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(sqlite3.OperationalError) unknown database "seller"

I'm trying to use a testdb(sqlite) to make my tests, but when i use Base.metadata.createall() to create the same tables of the production database, i got this error: (sqlite3.OperationalError) unknown database "seller".
Conftest.py:
DATABASE_URL = 'sqlite:///testedb.sqlite'
#pytest.fixture(scope="function")
def client() -> Generator:
config_database(DATABASE_URL)
with TestClient(app) as c:
yield c
Database.py:
Base = declarative_base()
def config_database(database_url):
engine = create_engine(database_url)
Base.metadata.create_all(bind=engine)
Example of model there i'm using:
class Seller(Base):
__table__ = Table(
"seller",
Base.metadata,
Column(
"seller_id",
Integer,
primary_key=True,
index=True,
nullable=False),
Column("cnpj", String, nullable=True),
Column("nickname", String, nullable=False),
schema="seller")

Some database back-ends like PostgreSQL and MS SQL Server support the notion of a database containing multiple schemas, each of which can contain tables, views, stored procedures, etc.. If we are connected to a database named "my_db" then
SELECT * FROM seller.thing
means 'select rows from the table named "thing" in the schema named "seller" in the current database (my_db)'.
Other database back-ends like MySQL and SQLite do not support schemas within a database. Instead, they treat "schema" and "database" as synonyms, so
SELECT * FROM seller.thing
means 'select rows from the table named "thing" in the database named "seller", regardless of the current database'.
Therefore,
from sqlalchemy import create_engine, Column, Integer, Table, MetaData
engine = create_engine("sqlite:///data.db")
thing = Table(
"thing",
MetaData(),
Column("id", Integer, primary_key=True, autoincrement=False),
schema="seller",
)
engine.echo = True
thing.create(engine)
will fail with the error
sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) unknown database seller
[SQL:
CREATE TABLE seller.thing (
id INTEGER NOT NULL,
PRIMARY KEY (id)
)
]
if the current SQLite database does not have an attached database named "seller".
That might be a bit confusing because in the above example the database "data.db" will be created automatically if it does not exist, but that happens when the code tries to establish a (DBAPI) connection to the database. The same "auto-create" behaviour does not occur when an SQL statement tries to refer to another database.
So, if you want to use a "schema" named "seller" in SQLite then you need to ATTACH it to the current database like so:
from sqlalchemy import create_engine, Column, event, Integer, Table, MetaData
engine = create_engine("sqlite:///data.db")
#event.listens_for(engine, "first_connect")
def schema_attach(dbapi_connection, connection_record):
dbapi_connection.execute("ATTACH DATABASE 'seller.db' AS seller")
thing = Table(
"thing",
MetaData(),
Column("id", Integer, primary_key=True, autoincrement=False),
schema="seller",
)
engine.echo = True
thing.create(engine)
(Note that in this case "seller.db" will be automatically created if it does not exist.)

Is there a way to use SQL Tables as classes or objects in python?

I have to tie database and programming for an assignment and I have an idea for a code but need to make sure that I can use the tables I created in mySQL as my classes or objects in Python.
Example: I use SQL to create a database of houses with specific addresses and zip codes. A client says they live in zipcode x. My program should then parse through the database and return all addresses within zipcode x. Then ideally create a table in SQL with the clients results.
Not the exact assignment but it gets the basic idea across.

You're looking for an ORM. See SQLAlchemy. Example:
from sqlalchemy import Column, String, Integer, Sequence
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
create_session = sessionmaker()
Base = declarative_base()
person_autoincr_seq = Sequence('person_autoincr_seq')
class Person(Base):
__tablename__ = "person"
id = Column(
Integer,
person_autoincr_seq,
server_default=person_autoincr_seq.next_value(),
nullable = False,
primary_key = True
)
name = Column(
String,
nullable = False
)
def __init__(self, name,id=None):
if id is not None:
self.id = id
self.name = name
Using the db:
import logging as log
from contextlib import closing
engine = sqlalchemy.engine.create_engine(
"postgresql://testuser:mypassword#127.0.0.1:5432/testdb"
)
create_session.configure(bind=engine)
try:
with closing(create_session()) as db_session:
name = db_session.query(Person.name).filter_by(id=5).one()[0]
except Exception:
log.exception("Something wrong while querying db")

Sqlalchemy if table does not exist

I wrote a module which is to create an empty database file
def create_database():
engine = create_engine("sqlite:///myexample.db", echo=True)
metadata = MetaData(engine)
metadata.create_all()
But in another function, I want to open myexample.db database, and create tables to it if it doesn't already have that table.
EG of the first, subsequent table I would create would be:
Table(Variable_TableName, metadata,
Column('Id', Integer, primary_key=True, nullable=False),
Column('Date', Date),
Column('Volume', Float))
(Since it is initially an empty database, it will have no tables in it, but subsequently, I can add more tables to it. Thats what i'm trying to say.)
Any suggestions?

