zarr-python
SolidChunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
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2901 forks Updated today MIT
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Skill Content
# Zarr Python
## Overview
Zarr is a Python library for storing large N-dimensional arrays with chunking and compression. Apply this skill for efficient parallel I/O, cloud-native workflows, and seamless integration with NumPy, Dask, and Xarray.
## Quick Start
### Installation
```bash
uv pip install zarr
```
Requires Python 3.11+. For cloud storage support, install additional packages:
```python
uv pip install s3fs # For S3
uv pip install gcsfs # For Google Cloud Storage
```
### Basic Array Creation
```python
import zarr
import numpy as np
# Create a 2D array with chunking and compression
z = zarr.create_array(
store="data/my_array.zarr",
shape=(10000, 10000),
chunks=(1000, 1000),
dtype="f4"
)
# Write data using NumPy-style indexing
z[:, :] = np.random.random((10000, 10000))
# Read data
data = z[0:100, 0:100] # Returns NumPy array
```
## Core Operations
### Creating Arrays
Zarr provides multiple convenience functions for array creation:
```python
# Create empty array
z = zarr.zeros(shape=(10000, 10000), chunks=(1000, 1000), dtype='f4',
store='data.zarr')
# Create filled arrays
z = zarr.ones((5000, 5000), chunks=(500, 500))
z = zarr.full((1000, 1000), fill_value=42, chunks=(100, 100))
# Create from existing data
data = np.arange(10000).reshape(100, 100)
z = zarr.array(data, chunks=(10, 10), store='data.zarr')
# Create like another array
z2 = zarr.zeros_like(z) # Matches shape, chunks, dtype of z
```
### Opening Existing Arra...
Details
- Author
- davila7
- Repository
- davila7/claude-code-templates
- Created
- 11 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
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