github-actions[bot]
commented
3 months ago Coverage Report
| Name | Stmts | Miss | Cover |
|---|---|---|---|
edsnlp/connectors/omop.pyMissing coverage at line 69 if not isinstance(row.ents, list):
- continue
Missing coverage at line 87 else:
- doc.spans[span.label_].append(span)
Missing coverage at line 127 if df.note_id.isna().any():
- df["note_id"] = range(len(df))
Missing coverage at line 171 if i > 0:
- df.term_modifiers += ";"
df.term_modifiers += ext + "=" + df[ext].astype(str) | 84 | 4 | 95% |
edsnlp/core/lazy_collection.pyMissing coverage at line 433 for name, pipe, *_ in self.torch_components():
- pipe.to(device)
return self | 146 | 1 | 99% |
edsnlp/core/pipeline.pyMissing coverage at line 533 if name in exclude:
- continue
if name not in components: | 358 | 1 | 99% |
edsnlp/core/registries.pyMissing coverage at line 73 if obj.error is not None:
- raise obj.error
| 157 | 1 | 99% |
edsnlp/core/torch_component.pyMissing coverage at line 42 elif not isinstance(batch, dict):
- return id(batch)
if "__batch_hash__" in batch:Missing coverage at line 82 if cache_key in cache:
- return cache[cache_key]
res = fn(self, doc)Missing coverage at line 397 if hasattr(self, "compiled"):
- res = self.compiled(batch)
else:Missing coverage at line 473 """
- return self.batch_process([doc])[0]
| 200 | 4 | 98% |
edsnlp/data/base.pyMissing coverage at lines 174-180 """
- data = LazyCollection.ensure_lazy(data)
- if converter:
- converter, kwargs = get_doc2dict_converter(converter, kwargs)
- data = data.map(converter, kwargs=kwargs)
-
- return data | 39 | 5 | 87% |
edsnlp/data/converters.pyMissing coverage at line 654 if isinstance(converter, type) or kwargs_to_init:
- return converter(**kwargs), {}
return converter, validate_kwargs(converter, kwargs) | 191 | 1 | 99% |
edsnlp/data/json.pyMissing coverage at line 96 if not is_jsonl:
- obj[FILENAME] = filename
results.append(obj)Missing coverage at line 98 results.append(obj)
- except Exception:
raise Exception(f"Cannot parse {filename}") | 107 | 2 | 98% |
edsnlp/data/polars.pyMissing coverage at line 26 if hasattr(data, "collect"):
- data = data.collect()
assert isinstance(data, pl.DataFrame) | 44 | 1 | 98% |
edsnlp/data/standoff.pyMissing coverage at line 43 def __init__(self, ann_file, line):
- super().__init__(f"File {ann_file}, unrecognized Brat line {line}")
Missing coverage at line 83 if not len(ann_paths):
- return {
"text": text,Missing coverage at line 197 )
- except Exception:
raise Exception( | 172 | 3 | 98% |
edsnlp/extensions.pyMissing coverage at line 13 elif isinstance(dt, pendulum.DateTime):
- pass
elif isinstance(dt, str): | 24 | 1 | 96% |
edsnlp/language.pyMissing coverage at line 103 if last != begin:
- logger.warning(
"Missed some characters during" | 51 | 1 | 98% |
edsnlp/matchers/simstring.pyMissing coverage at line 280 if custom:
- attr = attr[1:].lower()
Missing coverage at line 295 if custom:
- token_text = getattr(token._, attr)
else: | 146 | 2 | 99% |
edsnlp/optimization.pyMissing coverage at line 32 def param_groups(self, value):
- self.optim.param_groups = value
Missing coverage at line 36 def state(self):
- return self.optim.state
Missing coverage at line 40 def state(self, value):
- self.optim.state = value
Missing coverage at line 89 def __init__(self, groups):
- self.param_groups = groups
| 77 | 4 | 95% |
edsnlp/patch_spacy.pyMissing coverage at lines 67-69 # if module is reloaded.
