotonically increasing
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"""
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elements = gen_element_fn(dtype_)
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values = draw(st.lists(elements, min_size=min_size, max_size=max_size))
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xs = draw(
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st.lists(
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st.integers(min_value=0, max_value=2**32 - 1),
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unique=True,
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min_size=len(values),
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max_size=len(values),
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)
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.map(lambda t: map(float, sorted(set(t))))
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.map(lambda t: list(zip(t, values)))
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)
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return xs
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def empty_signal(dtype_: Union[Type[AllowedDtype], dtype]) -> SearchStrategy[argus.Signal]:
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new_dtype: dtype = dtype.convert(dtype_)
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sig: argus.Signal
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if new_dtype == dtype.bool_:
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sig = argus.BoolSignal()
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assert sig.kind == dtype.bool_
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elif new_dtype == dtype.uint64:
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sig = argus.UnsignedIntSignal()
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assert sig.kind == dtype.uint64
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elif new_dtype == dtype.int64:
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sig = argus.IntSignal()
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assert sig.kind == dtype.int64
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elif new_dtype == dtype.float64:
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sig = argus.FloatSignal()
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assert sig.kind == dtype.float64
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else:
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raise ValueError("unknown dtype")
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return st.just(sig)
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def constant_signal(dtype_: Union[Type[AllowedDtype], dtype]) -> SearchStrategy[argus.Signal]:
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element = gen_element_fn(dtype_)
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dtype_ = dtype.convert(dtype_)
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if dtype_ == dtype.bool_:
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return element.map(lambda val: argus.BoolSignal.constant(typing.cast(bool, val)))
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if dtype_ == dtype.uint64:
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return element.map(lambda val: argus.UnsignedIntSignal.constant(typing.cast(int, val)))
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if dtype_ == dtype.int64:
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return element.map(lambda val: argus.IntSignal.constant(typing.cast(int, val)))
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if dtype_ == dtype.float64:
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return element.map(lambda val: argus.FloatSignal.constant(typing.cast(float, val)))
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raise ValueError("unsupported data type for signal")
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def sampled_signal(xs: List[Tuple[float, AllowedDtype]], dtype_: Union[Type[AllowedDtype], dtype]) -> argus.Signal:
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dtype_ = dtype.convert(dtype_)
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if dtype_ == dtype.bool_:
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return argus.BoolSignal.from_samples(typing.cast(List[Tuple[float, bool]], xs))
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if dtype_ == dtype.uint64:
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return argus.UnsignedIntSignal.from_samples(typing.cast(List[Tuple[float, int]], xs))
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if dtype_ == dtype.int64:
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return argus.IntSignal.from_samples(typing.cast(List[Tuple[float, int]], xs))
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if dtype_ == dtype.float64:
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return argus.FloatSignal.from_samples(typing.cast(List[Tuple[float, float]], xs))
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raise ValueError("unsupported data type for signal")
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@composite
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def draw_index(draw: st.DrawFn, vec: List) -> int:
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if len(vec) > 0:
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return draw(st.integers(min_value=0, max_value=len(vec) - 1))
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else:
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return draw(st.just(0))
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def gen_dtype() -> SearchStrategy[Union[Type[AllowedDtype], dtype]]:
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return st.one_of(
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list(map(st.just, [dtype.bool_, dtype.uint64, dtype.int64, dtype.float64, bool, int, float])), # type: ignore[arg-type]
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)
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from .utils.signals_gen import (
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constant_signal,
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draw_index,
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empty_signal,
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gen_dtype,
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gen_element_fn,
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gen_samples,
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sampled_signal,
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)
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@given(st.data())
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0
pyargus/tests/utils/__init__.py
Normal file
0
pyargus/tests/utils/__init__.py
Normal file
73
pyargus/tests/utils/expr_gen.py
Normal file
73
pyargus/tests/utils/expr_gen.py
Normal file
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@ -0,0 +1,73 @@
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"""Hypothesis strategies to generate Argus expressions
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"""
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import hypothesis.strategies as st
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from hypothesis.extra.lark import from_lark
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from lark import Lark, Transformer
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class T(Transformer):
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def INT(self, tok): # noqa: N802,ANN # type: ignore
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"Convert the value of `tok` from string to int, while maintaining line number & column."
