chematic
Pure-Rust cheminformatics library for Python — SMILES parsing, 190+ descriptor values (71 functions), fingerprints, pKa prediction, ADMET profiling, and template-based retrosynthesis.
The 1.0.27 Python wheel retains the atom-output and source-atom provenance APIs, corrected RDKit-compatible HBA profile, and plain-SMILES ring-closure writer fix introduced in v1.0.25. The new caller-managed atom tags are a Rust API; they are not exposed as a Python feature in this release. Compatibility and performance claims remain operation- and corpus-scoped.
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 (70+ functions; several return vectors): MW,
LogP, TPSA, QED, Fsp3, SA Score, HBD,
vabc,schultz_mti,gutman_mti, andgravitational_index. RDKit agreement is metric-specific; see the validation report. - 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()andbulk.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; raiseschematic.PipelineV2Errorwith structured.diagnosticson failure
RDKit compatibility
The operation/profile boundaries and measured oracle lanes are listed in the Compatibility Contract dashboard. For persisted fingerprints, saved indices, canonical identity, stereo, and browser/Worker migration decisions, read the RDKit migration guide before changing a production workflow. Native ECFP and RDKit-compatible Morgan are separate profiles; rebuild stored fingerprints and indices under the chosen profile.
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
1 maintainer
Metadata
1 maintainer
Release files for chematic 1.0.35
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| chematic-1.0.35.tar.gz | 4.3 MB | Details |
Built distributions (wheels)
Total release size: 100.9 MB
Release files / chematic-1.0.35.tar.gz
| Download URL | chematic-1.0.35.tar.gz |
|---|---|
| Size | 4.3 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
190b89ebc67e5d22d985914f8f2351c5322a617840fddce771bf4f88743bea5f
|
|
BLAKE2b-256 checksum How to use checksums |
da14eb2e879392a0c9bea57ce7805dc5450de8c1cacb10e827f1cc7cb67b0834
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp313-cp313-win_amd64.whl
| Download URL | chematic-1.0.35-cp313-cp313-win_amd64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.13 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
effe68c172d67317eea8b487a6db7057a5d880882bc0cc9dbd7c569c903ccfe9
|
|
BLAKE2b-256 checksum How to use checksums |
028e37b83e8d532aa6eb18ec821bff7388fa39c0b4a2e0ea4856f5bec94de2ca
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp313-cp313-macosx_11_0_arm64.whl
| Download URL | chematic-1.0.35-cp313-cp313-macosx_11_0_arm64.whl |
|---|---|
| Size | 5.5 MB |
| Tags | CPython 3.13 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
85e3dfaaacce74028c57127f3339ed8b87eaf0baf1d292ee1e5e8990049eaa77
|
|
BLAKE2b-256 checksum How to use checksums |
835fe2ebd76ac4258bfddc79773c46b0744b3f99f9efa823cc434fbe82d766d7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp313-cp313-macosx_10_12_x86_64.whl
| Download URL | chematic-1.0.35-cp313-cp313-macosx_10_12_x86_64.whl |
|---|---|
| Size | 5.8 MB |
| Tags | CPython 3.13 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
e80e2aa4bba02195dcf0f33cc88f42dfa3af80ae0a639a43ccea4e08fba62c77
|
|
BLAKE2b-256 checksum How to use checksums |
2969da2a82de4feeea9014bf2d42d6e3d5054d6e01f60e6c853e3778da242e60
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp312-cp312-win_amd64.whl
| Download URL | chematic-1.0.35-cp312-cp312-win_amd64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.12 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
b576b3ab083c654f002033efb0995698d6f8fd307fa1aa90926eeb5d11c480d5
|
|
BLAKE2b-256 checksum How to use checksums |
373834faae0fe3885b357908961f3e2b2b8cff60f813bed7f16ba15673fe8e4c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp312-cp312-macosx_11_0_arm64.whl
| Download URL | chematic-1.0.35-cp312-cp312-macosx_11_0_arm64.whl |
|---|---|
| Size | 5.5 MB |
| Tags | CPython 3.12 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
34567e232988641f6633b9b6416828b61c2308c2dcb92a0b99d36d943d192d0f
|
|
BLAKE2b-256 checksum How to use checksums |
25525b4ec9539c9e1913dddc075e1d4cc147477309f409fae9a232753d5a6d3f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp312-cp312-macosx_10_12_x86_64.whl
| Download URL | chematic-1.0.35-cp312-cp312-macosx_10_12_x86_64.whl |
|---|---|
| Size | 5.8 MB |
| Tags | CPython 3.12 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
fe305e2f62285c85047d7e29e7402c2428879ce0c8582056f70d62bcaf4d1bbc
|
|
BLAKE2b-256 checksum How to use checksums |
fe8d66ea1cce73a45e94453cb24f3006aee5690ecbae6530f381843dd4b56ae9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp311-cp311-win_amd64.whl
