SimpliPy:
Efficient Simplification of Mathematical Expressions

PyPI version PyPI license Documentation Status

pytest quality checks CodeQL Advanced

Publications

  • Saegert & Köthe 2026, Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression (preprint, under review) https://arxiv.org/abs/2602.08885

Usage

pip install simplipy

The compiled Rust extension (simplipy._core) is required: the inline phase (simplify, conversions, validation) runs on it exclusively, and there is no pure-Python fallback. Prebuilt wheels are published for Linux (x86_64/aarch64), macOS (x86_64/arm64) and Windows (x64) on CPython ≥ 3.11, so pip install simplipy does not compile anything for most users. Installing from the source distribution (an unsupported platform, or --no-binary) requires a Rust toolchain (rustup, MSRV 1.83). If the extension is missing at runtime, constructing an engine raises ImportError.

import simplipy as sp

engine = sp.SimpliPyEngine.load("4-3", install=True)   # a published ruleset artifact

# Simplify prefix expressions
engine.simplify(('/', '<constant>', '*', '/', '*', 'x3', '<constant>', 'x3', 'log', 'x3'))
# > ('/', '<constant>', 'log', 'x3')

# Simplify infix expressions
engine.simplify('x3 * sin(<constant> + 1) / (x3 * x3)')
# > '<constant> / x3'

Normalization

The root-exported normalize_skeleton, normalize_expression, and normalize_variable_token helpers (also available as simplipy.normalization) canonicalize a prefix token sequence so that two expressions that are "the same" up to variable renaming / constant values compare equal. They are pure-string helpers with no engine state, so consumers such as holdout matching and symbolic-recovery scoring share identical behavior by construction.

import simplipy as sp

# Skeleton form: variables -> x{n}, numeric literals -> <constant>
sp.normalize_skeleton(['+', 'v1', '2.5'])
# > ['+', 'x1', '<constant>']

# Expression form: variables canonicalized, numeric literals kept intact
sp.normalize_expression(['+', 'V1', '2.5'])
# > ['+', 'x1', '2.5']

# Classify / canonicalize a single token -> (normalized_token, is_variable)
sp.normalize_variable_token('X3')
# > ('x3', True)
sp.normalize_variable_token('sin')
# > ('sin', False)

More examples can be found in the documentation.

Performance

As of 0.6.0 the simplify hot path defers match-time certificates to completed matches (memoized generationally, never stopping memoization), memoizes whole fixpoint passes and rule-normal subtrees, and runs on interned token ids (~20× fewer allocations per call) — all at byte-identical outputs. On a 65,536-expression training-prior benchmark, large certificate-bearing rulesets simplify ~59× faster than 0.5.0 and certificate-free rulesets ~2.3× faster; see the CHANGELOG for details. Since 0.7.0 there is a single compiled engine line; the published ruleset artifacts (2-1, 3-2, 4-3, …) are the distinguishing factor between engines. Rule application always considers every pattern in the loaded artifact (the former max_pattern_length knob was removed in 0.10.0). (To reproduce the historical dev_7-3 / v23.0-era behavior byte-for-byte, install simplipy<=0.6.0.)

Simplification time and ratio ECDFs: SimpliPy 0.9.1 vs SymPy across three axes (mined rulesets, safe vs aggressive, search budget) on 64k Lample-Charton expressions from the Flash-ANSR v23.0 prior

Empirical Cumulative Distribution Functions (ECDFs) of simplification wall-clock time (top row) and simplification ratio |simp| / |orig| in prefix tokens (bottom row, inset: zoom on the low-ratio tail), over 65,536 randomly generated Lample-Charton expressions sampled from the Flash-ANSR v23.0 training prior (0 to 17 unique variables, 1 to 35 symbols [Saegert & Köthe 2026]). Three axes vary SimpliPy (green) while SymPy [Meurer et al. 2017] (orange ratio=None / red ratio=1) is the fixed reference: Mined Rulesets — the published 2-1/3-2/4-3 artifacts, every pattern active (darker = larger); Safe vs Aggressive — 4-3 in the deployed SOUND mode vs the training-only LOSSY mode; Search Budget — 4-3 SOUND at node budgets 1 to 48. SimpliPy is timed per call (perf_counter, gc off); SymPy is given each <constant> as a free symbol and simplified symbolically inside a per-expression worker with a 1 s timeout, then scored by its native prefix length. The measured quantities are the two ECDFs; the plot, not this caption, reports what they show.

Development

Setup

To set up the development environment, run the following commands:

pip install -e .[dev]
pre-commit install

Tests

Test the package with pytest:

pytest tests --cov src --cov-report html

or to skip integration tests,

pytest tests --cov src --cov-report html -m "not integration"

Citation

@misc{saegert2026breakingsimplificationbottleneckamortized,
  title   = {Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression},
  author  = {Paul Saegert and Ullrich Köthe},
  year    = {2026},
  eprint  = {2602.08885},
  archivePrefix =  {arXiv},
  primaryClass  = {cs.LG},
  url     = {https://arxiv.org/abs/2602.08885},
}

% Optionally
@software{simplipy-2025,
    author = {Paul Saegert},
    title = {Efficient Simplification of Mathematical Expressions},
    year = 2026,
    publisher = {GitHub},
    version = {0.9.1},
    url = {https://github.com/psaegert/simplipy}
}

Project links

Data verified by PyPI on Jul 26, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.14.6)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for psaegert from gravatar.com psaegert

Credits

Author: Paul Saegert

GitHub Statistics

Data verified by PyPI on Jul 26, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.11

