chematic

Pure-Rust cheminformatics library for Python — SMILES parsing, 190+ descriptor values (71 functions), fingerprints, pKa prediction, ADMET profiling, and template-based retrosynthesis.

Installation

pip install chematic

Quick Start

import chematic

mol = chematic.from_smiles("CC(=O)Oc1ccccc1C(=O)O")  # aspirin

print(mol.mw)      # 180.16
print(mol.logp)    # 1.31
print(mol.tpsa)    # 63.6
print(mol.qed)     # 0.55

# New descriptors
print(mol.vabc)              # van der Waals volume (no 3D needed)
print(mol.schultz_mti)       # Schultz MTI
print(mol.gutman_mti)        # Gutman MTI*
print(mol.gravitational_index)  # gravitational index

# pKa prediction
print(mol.pka())   # {"most_acidic": 3.49, "most_basic": None}

# ADMET profile
print(mol.admet())
# {"bbb": False, "bbb_score": ..., "caco2": ..., "herg_risk": ..., "cyp3a4_risk": ...}

# Fingerprints (bytes, 2048-bit ECFP4)
fp = mol.ecfp4()

# Tanimoto similarity
mol2 = chematic.from_smiles("c1ccccc1")
sim = chematic.tanimoto(mol.ecfp4(), mol2.ecfp4())

# Natural-language property summary (for LLM / MCP agents)
print(mol.describe())

# Structural diff between two molecules
ibuprofen = chematic.from_smiles("CC(C)Cc1ccc(CC(C)C(=O)O)cc1")
d = mol.diff(ibuprofen)  # {"summary": "...", "delta_mw": 66.1, "delta_logp": 2.75, ...}

# SVG / PDF / EPS depiction
svg = mol.to_svg()
pdf_bytes = mol.to_pdf()   # bytes; requires pdf feature
eps_str   = mol.to_eps()   # PostScript string

# ChemicalJSON (Avogadro 2 / MolSSI)
cjson_str = mol.to_cjson(coords=[])   # coords: list of (x,y,z) tuples, optional
mol2, coords = chematic.from_cjson(cjson_str)

# Template-based retrosynthesis (60 retro-SMIRKS templates)
mol3 = chematic.from_smiles("CC(=O)Nc1ccccc1")  # acetanilide
results = mol3.retro_disconnect(max_results=5)
for r in results:
    print(r["template"], "→", r["precursors"])
# amide_secondary → ['CC(=O)O', 'Nc1ccccc1']

# Filter by reaction class
amides = mol3.retro_disconnect(reaction_class="AmideBond")

# Bulk substructure match against a pre-parsed Mol list (returns indices)
mols = [chematic.from_smiles(s) for s in ["CCO", "c1ccccc1O", "CC(=O)O"]]
hits = chematic.bulk.substructure_match("[OH]", mols)  # → [0, 1, 2]

# All descriptors as a dict (for Pandas)
import pandas as pd
smiles = ["CCO", "c1ccccc1", "CC(=O)O"]
df = pd.DataFrame([chematic.from_smiles(s).descriptors() for s in smiles])

# Opt-in v2 embedding pipeline: torsion-knowledge-aware distance geometry +
# stereo verification/repair + policy-gated force field, with full per-stage
# evidence (never just final coordinates)
config = chematic.PipelineV2Config.safe(
    force_field="mmff94_with_uff_fallback",
    stereo_policy="repair_and_verify",
    ring_torsion_policy="fail_closed",
)
try:
    result = mol.embed_pipeline_v2(config)
    coords = result["coords"]                       # same atom order as mol
    print(result["force_field"]["actual_force_field_used"])  # fallback if MMFF94 lacked params
    print(result["final_validation"]["sound"])
except chematic.PipelineV2Error as e:
    print(e.diagnostics["stage"], e.diagnostics["cause"])   # structured, not just a message

