@@ -28,28 +28,35 @@ library. Wheels are available for most platforms.
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Installing a wheel or via conda will install a pre-compiled binary distribution.
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However, if you have a newer CPU that supports the AVX2 instruction set (e.g.,
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Intel Haswell, Broadwell or Skylake) then installing via pip is preferable,
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- because this will compile the Blosc library from source with optimisations
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- for AVX2.
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+ because you can compile the Blosc library from source with optimisations
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+ for AVX2.::
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+
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+ $ pip install -v --no-cache-dir --no-binary numcodecs numcodecs
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Note that if you compile the C extensions on a machine with AVX2 support
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you probably then cannot use the same binaries on a machine without AVX2.
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- To disable compilation with AVX2 support regardless of the machine
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- architecture::
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- $ export DISABLE_NUMCODECS_AVX2=
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- $ pip install -v --no-cache-dir --no-binary numcodecs numcodecs
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+ If you specifically want to disable AVX2 or SSE2 when compiling, you can use
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+ the following environment variables::
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- To work with Numcodecs source code in development, install from GitHub::
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+ $ export DISABLE_NUMCODECS_AVX2=1
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+ $ export DISABLE_NUMCODECS_SSE2=1
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+
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+
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+ To work with Numcodecs source code in development, clone the repository from GitHub
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+ and then install in editable mode using `pip `.::
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$ git clone --recursive https://github.com/zarr-developers/numcodecs.git
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$ cd numcodecs
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- $ python setup.py install
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+ $ pip install -e .[test,msgpack,zfpy]
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+
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+ Note: if you prefer to use the GitHub CLI ``gh `` you will need to append ``-- --recurse-submodules ``
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+ to the clone command to everything works properly.
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To verify that Numcodecs has been fully installed (including the Blosc
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extension) run the test suite::
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- $ pip install nose
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- $ python -m nose -v numcodecs
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+ $ pytest -v
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Contents
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--------
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