I've managed to figure out what I intended to do. I used engine.dialect.has_table(engine, Variable_tableName) to check if the database has the table inside. IF it doesn't, then it will proceed to create a table in the database.
Sample code:
engine = create_engine("sqlite:///myexample.db") # Access the DB Engine
if not engine.dialect.has_table(engine, Variable_tableName): # If table don't exist, Create.
metadata = MetaData(engine)
# Create a table with the appropriate Columns
Table(Variable_tableName, metadata,
Column('Id', Integer, primary_key=True, nullable=False),
Column('Date', Date), Column('Country', String),
Column('Brand', String), Column('Price', Float),
# Implement the creation
metadata.create_all()
This seems to be giving me what i'm looking for.

Note that in 'Base.metadata' documentation it states about create_all:
Conditional by default, will not attempt to recreate tables already
present in the target database.
And if you can see that create_all takes these arguments: create_all(self, bind=None, tables=None, checkfirst=True), and according to documentation:
Defaults to True, don't issue CREATEs for tables already present in
the target database.
So if I understand your question correctly, you can just skip the condition.

The accepted answer prints a warning that engine.dialect.has_table() is only for internal use and not part of the public API. The message suggests this as an alternative, which works for me:
import os
import sqlalchemy
# Set up a connection to a SQLite3 DB
test_db = os.getcwd() + "/test.sqlite"
db_connection_string = "sqlite:///" + test_db
engine = create_engine(db_connection_string)
# The recommended way to check for existence
sqlalchemy.inspect(engine).has_table("BOOKS")
See also the SQL Alchemy docs.

For those who define the table first in some models.table file, among other tables.
This is a code snippet for finding the class that represents the table we want to create ( so later we can use the same code to just query it )
But together with the if written above, I still run the code with checkfirst=True
ORMTable.__table__.create(bind=engine, checkfirst=True)
models.table
class TableA(Base):
class TableB(Base):
class NewTableC(Base):
id = Column('id', Text)
name = Column('name', Text)
form
Then in the form action file:
engine = create_engine("sqlite:///myexample.db")
if not engine.dialect.has_table(engine, table_name):
# Added to models.tables the new table I needed ( format Table as written above )
table_models = importlib.import_module('models.tables')
# Grab the class that represents the new table
# table_name = 'NewTableC'
ORMTable = getattr(table_models, table_name)
# checkfirst=True to make sure it doesn't exists
ORMTable.__table__.create(bind=engine, checkfirst=True)

engine.dialect.has_table does not work for me on cx_oracle.
I am getting AttributeError: 'OracleDialect_cx_oracle' object has no attribute 'default_schema_name'
I wrote a workaround function:
from sqlalchemy.engine.base import Engine
def orcl_tab_or_view_exists(in_engine: Engine, in_object: str, in_object_name: str,)-> bool:
"""Checks if Oracle table exists in current in_engine connection
in_object: 'table' | 'view'
in_object_name: table_name | view_name
"""
obj_query = """SELECT {o}_name FROM all_{o}s WHERE owner = SYS_CONTEXT ('userenv', 'current_schema') AND {o}_name = '{on}'
""".format(o=in_object, on=in_object_name.upper())
with in_engine.connect() as connection:
result = connection.execute(obj_query)
return len(list(result)) > 0

This is the code working for me to create all tables of all model classes defined with Base class
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
class YourTable(Base):
__tablename__ = 'your_table'
id = Column(Integer, primary_key = True)
DB_URL="mysql+mysqldb://<user>:<password>#<host>:<port>/<db_name>"
scoped_engine = create_engine(DB_URL)
Base = declarative_base()
Base.metadata.create_all(scoped_engine)

SQLAlchemy alembic AmbiguousForeignKeysError for declarative type but not for equivalent non-declarative type