Provides Extra

dev torch

Tags

symbolic-regression simplification expression prefix rewriting rust

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

simplipy-0.10.1.tar.gz (1.8 MB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

simplipy-0.10.1-cp311-abi3-win_amd64.whl (884.5 kB view details)

Uploaded CPython 3.11+Windows x86-64

simplipy-0.10.1-cp311-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.0 MB view details)

Uploaded CPython 3.11+manylinux: glibc 2.17+ x86-64

simplipy-0.10.1-cp311-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (973.4 kB view details)

Uploaded CPython 3.11+manylinux: glibc 2.17+ ARM64

simplipy-0.10.1-cp311-abi3-macosx_11_0_arm64.whl (916.9 kB view details)

Uploaded CPython 3.11+macOS 11.0+ ARM64

simplipy-0.10.1-cp311-abi3-macosx_10_12_x86_64.whl (952.2 kB view details)

Uploaded CPython 3.11+macOS 10.12+ x86-64

File details

Details for the file simplipy-0.10.1.tar.gz.

File metadata

  • Download URL: simplipy-0.10.1.tar.gz
  • Upload date:
  • Size: 1.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for simplipy-0.10.1.tar.gz
Algorithm Hash digest
SHA256 092ea9db48c182a784ed0871fb791c81faf54ab9704dcc0610733dc24003c2e5
MD5 e87a674bbf58d0b5629ba042af9dc055
BLAKE2b-256 df09ef48aa3838005ab1a675aea3cb7d622b1f7c4772d364c7d377cd7ffa25ea

See more details on using hashes here.

Provenance

The following attestation bundles were made for simplipy-0.10.1.tar.gz:

Publisher: publish.yml on psaegert/simplipy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file simplipy-0.10.1-cp311-abi3-win_amd64.whl.

File metadata

  • Download URL: simplipy-0.10.1-cp311-abi3-win_amd64.whl
  • Upload date:
  • Size: 884.5 kB
  • Tags: CPython 3.11+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for simplipy-0.10.1-cp311-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 41cb1fdf8bf7b10fb967031f0b35a073018519349b6bc8182031661d13680fa0
MD5 e147122ef4cdbdff628cb6b3e7482b38
BLAKE2b-256 381186e8d70e52d3b78574a66d4a956fa71b371ce45a92328c7ab72902c2bbfe

See more details on using hashes here.

Provenance

The following attestation bundles were made for simplipy-0.10.1-cp311-abi3-win_amd64.whl:

Publisher: publish.yml on psaegert/simplipy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file simplipy-0.10.1-cp311-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for simplipy-0.10.1-cp311-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8d2f4fb9e9d1b32731e818ab3dcb9bb86e5851c865c2fd070a2307d73f599cdb
MD5 483208d652819466bf2f0d37d0587042
BLAKE2b-256 de8b91577f2e2d4a49ef8f0a6d901e14abd5065ecf6525e950b9797cf4a55a37

See more details on using hashes here.

Provenance

The following attestation bundles were made for simplipy-0.10.1-cp311-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: publish.yml on psaegert/simplipy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file simplipy-0.10.1-cp311-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for simplipy-0.10.1-cp311-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 dfcd01ab36e71535c57c7cc6eeebc19667a3a86a0ea665835f32d8e983872788
MD5 22ed441279963810e4f3872ae581d1e7
BLAKE2b-256 5a8eb12722529740a065e40392c3ff3836132c958d66352f1cfe587b7cc42e3c

See more details on using hashes here.

Provenance

The following attestation bundles were made for simplipy-0.10.1-cp311-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl:

Publisher: publish.yml on psaegert/simplipy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file simplipy-0.10.1-cp311-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for simplipy-0.10.1-cp311-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0b8b6c1ff0388e3f41c4c3195de258245c2cf005ed822804ceeb08ddf1643413
MD5 d25f8fe0aa4c33ab24ccfb37ebe861ae
BLAKE2b-256 8382adf47b6237ad475c426dd3f76d78511d17280dd3fec33e805cfd07195d78

See more details on using hashes here.

Provenance

The following attestation bundles were made for simplipy-0.10.1-cp311-abi3-macosx_11_0_arm64.whl:

Publisher: publish.yml on psaegert/simplipy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file simplipy-0.10.1-cp311-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for simplipy-0.10.1-cp311-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 1d28794e3513cc98ff52730b00068deb09f4a07655f2a94d384e74921ceab140
MD5 85f13d47770197ce5556739a3f84e4a1
BLAKE2b-256 4b60e815530db959ff3e6c115ddb27973a2a7cca189655ccf60d7f173555ce63

See more details on using hashes here.

Provenance

The following attestation bundles were made for simplipy-0.10.1-cp311-abi3-macosx_10_12_x86_64.whl:

Publisher: publish.yml on psaegert/simplipy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.14.6

6 files

0.14.5

6 files

0.14.4

6 files

0.14.2

6 files

0.14.1

6 files

0.14.0

6 files

0.13.1

6 files

0.13.0

6 files

0.12.0

6 files

0.11.0

6 files

This release

0.10.1 This release

6 files

0.10.0

6 files

0.9.1

6 files

0.9.0

6 files

0.8.0

6 files

0.7.1

6 files

0.7.0

6 files

0.4.2

6 files

0.4.1

6 files

0.4.0

6 files

0.3.1

6 files

0.3.0

6 files

0.2.15

2 files

0.2.14

2 files

0.2.13

2 files

0.2.12

2 files

0.2.11

2 files

0.2.10

2 files

0.2.9

2 files

0.2.8

2 files

0.2.7

2 files

0.2.6

2 files

0.2.5

2 files

0.2.4

2 files

0.2.3

2 files

0.2.2

2 files

0.2.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page