- existing_func = registry.factories.get(internal_name)
- if not util.is_same_func(factory_func, existing_func):
raise ValueError( | 31 | 2 | 94% |
edsnlp/pipes/core/contextual_matcher/contextual_matcher.pyMissing coverage at line 94 )
- label = label_name
if label is None:Missing coverage at line 343 if assigned is None:
- continue
if replace_entity: | 143 | 2 | 99% |
edsnlp/pipes/core/contextual_matcher/models.pyMissing coverage at lines 19-23 if isinstance(v, list):
- assert (
- len(v) == 2
- ), "`window` should be a tuple/list of two integer, or a single integer"
- v = tuple(v)
if isinstance(v, int): | 115 | 2 | 98% |
edsnlp/pipes/core/endlines/endlines.pyMissing coverage at lines 151-155 if end_lines_model is None:
- path = build_path(__file__, "base_model.pkl")
-
- with open(path, "rb") as inp:
- self.model = pickle.load(inp)
elif isinstance(end_lines_model, str):Missing coverage at lines 158-160 self.model = pickle.load(inp)
- elif isinstance(end_lines_model, EndLinesModel):
- self.model = end_lines_model
else:Missing coverage at line 191 ):
- return "ENUMERATION"
Missing coverage at line 278 if np.isnan(sigma):
- sigma = 1
| 87 | 7 | 92% |
edsnlp/pipes/core/normalizer/__init__.pyMissing coverage at line 7 def excluded_or_space_getter(t):
- return t.is_space or t.tag_ == "EXCLUDED"
| 5 | 1 | 80% |
edsnlp/pipes/misc/consultation_dates/consultation_dates.pyMissing coverage at line 131 else:
- self.date_matcher = None
Missing coverage at line 134 if not consultation_mention:
- consultation_mention = []
elif consultation_mention is True: | 48 | 2 | 96% |
edsnlp/pipes/misc/dates/dates.pyMissing coverage at line 222 if isinstance(absolute, str):
- absolute = [absolute]
if isinstance(relative, str):Missing coverage at line 224 if isinstance(relative, str):
- relative = [relative]
if isinstance(duration, str):Missing coverage at line 226 if isinstance(duration, str):
- relative = [duration]
if isinstance(false_positive, str):Missing coverage at lines 327-336 if self.merge_mode == "align":
- alignments = align_spans(matches, spans, sort_by_overlap=True)
- matches = []
- for span, aligned in zip(spans, alignments):
- if len(aligned):
- old = aligned[0]
- span.label_ = old.label_
- span._.set(self.date_label, old._.get(self.date_label))
- span._.set(self.duration_label, old._.get(self.duration_label))
- matches.append(span)
Missing coverage at line 417 elif d1 in seen or v1.bound is None or v2.bound is None:
- continue
Missing coverage at lines 428-430 if v1.mode == Mode.DURATION:
- m1 = Bound.FROM if v2.bound == Bound.UNTIL else Bound.UNTIL
- m2 = v2.mode or Bound.FROM
elif v2.mode == Mode.DURATION: | 147 | 15 | 90% |
edsnlp/pipes/misc/dates/models.pyMissing coverage at line 123 else:
- d["month"] = note_datetime.month
if self.day is None:Missing coverage at lines 127-133 else:
- if self.year is None:
- return None
- if self.month is None:
- d["month"] = default_month
- if self.day is None:
- d["day"] = default_day
Missing coverage at lines 136-138 return pendulum.datetime(**d, tz=tz)
- except ValueError:
- return None
Missing coverage at lines 146-153 ) -> Optional[pendulum.Duration]:
- if note_datetime and not isinstance(note_datetime, NaTType):
- note_datetime = pendulum.instance(note_datetime)
