my question is more about setting up and adding data.
I am making the first project with Mongo DB on VS Code and can not find solution what to do next.
Google said Instal Cosmos DB, so I did but what next? Does it talk to Flask already? I am lost, need help from someone who works on Flask and MongoDB on VSCode!
Feel like an idiot now!
from flask import Flask
from flask_pymongo import PyMongo
app = Flask(__name__)
app.config["MONGO_URI"] = "mongodb://localhost:27017/"
mongo = PyMongo(app)
from cocktails.main.views import main
app.register_blueprint(main)
Does it talk to Flask already?
Hi,Patrycja. Quick answer is YES! I follow your description and do the steps in this document1 and document2 to create Flask project which accesses Cosmos DB Mongo API.
My app.py looks like below:
from flask import Flask
from flask_pymongo import PyMongo
app = Flask(__name__)
app.debug = True
app.config["MONGO_URI"] = "******"
mongo = PyMongo(app)
print(mongo.db)
#app.route("/")
def home_page():
items = mongo.db.test.find()
for item in items:
name = item["name"]
return name
I use Cosmos DB Mongo API, the sample data as below:
Run the command python -m flask run: ,get output:
The key point is "MONGO_URI", it is the connection string:
If you concern about the cost,you could use Cosmos DB Emulator for your test. Surely, as #Stennie mentioned in the comment,cosmos db mongo api only supports partial features of Mongo DB. But if your work is only limited to simple queries, you could use it.Otherwise,please consider using Mongo Atlas.
Related
I'm very new on GCP and I've tried everything around to achieve this connection, my app connects to any other postgress service but not to Cloud SQL.
I've started to think that is a problem with my code in flask.
So far I have followed this guide:
https://cloud.google.com/sql/docs/postgres/connect-run#public-ip-default
and watched some Youtube Tutorials.
Maybe my problem is in the Cloud Proxy Auth.
MyCode looks like this:
import os
from os.path import join, dirname
from flask import Flask
from flask_cors import CORS
from flask_restful import Api
from flask_jwt_extended import JWTManager
from flask_bcrypt import Bcrypt
from flask_migrate import Migrate
from constants import ACTIVE_SCHEDULER
from db import db
from ma import ma
from resources.routes import initialize_routes, initialize_errors, initialize_cli
from sched import init_scheduler
app = Flask(__name__)
db_user = os.environ.get("DB_USER")
db_pass = os.environ.get("DB_PASS")
db_name = os.environ.get("DB_NAME")
unix_socket_path = os.environ.get("INSTANCE_UNIX_SOCKET")
db_url = 'postgresql+pg8000://{user}:{pw}#/{db}?unix_sock={path}/.s.PGSQL.5432'.format(user=db_user,pw=db_pass,db=db_name, path=unix_socket_path)
app.config["SQLALCHEMY_DATABASE_URI"] = db_url
app.config["SECRET_KEY"] = os.environ.get('JWT_SECRET_KEY', '')
app.config["SQLALCHEMY_TRACK_MODIFICATIONS"] = False
app.config["PROPAGATE_EXCEPTIONS"] = True
and the error that I always get is:
"error": "(pg8000.exceptions.InterfaceError) Can't create a connection to host 172.17.0.1 and port 5432 (timeout is None and source_address is None). (Background on this error at: https://sqlalche.me/e/14/rvf5)"
I'm out of ideas, I hope anyone knows any guide or solution to my problem, Maybe I'm missing some access to the service account, but I think I follow correctly the instructions I even try to connect Privately with the TCP instructions and is almost the same.
No code here, just a question. I have tried various means to get a streamlit app to run within a flask app. Main reason? Using Flask for user authentication into the streamlit app. Cannot get it to work out. Is it not possible perhaps?
Streamlit uses Tornado to serve HTTP and WebSocket data to its frontend. That is, it’s already its own web server, and is written in an existing web framework; it wouldn’t be trivial to wrap it inside another web framework.
Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed. By using non-blocking network I/O, Tornado can scale to tens of thousands of open connections, making it ideal for long polling, WebSockets, and other applications that require a long-lived connection to each user.
Flask is a synchronous web framework and not ideal for WebSockets etc.
Serving an interactive Streamlit app via flask.render_template isn’t feasible, because Streamlit apps are not static; when you interact with your Streamlit app, it is re-running your Python code to generate new results dynamically
Follow these discussions for more info
Integration with flask app
Serve streamlit within flask
import asyncio
import subprocess
from mlflow.server import app as mlflow_app
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.wsgi import WSGIMiddleware
import uvicorn
from fastapi.logger import logger
import uuid
from config import *
streamlit_app_process = None
streamlit_app_stdout = None
streamlit_app_stderr = None
async def registry_subprocess() -> None:
logger.debug("registry distance_matrix")
global streamlit_app_process
global streamlit_app_stdout
global streamlit_app_stderr
id = str(uuid.uuid1())
streamlit_app_stdout = open(f"/tmp/subprocess_stdout_{''.join(id.split('-'))}", 'w+b')
streamlit_app_stderr = open(f"/tmp/subprocess_stderr_{''.join(id.split('-'))}", 'w+b')
cmd = ['streamlit', 'run', f'{app_dir}/Home.py', f'--server.port={streamlit_app_port}', f'--server.address={streamlit_app_host}']
logger.info(f"subprocess start cmd {cmd}")
streamlit_app_process = subprocess.Popen(cmd, stdout=streamlit_app_stdout.fileno(), stderr=streamlit_app_stderr.fileno())
logger.info(f"subprocess start success {streamlit_app_process.pid} uid:{id}")
await asyncio.sleep(1)
streamlit_app_stdout.flush()
streamlit_app_stderr.flush()
[logger.info(i) for i in streamlit_app_stdout.readlines()]
[logger.info(i) for i in streamlit_app_stderr.readlines()]
async def close_subprocess() -> None:
logger.debug("close subprocess")
try:
streamlit_app_process.kill()
streamlit_app_stdout.flush()
streamlit_app_stderr.flush()
streamlit_app_stdout.close()
streamlit_app_stderr.close()
except Exception as error:
logger.error(error)
application = FastAPI()
application.add_event_handler("startup", registry_subprocess)
application.add_event_handler("shutdown", close_subprocess)
application.add_middleware(
CORSMiddleware,
allow_origins='*',
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
application.mount(f"/{mlflow_app_prefix.strip('/')}", WSGIMiddleware(mlflow_app))
if __name__ == "__main__":
uvicorn.run(application, host=mlflow_app_host, port=int(mlflow_app_port))
I would like to add data to a database with Flask-SQLAlchemy without the Flask app running.
