Merge branch 'master' into spacy.io

bin/ud/ud_train.py

@@ -12,6 +12,7 @@ import json
 
 import spacy
 import spacy.util
+from bin.ud import conll17_ud_eval
 from spacy.tokens import Token, Doc
 from spacy.gold import GoldParse
 from spacy.util import compounding, minibatch, minibatch_by_words
@@ -25,8 +26,6 @@ import itertools
 import random
 import numpy.random
 
-import conll17_ud_eval
-
 from spacy import lang
 from spacy.lang import zh
 from spacy.lang import ja

spacy/about.py

@@ -1,6 +1,6 @@
 # fmt: off
 __title__ = "spacy"
-__version__ = "2.2.0"
+__version__ = "2.2.1"
 __release__ = True
 __download_url__ = "https://github.com/explosion/spacy-models/releases/download"
 __compatibility__ = "https://raw.githubusercontent.com/explosion/spacy-models/master/compatibility.json"

spacy/attrs.pyx

@@ -142,18 +142,28 @@ def intify_attrs(stringy_attrs, strings_map=None, _do_deprecated=False):
             elif key.upper() in stringy_attrs:
                 stringy_attrs.pop(key.upper())
     for name, value in stringy_attrs.items():
-        if isinstance(name, int):
-            int_key = name
-        elif name in IDS:
-            int_key = IDS[name]
-        elif name.upper() in IDS:
-            int_key = IDS[name.upper()]
-        else:
-            continue
-        if strings_map is not None and isinstance(value, basestring):
-            if hasattr(strings_map, 'add'):
-                value = strings_map.add(value)
-            else:
-                value = strings_map[value]
-        inty_attrs[int_key] = value
+        int_key = intify_attr(name)
+        if int_key is not None:
+            if strings_map is not None and isinstance(value, basestring):
+                if hasattr(strings_map, 'add'):
+                    value = strings_map.add(value)
+                else:
+                    value = strings_map[value]
+            inty_attrs[int_key] = value
     return inty_attrs
+
+
+def intify_attr(name):
+    """
+    Normalize an attribute name, converting it to int.
+
+    stringy_attr (string): Attribute string name. Can also be int (will then be left unchanged)
+    RETURNS (int): int representation of the attribute, or None if it couldn't be converted.
+    """
+    if isinstance(name, int):
+        return name
+    elif name in IDS:
+        return IDS[name]
+    elif name.upper() in IDS:
+        return IDS[name.upper()]
+    return None

spacy/tests/regression/test_issue4367.py

@@ -0,0 +1,11 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+from spacy.tokens import DocBin
+
+
+def test_issue4367():
+    """Test that docbin init goes well"""
+    doc_bin_1 = DocBin()
+    doc_bin_2 = DocBin(attrs=["LEMMA"])
+    doc_bin_3 = DocBin(attrs=["LEMMA", "ENT_IOB", "ENT_TYPE"])

spacy/tests/serialize/test_serialize_doc.py

@@ -1,8 +1,12 @@
 # coding: utf-8
 from __future__ import unicode_literals
 
+import spacy
+
 import pytest
-from spacy.tokens import Doc
+
+from spacy.lang.en import English
+from spacy.tokens import Doc, DocBin
 from spacy.compat import path2str
 
 from ..util import make_tempdir
@@ -57,3 +61,17 @@ def test_serialize_doc_exclude(en_vocab):
         doc.to_bytes(user_data=False)
     with pytest.raises(ValueError):
         Doc(en_vocab).from_bytes(doc.to_bytes(), tensor=False)
+
+
+def test_serialize_doc_bin():
+    doc_bin = DocBin(attrs=["LEMMA", "ENT_IOB", "ENT_TYPE"], store_user_data=True)
+    texts = ["Some text", "Lots of texts...", "..."]
+    nlp = English()
+    for doc in nlp.pipe(texts):
+        doc_bin.add(doc)
+    bytes_data = doc_bin.to_bytes()
+
+    # Deserialize later, e.g. in a new process
+    nlp = spacy.blank("en")
+    doc_bin = DocBin().from_bytes(bytes_data)
+    docs = list(doc_bin.get_docs(nlp.vocab))

spacy/tokens/_serialize.py

@@ -2,13 +2,13 @@
 from __future__ import unicode_literals
 
 import numpy
-import gzip
+import zlib
 import srsly
 from thinc.neural.ops import NumpyOps
 
 from ..compat import copy_reg
 from ..tokens import Doc
-from ..attrs import SPACY, ORTH, intify_attrs
+from ..attrs import SPACY, ORTH, intify_attr
 from ..errors import Errors
 
 
@@ -53,7 +53,7 @@ class DocBin(object):
         DOCS: https://spacy.io/api/docbin#init
         """
         attrs = attrs or []
-        attrs = sorted(intify_attrs(attrs))
+        attrs = sorted([intify_attr(attr) for attr in attrs])
         self.attrs = [attr for attr in attrs if attr != ORTH and attr != SPACY]
         self.attrs.insert(0, ORTH)  # Ensure ORTH is always attrs[0]
         self.tokens = []
@@ -142,7 +142,7 @@ class DocBin(object):
         }
         if self.store_user_data:
             msg["user_data"] = self.user_data
-        return gzip.compress(srsly.msgpack_dumps(msg))
+        return zlib.compress(srsly.msgpack_dumps(msg))
 
     def from_bytes(self, bytes_data):
         """Deserialize the DocBin's annotations from a bytestring.
@@ -152,7 +152,7 @@ class DocBin(object):
 
         DOCS: https://spacy.io/api/docbin#from_bytes
         """
-        msg = srsly.msgpack_loads(gzip.decompress(bytes_data))
+        msg = srsly.msgpack_loads(zlib.decompress(bytes_data))
         self.attrs = msg["attrs"]
         self.strings = set(msg["strings"])
         lengths = numpy.fromstring(msg["lengths"], dtype="int32")

website/docs/usage/saving-loading.md

@@ -84,7 +84,7 @@ texts = ["Some text", "Lots of texts...", "..."]
 nlp = spacy.load("en_core_web_sm")
 for doc in nlp.pipe(texts):
     doc_bin.add(doc)
-bytes_data = docbin.to_bytes()
+bytes_data = doc_bin.to_bytes()
 
 # Deserialize later, e.g. in a new process
 nlp = spacy.blank("en")

website/src/widgets/quickstart-install.js

@@ -99,7 +99,15 @@ const QuickstartInstall = ({ id, title }) => (
                         set PYTHONPATH=/path/to/spaCy
                     </QS>
                     <QS package="source">pip install -r requirements.txt</QS>
-                    <QS data="lookups">pip install -U spacy-lookups-data</QS>
+                    <QS data="lookups" package="pip">
+                        pip install -U spacy-lookups-data
+                    </QS>
+                    <QS data="lookups" package="source">
+                        pip install -U spacy-lookups-data
+                    </QS>
+                    <QS data="lookups" package="conda">
+                        conda install -c conda-forge spacy-lookups-data
+                    </QS>
                     <QS package="source">python setup.py build_ext --inplace</QS>
                     {models.map(({ code, models: modelOptions }) => (
                         <QS models={code} key={code}>