Features

  • Zero C/C++ dependencies — pure Rust, no RDKit or OpenBabel required
  • SMILES / MOL / SDF / ChemicalJSON parsing and writing
  • 190+ descriptor values (71 functions; MQN returns 42 values, BCUT2D / autocorr2d / geary / moran return multi-value arrays): MW, LogP (±0.01, 96.5% of 4,999-mol ChEMBL subset), TPSA (±0.1 Ų, 98.1%), QED, Fsp3, SA Score, HBD (100% vs RDKit, incl. S-H), vabc, schultz_mti, gutman_mti, gravitational_index
  • 14 fingerprint algorithms: ECFP2/4/6, FCFP4/6, MACCS, AtomPair, Torsion, …
  • pKa prediction (15 SMARTS rules — unique to chematic)
  • ADMET profile: BBB, Caco-2, hERG, CYP3A4
  • Template-based retrosynthesis: mol.retro_disconnect() — 60 retro-SMIRKS templates, SA Score ranked
  • SMARTS substructure search — chematic.smarts_match() and bulk.substructure_match(smarts, mols) (pre-parsed Mol list, returns indices)
  • SVG / PDF / EPS depiction: mol.to_svg(), mol.to_pdf(), mol.to_eps()
  • ChemicalJSON: mol.to_cjson(coords=[]), chematic.from_cjson(s) — Avogadro 2 / MolSSI compatible
  • Opt-in v2 embedding pipeline: mol.embed_pipeline_v2(config) — torsion-knowledge-aware distance geometry, stereo verify/repair, and policy-gated force field (PipelineV2Config), returning full per-stage evidence (embed stats, torsion knowledge/optimization reports, stereo before/after, force-field actual policy and fallback, final geometry validation, stage timings) instead of just coordinates; raises chematic.PipelineV2Error with structured .diagnostics on failure

RDKit compatibility

chematic.rdkit_compat provides a lightweight RDKit-compatible subset for environments where RDKit is unavailable (WASM, serverless, conda-free CI):

from chematic import rdkit_compat as Chem
from chematic.rdkit_compat import Descriptors, rdMolDescriptors, DataStructs

mol = Chem.MolFromSmiles("CC(=O)Oc1ccccc1C(=O)O")

# Descriptors
Descriptors.MolWt(mol)          # 180.16
rdMolDescriptors.CalcTPSA(mol)  # 63.6

# Fingerprint (ExplicitBitVect) with bitInfo
bitInfo = {}
fp = rdMolDescriptors.GetMorganFingerprintAsBitVect(mol, 2, nBits=2048, bitInfo=bitInfo)
fp.GetNumBits()                         # 2048
bitInfo                                 # {bit: ((atom_idx, radius), ...)}
DataStructs.TanimotoSimilarity(fp, fp)  # 1.0
DataStructs.BulkTanimotoSimilarity(fp, [fp])  # [1.0]

import numpy as np
arr = DataStructs.ConvertToNumpyArray(fp)  # (2048,) int8 for sklearn / PyTorch

# Atom / Bond traversal
for atom in mol.GetAtoms():
    atom.GetSymbol(), atom.GetAtomicNum(), atom.IsInRing()
for bond in mol.GetBonds():
    bond.GetBondType(), bond.GetBondTypeAsDouble(), bond.IsInRing()

# Ring information
ri = mol.GetRingInfo()
ri.NumRings()       # 1
ri.AtomRings()      # tuple of tuples of atom indices
ri.NumAtomRings(0)  # rings containing atom 0

# SDF I/O with SD properties
with Chem.SDWriter("out.sdf") as w:
    mol.SetProp("ID", "aspirin")
    w.write(mol)
for m in Chem.SDMolSupplier("out.sdf"):
    print(m.GetProp("ID"))

Unsupported options raise NotImplementedError or TypeError — they are never silently ignored.

