asedb 0.0.1

Description:

asedb 0.0.1

ASE DB
This package provides a SQL Alchemy model
to the ASE Atoms object.
For more information, see the documentation.
Basic Usage
The AtomsModel is the main model that translates an atoms object (and attached calculator info) into
a SQL model.
from asedb import AtomsModel, Element, initialize_engine, make_sqlite_engine
import ase
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine


engine = make_sqlite_engine("foo.db") # Helper function to create a SQL Alchemy engine for sqlite
initialize_engine(engine) # Create necessary schema/tables

Session = sessionmaker(bind=engine)
session = Session()

atoms = ase.Atoms('H2',
positions=[[0, 0, 0],
[0, 0, 0.7]])

model = AtomsModel.from_atoms(atoms)

session.add(model)
session.commit()

model_id = model.id

loaded = session.query(AtomsModel).where(AtomsModel.id == model_id).scalar()
atoms_loaded = loaded.to_atoms() # The atoms object loaded from the database

print(atoms_loaded) # Atoms(symbols='H2', pbc=False, tags=...)

Here, we used the make_sqlite_engine helper function to create the SQL Alchemy engine
object for a sqlite database. You can also create your own engine, e.g. for postgres:
import urllib.parse
from sqlalchemy import create_engine

def make_engine():
database = os.environ["PG_DATABASE"]
user = os.environ["PG_USER"]
password = urllib.parse.quote_plus(os.environ["PG_PASSWORD"])
host = os.environ["PG_HOST"]
port = os.environ["PG_PORT"]
connection_string = (
f"postgresql+psycopg2://{user}:{password}@{host}:{port}/{database}"
)
return create_engine(connection_string)

where the parameters for the connection parameters have been stored in the environment variables.
Querying
We can construct queries using the SQL Alchemy models, e.g. looking for all atoms objects with at least 2 hydrogen atoms:
# Fetch all AtomsModel objects that fit the query
results = (session.query(AtomsModel)
.join(Element)
.where((Element.symbol == 'H') & (Element.count >= 2))
.all())
# Convert them into actual Atoms objects
all_atoms = [res.to_atoms() for res in results]

Schema
By default, the schema asedb is used - except for sqlite databases, which doesn't
utilize schemas. In this case, the make_sqlite_engine helper function ensures
the schema is remapped to None.
For any "real" database connections, such as Postgres, the schema asedb will be used.