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Unified image hashing — ThumbHash, BlurHash, and more — Rust-powered Python bindings

Project description

thumbleweed

Build & Publish Wheels Package version Supported Python versions MIT License

Unified image hashing for Python — ThumbHash, BlurHash, and ColorThief.
Rust-powered via PyO3 + maturin. Zero mandatory dependencies.

  • ThumbHash — compact image placeholder hashes (drop-in for thumbhash & fast-thumbhash)
  • BlurHash — smooth gradient placeholders (drop-in for blurhash-python)
  • ColorThief — dominant colour + palette extraction (drop-in for colorthief & fast-colorthief)
  • ✅ Python 3.10 – 3.14 (including free-threaded 3.13t / 3.14t)
  • ✅ Pillow > 11 integration (optional)
  • ✅ Typed (py.typed + .pyi stubs)
  • ✅ Pure-Rust core — no C extensions, no NumPy required

Installation

pip install thumbleweed
# with Pillow helpers:
pip install "thumbleweed[pillow]"

Development with uv

curl -LsSf https://astral.sh/uv/install.sh | sh
make sync
make test

All import paths work:

import thumbleweed   # the unified package
import thumbhash     # ThumbHash only (backward-compatible)
import blurhash      # BlurHash only
import colorthief    # ColorThief

Quick-start

ThumbHash

import thumbhash as th

# Encode — rgba_bytes must be bytes/bytearray of length w*h*4 (R G B A, non-premultiplied)
hash_bytes: bytes = th.encode(w, h, rgba_bytes)

# Decode
w_out, h_out, rgba_out = th.decode(hash_bytes)

# Helpers
r, g, b, a = th.average_rgba(hash_bytes)           # dominant colour [0, 1]
ratio = th.approximate_aspect_ratio(hash_bytes)     # width / height

BlurHash

import blurhash as bh

# Encode
hash_str: str = bh.encode(rgba_bytes, cx=4, cy=3, width=w, height=h)

# Decode
rgba: bytes = bh.decode(hash_str, width=64, height=64)

Pillow images / BytesIO

from PIL import Image
import io

# From a Pillow Image
import thumbhash as th
img = Image.open("photo.jpg")
hash_bytes = th.encode_image(img)           # any mode, any size
placeholder = th.decode_image(hash_bytes)   # → RGBA Image, ≈32 px

# From a BytesIO object
buf = io.BytesIO(open("photo.jpg", "rb").read())
hash_bytes = th.encode_image(buf)

# BlurHash
import blurhash as bh
hash_str = bh.encode_image(img, cx=4, cy=3)
placeholder = bh.decode_image(hash_str, width=64, height=64)

ColorThief

import colorthief as ct

# From encoded image bytes (PNG, JPEG, WebP, …)
dominant = ct.get_color(image_bytes)                    # → (r, g, b)
palette = ct.get_palette(image_bytes, color_count=5)   # → [(r, g, b), ...]

# From a file path
dominant = ct.get_color("photo.jpg")

# From a BytesIO object
import io
buf = io.BytesIO(open("photo.jpg", "rb").read())
dominant = ct.get_color(buf)                # accepts bytes, BytesIO, file path, or PIL Image
palette = ct.get_palette(buf, color_count=5)

# Class-based API (drop-in for the colorthief package)
thief = ct.ColorThief("photo.jpg")
dominant = thief.get_color()
palette = thief.get_palette(color_count=8)

thumbleweed (unified)

import thumbleweed

# ThumbHash
hash_bytes = thumbleweed.thumbhash_encode(w, h, rgba)
w, h, rgba = thumbleweed.thumbhash_decode(hash)

# BlurHash
hash_str = thumbleweed.blurhash_encode(rgba, 4, 3, w, h)
rgba = thumbleweed.blurhash_decode(hash_str, 64, 64)

# ColorThief
dominant = thumbleweed.colorthief_get_color_bytes(image_bytes)
palette = thumbleweed.colorthief_get_palette_bytes(image_bytes, 5, 10)

Project structure

thumbleweed/
├── src/
│   ├── lib.rs            # PyO3 module — Python bindings
│   ├── thumbhash.rs      # Pure Rust ThumbHash encode/decode
│   ├── blurhash.rs       # Pure Rust BlurHash encode/decode
│   └── colorthief.rs     # ColorThief — dominant colour & palette extraction
├── python/
│   ├── thumbleweed/      # Main package — re-exports everything
│   ├── thumbhash/        # Backward-compatible ThumbHash shim
│   ├── blurhash/         # BlurHash shim
│   └── colorthief/       # ColorThief shim
├── tests/
│   ├── test_thumbhash.py # 70 ThumbHash tests
│   ├── test_blurhash.py  # 28 BlurHash tests
│   ├── test_colorthief.py # ColorThief tests
│   └── test_imports.py   # import / version-consistency tests
└── Cargo.toml

