rustfits
A Python FITS library with the heavy lifting written in Rust.
What it does
rustfits reads and writes FITS files — the
astronomical data format — from Python. The Python surface mirrors fitsio
conventions: open a file with FITS(path), index into HDUs with fits[i] or
fits["sci"], call hdu.read() for the data, and slice with hdu[a:b, c:d].
What's there today:
- Images — read, slice, write, in-place edits, append rows
(
extend), BSCALE/BZERO and BLANK/MaskedArray support, unsigned-int trick (u2/u4/u8/i1). - Tables — read/write structured arrays, dict, and list+names
inputs; row / slice / fancy / column / cell / multi-column writes;
appendand schema edits (insert_column/delete_column); variable-length columns including stringPA; bit-packedX/PX/QX. - Tile-compressed images (ZIMAGE) — all five algorithms
(GZIP_1, GZIP_2, RICE_1, HCOMPRESS_1, PLIO_1), quantized and
unquantized floats, mutation (
__setitem__+extend) without compounding quantization loss,repack()to reclaim orphans. - Tile-compressed tables (ZTABLE) — full surface including VLA columns and the dual-descriptor heap.
- Headers — case-insensitive lookup, CONTINUE chains, HIERARCH
long keys, batched updates via
FITSHeaderEdit, in-place header grow,CHECKSUM/DATASUM/ZHECKSUM/ZDATASUM. - Cross-tool interop — files written by
rustfitsround-trip bit-exactly throughastropy.io.fitsandfitsio. Files written by those tools (or bycfitsio/fpack) read back inrustfitsunchanged.
Quick examples
import rustfits
# Read an image — auto-picks the first HDU with data.
img = rustfits.read("image.fits")
# Slice an existing image without loading the full array.
with rustfits.FITS("image.fits") as fits:
image = fits["sci"].read()
image = fits["sci"][:, :]
stamp = fits["sci"][100:200, 50:150]
# Read a table; subset columns and rows.
with rustfits.FITS("catalog.fits") as fits:
hdu = fits[1]
# using numpy-style slicing
tab = hdu[:]
tabsub = hdu[0:100]
ra = hdu['ra'][20:30]
radec = hdu[['ra', 'dec']][[3, 5, 25]]
# using the read() function
tab = hdu.read() # same as hdu[:]
tabsub = hdu.read(columns=["ra", "dec"], rows=[3, 5, 25])
# Write an image or table to a new file (auto-detects).
import numpy as np
rustfits.write("out.fits", np.zeros((1024, 1024), dtype="f4"))
cat = np.zeros(100, dtype=[("ra", "f8"), ("dec", "f8")])
rustfits.write("cat.fits", cat)
# Update the data with numpy-style setitem
with rustfits.FITS(fname, 'r+') as fits:
hdu = fits["table"]
hdu[10:20] = updated_rows
hdu['ra'] = new_values
hdu[['ra', 'dec']][10:50] = new_radec
See the tutorial for a guided tour covering images, tables, compression, headers, the error model, and known limitations.
Documentation
Full documentation is hosted at
rustfits.readthedocs.io.
The latest build tracks main; stable tracks the most recent
release tag.
To build the docs locally instead:
sphinx-build docs docs/_build/html
xdg-open docs/_build/html/index.html
Sphinx and the Furo theme are listed
in docs/requirements.txt if you need them in your env.
Building from source
There's no PyPI or conda-forge release yet; install from source.
The build needs:
- A Python environment with
numpyandmaturin>=1.0,<2.0. - A Rust toolchain installed via
rustup. Don't use conda'srustpackage — it interacts badly with PyO3's libpython linking.
The simplest setup uses conda for Python and rustup for Rust:
# 1. Clone.
git clone https://github.com/esheldon/rustfits
cd rustfits
# 2. Create / activate a Python env, then install the runtime
# + build deps.
conda install --file conda-requirements.txt
# 3. Install the Rust toolchain (skip if you already have rustup).
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
# 4. Build and install the editable wheel into the active env.
maturin develop # debug build, for iteration
# OR
maturin develop --release # optimized build, for actual use
After the build finishes, import rustfits works inside the
active env. Re-run the same command after any change to the
Rust code.
Debug vs release. maturin develop (no flag) produces an
unoptimized debug build: it compiles fast and is what you want
during a tight edit-build-test loop. maturin develop --release
turns on the full optimizer (LLVM -O3-equivalent, inlining,
SIMD, etc.) — slower to compile but the resulting .so runs
5–50× faster depending on workload. Use --release for
anything other than development — benchmarks, real data
reductions, scripts that touch lots of bytes. The debug build
is roughly 100× slower at decompressing tiles, for example,
which makes ZIMAGE reads feel broken if you forget the flag.
The release profile keeps line-table debug info
(debug = "line-tables-only" in Cargo.toml), so backtraces
still resolve to source lines without paying the dead-code-
elimination penalty of a true debug build.
Running tests
To run the test suite or contribute, install the dev requirements on top of the build env:
conda install --file conda-test-requirements.txt
Then:
pytest # Python tests
tools/cargo-test.sh # Rust unit tests (wrapped to find libpython)
The wrapper tools/cargo-test.sh prepends the conda env's lib
directory to LD_LIBRARY_PATH so the PyO3-linked test binary can
find libpython.X.so — bare cargo test fails without it.
Contributing
Contributions and bug reports are welcome. Please feel free to open pull requests or issues at https://github.com/esheldon/rustfits
rustfits is mostly written in rust. If you don't know rust, you can
still make contributions. The extensive CLAUDE.md file can be used
by claude code or other agents to help you fix bugs or add features.
Just start the agent, ask it to load from CLAUDE.md, and start working.
License
Dual-licensed under MIT or Apache-2.0, at your option.
1 maintainer
Metadata
1 maintainer
Release files for rustfits 0.1.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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|---|---|---|---|
| rustfits-0.1.8.tar.gz | 1.0 MB | Details |
Built distributions (wheels)
Total release size: 251.4 MB
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