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In order to support Python 3.13, we had to migrate to Cython 3.0. This caused some tricky interaction with our Pydantic usage, because Cython 3 uses the from __future__ import annotations semantics, which causes type annotations to be saved as strings. The end result is that we can't have Language.factory decorated functions in Cython modules anymore, as the Language.factory decorator expects to inspect the signature of the functions and build a Pydantic model. If the function is implemented in Cython, an error is raised because the type is not resolved. To address this I've moved the factory functions into a new module, spacy.pipeline.factories. I've added __getattr__ importlib hooks to the previous locations, in case anyone was importing these functions directly. The change should have no backwards compatibility implications. Along the way I've also refactored the registration of functions for the config. Previously these ran as import-time side-effects, using the registry decorator. I've created instead a new module spacy.registrations. When the registry is accessed it calls a function ensure_populated(), which cases the registrations to occur. I've made a similar change to the Language.factory registrations in the new spacy.pipeline.factories module. I want to remove these import-time side-effects so that we can speed up the loading time of the library, which can be especially painful on the CLI. I also find that I'm often working to track down the implementations of functions referenced by strings in the config. Having the registrations all happen in one place will make this easier. With these changes I've fortunately avoided the need to migrate to Pydantic v2 properly --- we're still using the v1 compatibility shim. We might not be able to hold out forever though: Pydantic (reasonably) aren't actively supporting the v1 shims. I put a lot of work into v2 migration when investigating the 3.13 support, and it's definitely challenging. In any case, it's a relief that we don't have to do the v2 migration at the same time as the Cython 3.0/Python 3.13 support.
71 lines
1.6 KiB
Cython
71 lines
1.6 KiB
Cython
cimport numpy as np
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from cymem.cymem cimport Pool
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from ..attrs cimport attr_id_t
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from ..structs cimport LexemeC, SpanC, TokenC
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from ..typedefs cimport attr_t
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from ..vocab cimport Vocab
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cdef attr_t get_token_attr(const TokenC* token, attr_id_t feat_name) noexcept nogil
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cdef attr_t get_token_attr_for_matcher(const TokenC* token, attr_id_t feat_name) noexcept nogil
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ctypedef const LexemeC* const_Lexeme_ptr
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ctypedef const TokenC* const_TokenC_ptr
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ctypedef fused LexemeOrToken:
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const_Lexeme_ptr
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const_TokenC_ptr
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cdef int set_children_from_heads(TokenC* tokens, int start, int end) except -1
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cdef int _set_lr_kids_and_edges(TokenC* tokens, int start, int end, int loop_count) except -1
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cdef int token_by_start(const TokenC* tokens, int length, int start_char) except -2
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cdef int token_by_end(const TokenC* tokens, int length, int end_char) except -2
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cdef int [:, :] _get_lca_matrix(Doc, int start, int end)
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cdef class Doc:
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cdef readonly Pool mem
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cdef readonly Vocab vocab
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cdef public object _vector
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cdef public object _vector_norm
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cdef public object tensor
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cdef public object cats
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cdef public object user_data
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cdef readonly object spans
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cdef TokenC* c
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cdef public float sentiment
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cdef public dict user_hooks
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cdef public dict user_token_hooks
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cdef public dict user_span_hooks
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cdef public bint has_unknown_spaces
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cdef public object _context
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cdef int length
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cdef int max_length
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cdef public object noun_chunks_iterator
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cdef object __weakref__
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cdef int push_back(self, LexemeOrToken lex_or_tok, bint has_space) except -1
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cpdef np.ndarray to_array(self, object features)
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