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| Author | SHA1 | Date | |
|---|---|---|---|
| 74d78b1957 | |||
| dbecef1977 | |||
| 27939ef3ea | |||
| 5ac6ff102f | |||
| 9142cb05fc | |||
| a256db0203 | |||
| d68bb79a97 |
@@ -1,6 +1,6 @@
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[project]
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name = "breakshaft"
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version = "0.1.4"
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version = "0.1.6.post5"
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description = "Library for in-time codegen for type conversion"
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authors = [
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{ name = "nikto_b", email = "niktob560@yandex.ru" }
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@@ -79,11 +79,14 @@ class ConvRepo:
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def convertor_set(self):
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return self._convertor_set
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def add_conversion_points(self, conversion_points: Iterable[ConversionPoint]):
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self._convertor_set |= set(conversion_points)
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def add_injector(self,
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func: Callable,
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rettype: Optional[type] = None,
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type_remap: Optional[dict[str, type]] = None):
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self._convertor_set |= set(ConversionPoint.from_fn(func, rettype=rettype, type_remap=type_remap))
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self.add_conversion_points(ConversionPoint.from_fn(func, rettype=rettype, type_remap=type_remap))
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def _callseq_from_callgraph(self, cg: Callgraph) -> list[ConversionPoint]:
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if len(cg.variants) == 0:
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@@ -191,9 +194,6 @@ class ForkedConvRepo(ConvRepo):
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self._convertor_set = fork_with
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self._base_repo = fork_from
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def add_injector(self, func: Callable, rettype: Optional[type] = None):
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self._convertor_set |= set(ConversionPoint.from_fn(func, rettype=rettype))
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@property
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def convertor_set(self):
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return self._base_repo.convertor_set | self._convertor_set
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@@ -4,7 +4,7 @@ from types import NoneType
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from typing import Callable, Optional
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from .models import ConversionPoint, Callgraph, CallgraphVariant, TransformationPoint, CompositionDirection
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from .util import extract_func_argtypes, all_combinations, extract_func_argtypes_seq, extract_return_type
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from .util import extract_func_argtypes, all_combinations, extract_func_argtypes_seq, extract_return_type, universal_qualname
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from typing import Iterable
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@@ -90,7 +90,7 @@ class GraphWalker:
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if subg is not None:
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variant_subgraphs.add(subg)
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consumed = frozenset(point.requires) & from_types
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consumed = (frozenset(point.requires) | frozenset(point.opt_args)) & from_types
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variant = CallgraphVariant(point, frozenset(variant_subgraphs), consumed)
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head = head.add_subgraph_variant(variant)
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@@ -56,7 +56,8 @@ class ConversionPoint:
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def from_fn(cls,
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func: Callable,
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rettype: Optional[type] = None,
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type_remap: Optional[dict[str, type]] = None) -> list[ConversionPoint]:
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type_remap: Optional[dict[str, type]] = None,
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ignore_basictype_return: bool = False) -> list[ConversionPoint]:
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if type_remap is None:
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annot = get_type_hints(func)
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else:
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@@ -86,7 +87,7 @@ class ConversionPoint:
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if any(map(lambda x: fn_rettype_origin is x, cm_out_origins)) and is_context_manager_factory(func):
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fn_rettype = get_args(fn_rettype)[0]
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if is_basic_type_annot(rettype):
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if not ignore_basictype_return and is_basic_type_annot(rettype):
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return []
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ret = []
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@@ -96,7 +97,10 @@ class ConversionPoint:
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if len(tuple_unwrapped) > 0 and Ellipsis not in tuple_unwrapped:
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for t in tuple_unwrapped:
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if not is_basic_type_annot(t):
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ret += ConversionPoint.from_fn(func, rettype=t, type_remap=type_remap)
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ret += ConversionPoint.from_fn(func,
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rettype=t,
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type_remap=type_remap,
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ignore_basictype_return=ignore_basictype_return)
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argtypes: list[list[type]] = []
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orig_args = extract_func_args(func, type_remap)
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@@ -7,7 +7,7 @@ import importlib.resources
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import jinja2
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from .models import ConversionPoint
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from .util import hashname, get_tuple_types, is_basic_type_annot
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from .util import hashname, get_tuple_types, is_basic_type_annot, universal_qualname
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class ConvertorRenderer(Protocol):
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@@ -51,6 +51,7 @@ class ConversionRenderData:
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is_ctxmanager: bool
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is_async: bool
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unwrap_tuple_result: UnwprappedTuple
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_injection: ConversionPoint
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@classmethod
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def from_inj(cls, inj: ConversionPoint, provided_types: set[type]):
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@@ -74,7 +75,8 @@ class ConversionRenderData:
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fnargs,
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inj.is_ctx_manager,
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inj.is_async,
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unwrap_tuple_result)
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unwrap_tuple_result,
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inj)
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@dataclass
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@@ -86,16 +88,18 @@ class ConversionArgRenderData:
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def deduplicate_callseq(conversion_models: list[ConversionRenderData]) -> list[ConversionRenderData]:
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deduplicated_conv_models: list[ConversionRenderData] = []
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deduplicated_hashes = set()
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for conv_model in conversion_models:
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if conv_model not in deduplicated_conv_models:
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if hash((conv_model.inj_hash, conv_model.funchash)) not in deduplicated_hashes:
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deduplicated_conv_models.append(conv_model)
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deduplicated_hashes.add(hash((conv_model.inj_hash, conv_model.funchash)))
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continue
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argnames = list(map(lambda x: x[1], conv_model.funcargs))
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argument_changed = False
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found_model = False
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for m in deduplicated_conv_models:
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if not found_model and m == conv_model:
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if not found_model and m.funchash == conv_model.funchash:
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found_model = True
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if found_model and m.inj_hash in argnames:
