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A lightweight SMILES reader and writer

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pysmiles: The lightweight and pure-python SMILES reader and writer

This is a small project I started because I couldn't find any SMILES reader or writer that was easy to install (read: Python only). Currently, the writer is extremely basic, and although it should produce valid SMILES they won't be pretty, but see also issue #17. The reader is in a better state, and should be usable.

SMILES strings are assumed to be as specified by the OpenSmiles standard.


Molecules are depicted as Networkx graphs. Atoms are the nodes of the graph, and bonds are the edges. Nodes can have the following attributes:

  • element: str. This describes the element of the atom. Defaults to '*' meaning unknown.
  • aromatic: bool. Whether the atom is part of an (anti)-aromatic system. Defaults to False.
  • isotope: float. The mass of the atom. Defaults to unknown.
  • hcount: int. The number of implicit hydrogens attached to this atom. Defaults to 0.
  • charge: int. The charge of this atom. Defaults to 0.
  • class: int. The "class" of this atom. Defaults to 0.

Edges have the following attributes:

  • order: Number. The bond order. 1.5 is used for aromatic bonds. Defaults to 1.

There is currently no way of specifying stereo chemical information, and this is discarded upon reading. Somewhere in the future this will probably be stored in the "stereo" attribute of nodes.

Reading SMILES

The function read_smiles(smiles, explicit_hydrogen=False, zero_order_bonds=True, reinterpret_aromatic=True) can be used to parse a SMILES string. It should not be used to validate whether a string is a valid SMILES string --- the function does very little validation whether your SMILES string makes chemical sense. Edges in the created molecule will always have an 'order' attribute. Nodes will have the relevant attributes in so far they are specified. Atoms for which the element is not known (*) will not have an element attribute.

  • explicit_hydrogen determines whether hydrogen atoms should be represented as explicit nodes in the created molecule, or implicit in the 'hcount' attribute.
  • zero_order_bonds determines whether zero-order bonds (.) in the SMILES string should result in edges in the produced molecule.
  • reinterpret_aromatic determines whether aromaticity should be reinterpreted, and determined from the constructed molecule, or whether the aromaticity specifications from the SMILES string (lower case elements) should be taken as leading. If True, will also set bond orders to 1 for bonds that are not part of an aromatic ring and have a bond order of 1.5. If False, will create a molecule using only the information in the SMILES string.

Stereochemical information

Currently the library cannot handle stereochemical information, neither E/Z nor R/S. Any stereochemical information that was in the SMILES string will be discarded upon parsing. This means there will be no difference between parsing e.g. N[C@](Br)(O)C, N[C@@](Br)(O)C and NC(Br)(O)C. Parsing these will result in the same molecule. The same holds for e.g. F/C=C/F and FC=CF. These will result in the same molecule.

Whenever stereochemical information is being discarded a warning will be logged using the built-in logging module. If you want to disable all the messages logged by pysmiles you can add the following snippet to your code, without interfering with any logging by your own code:

import logging
logging.getLogger('pysmiles').setLevel(logging.CRITICAL)  # Anything higher than warning

Writing SMILES

The function write_smiles(molecule, default_element='*', start=None) can be used to write SMILES strings from a molecule. The function does not check whether your molecule makes chemical sense. Instead, it writes a SMILES representation of the molecule you provided, and nothing else.

  • default_element is the element to use for nodes that do not have an 'element' attribute.
  • start is the key of the node where the depth first traversal should be started. Something clever is done if not specified.

Additional functions

In addition to these two core functions, four more functions are exposed that can help in creating chemically relevant molecules with minimal work.

  • fill_valence(mol, respect_hcount=True, respect_bond_order=True, max_bond_order=3) This function will fill the valence of all atoms in your molecule by incrementing the 'hcount' and, if specified, bond orders. Note that it does not use 'charge' attribute to find the correct valence.
    • repect_hcount: bool. Whether existing hcounts can be overwritten.
    • respect_bond_order: bool. Whether bond orders can be changed
    • max_bond_order: int. The maximum bond order that will be set.
  • add_explicit_hydrogens(mol) This function transforms implicit hydrogens, specified by 'hcount' attributes, to explicit nodes.
  • remove_explicit_hydrogens(mol) This function does the inverse of add_explicit_hydrogens: it will remove explicit hydrogen nodes and add them to the relevant 'hcount' attributes.
  • correct_aromatic_rings(mol) This function marks all (anti)-aromatic atoms in your molecule, and sets all bonds between (anti)-aromatic atoms to order 1.5. It fills the valence of all atoms (see also fill_valence) before trying to figure our which atoms are aromatic. It works by first finding all atoms that are in a ring. Next, for every atom in every ring it is checked whether the atoms are sp2 hybridized (note that this is a vague term. Strictly speaking we check whether their element is something that could be aromatic, and whether they have 2 or 3 bonds.). Finally, the number of electrons per ring is counted, and if this is even, the atoms in the ring are said to be aromatic. This function is the most fragile in the whole library, and I expect it to produce wrong answers in some cases. In particular for fused (aromatic) ring systems (such as indole) and rings with extracyclic heteroatoms (O=C1C=CC=C1). Buyer beware.