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return tok.update(value=int(tok) // 2**64)
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ARGUS_EXPR_GRAMMAR = Lark(
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r"""
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TRUE: "true" | "TRUE"
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FALSE: "false" | "FALSE"
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BOOLEAN: TRUE | FALSE
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IDENT: ESCAPED_STRING | CNAME
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num_expr: num_expr "*" num_expr
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| num_expr "/" num_expr
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| num_expr "+" num_expr
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| num_expr "-" num_expr
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| "-" num_expr
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| NUMBER
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| IDENT
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| "(" num_expr ")"
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cmp_expr: num_expr ">=" num_expr
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| num_expr "<=" num_expr
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| num_expr "<" num_expr
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| num_expr ">" num_expr
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| num_expr "==" num_expr
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| num_expr "!=" num_expr
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INTERVAL: "[" INT? "," INT? "]"
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bool_expr: bool_expr "&&" bool_expr
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| bool_expr "||" bool_expr
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| bool_expr "<=>" bool_expr
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| bool_expr "->" bool_expr
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| bool_expr "^" bool_expr
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| bool_expr WS_INLINE "U" WS_INLINE INTERVAL? bool_expr
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| "!" bool_expr
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| "G" WS_INLINE INTERVAL? bool_expr
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| "F" WS_INLINE INTERVAL? bool_expr
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| cmp_expr
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| BOOLEAN
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| IDENT
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| "(" bool_expr ")"
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phi: bool_expr
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%import common.ESCAPED_STRING
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%import common.CNAME
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%import common.NUMBER
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%import common.INT
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%import common.WS
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%import common.WS_INLINE
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%ignore WS
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""",
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start="phi",
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)
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@st.composite
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def argus_expr(draw: st.DrawFn) -> str:
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"""Strategy to generate an Argus STL expression from a pre-defined grammar"""
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return draw(from_lark(ARGUS_EXPR_GRAMMAR, start="phi"))
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116
pyargus/tests/utils/signals_gen.py
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116
pyargus/tests/utils/signals_gen.py
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@ -0,0 +1,116 @@
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import typing
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from typing import List, Tuple, Type, Union
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from hypothesis import strategies as st
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from hypothesis.strategies import SearchStrategy, composite
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import argus
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from argus import AllowedDtype, dtype
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def gen_element_fn(dtype_: Union[Type[AllowedDtype], dtype]) -> SearchStrategy[AllowedDtype]:
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new_dtype = dtype.convert(dtype_)
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if new_dtype == dtype.bool_:
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return st.booleans()
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elif new_dtype == dtype.int64:
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size = 2**64
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return st.integers(min_value=(-size // 2), max_value=((size - 1) // 2))
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elif new_dtype == dtype.uint64:
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size = 2**64
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return st.integers(min_value=0, max_value=(size - 1))
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elif new_dtype == dtype.float64:
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return st.floats(
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width=64,
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allow_nan=False,
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allow_infinity=False,
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allow_subnormal=False,
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)
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else:
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raise ValueError(f"invalid dtype {dtype_}")
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@composite
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def gen_samples(
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draw: st.DrawFn,
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min_size: int,
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max_size: int,
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dtype_: Union[Type[AllowedDtype], dtype],
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) -> List[Tuple[float, AllowedDtype]]:
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"""
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Generate arbitrary samples for a signal where the time stamps are strictly
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monotonically increasing
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"""
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elements = gen_element_fn(dtype_)
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values = draw(st.lists(elements, min_size=min_size, max_size=max_size))
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xs = draw(
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st.lists(
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st.integers(min_value=0, max_value=2**32 - 1),
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unique=True,
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min_size=len(values),
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max_size=len(values),
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)
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.map(lambda t: map(float, sorted(set(t))))
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.map(lambda t: list(zip(t, values)))
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)
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return xs
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def empty_signal(dtype_: Union[Type[AllowedDtype], dtype]) -> SearchStrategy[argus.Signal]:
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new_dtype: dtype = dtype.convert(dtype_)
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sig: argus.Signal
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if new_dtype == dtype.bool_:
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sig = argus.BoolSignal()
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assert sig.kind == dtype.bool_
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elif new_dtype == dtype.uint64:
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sig = argus.UnsignedIntSignal()
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assert sig.kind == dtype.uint64
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elif new_dtype == dtype.int64:
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sig = argus.IntSignal()
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assert sig.kind == dtype.int64
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elif new_dtype == dtype.float64:
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sig = argus.FloatSignal()
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assert sig.kind == dtype.float64
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else:
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raise ValueError("unknown dtype")
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return st.just(sig)
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def constant_signal(dtype_: Union[Type[AllowedDtype], dtype]) -> SearchStrategy[argus.Signal]:
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element = gen_element_fn(dtype_)
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dtype_ = dtype.convert(dtype_)
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if dtype_ == dtype.bool_:
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return element.map(lambda val: argus.BoolSignal.constant(typing.cast(bool, val)))
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if dtype_ == dtype.uint64:
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return element.map(lambda val: argus.UnsignedIntSignal.constant(typing.cast(int, val)))
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if dtype_ == dtype.int64:
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return element.map(lambda val: argus.IntSignal.constant(typing.cast(int, val)))
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if dtype_ == dtype.float64:
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return element.map(lambda val: argus.FloatSignal.constant(typing.cast(float, val)))
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raise ValueError("unsupported data type for signal")
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def sampled_signal(xs: List[Tuple[float, AllowedDtype]], dtype_: Union[Type[AllowedDtype], dtype]) -> argus.Signal:
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dtype_ = dtype.convert(dtype_)
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if dtype_ == dtype.bool_:
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return argus.BoolSignal.from_samples(typing.cast(List[Tuple[float, bool]], xs))
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if dtype_ == dtype.uint64:
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return argus.UnsignedIntSignal.from_samples(typing.cast(List[Tuple[float, int]], xs))
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if dtype_ == dtype.int64:
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return argus.IntSignal.from_samples(typing.cast(List[Tuple[float, int]], xs))
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if dtype_ == dtype.float64:
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return argus.FloatSignal.from_samples(typing.cast(List[Tuple[float, float]], xs))
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raise ValueError("unsupported data type for signal")
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@composite
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def draw_index(draw: st.DrawFn, vec: List) -> int:
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if len(vec) > 0:
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return draw(st.integers(min_value=0, max_value=len(vec) - 1))
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else:
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return draw(st.just(0))
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def gen_dtype() -> SearchStrategy[Union[Type[AllowedDtype], dtype]]:
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return st.one_of(
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list(map(st.just, [dtype.bool_, dtype.uint64, dtype.int64, dtype.float64, bool, int, float])), # type: ignore[arg-type]
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)
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