- dt = self.to_datetime(note_datetime=note_datetime, **kwargs)
- delta = dt.diff(note_datetime)
- return delta.as_interval()
- else:
- return None
Missing coverage at line 168 if self.second:
- norm += f"{self.second:02}s"
Missing coverage at line 181 def __str__(self):
- return self.norm()
Missing coverage at line 277 if td.in_seconds() > 0:
- norm = f"+{norm}"
Missing coverage at line 307 def __str__(self):
- return self.norm()
| 166 | 19 | 89% |
edsnlp/pipes/misc/measurements/measurements.pyMissing coverage at lines 146-148 def __getitem__(self, item: int):
- assert isinstance(item, int)
- return [self][item]
Missing coverage at lines 159-162 def __eq__(self, other: Any):
- if isinstance(other, SimpleMeasurement):
- return self.convert_to(other.unit) == other.value
- return False
Missing coverage at line 165 if other.unit == self.unit:
- return self.__class__(self.value + other.value, self.unit, self.registry)
return self.__class__(Missing coverage at line 194 def verify(cls, ent):
- return True
Missing coverage at line 233 def __lt__(self, other: Union[SimpleMeasurement, "RangeMeasurement"]):
- return max(self.convert_to(other.unit)) < min((part.value for part in other))
Missing coverage at line 244 return self.convert_to(other.unit) == other.value
- return False
Missing coverage at line 258 def verify(cls, ent):
- return True
Missing coverage at line 498 if isinstance(measurements, str):
- measurements = [measurements]
if isinstance(measurements, (list, tuple)):Missing coverage at line 711 if snippet.end != last and doclike.doc[last: snippet.end].text.strip() == "":
- pseudo.append("w")
pseudo = "".join(pseudo)Missing coverage at lines 875-877 unit_norm = self.unit_followers[unit_before.label_]
- except (KeyError, AttributeError, IndexError):
- pass
Missing coverage at line 920 ):
- ent = doc[unit_text.start: number.end]
else:Missing coverage at lines 927-929 dims = self.unit_registry.parse_unit(unit_norm)[0]
- except KeyError:
- continue
Missing coverage at lines 1034-1036 last._.set(last.label_, new_value)
- except (AttributeError, TypeError):
- merged.append(ent)
else: | 388 | 19 | 95% |
edsnlp/pipes/misc/sections/sections.pyMissing coverage at line 126 if sections is None:
- sections = patterns.sections
sections = dict(sections) | 45 | 1 | 98% |
edsnlp/pipes/misc/tables/tables.pyMissing coverage at line 129 else:
- self.tables_pattern = tables_pattern
Missing coverage at line 134 else:
- self.sep = sep_pattern
| 28 | 2 | 93% |
edsnlp/pipes/ner/adicap/models.pyMissing coverage at line 15 def norm(self) -> str:
- return self.code
Missing coverage at line 18 def __str__(self):
- return self.norm() | 14 | 2 | 86% |
edsnlp/pipes/ner/disorders/cerebrovascular_accident/cerebrovascular_accident.pyMissing coverage at lines 110-112 if span._.source == "ischemia":
- if "brain" not in span._.assigned.keys():
- continue
| 17 | 2 | 88% |
edsnlp/pipes/ner/disorders/ckd/ckd.pyMissing coverage at lines 119-122 dfg_value = float(dfg_span.text.replace(",", ".").strip())
- except ValueError:
- logger.trace(f"DFG value couldn't be extracted from {dfg_span.text}")
- return False
| 29 | 3 | 90% |
edsnlp/pipes/ner/disorders/connective_tissue_disease/connective_tissue_disease.pyMissing coverage at line 102 # Huge change of FP / Title section
