flask-sqlalchemy VS libcurl

You should probably use a database for this, using something like sqlite a single file "database" is probably the quickest way to get started, I recommend you use it with Flask-SQLAlchemy which makes working with the db easy as pie.

Flask-SQLAlchemy: An extension that integrates SQLAlchemy with Flask. You can install it using pip install flask-sqlalchemy.

flask-sqlalchemy: ORM for database access

I've made several runs at stripping the essential paginating functionality of flask-sqlalchemy for use with things like lists. That's where I'd start.

You can either use an ORM, which might be sqlalchemy, possibly wrapped up as a flask plugin https://flask-sqlalchemy.palletsprojects.com/ or more directly: https://www.sqlalchemy.org/

You can learn more about this approach and see an example is this Flask-SQLAlchemy PR.

Flask SQL Alchemy

I used for this project Flask and OpenAI CLIP. For the vector search I used approximate nearest neighbors provided by spotify/annoy. I used Flask-SQLAlchemy with GeoAlchemy2 to query GPS coordinates. The embedding was done using UMAP using the CLIP image vectors.

This appears to be this: https://github.com/pallets/flask-sqlalchemy/issues/910

from sqlalchemy.engine.reflection import Inspector from sqlalchemy.schema import DropConstraint, DropTable, MetaData, Table from extensions import db # from dotmap import DotMap def try_add(object): """ Try to add the column 'object' to its table in the database and return it. """ try: db.session.add(object) db.session.commit() return object except Exception: db.session.rollback() raise def drop_all_cascade(): """(On a live db) drops all foreign key constraints before dropping all tables. Workaround for SQLAlchemy not doing DROP ## CASCADE for drop_all() (https://github.com/pallets/flask-sqlalchemy/issues/722) """ con = db.engine.connect() trans = con.begin() inspector = Inspector.from_engine(db.engine) # We need to re-create a minimal metadata with only the required things to # successfully emit drop constraints and tables commands for postgres # (based on the actual schema of the running instance) meta = MetaData() tables = [] all_fkeys = [] for table_name in inspector.get_table_names(): fkeys = [] for fkey in inspector.get_foreign_keys(table_name): if not fkey["name"]: continue fkeys.append(db.ForeignKeyConstraint((), (), name=fkey["name"])) tables.append(Table(table_name, meta, *fkeys)) all_fkeys.extend(fkeys) for fkey in all_fkeys: con.execute(DropConstraint(fkey)) for table in tables: con.execute(DropTable(table)) trans.commit()

Then, in another terminal window, we use curl to hit the endpoint:

Made a PR to curl in line with the above: https://github.com/curl/curl/pull/13338

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From the GitHub Issue itself, the maintainer did end up creating a PR to fix a related issue: https://github.com/curl/curl/issues/12983

Also, the bot filed another issue despite the complaints.

This Docker image is designed to support implementing Github Actions with Python. As of version 4.0.0., it starts with the official python docker image as the base which is a Debian OS. It specifically uses python:3-slim to keep the image size down for faster loading of Github Actions that use pyaction. On top of the base, we've installed curl gpg, git, and the GitHub CLI. We added curl and gpg because they are needed to install the GitHub CLI, and they may come in handy anyway (especially curl) when implementing a GitHub Action.