summaryrefslogtreecommitdiff
path: root/database.py
blob: addcd30e977e2597c2f83297cab864f0cd761818 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
import os
from collections.abc import Generator

from dotenv import load_dotenv
from sqlalchemy import create_engine, inspect
from sqlalchemy.orm import DeclarativeBase, Session, sessionmaker

load_dotenv()

DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///./lumiere.db")

connect_args = {"check_same_thread": False} if DATABASE_URL.startswith("sqlite") else {}
engine = create_engine(DATABASE_URL, connect_args=connect_args)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)


class Base(DeclarativeBase):
    pass


def get_db() -> Generator[Session, None, None]:
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()


def init_db() -> None:
    import models

    _rebuild_films_table_if_needed(models.Film)
    Base.metadata.create_all(bind=engine)


def _rebuild_films_table_if_needed(film_model) -> None:
    if not DATABASE_URL.startswith("sqlite"):
        return

    inspector = inspect(engine)
    if "films" not in inspector.get_table_names():
        return

    existing_columns = {column["name"] for column in inspector.get_columns("films")}
    expected_columns = {column.name for column in film_model.__table__.columns}
    if existing_columns == expected_columns:
        return

    legacy_indexes = [index["name"] for index in inspector.get_indexes("films")]
    legacy_table = "films_legacy_schema"
    with engine.begin() as connection:
        connection.exec_driver_sql(f"DROP TABLE IF EXISTS {legacy_table}")
        connection.exec_driver_sql(f"ALTER TABLE films RENAME TO {legacy_table}")
        for index_name in legacy_indexes:
            connection.exec_driver_sql(f"DROP INDEX IF EXISTS {index_name}")
        film_model.__table__.create(bind=connection)

        target_columns = []
        select_expressions = []
        for column in film_model.__table__.columns:
            name = column.name
            if name in existing_columns:
                target_columns.append(name)
                select_expressions.append(name)
            elif name == "context" and "mood_tags" in existing_columns:
                target_columns.append(name)
                select_expressions.append("mood_tags")
            elif name == "rewatch":
                target_columns.append(name)
                select_expressions.append("0")
            elif name in {"rewatch_count", "stars"}:
                target_columns.append(name)
                select_expressions.append("0")
            elif name == "shelf":
                target_columns.append(name)
                select_expressions.append("'diary'")
            elif name in {"created_at", "updated_at"}:
                target_columns.append(name)
                select_expressions.append("CURRENT_TIMESTAMP")

        if target_columns:
            connection.exec_driver_sql(
                f"""
                INSERT INTO films ({", ".join(target_columns)})
                SELECT {", ".join(select_expressions)}
                FROM {legacy_table}
                """
            )

        connection.exec_driver_sql(f"DROP TABLE {legacy_table}")