diff --git a/spacy/pipeline.pyx b/spacy/pipeline.pyx
index c3b8f5fae..b1e046b5b 100644
--- a/spacy/pipeline.pyx
+++ b/spacy/pipeline.pyx
@@ -5,7 +5,6 @@ from __future__ import unicode_literals
 
 import numpy
 cimport numpy as np
-import cytoolz
 from collections import OrderedDict, defaultdict
 import srsly
 
@@ -302,7 +301,7 @@ class Pipe(object):
         Both __call__ and pipe should delegate to the `predict()`
         and `set_annotations()` methods.
         """
-        for docs in cytoolz.partition_all(batch_size, stream):
+        for docs in util.minibatch(stream, size=batch_size):
             docs = list(docs)
             scores, tensors = self.predict(docs)
             self.set_annotations(docs, scores, tensor=tensors)
@@ -479,7 +478,7 @@ class Tensorizer(Pipe):
         n_threads (int): Number of threads.
         YIELDS (iterator): A sequence of `Doc` objects, in order of input.
         """
-        for docs in cytoolz.partition_all(batch_size, stream):
+        for docs in util.minibatch(stream, size=batch_size):
             docs = list(docs)
             tensors = self.predict(docs)
             self.set_annotations(docs, tensors)
@@ -588,7 +587,7 @@ class Tagger(Pipe):
         return doc
 
     def pipe(self, stream, batch_size=128, n_threads=-1):
-        for docs in cytoolz.partition_all(batch_size, stream):
+        for docs in util.minibatch(stream, size=batch_size):
             docs = list(docs)
             tag_ids, tokvecs = self.predict(docs)
             self.set_annotations(docs, tag_ids, tensors=tokvecs)
@@ -1073,7 +1072,7 @@ class TextCategorizer(Pipe):
         return doc
 
     def pipe(self, stream, batch_size=128, n_threads=-1):
-        for docs in cytoolz.partition_all(batch_size, stream):
+        for docs in util.minibatch(stream, size=batch_size):
             docs = list(docs)
             scores, tensors = self.predict(docs)
             self.set_annotations(docs, scores, tensors=tensors)
diff --git a/spacy/syntax/nn_parser.pyx b/spacy/syntax/nn_parser.pyx
index 186c5c16c..61bbbc967 100644
--- a/spacy/syntax/nn_parser.pyx
+++ b/spacy/syntax/nn_parser.pyx
@@ -7,7 +7,6 @@ from __future__ import unicode_literals, print_function
 from collections import OrderedDict
 import numpy
 cimport cython.parallel
-import cytoolz
 import numpy.random
 cimport numpy as np
 from cpython.ref cimport PyObject, Py_XDECREF
@@ -213,10 +212,10 @@ cdef class Parser:
             beam_width = self.cfg.get('beam_width', 1)
         beam_density = self.cfg.get('beam_density', 0.)
         cdef Doc doc
-        for batch in cytoolz.partition_all(batch_size, docs):
+        for batch in util.minibatch(docs, size=batch_size):
             batch_in_order = list(batch)
             by_length = sorted(batch_in_order, key=lambda doc: len(doc))
-            for subbatch in cytoolz.partition_all(8, by_length):
+            for subbatch in util.minibatch(by_length, size=8):
                 subbatch = list(subbatch)
                 parse_states = self.predict(subbatch, beam_width=beam_width,
                                             beam_density=beam_density)
diff --git a/spacy/util.py b/spacy/util.py
index 7e700be03..0a682fcaa 100644
--- a/spacy/util.py
+++ b/spacy/util.py
@@ -11,7 +11,6 @@ from collections import OrderedDict
 from thinc.neural._classes.model import Model
 from thinc.neural.ops import NumpyOps
 import functools
-import cytoolz
 import itertools
 import numpy.random
 import srsly
@@ -403,7 +402,7 @@ def minibatch(items, size=8):
     items = iter(items)
     while True:
         batch_size = next(size_)
-        batch = list(cytoolz.take(int(batch_size), items))
+        batch = list(itertools.islice(items, int(batch_size)))
         if len(batch) == 0:
             break
         yield list(batch)