I have the following alembic migration:
revision = '535f7a49839'
down_revision = '46c675c68f4'
from alembic import op
import sqlalchemy as sa
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from datetime import datetime
Session = sessionmaker()
Base = declarative_base()
metadata = sa.MetaData()
# This table definition works
organisations = sa.Table(
'organisations',
metadata,
sa.Column('id', sa.Integer, primary_key=True),
sa.Column('creator_id', sa.Integer),
sa.Column('creator_staff_member_id', sa.Integer),
)
"""
# This doesn't...
class organisations(Base):
__tablename__ = 'organisations'
id = sa.Column(sa.Integer, primary_key=True)
creator_id = sa.Column(sa.Integer)
creator_staff_member_id = sa.Column(sa.Integer)
"""
def upgrade():
bind = op.get_bind()
session = Session(bind=bind)
session._model_changes = {} # if you are using Flask-SQLAlchemy, this works around a bug
print(session.query(organisations).all())
raise Exception("don't succeed")
def downgrade():
pass
Now the query session.query(organisations).all() works when I use the imperatively-defined table (the one not commented out). But if I use the declarative version, which as far as I understand should be equivalent, I get an error:
sqlalchemy.exc.AmbiguousForeignKeysError: Could not determine join
condition between parent/child tables on relationship
StaffMember.organisation - there are multiple foreign key paths
linking the tables. Specify the 'foreign_keys' argument, providing a
list of those columns which should be counted as containing a foreign
key reference to the parent table.
Now I understand what this error means: I have two foreign keys from organisations to staff_members in my actual models. But why does alembic care about these, and how does it even know they exist? How does this migration know that something called StaffMember exists? As far as I understand, alembic should only know about the models you explicitly tell it about in the migration.

Turns out the problem was with my Flask-script setup I was using to call alembic. The command I was using to call alembic was importing the code to initialise my Flask app which was itself importing my actual models.

How to write alter column name migrations with sqlalchemy-migrate?

I'm trying to alter a column name. First attempt was with this script:
meta = MetaData()
users = Table('users', meta,
Column('id', Integer, primary_key=True),
Column('name', String(50), unique=True),
Column('email', String(120), unique=True)
)
def upgrade(migrate_engine):
meta.bind = migrate_engine
users.c.id.alter(name='id')
def downgrade(migrate_engine):
meta.bind = migrate_engine
users.c.id.alter(name='user_id')
Running migrate.py test on my dev database (sqlite) works and so does upgrading and downgrading. But when deploying it to my test environment on Heroku (where PostgreSQL 8.3 is used) I get a trace when I try to upgrade. Gist is this message:
sqlalchemy.exc.ProgrammingError: (ProgrammingError) column "id" does not exist
I then tried to use users.c.user_idin the upgrade method. That fails in both environments.:
AttributeError: user_id
The workaround I'm using now is this script:
meta_old = MetaData()
meta_new = MetaData()
users_old = Table('users', meta_old,
Column('user_id', Integer, primary_key=True),
Column('name', String(50), unique=True),
Column('email', String(120), unique=True)
)
users_new = Table('users', meta_new,
Column('id', Integer, primary_key=True),
Column('name', String(50), unique=True),
Column('email', String(120), unique=True)
)
def upgrade(migrate_engine):
meta_old.bind = migrate_engine
users_old.c.user_id.alter(name='id')
def downgrade(migrate_engine):
meta_new.bind = migrate_engine
users_new.c.id.alter(name='user_id')
It's already recommended practice to copy-paste the model to the sqlalchemy-migrate scripts. But this extra duplications gets a bit too much for me. Anyone knows how this should be done. Assuming it's a bug, I'd like suggestions on how to DRY up the workaround some.

This one also works:
from alembic import op
....
def upgrade(migrate_engine):
op.alter_column('users', 'user_id', new_column_name='id')
def downgrade(migrate_engine):
op.alter_column('users', 'id', new_column_name='user_id')

Turns out there's an even DRY:er solution to this than I had hoped for. Introspection! Like so:
def upgrade(migrate_engine):
meta = MetaData(bind=migrate_engine)
users = Table('users', meta, autoload=True)
users.c.user_id.alter(name='id')
def downgrade(migrate_engine):
meta = MetaData(bind=migrate_engine)
users = Table('users', meta, autoload=True)
users.c.id.alter(name='user_id')
Works like a charm!

I bet that it can't generate any SQL because your metadata references are getting mixed up. You seem to be using two different metadata objects in your Table classes, and that's really not good. You only need one. The metadata tracks stale-ness of objects, whether it needs to issue queries for object updates, foreign key constraints, etc. and it needs to know about all your tables and relationships.
Change to use a single MetaData object, and pass echo=True to your sqlalchemy.create_engine call and it will print the SQL query that it's using to standard output. Try executing that query yourself while logged in as the same role (user) to Postgres. You may find that it's a simple permissions issue.
Regarding copy-pasting: I think Django has a good convention of placing Table and declarative classes in their own module and importing them. However, because you have to pass a MetaData object to the Table factory, that complicates matters. You can use a singleton/global metadata object, or just convert to declarative.
For a while I chose to implement one-argument functions that returned Table objects given a metadata and cached the result--in effect implementing a singleton model class. Then I decided that was silly and switched to declarative.