from sqlalchemy import Column, Computed, DateTime, Float, Index, Integer, String

# we might need vector concat later, then we'll have to bring in sqlalchemy_utils
# https://sqlalchemy-utils.readthedocs.io/en/latest/_modules/sqlalchemy_utils/types/ts_vector.html
from sqlalchemy.dialects.postgresql import TSVECTOR


# to correctly work with both alembic and fastapi we have to check
# if we are run as a module or as a script
# https://stackoverflow.com/questions/14132789/relative-imports-for-the-billionth-time/14132912
import sys
parent_module = sys.modules['.'.join(__name__.split('.')[:-1]) or '__main__']
if __name__ == '__main__' or parent_module.__name__ == '__main__':
    from database import Base
else:
    from .database import Base


class Header(Base):
    __tablename__ = "headers"

    database = Column(String, primary_key=True)
    spreadsheet = Column(String)


class ItemBase(Base):
    __tablename__ = "geodata"

    id = Column(Integer, primary_key=True, index=True)
    fadr = Column(String)
    internal_id = Column(String)
    x_coord = Column(String)
    y_coord = Column(String)
    gis_category = Column(String)
    category = Column(String)
    basin = Column(String)
    deposit = Column(String)
    well = Column(String)
    depth = Column(String)
    stratum = Column(String)
    owner = Column(String)
    org = Column(String)
    ownercontacts = Column(String)
    samplelist = Column(String)
    description = Column(String)
    form_dimentions = Column(String)
    datalist = Column(String)
    resolution = Column(String)
    date = Column(String)
    additional_info = Column(String)
    scanner = Column(String)
    comment = Column(String)


class ItemCreate(ItemBase):
    pass


class Item(ItemBase):
    # split on '-' replace ',' with '.' and cast as numeric
    depth_min = Column(
        Float,
        Computed(
            "CAST(REGEXP_REPLACE(SPLIT_PART(depth,'-',1), ',', '.') AS DOUBLE PRECISION)"
        ),
    )
    depth_max = Column(
        Float,
        Computed(
            "CAST(REGEXP_REPLACE(SPLIT_PART(depth,'-',2), ',', '.') AS DOUBLE PRECISION)"
        ),
    )

    geodata_search_ts = Column(
        TSVECTOR,
        Computed(
            "to_tsvector('russian', coalesce(geodata.description, '') || ' ' || coalesce(geodata.additional_info, '') || ' ' || coalesce(geodata.comment, ''))",
            persisted=True,
        ),
    )


Index("geodata_search_idx", Item.geodata_search_ts, postgresql_using="gin")