Zarr Python
Reads, writes, and manipulates Zarr data arrays in Python for efficient large dataset handling.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add jimmc414-zarr-python npx -- -y @trustedskills/jimmc414-zarr-python
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"jimmc414-zarr-python": {
"command": "npx",
"args": [
"-y",
"@trustedskills/jimmc414-zarr-python"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill provides Python bindings to the Zarr library, enabling efficient storage and retrieval of large, multi-dimensional arrays. It allows for chunked data organization within cloud object stores like AWS S3 or Google Cloud Storage. The skill facilitates working with datasets too large to fit in memory by streaming data directly from these remote locations.
When to use it
- Analyzing satellite imagery stored in Zarr format.
- Processing scientific simulations that generate massive numerical datasets.
- Building a data pipeline for serving large arrays to machine learning models.
- Working with genomic data stored as multi-dimensional arrays in the cloud.
Key capabilities
- Python bindings for Zarr library functions.
- Support for chunked array storage.
- Integration with cloud object stores (e.g., S3, GCS).
- Streaming of large datasets from remote locations.
Example prompts
- "Read the data from this Zarr dataset:
s3://my-bucket/data.zarrinto a NumPy array." - "Write this NumPy array to a new Zarr dataset at
gs://my-bucket/output.zarrwith chunk size 1024x1024." - “List all the datasets in this Zarr store:
s3://my-bucket/store.”
Tips & gotchas
- Requires Python and the Zarr library to be installed in the environment.
- Ensure proper authentication credentials are configured for accessing cloud storage.
Tags
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