Merge branch 'master' into no_avx_instruction

docs/contributing.rst

@@ -305,10 +305,8 @@ Tag the version (where "X.X.X" stands for the version number, e.g., "2.2.0")::
     $ git tag -a v$version -m v$version
     $ git push --tags
 
-Release source code to PyPI::
-
-    $ python setup.py register sdist
-    $ twine upload dist/numcodecs-${version}.tar.gz
+This will trigger a GitHub Action which will build the source
+distribution as well as wheels for all major platforms.
 
 Obtain checksum for release to conda-forge::
 

docs/index.rst

@@ -24,7 +24,9 @@ Alternatively, install via conda::
     $ conda install -c conda-forge numcodecs
 
 Numcodecs includes a C extension providing integration with the Blosc_
-library. Installing via conda will install a pre-compiled binary distribution.
+library. Wheels are available for most platforms.
+
+Installing a wheel or via conda will install a pre-compiled binary distribution.
 However, if you have a newer CPU that supports the AVX2 instruction set (e.g.,
 Intel Haswell, Broadwell or Skylake) then installing via pip is preferable,
 because this will compile the Blosc library from source with optimisations
@@ -36,7 +38,7 @@ To disable compilation with AVX2 support regardless of the machine
 architecture::
 
     $ export DISABLE_NUMCODECS_AVX2=
-    $ pip install -v --no-cache-dir numcodecs
+    $ pip install -v --no-cache-dir --no-binary numcodecs numcodecs
 
 To work with Numcodecs source code in development, install from GitHub::