Use cards on homepage for now

Author: maxrjones

.pre-commit-config.yaml

@@ -20,6 +20,7 @@ repos:
     rev: v5.0.0
     hooks:
       - id: check-yaml
+        exclude: mkdocs.yml
       - id: trailing-whitespace
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v1.16.1

docs/index.md

@@ -33,187 +33,45 @@ or `conda`:
 conda install --channel conda-forge zarr
 ```
 
-## Quick Start 🚀
-
-This section  will help you get up and running with
-the Zarr library in Python to efficiently manage and analyze multi-dimensional arrays.
-
-### Creating an Array
-
-To get started, you can create a simple Zarr array:
-
-```python
-import zarr
-import numpy as np
-
-# Create a 2D Zarr array
-z = zarr.create_array(
-   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
-
-# Type               : Array
-# Zarr format        : 3
-# Data type          : DataType.float32
-# Shape              : (100, 100)
-# Chunk shape        : (10, 10)
-# Order              : C
-# Read-only          : False
-# Store type         : LocalStore
-# Codecs             : [{'endian': <Endian.little: 'little'>}, {'level': 0, 'checksum': False}]
-# No. bytes          : 40000 (39.1K)
-```
-
-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.
-
-#### Compression and Filters
-
-Zarr supports data compression and filters. For example, to use Blosc compression:
-
-```python
-z = zarr.create_array(
-   "data/example-3.zarr",
-   mode="w", shape=(100, 100),
-   chunks=(10, 10), dtype="f4",
-   compressors=zarr.codecs.BloscCodec(cname="zstd", clevel=3, shuffle=zarr.codecs.BloscShuffle.shuffle)
-)
-z[:, :] = np.random.random((100, 100))
-z.info
-# Type               : Array
-# Zarr format        : 3
-# Data type          : DataType.float32
-# Shape              : (100, 100)
-# Chunk shape        : (10, 10)
-# Order              : C
-# Read-only          : False
-# Store type         : LocalStore
-# Codecs             : [{'endian': <Endian.little: 'little'>}, {'level': 0, 'checksum': False}]
-# No. bytes          : 40000 (39.1K)
-```
-
-This compresses the data using the Zstandard codec with shuffle enabled for better compression.
-
-### Hierarchical Groups
+## Navigating the documentation
 
-Zarr allows you to create hierarchical groups, similar to directories:
+<div class="grid cards" markdown>
 
-```python
-# 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), dtype="f4"
-)
-spam = foo.create_array(name="spam", shape=(10,), dtype="i4")
+-   [:material-clock-fast:{ .lg .middle } __Quick start__](quick-start.md)
 
-# Assign values
-bar[:, :] = np.random.random((100, 10))
-spam[:] = np.arange(10)
+    ---
 
-# print the hierarchy
-root.tree()
-# /
-# ├── bar (100, 10) float32
-# └── foo
-#     └── spam (10,) int32
-```
+    New to Zarr? Check out the quick start guide. It contains a brief
+    introduction to Zarr's main concepts and links to additional tutorials.
 
-This creates a group with two datasets: `foo` and `bar`.
-
-#### Batch Hierarchy Creation
-
-Zarr provides tools for creating a collection of arrays and groups with a single function call.
-Suppose we want to copy existing groups and arrays into a new storage backend:
-
-```python
-# Create nested groups and add arrays
-root = zarr.group("data/example-3.zarr", attributes={'name': 'root'})
-foo = root.create_group(name="foo")
-bar = root.create_array(
-    name="bar", shape=(100, 10), chunks=(10, 10), dtype="f4"
-)
-nodes = {'': root.metadata} | {k: v.metadata for k,v in root.members()}
-print(nodes)
-from zarr.storage import MemoryStore
