@@ -12,27 +12,25 @@ Highlights
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* Create N-dimensional arrays with any NumPy dtype.
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* Chunk arrays along any dimension.
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- * Compress chunks using the fast Blosc _ meta-compressor or alternatively using zlib, BZ2 or LZMA .
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+ * Compress and/ or filter chunks using any numcodecs _ codec .
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* Store arrays in memory, on disk, inside a Zip file, on S3, ...
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* Read an array concurrently from multiple threads or processes.
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* Write to an array concurrently from multiple threads or processes.
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* Organize arrays into hierarchies via groups.
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- * Use filters to preprocess data and improve compression.
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Status
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------
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- Zarr is still in an early phase of development. Feedback and bug
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- reports are very welcome, please get in touch via the `GitHub issue
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- tracker <https://github.com/alimanfoo/zarr/issues> `_.
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+ Zarr is still a young project. Feedback and bug reports are very welcome, please get in touch via
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+ the `GitHub issue tracker <https://github.com/alimanfoo/zarr/issues >`_.
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Installation
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------------
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Zarr depends on NumPy. It is generally best to `install NumPy
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- <http://docs.scipy.org/doc/numpy/user/install.html> `_ first using
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- whatever method is most appropriate for you operating system and
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- Python distribution .
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+ <http://docs.scipy.org/doc/numpy/user/install.html> `_ first using whatever method is most
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+ appropriate for you operating system and Python distribution. Other dependencies should be
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+ installed automatically if using one of the installation methods below .
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Install Zarr from PyPI::
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@@ -41,26 +39,18 @@ Install Zarr from PyPI::
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Alternatively, install Zarr via conda::
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$ conda install -c conda-forge zarr
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-
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- Zarr includes a C extension providing integration with the Blosc _
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- library. Installing 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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-
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+
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To work with Zarr source code in development, install from GitHub::
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$ git clone --recursive https://github.com/alimanfoo/zarr.git
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$ cd zarr
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$ python setup.py install
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- To verify that Zarr has been fully installed (including the Blosc
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- extension) run the test suite::
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+ To verify that Zarr has been fully installed, run the test suite::
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$ pip install nose
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$ python -m nose -v zarr
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-
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+
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Contents
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--------
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@@ -75,13 +65,20 @@ Contents
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Acknowledgments
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---------------
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- Zarr bundles the `c-blosc <https://github.com/Blosc/c-blosc >`_
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- library and uses it as the default compressor.
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+ The following people have contributed to the development of Zarr, by contributing code and/or
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+ providing ideas, feedback and advice:
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+
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+ * `Francesc Alted <https://github.com/FrancescAlted >`_
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+ * `Stephan Hoyer <https://github.com/shoyer >`_
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+ * `John Kirkham <https://github.com/jakirkham >`_
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+ * `Alistair Miles <https://github.com/alimanfoo >`_
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+ * `Matthew Rocklin <https://github.com/mrocklin >`_
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+ * `Vincent Schut <https://github.com/vincentschut >`_
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Zarr is inspired by `HDF5 <https://www.hdfgroup.org/HDF5/ >`_, `h5py
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<http://www.h5py.org/> `_ and `bcolz <http://bcolz.blosc.org/ >`_.
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- Development of this package is supported by the
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+ Development of Zarr is supported by the
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`MRC Centre for Genomics and Global Health <http://www.cggh.org >`_.
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Indices and tables
@@ -91,4 +88,4 @@ Indices and tables
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* :ref: `modindex `
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* :ref: `search `
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- .. _ Blosc : http://www.blosc.org /
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+ .. _ numcodecs : http://numcodecs.readthedocs.io /
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