SMILES to PDF And Back

PDF Parsing is going to be handling by a separate package called MolPDF. It has pretty much a fixed template and is used for handling data distribution quickly so we can get a general feel of a molecule list.

GitHub - Sulstice/molpdf: Convert SMILES to PDF 2D Skeletal Diagrams and back again.GitHub

The philosophy is very simple. We don't really need a template but a simple PDF document to transfer data quickly especially in the case of a supplementary information. We use the meta data stored in the PDF to store the SMILES in accordance with the images. That way it makes it easier to mine the data quickly into a python object.

Imports

from global_chem import GlobalChem
from global_chem_extensions import GlobalChemExtensions

gc = GlobalChem()
cheminformatics = GlobalChemExtensions().cheminformatics()

SMILES to PDF

Code

smiles_list = list(gc.get_node_smiles('pihkal').values())

cheminformatics.smiles_to_pdf(
    smiles=smiles_list,
    labels = [],
    file_name = 'molecules.pdf',
    include_failed_smiles = True,
    title = 'MY MOLECULES',
)

Output

Method: 'generate' Time: 4.98 seconds

PDF to SMILES

Code

molecules = cheminformatics.pdf_to_smiles(
    'molecules.pdf',
)

print (len(molecules))