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@@ -103,9 +107,28 @@ def deduplicate_callseq(conversion_models: list[ConversionRenderData]) -> list[C
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break
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if argument_changed:
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deduplicated_conv_models.append(conv_model)
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deduplicated_hashes.add(hash((conv_model.inj_hash, conv_model.funchash)))
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return deduplicated_conv_models
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def render_data_from_callseq(from_types: Sequence[type],
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fnmap: dict[int, Callable],
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callseq: Sequence[ConversionPoint]):
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conversion_models: list[ConversionRenderData] = []
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ret_hash = 0
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for call_id, call in enumerate(callseq):
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provided_types = set(from_types)
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for _call in callseq[:call_id]:
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provided_types |= {_call.injects}
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provided_types |= set(_call.requires)
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fnmap[hash(call.fn)] = call.fn
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conv = ConversionRenderData.from_inj(call, provided_types)
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conversion_models.append(conv)
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return conversion_models
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class InTimeGenerationConvertorRenderer(ConvertorRenderer):
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templateLoader: jinja2.BaseLoader
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templateEnv: jinja2.Environment
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@@ -128,19 +151,10 @@ class InTimeGenerationConvertorRenderer(ConvertorRenderer):
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store_sources: bool = False) -> Callable:
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fnmap = {}
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conversion_models: list[ConversionRenderData] = []
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conversion_models: list[ConversionRenderData] = render_data_from_callseq(from_types, fnmap, callseq)
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ret_hash = 0
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is_async = force_async
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for call_id, call in enumerate(callseq):
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provided_types = set(from_types)
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for _call in callseq[:call_id]:
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provided_types |= {_call.injects}
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provided_types |= set(_call.requires)
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fnmap[hash(call.fn)] = call.fn
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conv = ConversionRenderData.from_inj(call, provided_types)
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conversion_models.append(conv)
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if call.is_async:
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is_async = True
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@@ -134,9 +134,21 @@ def is_basic_type_annot(type_annot) -> bool:
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def universal_qualname(any: Any) -> str:
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ret = ''
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if hasattr(any, '__qualname__'):
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return any.__qualname__
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if hasattr(any, '__name__'):
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return any.__name__
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ret = any.__qualname__
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elif hasattr(any, '__name__'):
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ret = any.__name__
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else:
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ret = str(any)
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return str(any)
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ret = (ret
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.replace('.', '_')
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.replace('[', '_of_')
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.replace(']', '_of_')
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.replace(',', '_and_')
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.replace(' ', '_')
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.replace('\'', '')
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.replace('<', '')
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.replace('>', ''))
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return ret
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@@ -47,6 +47,37 @@ def test_default_consumer_args():
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assert dep == (123, '1')
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def test_optional_default_none_consumer_args():
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repo = ConvRepo()
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@repo.mark_injector()
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def b_to_a(b: B | None = None) -> A:
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return A(int(b.b))
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@repo.mark_injector()
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def a_to_b(a: A) -> B | None:
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return B(float(a.a))
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@repo.mark_injector()
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def int_to_a(i: int) -> A:
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return A(i)
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def consumer(dep: A, opt_dep: optC = '42') -> tuple[int, str]:
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return dep.a, opt_dep
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fn1 = repo.get_conversion((B,), consumer, force_commutative=True, force_async=False, allow_async=False)
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dep = fn1(B(42.1))
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assert dep == (42, '42')
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fn2 = repo.get_conversion((int,), consumer, force_commutative=True, force_async=False, allow_async=False)
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dep = fn2(123)
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assert dep == (123, '42')
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fn3 = repo.get_conversion((int, optC), consumer, force_commutative=True, force_async=False, allow_async=False)
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dep = fn3(123, '1')
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assert dep == (123, '1')
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def test_default_inj_args():
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repo = ConvRepo()
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@@ -79,7 +110,6 @@ def test_default_inj_args():
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def test_default_graph_override():
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repo = ConvRepo()
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@repo.mark_injector()
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@@ -111,4 +141,4 @@ def test_default_graph_override():
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fn3 = repo.get_conversion((int, optC,), consumer, force_commutative=True, force_async=False, allow_async=False)
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dep = fn3(123, '0')
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assert dep == 123
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assert dep == 123
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@@ -17,7 +17,7 @@ type optC = str
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def test_default_consumer_args():
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repo = ConvRepo()
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repo = ConvRepo(store_sources=True)
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@repo.mark_injector()
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def b_to_a(b: B) -> A:
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@@ -106,3 +106,13 @@ def test_pipeline_with_subgraph_duplicates():
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assert b_to_a_calls[0] == 1
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assert cons1_calls[0] == 5
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assert cons2_calls[0] == 4
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def convertor(_5891515089754: "<class 'test_pipeline.B'>"):
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# <function test_default_consumer_args.<locals>.b_to_a at 0x7f5bb1be02c0>
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_5891515089643 = _conv_funcmap[8751987548204](b=_5891515089754)
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# <function test_default_consumer_args.<locals>.consumer1 at 0x7f5bb1be0c20>
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_8751987542640 = _conv_funcmap[8751987548354](dep=_5891515089643)
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# <function test_default_consumer_args.<locals>.consumer2 at 0x7f5bb1be0540>
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_8751987537115 = _conv_funcmap[8751987548244](dep=_5891515089643, dep1=_8751987542640)
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return _8751987542640
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