From 4a39c97306f732c2026de3dde1b98a8a793b4c56 Mon Sep 17 00:00:00 2001
From: Matthias Bussonnier <bussonniermatthias@gmail.com>
Date: Thu, 22 Oct 2020 12:09:16 -0700
Subject: [PATCH] Doctest seem to be stricter now, updating tostring() to
 tobytes()

---
 docs/tutorial.rst | 8 +++++---
 zarr/storage.py   | 4 ++--
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/docs/tutorial.rst b/docs/tutorial.rst
index ebc5db7165..0327cb248a 100644
--- a/docs/tutorial.rst
+++ b/docs/tutorial.rst
@@ -797,12 +797,14 @@ Here is an example using S3Map to read an array created previously::
     Compressor         : Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)
     Store type         : fsspec.mapping.FSMap
     No. bytes          : 21
+    No. bytes stored   : 382
+    Storage ratio      : 0.1
     Chunks initialized : 3/3
     >>> z[:]
     array([b'H', b'e', b'l', b'l', b'o', b' ', b'f', b'r', b'o', b'm', b' ',
            b't', b'h', b'e', b' ', b'c', b'l', b'o', b'u', b'd', b'!'],
           dtype='|S1')
-    >>> z[:].tostring()
+    >>> z[:].tobytes()
     b'Hello from the cloud!'
 
 Zarr now also has a builtin storage backend for Azure Blob Storage.
@@ -841,11 +843,11 @@ store. E.g.::
     >>> z = root['foo/bar/baz']
     >>> from timeit import timeit
     >>> # first data access is relatively slow, retrieved from store
-    ... timeit('print(z[:].tostring())', number=1, globals=globals())  # doctest: +SKIP
+    ... timeit('print(z[:].tobytes())', number=1, globals=globals())  # doctest: +SKIP
     b'Hello from the cloud!'
     0.1081731989979744
     >>> # second data access is faster, uses cache
-    ... timeit('print(z[:].tostring())', number=1, globals=globals())  # doctest: +SKIP
+    ... timeit('print(z[:].tobytes())', number=1, globals=globals())  # doctest: +SKIP
     b'Hello from the cloud!'
     0.0009490990014455747
 
diff --git a/zarr/storage.py b/zarr/storage.py
index 89f85f8eec..90dbc7dae6 100644
--- a/zarr/storage.py
+++ b/zarr/storage.py
@@ -1972,11 +1972,11 @@ class LRUStoreCache(MutableMapping):
         >>> z = root['foo/bar/baz']  # doctest: +REMOTE_DATA
         >>> from timeit import timeit
         >>> # first data access is relatively slow, retrieved from store
-        ... timeit('print(z[:].tostring())', number=1, globals=globals())  # doctest: +SKIP
+        ... timeit('print(z[:].tobytes())', number=1, globals=globals())  # doctest: +SKIP
         b'Hello from the cloud!'
         0.1081731989979744
         >>> # second data access is faster, uses cache
-        ... timeit('print(z[:].tostring())', number=1, globals=globals())  # doctest: +SKIP
+        ... timeit('print(z[:].tobytes())', number=1, globals=globals())  # doctest: +SKIP
         b'Hello from the cloud!'
         0.0009490990014455747