Compatibility matrix

Area Status Notes
SMILES I/O ✅ Supported MolFromSmiles (aromaticity perceived when sanitize=True) / MolToSmiles
SDF I/O ✅ Supported SDMolSupplier / SDWriter + SD properties
Mol properties ✅ Supported Get/Set/Has/ClearProp, typed setters, GetPropsAsDict
Mol / Atom / Bond ✅ Supported read-only traversal (GetAtoms/GetBonds/GetAtomWithIdx/…)
RingInfo ✅ Supported SSSR-based; NumRings/AtomRings/BondRings/NumAtomRings/NumBondRings
Substructure 🟡 Partial SMARTS via chematic; match order may differ from RDKit (use set comparison)
Descriptors ✅ Supported MW/HBA/HBD exact, TPSA ±1.0, LogP ±0.5 vs RDKit (differential-tested)
Morgan fingerprint 🟡 Partial nBits folding + bitInfo shape-/origin-consistent, not RDKit bit-identical (FNV-1a vs MurmurHash)
DataStructs ✅ Supported TanimotoSimilarity/DiceSimilarity/BulkTanimotoSimilarity/ConvertToNumpyArray
RWMol / editing ❌ Unsupported read-only layer
useFeatures, useBondTypes=False 🔊 Fails loudly raise NotImplementedError instead of silently ignoring

A live differential suite (tests/test_rdkit_diff.py, auto-skipped when RDKit is absent) compares chematic against RDKit across descriptors, ring counts, SMARTS match counts, SDF round-trips, and Morgan self-similarity, writing an explainable diff to validation/results/rdkit_diff.jsonl.

chematic.rdkit_compat is not a full RDKit clone — it is a lightweight RDKit-compatible subset for common 2D cheminformatics workflows. See the full RDKit migration guide (compatibility matrix, differential-validation results, known divergences, and runnable examples).

License

MIT OR Apache-2.0

Project links

Data verified by PyPI on Aug 31, 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 (1.0.5)

1 maintainer

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

GitHub Statistics

Data verified by PyPI on Aug 31, 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

Apache Software License, MIT License (MIT OR Apache-2.0)

Requires

Python >=3.9

Tags

cheminformatics smiles chemistry rdkit fingerprints drug-discovery molecular-descriptors wasm admet qed

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

chematic-0.46.0.tar.gz (4.0 MB view details)

Uploaded Source

Built Distributions

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

chematic-0.46.0-cp313-cp313-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.13Windows x86-64

chematic-0.46.0-cp313-cp313-macosx_11_0_arm64.whl (4.6 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

chematic-0.46.0-cp313-cp313-macosx_10_12_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.13macOS 10.12+ x86-64

chematic-0.46.0-cp312-cp312-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.12Windows x86-64

chematic-0.46.0-cp312-cp312-macosx_11_0_arm64.whl (4.6 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

chematic-0.46.0-cp312-cp312-macosx_10_12_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.12macOS 10.12+ x86-64

chematic-0.46.0-cp311-cp311-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.11Windows x86-64

chematic-0.46.0-cp311-cp311-macosx_11_0_arm64.whl (4.7 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

chematic-0.46.0-cp311-cp311-macosx_10_12_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.11macOS 10.12+ x86-64

chematic-0.46.0-cp310-cp310-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.10Windows x86-64

chematic-0.46.0-cp310-cp310-macosx_11_0_arm64.whl (4.7 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

chematic-0.46.0-cp310-cp310-macosx_10_12_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.10macOS 10.12+ x86-64

chematic-0.46.0-cp39-cp39-win_amd64.whl (4.9 MB view details)

Uploaded CPython 3.9Windows x86-64

chematic-0.46.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

chematic-0.46.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (4.8 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ ARM64

chematic-0.46.0-cp39-cp39-macosx_11_0_arm64.whl (4.7 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

chematic-0.46.0-cp39-cp39-macosx_10_12_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.9macOS 10.12+ x86-64

File details

Details for the file chematic-0.46.0.tar.gz.

File metadata

  • Download URL: chematic-0.46.0.tar.gz
  • Upload date:
  • Size: 4.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for chematic-0.46.0.tar.gz
Algorithm Hash digest
SHA256 3a75bd49f35f68ceb374c27bdc9a4258f90fdd75c53607b4edb7e4f2b542a0f7
MD5 ec778d5a165c80c4e92b7dd3e6c8d72a
BLAKE2b-256 d6eca0955c6b45e55a1b3e61ba69292b25be7cf5f0fe2a3f8d64468aa8e07623

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0.tar.gz:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: chematic-0.46.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 4.9 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for chematic-0.46.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 8142bcde4716962edbb4b0fe4f307947ac91a339a8a9af0c149a9d2be0dac455
MD5 7960d8b8148ae5f3264d2f1a850bcf85
BLAKE2b-256 a44b6aba436d9ce4564e601339e300d1ce43c41d2c1a6f99bae071855772d38a

