more mods

Author: jhamman

docs/developers/index.rst

@@ -1,6 +1,6 @@
 
-Developer Guide
----------------
+Developer's Guide
+-----------------
 
 .. toctree::
     :maxdepth: 1

docs/index.rst

@@ -9,21 +9,14 @@ Zarr-Python
     :hidden:
 
     quickstart
+    about
     user-guide/index
     api/index
     developers/index
-    about
+    developers/release
 
 **Version**: |version|
 
-**Download documentation**: `PDF/Zipped HTML <https://readthedocs.org/projects/zarr/downloads/>`_
-
-**Useful links**:
-`Source Repository <https://github.com/zarr-developers/zarr-python>`_ |
-`Issue Tracker <https://github.com/zarr-developers/zarr-python/issues>`_ |
-`Zulip Chat <https://ossci.zulipchat.com/>`_ |
-`Zarr specifications <https://zarr-specs.readthedocs.io>`_
-
 Zarr is a storage format for chunked, compressed, N-dimensional arrays based on an open-source specification. Highlights include:
 
 * Create N-dimensional arrays with any NumPy dtype.
@@ -34,9 +27,6 @@ Zarr is a storage format for chunked, compressed, N-dimensional arrays based on
 * Write to an array concurrently from multiple threads or processes.
 * Organize arrays into hierarchies via groups.
 
-Zarr-Python Documentation
--------------------------
-
 .. grid:: 2
 
     .. grid-item-card::
@@ -93,23 +83,33 @@ Zarr-Python Documentation
             :color: dark
             :click-parent:
 
-            To the api reference guide
+            To the API reference guide
 
     .. grid-item-card::
         :img-top: _static/index_contribute.svg
 
-        Contributor's Guide
-        ^^^^^^^^^^^^^^^^^^^
+        Developer's Guide
+        ^^^^^^^^^^^^^^^^^
 
         Want to contribute to Zarr? We welcome contributions in the form of bug reports,
         bug fixes, documentation, enhancement proposals and more. The contributing
         guidelines will guide you through the process of improving Zarr.
 
         +++
 
-        .. button-ref:: developers/contributing
+        .. button-ref:: developers/index
             :expand:
             :color: dark
             :click-parent:
 
-            To the contributor's guide
+            To the developers's guide
+
+**Useful links**:
+`Source Repository <https://github.com/zarr-developers/zarr-python>`_ |
+`Issue Tracker <https://github.com/zarr-developers/zarr-python/issues>`_ |
+`Zulip Chat <https://ossci.zulipchat.com/>`_ |
+`Zarr specifications <https://zarr-specs.readthedocs.io>`_
+
+**Download documentation**: `PDF/Zipped HTML <https://readthedocs.org/projects/zarr/downloads/>`_
+
+.. _NumCodecs: https://numcodecs.readthedocs.io

docs/quickstart.rst

@@ -10,9 +10,12 @@
 Quickstart
 ==========
 
-Welcome to the Zarr-Python Quickstart guide! This page will help you get up and running with the Zarr library in Python to efficiently manage and analyze multi-dimensional arrays.
+Welcome to the Zarr-Python Quickstart guide! This page will help you get up and running with
+the Zarr library in Python to efficiently manage and analyze multi-dimensional arrays.
 
-Zarr is a powerful library for storage of n-dimensional arrays, supporting chunking, compression, and various backends, making it a versatile choice for scientific and large-scale data.
+Zarr is a powerful library for storage of n-dimensional arrays, supporting chunking,
+compression, and various backends, making it a versatile choice for scientific and
+large-scale data.
 
 Installation
 ------------
@@ -32,102 +35,136 @@ or `conda`:
 Creating an Array
 -----------------
 
-To get started, you can create a simple Zarr array using the in-memory store:
+To get started, you can create a simple Zarr array:
 
 .. ipython:: python
 
     import zarr
     import numpy as np
 
     # Create a 2D Zarr array
-    z = zarr.zeros((100, 100), chunks=(10, 10), dtype='f4')
+    z = zarr.zeros(
+        store="data/example-1.zarr",
+        shape=(100, 100),
+        chunks=(10, 10),
+        dtype="f4"
+    )
 
     # Assign data to the array
     z[:, :] = np.random.random((100, 100))
+    z.info
 
-    print(z.info)
-
-Here, we created a 2D array of shape ``(100, 100)``, chunked into blocks of ``(10, 10)``, and filled it with random floating-point data.
+Here, we created a 2D array of shape ``(100, 100)``, chunked into blocks of
+``(10, 10)``, and filled it with random floating-point data. This array was
+written to a ``LocalStore`` in the ``data/example-1.zarr`` directory.
 
