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Copy file name to clipboardExpand all lines: python/api/tensorstore.virtual_chunked.html
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<dd><p>Creates a <aclass="reference internal" href="tensorstore.TensorStore.html" title="tensorstore.TensorStore (Python class) — Asynchronous multi-dimensional array handle."><codeclass="xref py py-obj docutils literal notranslate"><spanclass="pre">TensorStore</span></code></a> where the content is read/written chunk-wise by an arbitrary function.</p>
Copy file name to clipboardExpand all lines: python/tutorial.html
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<h2id="reading-and-writing-a-local-n5-dataset">Reading and writing a local N5 dataset<aclass="headerlink" href="#reading-and-writing-a-local-n5-dataset" title="Link to this heading">¶</a></h2>
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<p>Create a new <aclass="reference internal" href="../driver/n5/index.html#n5-driver"><spanclass="std std-ref">N5</span></a> dataset on the local filesystem using the
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<aclass="reference internal" href="../kvstore/file/index.html#file-kvstore-driver"><spanclass="std std-ref">file Key-Value Store driver</span></a>:</p>
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<p>While this dataset is public, the <aclass="reference internal" href="../kvstore/gcs/index.html#gcs-kvstore-driver"><spanclass="std std-ref">gcs Key-Value Store driver</span></a> currently requires
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that you supply <aclass="reference internal" href="../kvstore/gcs/index.html#gcs-authentication"><spanclass="std std-ref">Google Cloud credentials</span></a>.</p>
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<p>Open the dataset asynchronously to obtain a <aclass="reference internal" href="api/tensorstore.Future.html" title="tensorstore.Future (Python class) — Handle for consuming the result of an asynchronous operation."><codeclass="xref py py-obj docutils literal notranslate"><spanclass="pre">tensorstore.Future</span></code></a>:</p>
<p>Conversion to an <aclass="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v1.24)"><codeclass="xref py py-obj docutils literal notranslate"><spanclass="pre">numpy.ndarray</span></code></a> also implicitly performs a synchronous
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