from typing import Optional
from thinc.api import Model

from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from .syntax_iterators import SYNTAX_ITERATORS
from .punctuation import TOKENIZER_INFIXES
from .lemmatizer import EnglishLemmatizer
from ...language import Language
from ...lookups import Lookups
from ...util import load_config_from_str


DEFAULT_CONFIG = """
[initialize]

[initialize.lookups]
@misc = "spacy.LookupsDataLoader.v1"
lang = ${nlp.lang}
tables = ["lexeme_norm"]
"""


class EnglishDefaults(Language.Defaults):
    config = load_config_from_str(DEFAULT_CONFIG)
    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
    infixes = TOKENIZER_INFIXES
    lex_attr_getters = LEX_ATTRS
    syntax_iterators = SYNTAX_ITERATORS
    stop_words = STOP_WORDS


class English(Language):
    lang = "en"
    Defaults = EnglishDefaults


@English.factory(
    "lemmatizer",
    assigns=["token.lemma"],
    default_config={"model": None, "mode": "rule", "lookups": None},
    default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(
    nlp: Language,
    model: Optional[Model],
    name: str,
    mode: str,
    lookups: Optional[Lookups],
):
    lookups = EnglishLemmatizer.load_lookups(nlp.lang, mode, lookups)
    return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)


__all__ = ["English"]

from typing import Optional
from thinc.api import Model

from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from .syntax_iterators import SYNTAX_ITERATORS
from .punctuation import TOKENIZER_INFIXES
from .lemmatizer import EnglishLemmatizer
from ...language import Language
from ...lookups import Lookups


class EnglishDefaults(Language.Defaults):
    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
    infixes = TOKENIZER_INFIXES
    lex_attr_getters = LEX_ATTRS
    syntax_iterators = SYNTAX_ITERATORS
    stop_words = STOP_WORDS


class English(Language):
    lang = "en"
    Defaults = EnglishDefaults


@English.factory(
    "lemmatizer",
    assigns=["token.lemma"],
    default_config={"model": None, "mode": "rule", "lookups": None},
    default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(
    nlp: Language,
    model: Optional[Model],
    name: str,
    mode: str,
    lookups: Optional[Lookups],
):
    lookups = EnglishLemmatizer.load_lookups(nlp.lang, mode, lookups)
    return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)


__all__ = ["English"]

Remove English [initialize] default block for now to get tests to pass
Remove English [initialize] default block for now to get tests to pass

  from typing import Optional
  from thinc.api import Model
  
  from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
  from .stop_words import STOP_WORDS
  from .lex_attrs import LEX_ATTRS
  from .syntax_iterators import SYNTAX_ITERATORS
  from .punctuation import TOKENIZER_INFIXES
  from .lemmatizer import EnglishLemmatizer
  from ...language import Language
  from ...lookups import Lookups
- from ...util import load_config_from_str
- 
- 
- DEFAULT_CONFIG = """
- [initialize]
- 
- [initialize.lookups]
- @misc = "spacy.LookupsDataLoader.v1"
- lang = ${nlp.lang}
- tables = ["lexeme_norm"]
- """
  
  
  class EnglishDefaults(Language.Defaults):
-     config = load_config_from_str(DEFAULT_CONFIG)
      tokenizer_exceptions = TOKENIZER_EXCEPTIONS
      infixes = TOKENIZER_INFIXES
      lex_attr_getters = LEX_ATTRS
      syntax_iterators = SYNTAX_ITERATORS
      stop_words = STOP_WORDS
  
  
  class English(Language):
      lang = "en"
      Defaults = EnglishDefaults
  
  
  @English.factory(
      "lemmatizer",
      assigns=["token.lemma"],
      default_config={"model": None, "mode": "rule", "lookups": None},
      default_score_weights={"lemma_acc": 1.0},
  )
  def make_lemmatizer(
      nlp: Language,
      model: Optional[Model],
      name: str,
      mode: str,
      lookups: Optional[Lookups],
  ):
      lookups = EnglishLemmatizer.load_lookups(nlp.lang, mode, lookups)
      return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)
  
  
  __all__ = ["English"]
  
Remove English [initialize] default block for now to get tests to pass
## Code Before:
from typing import Optional
from thinc.api import Model

from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from .syntax_iterators import SYNTAX_ITERATORS
from .punctuation import TOKENIZER_INFIXES
from .lemmatizer import EnglishLemmatizer
from ...language import Language
from ...lookups import Lookups
from ...util import load_config_from_str


DEFAULT_CONFIG = """
[initialize]

[initialize.lookups]
@misc = "spacy.LookupsDataLoader.v1"
lang = ${nlp.lang}
tables = ["lexeme_norm"]
"""


class EnglishDefaults(Language.Defaults):
    config = load_config_from_str(DEFAULT_CONFIG)
    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
    infixes = TOKENIZER_INFIXES
    lex_attr_getters = LEX_ATTRS
    syntax_iterators = SYNTAX_ITERATORS
    stop_words = STOP_WORDS


class English(Language):
    lang = "en"
    Defaults = EnglishDefaults


@English.factory(
    "lemmatizer",
    assigns=["token.lemma"],
    default_config={"model": None, "mode": "rule", "lookups": None},
    default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(
    nlp: Language,
    model: Optional[Model],
    name: str,
    mode: str,
    lookups: Optional[Lookups],
):
    lookups = EnglishLemmatizer.load_lookups(nlp.lang, mode, lookups)
    return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)


__all__ = ["English"]

## Instruction:
Remove English [initialize] default block for now to get tests to pass
## Code After:
from typing import Optional
from thinc.api import Model

from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from .syntax_iterators import SYNTAX_ITERATORS
from .punctuation import TOKENIZER_INFIXES
from .lemmatizer import EnglishLemmatizer
from ...language import Language
from ...lookups import Lookups


class EnglishDefaults(Language.Defaults):
    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
    infixes = TOKENIZER_INFIXES
    lex_attr_getters = LEX_ATTRS
    syntax_iterators = SYNTAX_ITERATORS
    stop_words = STOP_WORDS


class English(Language):
    lang = "en"
    Defaults = EnglishDefaults


@English.factory(
    "lemmatizer",
    assigns=["token.lemma"],
    default_config={"model": None, "mode": "rule", "lookups": None},
    default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(
    nlp: Language,
    model: Optional[Model],
    name: str,
    mode: str,
    lookups: Optional[Lookups],
):
    lookups = EnglishLemmatizer.load_lookups(nlp.lang, mode, lookups)
    return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)


__all__ = ["English"]
