From 05dedaa2cf2e57469ac860fbd0af638c27c02148 Mon Sep 17 00:00:00 2001
From: svlandeg <sofie.vanlandeghem@gmail.com>
Date: Wed, 12 Feb 2020 12:00:13 +0100
Subject: [PATCH] add unit test

---
 spacy/tests/regression/test_issue4903.py | 40 ++++++++++++++++++++++++
 spacy/tests/regression/test_issue4924.py |  2 +-
 2 files changed, 41 insertions(+), 1 deletion(-)
 create mode 100644 spacy/tests/regression/test_issue4903.py

diff --git a/spacy/tests/regression/test_issue4903.py b/spacy/tests/regression/test_issue4903.py
new file mode 100644
index 000000000..97293aec7
--- /dev/null
+++ b/spacy/tests/regression/test_issue4903.py
@@ -0,0 +1,40 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+import spacy
+from spacy.tokens import Span, Doc
+
+
+class CustomPipe:
+    name = "my_pipe"
+
+    def __init__(self):
+        Span.set_extension("my_ext", getter=self._get_my_ext)
+        Doc.set_extension("my_ext", default=None)
+
+    def __call__(self, doc):
+        gathered_ext = []
+        for sent in doc.sents:
+            sent_ext = self._get_my_ext(sent)
+            sent._.set("my_ext", sent_ext)
+            gathered_ext.append(sent_ext)
+
+        doc._.set("my_ext", "\n".join(gathered_ext))
+
+        return doc
+
+    @staticmethod
+    def _get_my_ext(span):
+        return str(span.end)
+
+
+def test_issue4903():
+    # ensures that this runs correctly and doesn't hang or crash on Windows / macOS
+    nlp = spacy.load("en_core_web_sm")
+    custom_component = CustomPipe()
+    nlp.add_pipe(custom_component, after="parser")
+
+    text = ["I like bananas.", "Do you like them?", "No, I prefer wasabi."]
+    # works without 'n_process'
+    for doc in nlp.pipe(text, n_process=2):
+        print(doc)
diff --git a/spacy/tests/regression/test_issue4924.py b/spacy/tests/regression/test_issue4924.py
index 8aea2c3d5..0e45291a9 100644
--- a/spacy/tests/regression/test_issue4924.py
+++ b/spacy/tests/regression/test_issue4924.py
@@ -11,6 +11,6 @@ def nlp():
     return spacy.blank("en")
 
 
-def test_evaluate(nlp):
+def test_issue4924(nlp):
     docs_golds = [("", {})]
     nlp.evaluate(docs_golds)