- continue
| 14 | 1 | 93% |
edsnlp/pipes/ner/disorders/diabetes/diabetes.pyMissing coverage at line 133 # Mostly FP
- continue
Missing coverage at line 136 elif self.has_far_complications(span):
- span._.status = 2
Missing coverage at line 148 if next(iter(self.complication_matcher(context)), None) is not None:
- return True
return False | 31 | 3 | 90% |
edsnlp/pipes/ner/disorders/peripheral_vascular_disease/peripheral_vascular_disease.pyMissing coverage at line 106 if "peripheral" not in span._.assigned.keys():
- continue
| 15 | 1 | 93% |
edsnlp/pipes/ner/disorders/solid_tumor/solid_tumor.pyMissing coverage at lines 114-117 if use_tnm:
- from edsnlp.pipes.ner.tnm import TNM
-
- self.tnm = TNM(nlp, pattern=None, attr="TEXT")
Missing coverage at lines 119-129 def process_tnm(self, doc):
- spans = self.tnm.process(doc)
- spans = self.tnm.parse(spans)
-
- for span in spans:
- span.label_ = "solid_tumor"
- span._.source = "tnm"
- metastasis = span._.value.dict().get("metastasis", "0")
- if metastasis == "1":
- span._.status = 2
- yield span
Missing coverage at line 149 if self.use_tnm:
- yield from self.process_tnm(doc) | 35 | 12 | 66% |
edsnlp/pipes/ner/scores/base_score.pyMissing coverage at line 154 if value is None:
- continue
normalized_value = self.score_normalization(value) | 47 | 1 | 98% |
edsnlp/pipes/ner/scores/charlson/patterns.pyMissing coverage at lines 21-23 return int(extracted_score)
- except ValueError:
- return None | 13 | 2 | 85% |
edsnlp/pipes/ner/scores/elston_ellis/patterns.pyMissing coverage at line 26 if x <= 5:
- return 1
Missing coverage at lines 32-36 else:
- return 3
-
- except ValueError:
- return None | 21 | 4 | 81% |
edsnlp/pipes/ner/scores/sofa/sofa.pyMissing coverage at line 32 if not assigned:
- continue
if assigned.get("method_max") is not None:Missing coverage at line 40 else:
- method = "Non précisée"
| 25 | 2 | 92% |
edsnlp/pipes/ner/tnm/model.pyMissing coverage at line 139 def __str__(self):
- return self.norm()
Missing coverage at line 163 )
- exclude_unset = skip_defaults
| 104 | 2 | 98% |
edsnlp/pipes/ner/tnm/tnm.pyMissing coverage at lines 156-158 value = TNM.parse_obj(groupdict)
- except ValidationError:
- value = TNM.parse_obj({})
| 44 | 2 | 95% |
edsnlp/pipes/qualifiers/base.pyMissing coverage at line 17 if normalizer and not normalizer.lowercase:
- logger.warning(
"You have chosen the NORM attribute, but disabled lowercasing " | 44 | 1 | 98% |
edsnlp/pipes/qualifiers/family/family.pyMissing coverage at line 21 else:
- return None
| 59 | 1 | 98% |
edsnlp/pipes/qualifiers/history/history.pyMissing coverage at lines 20-26 def history_getter(token: Union[Token, Span]) -> Optional[str]:
- if token._.history is True:
- return "ATCD"
- elif token._.history is False:
- return "CURRENT"
- else:
- return None
Missing coverage at lines 302-308 note_datetime = note_datetime.set(tz="Europe/Paris")
- except ValueError:
- logger.debug(
- "note_datetime must be a datetime objects. "
- "Skipping history qualification from note_datetime."
- )
- note_datetime = None
Missing coverage at lines 314-320 birth_datetime = birth_datetime.set(tz="Europe/Paris")
- except ValueError:
- logger.debug(
- "birth_datetime must be a datetime objects. "
- "Skipping history qualification from birth date."
