spork-pds

PyPI - Version

spork-pds provides fast, immutable persistent data structures for CPython. They use familiar collection operators, but return new values while sharing unchanged structure with the original. Snapshots stay inexpensive and previous values remain unchanged.

The package is the standalone home of the persistent data structures originally developed for Spork. It has no dependency on the Spork language or runtime.

Alpha: The API and binary compatibility may change between releases.

Features

Vector: bit-partitioned persistent vector with indexing, slicing, + concatenation, and * repetition
Map: persistent hash map backed by a HAMT with dict-style | merging
Set: persistent hash set with |, &, -, and ^ operations
SortedVector: ordered persistent collection backed by a size-annotated red-black tree
Cons: immutable linked-list cells
DoubleVector and IntVector: specialized float64 and int64 vectors with the read-only buffer protocol
Transient variants for efficient batches of controlled mutation
Structural ABC integration, hashing, iteration, generic aliases, and pickle support
CPython 3.10+ support, including free-threaded CPython 3.14 builds

Installation

python -m pip install spork-pds

A C compiler and Python development headers are required when installing from a source distribution. Published releases are intended to provide wheels for supported Python versions and platforms.

Quick start

from spork_pds import Map, Set, Vector, sorted_vec

numbers = Vector([1, 2, 3])
extended = numbers + [4, 5]
repeated = numbers * 2

assert list(numbers) == [1, 2, 3]
assert list(extended) == [1, 2, 3, 4, 5]
assert list(repeated) == [1, 2, 3, 1, 2, 3]

config = Map({"host": "localhost", "port": 8000})
production = config | {"host": "example.com"}

assert config["host"] == "localhost"
assert production["host"] == "example.com"

roles = Set(["reader", "writer"])
admin_roles = roles | {"admin"}

assert "admin" not in roles
assert "admin" in admin_roles

ordered = sorted_vec([5, 1, 3, 2, 4])
assert list(ordered) == [1, 2, 3, 4, 5]

Native operators, persistent values

Operators always produce persistent spork_pds collections and leave their operands unchanged:

updated_map = config | {"port": 443}
combined_set = roles | {"admin", "auditor"}
reduced_set = combined_set - {"reader"}
longer_vector = numbers + range(4, 7)

Augmented assignment follows Python's normal immutable-value behavior. It rebinds the name rather than mutating the collection:

original = Map({"users": 100})
updated = original
updated |= {"users": 101}

assert original["users"] == 100
assert updated["users"] == 101

The named persistent operations—such as .assoc(), .conj(), and .disj()—remain available when an individual update is clearer.

Batch updates with transients

Persistent updates are ideal when each intermediate version matters. For a batch where only the final value matters, use a transient:

from spork_pds import EMPTY_VECTOR

builder = EMPTY_VECTOR.transient()
for value in range(100_000):
    builder.conj_mut(value)

values = builder.persistent()
assert values[-1] == 99_999

Calling persistent() invalidates the transient. Further edits and element access raise RuntimeError; discard the transient immediately after conversion.

Typed vectors and NumPy

from spork_pds import vec_f64, vec_i64

floats = vec_f64(1.0, 2.0, 3.0)
integers = vec_i64(1, 2, 3)

# The exported buffers are read-only.
assert memoryview(floats).format == "d"
assert memoryview(integers).format == "q"

# NumPy can view the vectors through the buffer protocol.
import numpy as np
array = np.asarray(floats)

The first buffer request materializes and caches contiguous storage; subsequent views reuse that immutable cache.

Documentation

Development

Clone the repository and set up the development environment:

git clone https://github.com/spork-it/spork-pds.git
cd spork-pds

make venv
make test
make fuzz

Useful targets:

make build
make build-debug
make benchmark BENCH_ARGS="--size 100000 --iter 50"
make dist
make check-dist

See make help for the complete target list.

License

MIT. See LICENSE.

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spork-pds 0.1.0

spork-pds

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Quick start

Native operators, persistent values

Batch updates with transients

Typed vectors and NumPy

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BLAKE2b-256	`d5c1a503f565b71556ef6ef2795fdc8298c861c962682c7aca166e662ebdef9e`

Algorithm	Hash digest
SHA256	`fe9a4de3da831e85174513722c4fea9e473658e2b3ec07aa5216e00448b9f0f4`
MD5	`e73e29ea856436a51862c256e1fd2508`
BLAKE2b-256	`bb876a49fd009e0bd55a44bb5408838ea1717206ff87be7c4ebf7ab7adbf59c4`

Algorithm	Hash digest
SHA256	`35d84110f479c1083e5789b5f4ec9434c047b6ca9f6c26e1559d39daa3376a8f`
MD5	`22e3aaaef437373e47cc523c0ac3dc5e`
BLAKE2b-256	`326480451c8373641f8ae0e78a53bcb9209db85b20549ea70574f6c7d29cadd1`

Algorithm	Hash digest
SHA256	`61bb2a810e9228ec866498df2ee661da5c5779d57d540176abd811b0352be710`
MD5	`10878fe3b5a02f39324794c3e6ea3a7f`
BLAKE2b-256	`dad22c0c35374d0ccc13c8011299fc9f526baca16f5e598ebe1be315292103fb`