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Adding multiple columns in a table such as using a for / while loop in flask-sqlalchemy

I want to create a child table using Flask-SQLAlchemy that holds around 600 columns.
Each column is supposed to be a different hobby with a boolean value of true or false (whether or not he has this hobby).
However I do have an issue. Using Flask-SQLAlchemy's Model to create it seems problematic since I will have to write each field myself.
i.e:
class hobbies(database.Model):
id = db.Column(db.Integer, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'))
hobby1 = db.Column(db.Boolean)
hobby2 = db.Column(db.Boolean)
hobby3 = db.Column(db.Boolean)
....
....
hobby600 = db.Column(db.Boolean)
(database stands for the variable that holds - database = SQLAlchemy(app))
Is there a way such as using a for or a while loop to add all of the columns to the table?
Thank you for your time.

This is bad table design(no offence), instead of this you can create table as given below
class Hobbies(database.Model):
id = db.Column(db.Integer, primary_key=True)
hobby = db.Column(db.String(50))
class UserHobbies(database.Model):
user_id = db.Column(db.Integer, db.ForeignKey('user.id'),primary_key=True)
hobbie_id = db.Column(db.Integer, db.ForeignKey('hobbies.id'),primary_key=True)
Instead of creating 600 columns in hobbies table just create 600 rows and create another table UserHobbies for many to many relationship with users and hobbies.
You can also utilize bulk_insert_mappings(ModelName,list_data) function for inserting bulk data in to hobbies table.

Linking two tables where the same value exists, without Primary key - SQLAlchemy

I have the following tables defined (very simplified version):
class Orders(db.Model):
id = db.Column(db.Integer, primary_key=True)
order_id = db.Column(db.Integer,nullable=False)
date_created = db.Column(db.DateTime, nullable=False)
class ProductOrders(db.Model):
id = db.Column(db.Integer, primary_key=True)
order_id = db.Column(db.Integer, nullable=False)
product_id = db.Column(db.Integer, nullable=False)
base_price = db.Column(db.Float, nullable=False)
I am using BigCommerce API and have multiple order_ids in both tables. The order_id is not unique globally but is unique per store. I am trying to work out how to link the two tables. I do have a Store table (shown below) that holds the store.id for each store, but I just cannot work out how to join the Orders and ProductOrders tables together so I can access both tables data where the store.id is the same. I just want to query, for example, a set of Orders.order_id or Orders.date_created and get ProductOrders.base_price as well.
class Store(db.Model):
id = db.Column(db.Integer, primary_key=True)
Any ideas?

Assuming id in both queries is the store_id and order_id is unique per store, you will have to apply join with AND statement.
For example: (in SQL)
Orders join ProductOrders on Orders.id = ProductOrders.id and Orders.order_id = ProductOrders.order_id
Answer is based on what I have understood from your question, sorry if that's not your required answer.
Edit:
In sqlalchemy it would be something like below:
from sqlalchemy import and_
session.query(Orders, ProductOrders).filter(and_(Orders.id == ProductOrders.id, Orders.order_id == ProductOrders.order_id)).all()
References:
https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_orm_working_with_joins.htm
Using OR in SQLAlchemy

SQLAlchemy upsert Function for MySQL

I have used the following documentation as a guide and tried to implement an upset mechanism for my Games table. I want to be able to dynamically update all columns of the selected table at a time (without having to specify each column individually). I have tried different approaches, but none have provided a proper SQL query which can be executed. What did I misunderstand respectively what are the errors in the code?
https://docs.sqlalchemy.org/en/12/dialects/mysql.html?highlight=on_duplicate_key_update#insert-on-duplicate-key-update-upsert
https://github.com/sqlalchemy/sqlalchemy/issues/4483
class Game(CustomBase, Base):
__tablename__ = 'games'
game_id = Column('id', Integer, primary_key=True)
date_time = Column(DateTime, nullable=True)
hall_id = Column(Integer, ForeignKey(SportPlace.id), nullable=False)
team_id_home = Column(Integer, ForeignKey(Team.team_id))
team_id_away = Column(Integer, ForeignKey(Team.team_id))
score_home = Column(Integer, nullable=True)
score_away = Column(Integer, nullable=True)
...
def put_games(games): # games is a/must be a list of type Game
insert_stmt = insert(Game).values(games)
#insert_stmt = insert(Game).values(id=Game.game_id, data=games)
on_upset_stmt = insert_stmt.on_duplicate_key_update(**games)
print(on_upset_stmt)
...
I regularly load original data from an external API (incl. ID) and want to update my database with it, i.e. update the existing entries (with the same ID) with the new data and add missing ones without completely reloading the database.
Updates
The actual code results in
TypeError: on_duplicate_key_update() argument after ** must be a
mapping, not list
With the commented line #insert_statement... instead of first insert_stmt is the error message
sqlalchemy.exc.CompileError: Unconsumed column names: data