- )
- birth_datetime = None
Missing coverage at lines 386-389 )
- except ValueError as e:
- absolute_date = None
- logger.warning(
"In doc {}, the following date {} raises this error: {}. " | 155 | 14 | 91% |
edsnlp/pipes/qualifiers/hypothesis/hypothesis.pyMissing coverage at line 21 else:
- return None
| 74 | 1 | 99% |
edsnlp/pipes/qualifiers/negation/negation.pyMissing coverage at line 22 else:
- return None
| 77 | 1 | 99% |
edsnlp/pipes/qualifiers/reported_speech/reported_speech.pyMissing coverage at lines 18-22 return "REPORTED"
- elif token._.rspeech is False:
- return "DIRECT"
- else:
- return None
| 73 | 3 | 96% |
edsnlp/pipes/trainable/embeddings/span_pooler/span_pooler.pyMissing coverage at line 99 for qlf in self.qualifiers or ():
- if not Span.has_extension(qlf):
Span.set_extension(qlf, default=None) | 65 | 1 | 98% |
edsnlp/pipes/trainable/embeddings/transformer/transformer.pyMissing coverage at lines 152-169 if new_tokens:
- self.tokenizer.add_tokens(sorted(set(t[1] for t in new_tokens)))
- original_normalizer = self.tokenizer.backend_tokenizer.normalizer
- self.tokenizer.backend_tokenizer.normalizer = (
- tokenizers.normalizers.Sequence(
- [
- *(
- tokenizers.normalizers.Replace(
- tokenizers.Regex(pattern), replacement
- )
- for pattern, replacement in new_tokens
- ),
- original_normalizer,
- ]
- )
- )
- # and add a new entry to the model's embeddings
- self.transformer.resize_token_embeddings(
max(self.tokenizer.vocab.values()) + 1 | 140 | 4 | 97% |
edsnlp/pipes/trainable/layers/crf.pyMissing coverage at line 21 # out: 2 * N * O
- return (log_A.unsqueeze(-1) + log_B.unsqueeze(-3)).logsumexp(-2)
Missing coverage at line 29 # out: 2 * N * O
- return (log_A.unsqueeze(-1) + log_B.unsqueeze(-3)).max(-2)
Missing coverage at line 97 if learnable_transitions:
- self.transitions = torch.nn.Parameter(
torch.zeros_like(forbidden_transitions, dtype=torch.float)Missing coverage at line 107 if learnable_transitions and with_start_end_transitions:
- self.start_transitions = torch.nn.Parameter(
torch.zeros(num_tags, dtype=torch.float)Missing coverage at line 116 if learnable_transitions and with_start_end_transitions:
- self.end_transitions = torch.nn.Parameter(
torch.zeros(num_tags, dtype=torch.float) | 136 | 5 | 96% |
edsnlp/pipes/trainable/ner_crf/ner_crf.pyMissing coverage at line 238 if self.labels is not None and not self.infer_span_setter:
- return
Missing coverage at lines 246-248 if callable(self.target_span_getter):
- for ent in self.target_span_getter(doc):
- inferred_labels.add(ent.label_)
else: | 152 | 3 | 98% |
edsnlp/pipes/trainable/span_linker/span_linker.pyMissing coverage at lines 375-377 if self.reference_mode == "synonym":
- embeds = embeds.to(new_lin.weight)
- new_lin.weight.data = embeds
else: | 165 | 2 | 99% |
edsnlp/processing/deprecated_pipe.pyMissing coverage at lines 162-164 KoalasDataFrame = sys.modules["databricks.koalas.frame"].DataFrame
- except (AttributeError, KeyError):
- KoalasDataFrame = None
is_koalas = KoalasDataFrame and isinstance(df, KoalasDataFrame) # type: ignoreMissing coverage at lines 207-209 def converter(doc):
- res = results_extractor(doc)
- return (
[{"note_id": doc._.note_id, **row} for row in res] | 57 | 4 | 93% |
edsnlp/processing/multiprocessing.pyMissing coverage at lines 231-235 if os.environ.get("TORCH_SHARING_STRATEGY"):
- try:
- torch.multiprocessing.set_sharing_strategy(os.environ["TORCH_SHARING_STRATEGY"])
- except NameError:
- pass
Missing coverage at line 253 def save_align_devices_hook(pickler: Any, obj: Any):
- pickler.save_reduce(load_align_devices_hook, (obj.__dict__,), obj=obj)
Missing coverage at lines 256-263 def load_align_devices_hook(state):
- state["execution_device"] = MAP_LOCATION
- new_obj = AlignDevicesHook.__new__(AlignDevicesHook)
- new_obj.__dict__.update(state)
- return new_obj
-
- except ImportError:
- AlignDevicesHook = None
Missing coverage at line 455
- new_batch_iterator = None