from pysmiles import read_smiles

smiles = 'C1CC[13CH2]CC1C1CCCCC1'
mol = read_smiles(smiles)

# [(0, 'C'),
#  (1, 'C'),
#  (2, 'C'),
#  (3, 'C'),
#  (4, 'C'),
#  (5, 'C'),
#  (6, 'C'),
#  (7, 'C'),
#  (8, 'C'),
#  (9, 'C'),
#  (10, 'C'),
#  (11, 'C')]
# [(0, 2),
#  (1, 2),
#  (2, 2),
#  (3, 2),
#  (4, 2),
#  (5, 1),
#  (6, 1),
#  (7, 2),
#  (8, 2),
#  (9, 2),
#  (10, 2),
#  (11, 2)]

mol_with_H = read_smiles(smiles, explicit_hydrogen=True)
# [(0, 'C'),
#  (1, 'C'),
#  (2, 'C'),
#  (3, 'C'),
#  (4, 'C'),
#  (5, 'C'),
#  (6, 'C'),
#  (7, 'C'),
#  (8, 'C'),
#  (9, 'C'),
#  (10, 'C'),
#  (11, 'C'),
#  (12, 'H'),
#  (13, 'H'),
#  (14, 'H'),
#  (15, 'H'),
#  (16, 'H'),
#  (17, 'H'),
#  (18, 'H'),
#  (19, 'H'),
#  (20, 'H'),
#  (21, 'H'),
#  (22, 'H'),
#  (23, 'H'),
#  (24, 'H'),
#  (25, 'H'),
#  (26, 'H'),
#  (27, 'H'),
#  (28, 'H'),
#  (29, 'H'),
#  (30, 'H'),
#  (31, 'H'),
#  (32, 'H'),
# (33, 'H')]


import networkx as nx
from pysmiles import write_smiles, fill_valence

mol = nx.Graph()
mol.add_edges_from([(0, 1), (1, 2), (1, 3), (3, 4), (1, 5), (3, 6)])
for idx, ele in enumerate('CCCCOCO'):
    mol.nodes[idx]['element'] = ele
mol.nodes[4]['charge'] = -1
mol.nodes[4]['hcount'] = 0
mol.edges[3, 6]['order'] = 2

# [O-]C(=O)C([C])([C])[C]
fill_valence(mol, respect_hcount=True)
# [O-]C(=O)C(C)(C)C


  • The writer produces non-recommended SMILES strings (as per OpenSmiles).
  • The writer is better described as a "serializer": if the graph provided doesn't make chemical sense the produced "SMILES" string will be an exact representation of that graph. Because of this, the SMILES string will be invalid though.
  • fill_valence does not use 'charge' to find the correct valence.
  • correct_aromatic_rings is fragile.
  • There is currently no way of specifying stereo chemical information. The parser can deal with it, but it will be discarded.
  • It only processes SMILES. This might later be extended to e.g. InChi, SLN, SMARTS, etc.


Similar projects

There are more python projects that deal with SMILES, and I try to list at least some of them here. If yours is missing, feel free to open up a PR.

  • PySMILE: A similar named project, capable of encoding/decoding SMILE format objects. Doesn't deal with SMILES.
  • RDKit: A collection of cheminformatics and machine-learning software, capable of reading and writing SMILES, InChi, and others.
  • OpenEye Chem toolkit: The OpenEye chemistry toolkit is a programming library for chemistry and cheminformatics. It is capable of dealing with (canonical) SMILES and InChi.


PySmiles is distributed under the Apache 2.0 license. Copyright 2018 Peter C Kroon

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
See the License for the specific language governing permissions and
limitations under the License.

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