george_ciobanu

You may have read this story on HN or somewhere else: fisherman hangs out at the beach all day, and the rich man works hard all his life to get to the same place (https://thestorytellers.com/the-businessman-and-the-fisherman/).

Except the parable doesn't think through a few super important things.

1. Children If you have them you need money to raise them, send to college etc. Fishing isn't going to cut it.

2. Backup If you've saved money and you get ill or have some other kind of emergency you can use the savings. But if you've just been living paycheck to paycheck (or fishcheck?) and you get some health issue you're kind of screwed (at least in the US).

3. Work can be meaningful I haven't loved all my jobs but a lot of them were quite rewarding. I do like to fish, but it's never been quite as intellectually stimulating or rewarding as solving a complex people & systems problem, or as educational.

what is this: schema = { "actor" => { "direct_fields" => [{ "actor_id" => "smallint unsigned" }, { "first_name" => "varchar(45)" }, { "last_name" => "varchar(45)" }, { "last_update" => "timestamp" }], "primary_key" => ["actor_id"], "outbound_relationships" => {}, "inbound_relationships" => { "film_actor" => [{ "source_column" => "actor_id", "referenced_column" => "actor_id" }] } }, "address" => { "direct_fields" => [{ "address_id" => "smallint unsigned" }, { "address" => "varchar(50)" }, { "address2" => "varchar(50)" }, { "district" => "varchar(20)" }, { "city_id" => "smallint unsigned" }, { "postal_code" => "varchar(10)" }, { "phone" => "varchar(20)" }, { "location" => "geometry" }, { "last_update" => "timestamp" }], "primary_key" => ["address_id"], "outbound_relationships" => { "city" => [{ "source_column" => "city_id", "referenced_column" => "city_id" }] }, "inbound_relationships" => { "customer" => [{ "source_column" => "address_id", "referenced_column" => "address_id" }], "staff" => [{ "source_column" => "address_id", "referenced_column" => "address_id" }], "store" => [{ "source_column" => "address_id", "referenced_column" => "address_id" }] }[...] }

This is a description of a database schema, including the names of tables and the fields and relationships in each table. The schema is written in a structured format using a combination of nested dictionaries and lists. The schema is not specific to any particular database management system, so it can be used as a general reference for the structure of the database.

Ionut Georgian Ciobanu how do you know what are the table names in this schema: schema = { In the schema you provided, the list of tables is: actor, address, category, city, country, customer, film, film_actor, film_category, film_text, inventory, language, payment, rental, staff, and store. The names of the tables are the keys of the schema. For example, "actor" is the name of the actor table.

Ionut Georgian Ciobanu how did you figure that out?

I looked at the schema and saw that the keys of the outermost dictionary are the names of the tables. For example, the keys "actor" and "address" in this line:

Copy code schema = { "actor" => { "direct_fields" => [{ "actor_id" => "smallint unsigned" }, { "first_name" => "varchar(45)" }, { "last_name" => "varchar(45)" }, { "last_update" => "timestamp" }], "primary_key" => ["actor_id"], "outbound_relationships" => {}, "inbound_relationships" => { "film_actor" => [{ "source_column" => "actor_id", "referenced_column" => "actor_id" }] } }, "address" => { "direct_fields" => [{ "address_id" => "smallint unsigned" }, { "address" => "varchar(50)" }, { "address2" => "varchar(50)" }, { "district" => "varchar(20)" }, { "city_id" => "smallint unsigned" }, { "postal_code" => "varchar(10)" }, { "phone" => "varchar(20)" }, { "location" => "geometry" }, { "last_update" => "timestamp" }], "primary_key" => ["address_id"], "outbound_relationships" => { "city" => [{ "source_column" => "city_id", "ref