Converting a pandas dataframe to a class and saving using orm

My code is working with a mixture of pandas dataframes and orm tables. Because I wanted to speed up the retrieval of data using an index (as opposed to reading an entire file into a dataframe and re-writing it each time), I created a class statement to facilitate orm queries. But I'm struggling to put it all together.
Here is my class statement:
engine_local = create_engine(Config.SQLALCHEMY_DATABASE_URI_LOCAL)
Base_local = declarative_base()
Base_local.metadata.create_all(engine_local)
Session_local = sessionmaker(bind=engine_local)
Session_local.configure(bind=engine_local)
session_local = Session_local()
class Clients(Base_local):
__tablename__ = 'clients'
id = sa.Column(sa.Integer, primary_key=True)
client_id = sa.Column(sa.Integer, primary_key=True)
client_year = sa.Column(sa.Integer, primary_key=True)
client_cnt = sa.Column(sa.Integer, nullable=False)
date_posted = sa.Column(sa.DateTime, nullable=False, default=datetime.utcnow)
client_company = sa.Column(sa.Integer, nullable=False)
client_terr = sa.Column(sa.Integer, nullable=False)
client_credit = sa.Column(sa.Integer, nullable=False)
client_ann_prem = sa.Float(sa.Float)
def __repr__(self):
return f"Clients('{self.client_id}', '{self.client_year}', '{self.client_ann_prem}')"
meta = sa.MetaData()
meta.bind = engine_local
meta.drop_all(engine_local)
meta.create_all(engine_local)
And here is my panda definition statement:
clients_df = pd.DataFrame(client_id, columns=feature_list)
clients_df['client_year'] = client_year
clients_df['client_cnt'] = client_cnt
clients_df['client_company'] = client_company
clients_df['client_terr'] = client_terr
clients_df['client_credit'] = client_credit
clients_df['client_ann_prem'] = client_ann_prem
I have an initialize step where I need to save this entire dataframe for the first time (so it will constitute the entire database and can write over any pre-existing data). Later, however, I will want to import only a portion of the table based on client_year, and then append the updated dataframe to the existing table.
Questions I am struggling with:
Is it useful to define a class at all? (I'm choosing this path since I believe orm is easier than raw SQL)
Will the pd.to_sql statement automatically match the dataframes to the class definitions?
If I want to create new versions of the table (e.g. for a threaded process), can i create inherited classes based upon Clients without having to go through an initialize step? (e.g. a Clients01 and Clients02 table).
Thanks!

How to count child table items with or without join to parent table using SQLAlchemy?

I used SQLAlchemy to create a SQLite database which stores bibliographic data of some document, and I want to query the author number of each document.
I know how to do this in raw SQL, but how can I achieve the same result using SQLAlchemy? It is possible without using join?
Here is the classes that I have defined:
class WosDocument(Base):
__tablename__ = 'wos_document'
document_id = Column(Integer, primary_key=True)
unique_id = Column(String, unique=True)
......
authors = relationship('WosAuthor', back_populates='document')
class WosAuthor(Base):
__tablename__ = 'wos_author'
author_id = Column(Integer, primary_key=True, autoincrement=True)
document_unique_id = Column(String, ForeignKey('wos_document.unique_id'))
document = relationship('WosDocument', back_populates='authors')
last_name = Column(String)
first_name = Column(String)
And my goal is to get the same result as this SQL query does:
SELECT a.unique_id, COUNT(*)
FROM wos_document AS a
LEFT JOIN wos_author AS b
ON a.unique_id = b.document_unique_id
GROUP BY a.unique_id
I tried the codes below:
session.query(WosDocument.unique_id, len(WosDocument.authors)).all()
session.query(WosDocument.unique_id, func.count(WosDocument.authors)).all()
The first line raised an error, the second line doesn't give me the desired result, it return only one row and I don't recognize what it is:
[('000275510800023', 40685268)]
Since WosDocument Object has a one-to-many relationship authors, I supposed that I can query the author number of each document without using join explicitly, but I can't find out how to do this with SQLAlchemy.
Can you help me? Thanks!

If you have written the right relation in your model. Then the query would be like:
db.session.query(ParentTable.pk,func.count('*').label("count")).join(Childtable).group_by(ParentTable).all()
The detail of the document of the join() is
https://docs.sqlalchemy.org/en/latest/orm/query.html#sqlalchemy.orm.query.Query.join
If you don't join() explictly you would need to deal with something like parent.relations as a field.