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"""The most widely adopted free and open-source engine to write rules as code.""" | ||
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from openfisca_core.commons import ( | ||
apply_thresholds, | ||
average_rate, | ||
concat, | ||
marginal_rate, | ||
switch, | ||
) | ||
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from . import types | ||
from .experimental import MemoryConfig | ||
from .simulations import ( | ||
Simulation, | ||
SimulationBuilder, | ||
calculate_output_add, | ||
calculate_output_divide, | ||
check_type, | ||
transform_to_strict_syntax, | ||
) | ||
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__all__ = [ | ||
"MemoryConfig", | ||
"Simulation", | ||
"SimulationBuilder", | ||
"apply_thresholds", | ||
"average_rate", | ||
"calculate_output_add", | ||
"calculate_output_divide", | ||
"check_type", | ||
"concat", | ||
"marginal_rate", | ||
"switch", | ||
"transform_to_strict_syntax", | ||
"types", | ||
] |
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@@ -1,24 +1,9 @@ | ||
# Transitional imports to ensure non-breaking changes. | ||
# Could be deprecated in the next major release. | ||
# | ||
# How imports are being used today: | ||
# | ||
# >>> from openfisca_core.module import symbol | ||
# | ||
# The previous example provokes cyclic dependency problems | ||
# that prevent us from modularizing the different components | ||
# of the library so to make them easier to test and to maintain. | ||
# | ||
# How could them be used after the next major release: | ||
# | ||
# >>> from openfisca_core import module | ||
# >>> module.symbol() | ||
# | ||
# And for classes: | ||
# | ||
# >>> from openfisca_core.module import Symbol | ||
# >>> Symbol() | ||
# | ||
# See: https://www.python.org/dev/peps/pep-0008/#imports | ||
"""Experimental features of OpenFisca-Core.""" | ||
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from .memory_config import MemoryConfig # noqa: F401 | ||
from ._errors import MemoryConfigWarning | ||
from ._memory_config import MemoryConfig | ||
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__all__ = [ | ||
"MemoryConfig", | ||
"MemoryConfigWarning", | ||
] |
3 changes: 3 additions & 0 deletions
3
openfisca_core/warnings/memory_warning.py → openfisca_core/experimental/_errors.py
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@@ -1,2 +1,5 @@ | ||
class MemoryConfigWarning(UserWarning): | ||
"""Custom warning for MemoryConfig.""" | ||
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__all__ = ["MemoryConfigWarning"] |
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from __future__ import annotations | ||
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from collections.abc import Iterable | ||
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import warnings | ||
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from ._errors import MemoryConfigWarning | ||
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class MemoryConfig: | ||
"""Experimental memory configuration.""" | ||
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#: Maximum memory occupation allowed. | ||
max_memory_occupation: float | ||
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#: Priority variables. | ||
priority_variables: frozenset[str] | ||
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#: Variables to drop. | ||
variables_to_drop: frozenset[str] | ||
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def __init__( | ||
self, | ||
max_memory_occupation: str | float, | ||
priority_variables: Iterable[str] = frozenset(), | ||
variables_to_drop: Iterable[str] = frozenset(), | ||
) -> None: | ||
message = [ | ||
"Memory configuration is a feature that is still currently under " | ||
"experimentation. You are very welcome to use it and send us " | ||
"precious feedback, but keep in mind that the way it is used might " | ||
"change without any major version bump.", | ||
] | ||
warnings.warn(" ".join(message), MemoryConfigWarning, stacklevel=2) | ||
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self.max_memory_occupation = float(max_memory_occupation) | ||
if self.max_memory_occupation > 1: | ||
msg = "max_memory_occupation must be <= 1" | ||
raise ValueError(msg) | ||
self.max_memory_occupation_pc = self.max_memory_occupation * 100 | ||
self.priority_variables = frozenset(priority_variables) | ||
self.variables_to_drop = frozenset(variables_to_drop) |
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