| Download URL | chematic-1.0.35-cp311-cp311-win_amd64.whl |
|---|---|
| Size | 5.8 MB |
| Tags | CPython 3.11 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
d1b8ce3ffb1d8580d283bf53152d28ab5847bdb14bf44b775f127a1c8f36c98d
|
|
BLAKE2b-256 checksum How to use checksums |
e57997b6c817e9b814ec0e6d4f53d7bcb3bebd8281018d797f3afe8800f61c02
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp311-cp311-macosx_11_0_arm64.whl
| Download URL | chematic-1.0.35-cp311-cp311-macosx_11_0_arm64.whl |
|---|---|
| Size | 5.5 MB |
| Tags | CPython 3.11 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
ce647b90352e344b2b9d55c5672a7e3ac6ceb79b629dca639b656c538d339815
|
|
BLAKE2b-256 checksum How to use checksums |
9a170e351b255fe81fd9a6f2534ded2782cdae3a55b66a369af04df3983fd99d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp311-cp311-macosx_10_12_x86_64.whl
| Download URL | chematic-1.0.35-cp311-cp311-macosx_10_12_x86_64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.11 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
ec4b1a7f4c36830bd781cd71f61c43704528ce4e718e5e339590d32a1bcf3efd
|
|
BLAKE2b-256 checksum How to use checksums |
06cc2a1cdd157e34e3ad587e7bff2dda26c49f3fa791964978dbde9b23c89e86
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp310-cp310-win_amd64.whl
| Download URL | chematic-1.0.35-cp310-cp310-win_amd64.whl |
|---|---|
| Size | 5.8 MB |
| Tags | CPython 3.10 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
449b315fda2dde6445b6c918ba8866f1394ff713a2c53606b1378c207cb1a1b2
|
|
BLAKE2b-256 checksum How to use checksums |
54f9c725387503a08bcce5aecc8a462bfff93e825a474be9848a578b37784ed3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | chematic-1.0.35-cp310-cp310-macosx_11_0_arm64.whl |
|---|---|
| Size | 5.5 MB |
| Tags | CPython 3.10 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
ab2daaad6029c198b62b4c433fa83124d4851c64648b6f0ed7c643d640ead804
|
|
BLAKE2b-256 checksum How to use checksums |
435bb340c2cd3ed697c898c923f1e3e457d2dfebf7bf5bf8d442488cbee62701
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp310-cp310-macosx_10_12_x86_64.whl
| Download URL | chematic-1.0.35-cp310-cp310-macosx_10_12_x86_64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.10 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
33cab9a29b44eddf17716448856ab61770836fed3197b41e9bc341bb7aacf6a8
|
|
BLAKE2b-256 checksum How to use checksums |
0a8ead1b75606edf4837fef477c67ad57532df33d06a3c1a4fb6f9b73bedaa84
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp39-cp39-win_amd64.whl
| Download URL | chematic-1.0.35-cp39-cp39-win_amd64.whl |
|---|---|
| Size | 5.8 MB |
| Tags | CPython 3.9 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
96067da355d9def3f7b4d700801ef36759ef6306efb0bdf47b3ed0231298e5f6
|
|
BLAKE2b-256 checksum How to use checksums |
060067ddd7304ab29a71f99c439bc9dba522b7ac1593e969325095c116db6ec3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | chematic-1.0.35-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
|---|---|
| Size | 6.0 MB |
| Tags | CPython 3.9 Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
79eca3a930f21c0afd1fd9faac98b7997d4c2af815700a7574c0a3f0b9061f64
|
|
BLAKE2b-256 checksum How to use checksums |
87bef167d51c1d0f72b841912fdee3b2a8d3c6fd5c8f3c2056470c46cccbf031
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | chematic-1.0.35-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.9 Linux glibc 2.17+ ARM64 |
|
SHA-256 checksum How to use checksums |
57ee53c66acd9077b6e1df7b6c07ae730f4694e9d48655a6262b9ab3f555c898
|
|
BLAKE2b-256 checksum How to use checksums |
f4a8e528bcd36f7d853af98632e40530c0c87b4b2c4ffde7356bbc107592dade
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp39-cp39-macosx_11_0_arm64.whl
| Download URL | chematic-1.0.35-cp39-cp39-macosx_11_0_arm64.whl |
|---|---|
| Size | 5.5 MB |
| Tags | CPython 3.9 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
83f7580d8c48cb0f5cb02de1c3f3ee3b4614e5b50ad07913b2f081c11a5dc720
|
|
BLAKE2b-256 checksum How to use checksums |
4eca5b3b9b40783420da219b6a17f1b9bdef5e592ade2f71b727e986575f0e84
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency logRelease files / chematic-1.0.35-cp39-cp39-macosx_10_12_x86_64.whl
| Download URL | chematic-1.0.35-cp39-cp39-macosx_10_12_x86_64.whl |
|---|---|
| Size | 5.7 MB |
| Tags | CPython 3.9 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
f8f3bf724b284bc6ea2019071c2077669d2ccec7eaff6dcfac15c6d3c95e06c5
|
|
BLAKE2b-256 checksum How to use checksums |
673e54d99a93a30b77568bbb41024858af4a50dad500c7b2ca49c19f3f9c7847
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 5, 2026.
Transparency log
