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Modify the link in README.md from V2 to V3 docs (#2915)
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README.md

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@@ -101,13 +101,13 @@ Zarr is a Python package providing an implementation of compressed, chunked, N-d
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## Main Features
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- [**Create**](https://zarr.readthedocs.io/en/stable/tutorial.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.
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- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#chunk-optimizations) along any dimension.
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- [**Compress**](https://zarr.readthedocs.io/en/stable/tutorial.html#compressors) and/or filter chunks using any NumCodecs codec.
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- [**Store arrays**](https://zarr.readthedocs.io/en/stable/tutorial.html#tutorial-storage) in memory, on disk, inside a zip file, on S3, etc...
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- [**Read**](https://zarr.readthedocs.io/en/stable/tutorial.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/tutorial.html#parallel-computing-and-synchronization) 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**](https://zarr.readthedocs.io/en/stable/tutorial.html#groups).
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- [**Create**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#creating-an-array) N-dimensional arrays with any NumPy `dtype`.
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- [**Chunk arrays**](https://zarr.readthedocs.io/en/stable/user-guide/performance.html#chunk-optimizations) along any dimension.
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- [**Compress**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#compressors) and/or filter chunks using any NumCodecs codec.
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- [**Store arrays**](https://zarr.readthedocs.io/en/stable/user-guide/storage.html) in memory, on disk, inside a zip file, on S3, etc...
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- [**Read**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#reading-and-writing-data) an array [**concurrently**](https://zarr.readthedocs.io/en/stable/user-guide/performance.html#parallel-computing-and-synchronization) from multiple threads or processes.
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- [**Write**](https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#reading-and-writing-data) to an array concurrently from multiple threads or processes.
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- Organize arrays into hierarchies via [**groups**](https://zarr.readthedocs.io/en/stable/quickstart.html#hierarchical-groups).
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## Where to get it
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