-Persistent Storage
-------------------
+Compression and Filters
+~~~~~~~~~~~~~~~~~~~~~~~
 
-Zarr supports persistent storage to disk or cloud-compatible backends. To store arrays on the filesystem:
+Zarr supports data compression and filters. For example, to use Blosc compression:
 
 .. ipython:: python
 
-    # Store the array in a directory on disk
+    from numcodecs import Blosc
+
     z = zarr.open(
-        'data/example-1.zarr',
-        mode='w', shape=(100, 100), chunks=(10, 10), dtype='f4'
+        "data/example-3.zarr",
+        mode="w", shape=(100, 100),
+        chunks=(10, 10), dtype="f4",
+        compressor=Blosc(cname="zstd", clevel=3, shuffle=Blosc.SHUFFLE),
+        zarr_format=2
     )
     z[:, :] = np.random.random((100, 100))
 
-    print("Array stored at 'data/example-1.zarr'")
+    z.info
 
-To open an existing array:
-
-.. ipython:: python
-
-    z = zarr.open('data/example-1.zarr', mode='r')
-    print(z[:])
+This compresses the data using the Zstandard codec with shuffle enabled for better compression.
 
 Hierarchical Groups
 -------------------
 
-Zarr allows creating hierarchical groups, similar to directories:
+Zarr allows you to create hierarchical groups, similar to directories:
 
 .. ipython:: python
 
-    # Create a group and add arrays
-    root = zarr.group('data/example-2.zarr')
-    foo = root.create_array(name='foo', shape=(1000, 100), chunks=(10, 10), dtype='f4')
-    bar = root.create_array(name='bar', shape=(100,), dtype='i4')
+    # Create nested groups and add arrays
+    root = zarr.group("data/example-2.zarr")
+    foo = root.create_group(name="foo")
+    bar = root.create_array(
+        name="bar", shape=(100, 10), chunks=(10, 10)
+    )
+    spam = foo.create_array(name="spam", shape=(10,), dtype="i4")
 
     # Assign values
-    foo[:, :] = np.random.random((1000, 100))
-    bar[:] = np.arange(100)
+    bar[:, :] = np.random.random((100, 10))
+    spam[:] = np.arange(10)
 
+    # print the hierarchy
     root.tree()
 
 This creates a group with two datasets: ``foo`` and ``bar``.
 
-.. Compression and Filters
-.. -----------------------
+Persistent Storage
+------------------
+
+Zarr supports persistent storage to disk or cloud-compatible backends. While examples above
+utilized a :class:`zarr.storage.LocalStore`, a number of other storage options are available,
+including the :class:`zarr.storage.ZipStore` and :class:`zarr.storage.FsspecStore`.
 
-.. Zarr supports data compression and filters. For example, to use Blosc compression:
+.. ipython:: python
 
-.. .. ipython:: python
-..    :verbatim:
+    # Store the array in a ZIP file
+    store = zarr.storage.ZipStore("data/example-3.zip", mode='w')
 
-..     z = zarr.open('data/example-3.zarr', mode='w', shape=(100, 100), chunks=(10, 10), dtype='f4',
-..                   compressor=zarr.Blosc(cname='zstd', clevel=3, shuffle=zarr.Blosc.SHUFFLE))
-..     z[:, :] = np.random.random((100, 100))
+    z = zarr.open(
+        store=store,
+        mode="w",
+        shape=(100, 100),
+        chunks=(10, 10),
+        dtype="f4"
+    )
 
-..     print(z.info)
+    # write to the array
+    z[:, :] = np.random.random((100, 100))
 
-.. This compresses the data using the Zstandard codec with shuffle enabled for better compression.
+    # the ZipStore must be explicitly closed
+    store.close()
+
+To open an existing array:
+
+.. ipython:: python
+
+    # Open the ZipStore in read-only mode
+    store = zarr.storage.ZipStore("data/example-3.zip", read_only=True)
+
+    z = zarr.open(store, mode='r')
+
+    # read the data as a NumPy Array
+    z[:]
 
 Cloud Storage Backends
-----------------------
+~~~~~~~~~~~~~~~~~~~~~~
 
-Zarr integrates seamlessly with cloud storage such as Amazon S3 and Google Cloud Storage using external libraries like `s3fs` or `gcsfs`.
+Zarr integrates seamlessly with cloud storage such as Amazon S3 and Google Cloud Storage
+using external libraries like `s3fs <https://s3fs.readthedocs.io>`_ or
+`gcsfs <https://gcsfs.readthedocs.io>`_.
 
 For example, to use S3:
 
 .. ipython:: python
    :verbatim:
 
     import s3fs
-    import zarr
 
-    z = zarr.open("s3://example-bucket/foo", mode='w', shape=(100, 100), chunks=(10, 10))
+    z = zarr.open("s3://example-bucket/foo", mode="w", shape=(100, 100), chunks=(10, 10))
     z[:, :] = np.random.random((100, 100))
 
+Read more about Zarr's storage options in the `User Guide <user-guide/storage.html>`_.
+
 Next Steps
 ----------
 
 Now that you're familiar with the basics, explore the following resources:
 
-- `User Guide <guide>`_
+- `User Guide <user-guide>`_
 - `API Reference <api>`_