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp313-cp313-win_amd64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 24f64022a05167bd62ba3631114ecdf786e3e664c01c30cbaceb804062a1423d
MD5 d18629bac504005c10391c300a980598
BLAKE2b-256 a2e8d4ea8f5899fcfb8dfd8dca725fea375e429c79ba0549cfda563977e2102a

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp313-cp313-macosx_11_0_arm64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp313-cp313-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp313-cp313-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 f69a6335196d269fb1ecbbc135f3af13d7857b229e433dcf0b954c7a3b023088
MD5 86de207a05ccd047fd51843e8019ef6a
BLAKE2b-256 04ac1af7790fa06ffc2aec7b02878b58b191f844a6e6987c482dbdd1816dc579

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp313-cp313-macosx_10_12_x86_64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: chematic-0.46.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 4.9 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for chematic-0.46.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 c2d6617abad0f3d3ceb9519159322b3d3a31348412d77a910886251315acf209
MD5 00dcb4c123f53391dd217f52191c9969
BLAKE2b-256 9df15f9acc976c6d39c1bb67df0a97948849252a1ec04a875546a647df874d6c

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp312-cp312-win_amd64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7540e96c055b4574bcee8b2798e8dbfc1bee08d371d98d492b477e39851cf6a7
MD5 381a9e3d4d1dd40997553ac5bb549ce7
BLAKE2b-256 a79fd55908bcbc15e914d74f24fa1579b9ae3a479afc17b2377be1695ed3cc26

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp312-cp312-macosx_11_0_arm64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp312-cp312-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp312-cp312-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 f00dcf6b8bb89e5411d8292dae9abef4300dcc703034b4abe71807cd10048d4b
MD5 4f5a09d5b40cd628f64ed635939f1d56
BLAKE2b-256 f51901f07193eb2da27ac6be398ba8f95db1c3b720a42df633db88c359735c98

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp312-cp312-macosx_10_12_x86_64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: chematic-0.46.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 4.9 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for chematic-0.46.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 37d6305cc2acf6e420aafd79b0d49b1cf2cc8c2b26b55a3192496cc98a3b618b
MD5 47a8b4adaed4b5ad72fc6fe6d26aa354
BLAKE2b-256 c074531fdbcbafe050afda7ed527961be333656211e91593de45a6c609dae390

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp311-cp311-win_amd64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 66a945f29f7f29cacb3a26dc8ff68a1effc532b2a1b0867c1de69a51fe9e43a2
MD5 c6df1a805905a6538e00ce3c1b9c2286
BLAKE2b-256 d99c5fc7773b7db3035789613e8720d4d19aa9e610c15265529381e1b4258490

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp311-cp311-macosx_11_0_arm64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp311-cp311-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp311-cp311-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 b34fd012e0162457213fd4ba6422ae954de6b0d96823095ca8cd4b6096dab012
MD5 588ce7e70ea371a3a83aa3351cefeb53
BLAKE2b-256 4652e3fe1fde49fa7748fe78ec714ba5344a2021ac3522686769232e060ce5b6

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp311-cp311-macosx_10_12_x86_64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: chematic-0.46.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 4.9 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for chematic-0.46.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 1e46c1dabe102614bc0c1a6e093b24032c6194979ab01eabf4060a3c6e3bead8
MD5 406676d68803b523643dc5b4d1fc9858
BLAKE2b-256 339bd101a5ad18263a296254ce324bdc0a59daf914252a7ffeeef298bf402248

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp310-cp310-win_amd64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7e97db5fd6b48f5511b84c5d37fa1efa6eac2b4d748b65c54e7575f77f60d0cc
MD5 a15496393e1e6199660a9a6186566d3e
BLAKE2b-256 2d1f7156d8de7eb110af228bdc52280d44586b92861a4ea8b5eecd0f6c4e8ca8

