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A command-line tool for exploring huge `.h5ad`(AnnData) files without loading them fully into memory. Streams data directly from disk for efficient inspection of structure, metadata, and matrices.
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A command-line tool for exploring huge AnnData stores (`.h5ad`and `.zarr`) without loading them fully into memory. Streams data directly from disk for efficient inspection of structure, metadata, and matrices.
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## Features
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-**`info`** – Show file structure and dimensions (`n_obs × n_var`)
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-**`table`** – Export obs/var metadata to CSV with chunked streaming
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-**`subset`** – Filter h5ad files by cell/gene names (supports dense and sparse CSR/CSC matrices)
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- Memory-efficient chunked processing for large files
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- Rich terminal output with colors and progress bars
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- Streaming access to very large `.h5ad` and `.zarr` stores
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- Auto-detects `.h5ad` files vs `.zarr` directories
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- Chunked processing for dense and sparse matrices (CSR/CSC)
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- Rich terminal output with progress indicators
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## Installation
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Using [uv](https://docs.astral.sh/uv/) (recommended):
uv run h5ad table data.h5ad --axis obs --out obs_metadata.csv
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pip install -e ".[dev]"
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```
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**Export selected obs columns to stdout:**
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```bash
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uv run h5ad table data.h5ad --axis obs --cols cell_type,donor
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```
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See [docs/TESTING.md](docs/TESTING.md) for testing documentation.
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**Export var metadata with custom chunk size:**
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```bash
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uv run h5ad table data.h5ad --axis var --chunk-rows 5000 --out var_metadata.csv
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```
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## Commands (Overview)
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**Subset by cell names:**
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```bash
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uv run h5ad subset input.h5ad output.h5ad --obs cells.txt
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```
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Run help at any level (e.g. `uv run h5ad --help`, `uv run h5ad export --help`).
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**Subset by both cells and genes:**
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```bash
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uv run h5ad subset input.h5ad output.h5ad --obs cells.txt --var genes.txt
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```
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-`info` – read-only inspection of store layout, shapes, and type hints; supports drilling into paths like `obsm/X_pca` or `uns`.
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-`subset` – stream and write a filtered copy based on obs/var name lists, preserving dense and sparse matrix encodings.
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-`export` – extract data from a store; subcommands: `dataframe` (obs/var to CSV), `array` (dense to `.npy`), `sparse` (CSR/CSC to `.mtx`), `dict` (JSON), `image` (PNG).
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-`import` – write new data into a store; subcommands: `dataframe` (CSV → obs/var), `array` (`.npy`), `sparse` (`.mtx`), `dict` (JSON).
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All commands stream from disk, so even multi-GB `.h5ad` files remain responsive.
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See [docs/GET_STARTED.md](docs/GET_STARTED.md) for a short tutorial.
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