-new_nodes = dict(zarr.create_hierarchy(store=MemoryStore(), nodes=nodes))
-new_root = new_nodes['']
-assert new_root.attrs == root.attrs
-```
 
-Note that `zarr.create_hierarchy` will only initialize arrays and groups -- copying array data must
-be done in a separate step.
+-   [:material-book-open:{ .lg .middle } __User guide__](user-guide/installation.md)
 
-### Persistent Storage
+    ---
 
-Zarr supports persistent storage to disk or cloud-compatible backends. While examples above
-utilized a `zarr.storage.LocalStore`, a number of other storage options are available.
+    A detailed guide for how to use Zarr-Python.
 
-Zarr integrates seamlessly with cloud object storage such as Amazon S3 and Google Cloud Storage
-using external libraries like [s3fs](https://s3fs.readthedocs.io) or
-[gcsfs](https://gcsfs.readthedocs.io):
 
-```python
-import s3fs
+-   [:material-api:{ .lg .middle } __API Reference__](api/open.md)
 
-z = zarr.create_array("s3://example-bucket/foo", mode="w", shape=(100, 100), chunks=(10, 10), dtype="f4")
-z[:, :] = np.random.random((100, 100))
-```
+    ---
 
-A single-file store can also be created using the `zarr.storage.ZipStore`:
+    The reference guide contains a detailed description of the functions, modules,
+    and objects included in Zarr. The reference describes how the methods work and
+    which parameters can be used. It assumes that you have an understanding of the
+    key concepts.
 
-```python
-# Store the array in a ZIP file
-store = zarr.storage.ZipStore("data/example-3.zip", mode='w')
 
-z = zarr.create_array(
-    store=store,
-    mode="w",
-    shape=(100, 100),
-    chunks=(10, 10),
-    dtype="f4"
-)
+-   [:material-account-group:{ .lg .middle } __Contributor's Guide__](contributing.md)
 
-# write to the array
-z[:, :] = np.random.random((100, 100))
+    ---
 
-# the ZipStore must be explicitly closed
-store.close()
-```
+    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.
 
-To open an existing array from a ZIP file:
-
-```python
-# Open the ZipStore in read-only mode
-store = zarr.storage.ZipStore("data/example-3.zip", read_only=True)
-
-z = zarr.open_array(store, mode='r')
-
-# read the data as a NumPy Array
-z[:]
-# array([[0.66734236, 0.15667458, 0.98720884, ..., 0.36229587, 0.67443246,
-#         0.34315267],
-#     [0.65787303, 0.9544212 , 0.4830079 , ..., 0.33097172, 0.60423803,
-#         0.45621237],
-#     [0.27632037, 0.9947008 , 0.42434934, ..., 0.94860053, 0.6226942 ,
-#         0.6386924 ],
-#     ...,
-#     [0.12854576, 0.934397  , 0.19524333, ..., 0.11838563, 0.4967675 ,
-#         0.43074256],
-#     [0.82029045, 0.4671437 , 0.8090906 , ..., 0.7814118 , 0.42650765,
-#         0.95929915],
-#     [0.4335856 , 0.7565437 , 0.7828931 , ..., 0.48119593, 0.66220033,
-#         0.6652362 ]], shape=(100, 100), dtype=float32)
-```
+</div>
 
-Read more about Zarr's storage options in the [User Guide](user-guide/storage.md).
 
 ## Project Status
 
@@ -224,7 +82,7 @@ If you are using Zarr-Python, we would [love to hear about it](https://github.co
 ### Funding and Support
 The project is fiscally sponsored by [NumFOCUS](https://numfocus.org/), a US
 501(c)(3) public charity, and development has been supported by the
-[MRC Centre for Genomics and Global Health](https://www.cggh.org)
+[MRC Centre for Genomics and Global Health](https://www.sanger.ac.uk/collaboration/mrc-centre-genomics-and-global-health-cggh/)
 and the [Chan Zuckerberg Initiative](https://chanzuckerberg.com/).
 
 [Donate to Zarr](https://numfocus.org/donate-to-zarr) to support the project!