import pandas as pd
from molvs import Standardizer
from rdkit import Chem

def standardize_smiles(smiles):
    mol = Chem.MolFromSmiles(smiles)
    if mol is None:
        return None
    std = Standardizer()
    try:
        std_mol = std.standardize(mol)
        return Chem.MolToSmiles(std_mol)
    except:
        return None

# Load and manually parse .txt file
data = []
with open("EDC_data.txt", "r") as f:
    for line in f:
        parts = line.strip().split()
        if len(parts) < 6:
            continue  # skip malformed lines
        sample_id = parts[0]
        smiles = parts[1]
        name = parts[3]
        label = parts[-2]  # sometimes it's merged, so this may need refining
        source = parts[-1]
        data.append((sample_id, smiles, name, label, source))

df = pd.DataFrame(data, columns=["id", "smiles", "name", "label", "source"])

# Sanitize
df["standardized_smiles"] = df["smiles"].apply(standardize_smiles)
df.dropna(subset=["standardized_smiles"], inplace=True)

# Save
df.to_csv("EDC_data_sanitized.csv", index=False)