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp310-cp310-macosx_11_0_arm64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp310-cp310-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp310-cp310-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 54007dfc5cd4a1e36bcf29f8288a881cefcc9536ca0400dc6c12474f17ec242b
MD5 8e8f59c5b841efa4c74dad3c84d2420b
BLAKE2b-256 5f1c598bea8d6c0e1cf214068e0592316764e49ad3f371b3057b61b94a38513e

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp310-cp310-macosx_10_12_x86_64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: chematic-0.46.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 4.9 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for chematic-0.46.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 7b20525dcefc392295de7f7dabab9186511598e548797c0347f881a14e82c31e
MD5 a35183e2bbe31698edd08280a9620046
BLAKE2b-256 c6998621e25a5923b43efb41724cc17c214af5b219defb4c8d0e1758cad3bae6

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp39-cp39-win_amd64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 481800d154b4592f53e819fd78b77faf644d18ff84653375aa8fce55e1a93f15
MD5 29363c3370c76d5d69f8572fa6e2e135
BLAKE2b-256 914b8ed19de65d5d261620b866278254f3679e1fe1c6242783d19c7593e36611

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 6a15a8eb4cfe0ce3beb02d2d357b1562c23aa4f26f82a76a44b46e9341f136c8
MD5 a271b65b26425ae44855057cc4013a66
BLAKE2b-256 eed0d6dba0a033a03eaf66ecc9e28fb08ae4b5466819896ca3cc36a5d28772da

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8d406eb0acd592a12615bc289edea8f236507db976895ffa7a5c4f6670931e10
MD5 5b51395ea4df9c2a165477f1560a011e
BLAKE2b-256 3912d6f453b500f096041e0e69d66b3bd51be263032eabea836a76508533b4ca

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp39-cp39-macosx_11_0_arm64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

File details

Details for the file chematic-0.46.0-cp39-cp39-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for chematic-0.46.0-cp39-cp39-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 13fcb45d475ede07eb42b94cec2afbb67e503b680b196e6e4fba0e416d72da9c
MD5 a05560fe1a7d59a295dd73604d0b20fa
BLAKE2b-256 5a0b2de0f3549a2d970a51bc95b138104f2c83d3cba0deba701b169afbec06df

See more details on using hashes here.

Provenance

The following attestation bundles were made for chematic-0.46.0-cp39-cp39-macosx_10_12_x86_64.whl:

Publisher: publish-pypi.yml on kent-tokyo/chematic

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

Release history Release notifications | RSS feed

1.0.5

18 files

1.0.4

18 files

1.0.3

18 files

1.0.2

18 files

1.0.1

18 files

1.0.0

18 files

0.89.0

18 files

0.49.0

18 files

0.48.0

18 files

0.47.0

18 files

This release

0.46.0 This release

18 files

0.45.0

18 files

0.44.0

18 files

0.43.0

18 files

0.42.0

18 files

0.41.0

18 files

0.40.0

18 files

0.39.0

18 files

0.38.0

18 files

0.37.0

18 files

0.36.0

18 files

0.35.0

18 files

0.34.0

18 files

0.33.0

18 files

0.31.0

18 files

0.30.0

18 files

0.29.0

18 files

0.28.0

18 files

0.27.0

18 files

0.26.0

18 files

0.25.0

18 files

0.24.0

18 files

0.23.0

18 files

0.22.0

18 files

0.21.0

18 files

0.20.1

18 files

0.20.0

18 files

0.19.0

18 files

0.18.0

18 files

0.17.0

18 files

0.16.0

18 files

0.15.0

18 files

0.14.1

18 files

0.14.0

18 files

0.13.0

18 files

0.12.0

18 files

0.11.0

18 files

0.10.0

18 files

0.9.0

18 files

0.8.1

18 files

0.8.0

18 files

0.7.0

18 files

0.6.0

18 files

0.5.0

18 files

0.4.30

18 files

0.4.29

18 files

0.4.28

18 files

0.4.22

18 files

0.4.21

18 files

0.4.20

18 files

0.4.19

18 files

0.4.18

18 files

0.4.17

18 files

0.4.16

18 files

0.4.15

18 files

0.4.14

18 files

0.4.9

18 files

0.4.8

18 files

0.4.7

18 files

0.4.6

6 files

0.4.5

6 files

0.4.4

6 files

0.4.0

6 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