API reference

ThumbHash (import thumbhash)

Function Description
encode(w, h, rgba) → bytes Encode raw RGBA bytes → ThumbHash
decode(hash) → (w, h, rgba) Decode ThumbHash → raw RGBA bytes
average_rgba(hash) → (r,g,b,a) Dominant colour in [0, 1]
approximate_aspect_ratio(hash) → float Width / height of the original image
encode_image(img) → bytes Encode a Pillow Image, bytes, BytesIO, or file path → ThumbHash
decode_image(hash) → Image Decode to a Pillow Image (requires Pillow)

BlurHash (import blurhash)

Function Description
encode(pixels, cx, cy, w, h) → str Encode raw RGBA bytes → BlurHash string
decode(hash, w, h) → bytes Decode BlurHash → raw RGBA bytes
encode_image(img, cx, cy) → str Encode a Pillow Image, bytes, BytesIO, or file path → BlurHash
decode_image(hash, w, h) → Image Decode to a Pillow Image (requires Pillow)

ColorThief (import colorthief)

Function Description
get_color(image, quality) → (r,g,b) Dominant colour from bytes, BytesIO, file path, or PIL Image
get_palette(image, color_count, quality) → list[(r,g,b)] Colour palette from bytes, BytesIO, file path, or PIL Image
ColorThief(image) Class-based API — accepts bytes, BytesIO, file path, or PIL Image

Performance benchmarks

Performance Benchmark Results

Benchmark configuration: 5 rounds × 100 iterations (pure-Python libraries use 5 iterations). Input corpus: all real image fixtures in tests/ (one.jpg, two.jpg, four.jpg, OPS.jpg). All times are mean per-call latency. Lower is better.

ThumbHash

Operation Library Mean latency vs thumbleweed
ThumbHash encode (real test images) thumbleweed (Rust) 825.4 µs — (baseline)
ThumbHash encode (real test images) thumbhash-python (pure Python) 27.26 ms 33.0× faster
ThumbHash decode (real test images) thumbleweed (Rust) 56.4 µs — (baseline)
ThumbHash decode (real test images) thumbhash-python (pure Python) 5.49 ms 97.3× faster

BlurHash

Operation Library Mean latency vs thumbleweed
BlurHash encode (real test images) thumbleweed (Rust) 4.98 ms — (baseline)
BlurHash encode (real test images) blurhash-python (pure Python) 4.42 ms 1.1× slower
BlurHash decode 64×64 (real test images) thumbleweed (Rust) 902.4 µs — (baseline)
BlurHash decode 64×64 (real test images) blurhash-python (pure Python) 842.2 µs 1.1× slower

ColorThief

Operation Library Mean latency vs thumbleweed
ColorThief dominant (real test images) thumbleweed (Rust) 5.09 ms — (baseline)
ColorThief dominant (real test images) fast-colorthief (C ext + NumPy) 18.62 ms 3.7× faster
ColorThief palette-10 (real test images) thumbleweed (Rust) 5.17 ms — (baseline)
ColorThief palette-10 (real test images) fast-colorthief (C ext + NumPy) 18.38 ms 3.6× faster

Notes on ColorThief timing: thumbleweed includes image decode in its timing because it accepts raw encoded bytes from the real test fixtures, while fast-colorthief also reads from in-memory file-like objects in these benchmarks. This measures realistic end-to-end usage rather than just the inner palette routine.


Building from source

git clone https://github.com/New-Elysium/thumbleweed.git
cd thumbleweed
make sync   # sync uv environment + install editable
make test   # run Python + Rust tests

Make targets

  • make sync — sync uv environment and install the extension in editable mode
  • make test — run Python tests and Rust tests
  • make dist — build wheels into dist/
  • make upload — upload dist/* with twine

Running Benchmarks

Benchmarks require bench dependencies which might not be compatible with all Python versions (e.g. thumbhash-python fails to resolve on Python 3.14). To avoid conflicts, run them with a supported Python version (e.g. 3.12):

# Sync using a Python version that supports the benchmark dependencies
uv sync --group bench --python 3.12
uv run python tests/bench_comparison.py

Licence

MIT — see LICENCE.

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