Missing coverage at line 934 if isinstance(outputs, BaseException):
- raise outputs
Missing coverage at line 1002 if v is not None:
- os.environ[k] = v
| 417 | 14 | 97% |
edsnlp/processing/simple.pyMissing coverage at lines 37-39 no_grad = sys.modules["torch"].no_grad
- except (KeyError, AttributeError):
- no_grad = nullcontext
reader = lc.reader | 59 | 2 | 97% |
edsnlp/processing/spark.pyMissing coverage at line 50 getActiveSession = SparkSession.getActiveSession
- except AttributeError:
| 43 | 1 | 98% |
edsnlp/train.pyMissing coverage at line 195 else:
- sample_len = lambda idx, noise=True: 1 # noqa: E731
Missing coverage at lines 262-268 if total + num_tokens > self.grad_accumulation_max_tokens:
- print(
- f"Mini batch size was becoming too large: {total} > "
- f"{self.grad_accumulation_max_tokens} so it was split"
- )
- total = 0
- mini_batches.append([])
total += num_tokensMissing coverage at line 354 if 0 <= self.limit <= count:
- break
if not (len(doc) and (filter_fn is None or filter_fn(doc))):Missing coverage at line 356 if not (len(doc) and (filter_fn is None or filter_fn(doc))):
- continue
count += 1Missing coverage at lines 390-392 for ent in doc.ents:
- for token in ent:
- token.is_sent_start = False
for sent in doc.sents if doc.has_annotation("SENT_START") else (doc[:],): | 249 | 8 | 97% |
edsnlp/utils/bindings.pyMissing coverage at line 22 return "." + path
- return path
| 66 | 1 | 98% |
edsnlp/utils/filter.pyMissing coverage at line 206 if isinstance(label, int):
- return [span for span in spans if span.label == label]
else: | 74 | 1 | 99% |
edsnlp/utils/lazy_module.pyMissing coverage at line 46 ):
- continue
for import_node in node.body: | 31 | 1 | 97% |
edsnlp/utils/numbers.pyMissing coverage at line 34 else:
- string = s
string = string.lower().strip()Missing coverage at lines 38-41 return int(string)
- except ValueError:
- parsed = DIGITS_MAPPINGS.get(string, None)
- return parsed | 16 | 4 | 75% |
edsnlp/utils/package.pyMissing coverage at line 47 if isinstance(obj, ModuleType):
- module_name = obj.__name__
else:Missing coverage at line 59 return package, version
- except (ImportError, AttributeError):
raise Exception(f"Cound not find package of type {obj}")Missing coverage at lines 78-82 def save_module(pickler, obj, *args, **kwargs):
- package_name = get_package(obj)
- if package_name is not None:
- pickler.packages.add(package_name)
- return dill_save_module(pickler, obj, *args, **kwargs)
Missing coverage at line 400 # self.pipeline = edsnlp.load(self.pipeline)
- shutil.copytree(
self.pipeline, | 190 | 7 | 96% |
edsnlp/utils/resources.pyMissing coverage at line 33 if not verbs:
- return conjugated_verbs
| 24 | 1 | 96% |
edsnlp/utils/span_getters.pyMissing coverage at lines 52-55 else:
- for span in candidates:
- if span.label_ in span_filter:
- yield span
Missing coverage at lines 59-61 if span_getter is None:
- yield doc[:], None
- return
if callable(span_getter):Missing coverage at lines 62-64 if callable(span_getter):
- yield from span_getter(doc)
- return
for key, span_filter in span_getter.items():Missing coverage at line 66 if key == "*":
- candidates = (
(span, group) for group in doc.spans.values() for span in groupMissing coverage at lines 75-78 else:
- for span, group in candidates:
- if span.label_ in span_filter:
- yield span, group
Missing coverage at line 82 if callable(span_setter):
- span_setter(doc, matches)
else:Missing coverage at line 124 elif isinstance(v, str):
- new_value[k] = [v]
elif isinstance(v, list) and all(isinstance(i, str) for i in v):Missing coverage at line 162 elif isinstance(v, str):
- new_value[k] = [v]
elif isinstance(v, list) and all(isinstance(i, str) for i in v): | 158 | 14 | 91% |
edsnlp/viz/quick_examples.pyMissing coverage at lines 88-91 if end > istart:
- interval = (start, iend)
- del intervals[idx]
- break
| 80 | 3 | 96% |
| TOTAL | 9020 | 237 | 97% |
253 files skipped due to complete coverage.
Checklist