flask-sqlalchemy
Flask
flask-sqlalchemy | Flask | |
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11 | 135 | |
4,152 | 66,417 | |
0.4% | 0.5% | |
7.9 | 8.7 | |
5 days ago | 5 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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flask-sqlalchemy
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Voting webapp saves votes locally, but not on server
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.
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How to build an API using Flask
Flask-SQLAlchemy: An extension that integrates SQLAlchemy with Flask. You can install it using pip install flask-sqlalchemy.
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How to dynamically generate graphics and PDFs using Python an jinja
flask-sqlalchemy: ORM for database access
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pagination in flask
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.
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Connect Flask APP to Two Already Existing Tables in two distinct databases
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/
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Methods for dynamically loading test db data
You can learn more about this approach and see an example is this Flask-SQLAlchemy PR.
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Usage of Restful API + Database with Flask
Flask SQL Alchemy
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I built an Image Search Engine using OpenAI CLIP and Images from Wikimedia
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.
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I uninstalled an reinstalled sqalalchemy to get the latest version. Now my flask app won't work.
This appears to be this: https://github.com/pallets/flask-sqlalchemy/issues/910
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Problem with circular imports and app context
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()
Flask
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Ask HN: High quality Python scripts or small libraries to learn from
I'd suggest Flask or some of the smaller projects in the Pallets ecosystem:
https://github.com/pallets/flask
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Rapid Prototyping with Flask, Bootstrap and Secutio
#!/usr/bin/python # # https://flask.palletsprojects.com/en/3.0.x/installation/ # from flask import Flask, jsonify, request contacts = [ { "id": "1", "firstname": "Lorem", "lastname": "Ipsum", "email": "[email protected]", }, { "id": "2", "firstname": "Mauris", "lastname": "Quis", "email": "[email protected]", }, { "id": "3", "firstname": "Donec Purus", "lastname": "Purus", "email": "[email protected]", } ] app = Flask(__name__, static_url_path='', static_folder='public',) @app.route("/contact//save", methods=["PUT"]) def save_contact(id): data = request.json contacts[id - 1] = data return jsonify(contacts[id - 1]) @app.route("/contact/", methods=["GET"]) @app.route("/contact//edit", methods=["GET"]) def get_contact(id): return jsonify(contacts[id - 1]) @app.route('/') def root(): return app.send_static_file('index.html') if __name__ == '__main__': app.run(debug=True)
- Microdot "The impossibly small web framework for Python and MicroPython"
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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10 Github repositories to achieve Python mastery
Explore here.
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Ask HN: What would you use to build a mostly CRUD back end today?
I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.
Now...
Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?
- [0]: https://flask.palletsprojects.com
- [1]: https://flask-admin.readthedocs.io/en/latest
- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery
- [3]: https://sentry.io
- [4]: https://posthog.com
- [5]: https://www.docker.com
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Implementing continuous delivery pipelines with GitHub Actions
In the lab to follow, we will be setting up an end-to-end DevOps workflow for a Flask microservice with GitHub Actions, using a self-managed custom runner for maximal control over the pipeline execution environment and automating deployments to a local Kubernetes cluster. Furthermore, we will construct separate pipelines for our "development" and "production" environments to further elaborate on the concepts of continuous deployment and delivery.
- How do you iterate on a library built locally?
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Flask Application Load Balancing using Docker Compose and Nginx
Flask Micro web Framework: You will use Flask to build a Flask web application.
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Open Source Flask-based web applications
In an earlier post I mentioned a bunch of Open Source web applications. Let's now focus on the ones written in Python using Flask the light-weight web framework.
What are some alternatives?
flask-sqlacodegen - :sake: Automatic model code generator for SQLAlchemy with Flask support
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
sqlalchemy-hana - SQLAlchemy Dialect for SAP HANA
Django - The Web framework for perfectionists with deadlines.
sqlalchemy-filters-plus - Lightweight library for providing filtering mechanism for your APIs using SQLAlchemy
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
geoalchemy2 - Geospatial extension to SQLAlchemy
starlette - The little ASGI framework that shines. 🌟
flask-file-upload - Easy file uploads for Flask.
quart - An async Python micro framework for building web applications.
graphql-sqlalchemy - Generate GraphQL Schemas from your SQLAlchemy models
Tornado - Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed.