This makes it easier to see where the problem is.įinally, I think they made some fixes to this in Python 3.6.
Python typo generator generator#
Remember that if you’re not sure which stage of the generator is messing you up, you can always call list() on it to exhaust it. This should give you a better chance to localise the error. Then also move the generator you have inside the call to nlp.pipe() out of the generator function. It’s very frustrating - let me dig into this a bit and see if I can figure it out.Įdit: This is likely beside the point, but try simplifying your logic a bit? Break the segment_documents() function into two, for each branch of the conditional – and then move the conditional out to where you call the function. We did have that error at various points. You haven’t changed anything like that have you? Also I don’t suppose you’re testing this with pytest, which could be doing something sneaky? Waitress by default would launch multiple threads, but we disable that in the app.py. Hmm there shouldn’t be any threading issues. Is split_sentences(nlp, stream) adding some thread safety? Log("RECIPE: Loaded model Īll the Googling I do about this error message turns up references to generators not being thread-safe. Log("RECIPE: Starting recipe ner.make-gold", locals()) Spans = disjoint_spans(span for span in doc.ents + pattern_matches if span.label_ in labels) Pattern_matches = tuple(Span(doc, start, end, label) for label, start, end in matcher(doc)) Texts = ((eg, eg) for eg in stream)įor doc, eg in nlp.pipe(texts, as_tuples=True):
"""Add a 'spans' key to each example, with predicted entities."""
Patterns=None, labels=None, exclude=None, unsegmented=False):Ĭreate gold data for NER by correcting a model's suggestions.įor document, eg in nlp.pipe(((eg, eg) for eg in stream), as_tuples=True):Įg = path_value_from_dict(eg, id_path)įor i, sentence in enumerate(nts, 1): What am I doing wrong here? path to document ID", "option", None, str),ĭef make_gold(dataset, spacy_model, source=None, api=None, loader=None, But I get a “generator already executing” error when I try to enumerate the stream inside segment_documents(). In particular I’m doing my best to imitate the iteration logic in make_tasks(). I think I’m copying the logic for these stream functions correctly. I am replacing the stream = split_sentences(stream) call with my own segment_documents() function that passes along some information about the original document when splitting it into sentences. Import io import re from collections import deque, namedtuple from typing import ( Dict, List, Tuple, Set, Deque, NamedTuple, IO, Pattern, Match, Text, Optional, Sequence, Iterable, Mapping, MutableMapping, Any, ) # without initializing x : int # any type y : Any y = 1 y = "1" # built-in var_int : int = 1 var_str : str = "Hello Typing" var_byte : bytes = b "Hello Typing" var_bool : bool = True var_float : float = 1.I am writing a custom ner.make-gold recipe. Restricting to a fixed set of possible types Using TypeVar and Generic as class template The main goal of this cheat sheet is to show someĬommon usage about type hints in Python3. That would be helpful to aid a pythoneer to understand reasons why Python Philosophy, it is crucial to read PEP 483
Moreover, to better understand the type hints design Specification about what a type system should look like in Python3, introduced
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