diff --git a/bin/get_freqs.py b/bin/get_freqs.py
index c9f858b22..e126a2eee 100755
--- a/bin/get_freqs.py
+++ b/bin/get_freqs.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 
-from __future__ import unicode_literals
+from __future__ import unicode_literals, print_function
 
 import plac
 import joblib
@@ -12,9 +12,11 @@ import codecs
 from preshed.counter import PreshCounter
 from joblib import Parallel, delayed
 
-import spacy.en
+from spacy.en import English
 from spacy.strings import StringStore
-from spacy.en.attrs import ORTH
+from spacy.attrs import ORTH
+from spacy.tokenizer import Tokenizer
+from spacy.vocab import Vocab
 
 
 def iter_comments(loc):
@@ -23,37 +25,22 @@ def iter_comments(loc):
             yield ujson.loads(line)
 
 
-def null_props(string):
-    return {
-        'flags': 0,
-        'length': len(string),
-        'orth': string,
-        'lower': string,
-        'norm': string,
-        'shape': string,
-        'prefix': string,
-        'suffix': string,
-        'cluster': 0,
-        'prob': -22,
-        'sentiment': 0
-    }
-
-
 def count_freqs(input_loc, output_loc):
-    print output_loc
-    nlp = spacy.en.English(Parser=None, Tagger=None, Entity=None, load_vectors=False)
-    nlp.vocab.lexeme_props_getter = null_props
+    print(output_loc)
+    vocab = English.default_vocab(get_lex_attr=None)
+    tokenizer = Tokenizer.from_dir(vocab,
+                    path.join(English.default_data_dir(), 'tokenizer'))
 
     counts = PreshCounter()
-    tokenizer = nlp.tokenizer
     for json_comment in iter_comments(input_loc):
         doc = tokenizer(json_comment['body'])
         doc.count_by(ORTH, counts=counts)
 
     with codecs.open(output_loc, 'w', 'utf8') as file_:
         for orth, freq in counts:
-            string = nlp.vocab.strings[orth]
-            file_.write('%d\t%s\n' % (freq, repr(string)))
+            string = tokenizer.vocab.strings[orth]
+            if not string.isspace():
+                file_.write('%d\t%s\n' % (freq, string))
 
 
 def parallelize(func, iterator, n_jobs):
@@ -64,12 +51,12 @@ def merge_counts(locs, out_loc):
     string_map = StringStore()
     counts = PreshCounter()
     for loc in locs:
-        with codecs.open(loc, 'r', 'utf8') as file_:
+        with io.open(loc, 'r', encoding='utf8') as file_:
             for line in file_:
                 freq, word = line.strip().split('\t', 1)
                 orth = string_map[word]
                 counts.inc(orth, int(freq))
-    with codecs.open(out_loc, 'w', 'utf8') as file_:
+    with io.open(out_loc, 'w', encoding='utf8') as file_:
         for orth, count in counts:
             string = string_map[orth]
             file_.write('%d\t%s\n' % (count, string))
@@ -98,7 +85,7 @@ def main(input_loc, freqs_dir, output_loc, n_jobs=2, skip_existing=False):
     if tasks:
         parallelize(count_freqs, tasks, n_jobs)
 
-    print "Merge"
+    print("Merge")
     merge_counts(outputs, output_loc)
                 
 
diff --git a/setup.py b/setup.py
index 21f9c6f53..f06be8104 100644
--- a/setup.py
+++ b/setup.py
@@ -179,7 +179,7 @@ VERSION = '0.95'
 def main(modules, is_pypy):
     language = "cpp"
     includes = ['.', path.join(sys.prefix, 'include')]
-    if sys.prefix == 'darwin':
+    if sys.platform.startswith('darwin'):
         compile_options['other'].append(['-mmacosx-version-min=10.8', '-stdlib=libc++'])
         link_opions['other'].append('-lc++')
     if use_cython: