Tidy up and auto-format

spacy/cli/debug_data.py

@@ -298,7 +298,8 @@ def debug_data(
                 )
             )
         if gold_train_data["n_cats_multilabel"] > 0:
-            msg.info("The train data contains instances without "
+            msg.info(
+                "The train data contains instances without "
                 "mutually-exclusive classes. Use '--textcat-multilabel' "
                 "when training."
             )
@@ -481,7 +482,6 @@ def debug_data(
                 )
             )
 
-
     msg.divider("Summary")
     good_counts = msg.counts[MESSAGES.GOOD]
     warn_counts = msg.counts[MESSAGES.WARN]

spacy/cli/train.py

@@ -182,7 +182,7 @@ def train(
                     base_cfg = {
                         "exclusive_classes": textcat_cfg["exclusive_classes"],
                         "architecture": textcat_cfg["architecture"],
-                        "positive_label": textcat_cfg["positive_label"]
+                        "positive_label": textcat_cfg["positive_label"],
                     }
                     pipe_cfg = {
                         "exclusive_classes": not textcat_multilabel,
@@ -190,12 +190,13 @@ def train(
                         "positive_label": textcat_positive_label,
                     }
                     if base_cfg != pipe_cfg:
-                        msg.fail("The base textcat model configuration does"
+                        msg.fail(
+                            "The base textcat model configuration does"
                             "not match the provided training options. "
                             "Existing cfg: {}, provided cfg: {}".format(
                                 base_cfg, pipe_cfg
                             ),
-                            exits=1
+                            exits=1,
                         )
     else:
         msg.text("Starting with blank model '{}'".format(lang))
@@ -300,7 +301,8 @@ def train(
             msg.fail(
                 "Cannot extend textcat model using data with different "
                 "labels. Base model labels: {}, training data labels: "
-                    "{}.".format(textcat_labels, list(train_labels)), exits=1
+                "{}.".format(textcat_labels, list(train_labels)),
+                exits=1,
             )
         if textcat_multilabel:
             msg.text(

spacy/lang/char_classes.py

@@ -201,7 +201,9 @@ _ukrainian = r"а-щюяіїєґА-ЩЮЯІЇЄҐ"
 _upper = LATIN_UPPER + _russian_upper + _tatar_upper + _greek_upper + _ukrainian_upper
 _lower = LATIN_LOWER + _russian_lower + _tatar_lower + _greek_lower + _ukrainian_lower
 
-_uncased = _bengali + _hebrew + _persian + _sinhala + _hindi + _kannada + _tamil + _telugu
+_uncased = (
+    _bengali + _hebrew + _persian + _sinhala + _hindi + _kannada + _tamil + _telugu
+)
 
 ALPHA = group_chars(LATIN + _russian + _tatar + _greek + _ukrainian + _uncased)
 ALPHA_LOWER = group_chars(_lower + _uncased)

spacy/language.py

@@ -32,7 +32,6 @@ from .lang.tokenizer_exceptions import TOKEN_MATCH
 from .lang.tag_map import TAG_MAP
 from .lang.lex_attrs import LEX_ATTRS, is_stop
 from .errors import Errors, Warnings, deprecation_warning
-from .strings import hash_string
 from . import util
 from . import about
 

spacy/tests/test_scorer.py

@@ -1,11 +1,9 @@
 # coding: utf-8
 from __future__ import unicode_literals
 
-import numpy as np
 from numpy.testing import assert_almost_equal, assert_array_almost_equal
 import pytest
 from pytest import approx
-from spacy.errors import Errors
 from spacy.gold import GoldParse
 from spacy.scorer import Scorer, ROCAUCScore
 from spacy.scorer import _roc_auc_score, _roc_curve
@@ -81,7 +79,7 @@ def test_roc_auc_score():
     roc_auc = _roc_auc_score(y_true, y_score)
     assert_array_almost_equal(tpr, [0, 0, 1])
     assert_array_almost_equal(fpr, [0, 1, 1])
-    assert_almost_equal(roc_auc, 1.)
+    assert_almost_equal(roc_auc, 1.0)
 
     y_true = [0, 1]
     y_score = [1, 0]
@@ -89,7 +87,7 @@ def test_roc_auc_score():
     roc_auc = _roc_auc_score(y_true, y_score)
     assert_array_almost_equal(tpr, [0, 1, 1])
     assert_array_almost_equal(fpr, [0, 0, 1])
-    assert_almost_equal(roc_auc, 0.)
+    assert_almost_equal(roc_auc, 0.0)
 
     y_true = [1, 0]
     y_score = [1, 1]
@@ -105,7 +103,7 @@ def test_roc_auc_score():
     roc_auc = _roc_auc_score(y_true, y_score)
     assert_array_almost_equal(tpr, [0, 0, 1])
     assert_array_almost_equal(fpr, [0, 1, 1])
-    assert_almost_equal(roc_auc, 1.)
+    assert_almost_equal(roc_auc, 1.0)
 
     y_true = [1, 0]
     y_score = [0.5, 0.5]
@@ -113,14 +111,13 @@ def test_roc_auc_score():
     roc_auc = _roc_auc_score(y_true, y_score)
     assert_array_almost_equal(tpr, [0, 1])
     assert_array_almost_equal(fpr, [0, 1])
-    assert_almost_equal(roc_auc, .5)
+    assert_almost_equal(roc_auc, 0.5)
 
     # same result as above with ROCAUCScore wrapper
     score = ROCAUCScore()
     score.score_set(0.5, 1)
     score.score_set(0.5, 0)
-    assert_almost_equal(score.score, .5)
+    assert_almost_equal(score.score, 0.5)
-
 
     # check that errors are raised in undefined cases and score is -inf
     y_true = [0, 0]