I'm making a project where I need to create a class instance which has methods which connect to a db and fetch data from it (I'm using SQLite as a backend).
I've had some experience with flask-sqlalchemy, but I'm lost when it comes to pure SQLAlchemy.
The concept is as follows:
User creates an instance of DataSet, and passes a path to the database as an __init__ parameter. If the database already exists, I would like just to connect to it and do queries, if it doesn't, I want to create a new one using a model. But I can't understand how to do so.
Here's the DataSet code:
from os.path import normcase, split, join, isfile
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
import errors
import trainset
import testset
class DataSet:
def __init__(self, path_to_set, path_to_db, train_set=False, path_to_labels=None, label_dict=None,
custom_name=None):
self.__path_to_set = path_to_set
self.__label_dict = label_dict
if custom_name is None:
dbpath = join(path_to_db, 'train.db')
if train_set is False:
dbpath = join(path_to_db, 'test.db')
else:
dbpath = join(path_to_db, custom_name)
if isfile(dbpath):
self.__prepopulated = True
else:
self.__prepopulated = False
self.__dbpath = dbpath
if train_set is True and path_to_labels is None:
raise errors.InsufficientData('labels', 'specified')
if train_set is True and not isfile(path_to_labels):
raise errors.InsufficientData('labels', 'found at specified path', path_to_labels)
def prepopulate(self):
engine = create_engine('sqlite:////' + self.__dbpath)
self.__prepopulated = True
Here's the trainset code:
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, String, PickleType, Integer, MetaData
Base = declarative_base()
metadata = MetaData()
class TrainSet(Base):
__tablename__ = 'train set'
id = Column(Integer, primary_key=True)
real_id = Column(String(60))
path = Column(String(120))
labels = Column(PickleType)
features = Column(PickleType)
Here's the testset code:
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, String, PickleType, Integer, MetaData
Base = declarative_base()
metadata = MetaData()
class TestSet(Base):
__tablename__ = 'test set'
id = Column(Integer, primary_key=True)
real_id = Column(String(60))
path = Column(String(120))
features = Column(PickleType)
So, if the user passes train_set=True when creating a DataSet instance, I would like to create a database using the TrainSet model, and create a TestSet database otherwise. I would like this to happen in the prepopulate method, however, I don't understand how to do it - the documentation calls for this: Base.metadata.create_all(engine), but I'm lost as to where to put this code.