Is there a way to get db back from the app after the app and the database have been initialized.
My code looks like
db = SQLAlchemy()
def init_app():
app = Flask(__name__)
db = SQLAlchemy(app)
db.init_app(app)
return app
And what I would like to do is something like
from app import init_app
app = init_app() # initialized but not running
# db is used in model.py, but not initialized
# with Flask
# from db = SQLAlchemy()
from model import Machine # class Machine(db.Model)
p = Machine(name='something')
# now I need the initialized db from somewhere
db.session.add(p)
db.session.commit()
Basically I would like to do what's described here:
Another disadvantage is that Flask-SQLAlchemy makes using the database
outside of a Flask context difficult. This is because, with
FLask-SQLAlchemy, the database connection, models, and app are all
located within the app.py file. Having models within the app file, we
have limited ability to interact with the database outside of the app.
This makes loading data outside of your app difficult. Additionally,
this makes it hard to retrieve data outside of the Flask context.
Well, once you initialize the app, Flask spines a server (either development or production, whichever you set), so if you would like to add data to a database with Flask-SQLAlchemy without the Flask app running, you would better use the flask shell command which runs in the context of the current app, then you could add your data.
But first, it would be better is you set up your app as the following so we could directly import stuff like db, auth, etc:
...
from flask_sqlalchemy import SQLAlchemy
db = SQLAlchemy()
def init_app():
app = Flask(__name__)
db.init_app(app)
return app
In the root of your project, type in the terminal the following command
flask shell
Now that you have a shell running in the context of the current app but not the server not running:
from app import db
from model import Machine # class Machine(db.Model)
p = Machine(name='something')
# now I need the initialized db from somewhere
db.session.add(p)
db.session.commit()
From the wonderful tutorial...
https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-iv-database
Define something like this...
from app import app, db
from app.models import User, Post
#app.shell_context_processor
def make_shell_context():
return {'db': db, 'User': User, 'Post': Post}
And then...
(venv) $ flask shell
>>> db
<SQLAlchemy engine=sqlite:////Users/migu7781/Documents/dev/flask/microblog2/app.db>
>>> User
<class 'app.models.User'>
>>> Post
<class 'app.models.Post'>
Currently, I run
$ flask db init
$ flask db migrate -m "initialization"
$ flask db upgrade
if the database does not exist. I would like to run this within Python, e.g. something like
app.create_db()
so that I don't have to care about setting the database up. Is that possible?
I use the flask-sqlalchemy and flask-migrations plugins
You can use SQLAlchemy-Utils for this.
from sqlalchemy import create_engine
from sqlalchemy_utils import database_exits,create_database
def validate_database():
engine = create_engine('postgres://postgres#localhost/name')
if not database_exists(engine.url): # Checks for the first time
create_database(engine.url) # Create new DB
print("New Database Created"+database_exists(engine.url)) # Verifies if database is there or not.
else:
print("Database Already Exists")
call this method in your __init__.py file so that it checks every time your server starts.
Obviously, you have installed flask-migrate, flask-sqlalchemy.
So, you can do like this:
from flask_sqlalchemy import SQLAlchemy
from flask import Flask
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////tmp/test.db'
db = SQLAlchemy(app)
db.create_all()
API DOC: flask.ext.sqlalchemy.SQLAlchemy.create_all
but your Question has confused me. why restricted by SQLAlchemy and Alembic?
There's db.create_all() but I think that when you're using migrations you should stick to migration scripts.
Something to note is that if you have your migration files all set up (i.e migration folder) then all you need is flask db migrate
If you're running this locally, I would stick to doing this command manually.
If you're using this on a server, you should probably use a deployment script that does this for you. You can look at fabric (www.fabfile.org) for information on how to run terminal commands
am trying out creating a web app using python flask framework. I've installed flask-mysql library to interact with mysql db. However, am having trouble getting rows as dictionaries rather than tuples. With the usual python-mysql library, it's a matter of adding "cursorclass=MySQLdb.cursors.DictCursor," to my database handle.
from flaskext.mysql import MySQL
app = Flask(__name__)
mysql = MySQL()
# MySQL configurations
app.config['MYSQL_DATABASE_USER'] = 'user'
app.config['MYSQL_DATABASE_PASSWORD'] = 'password'
app.config['MYSQL_DATABASE_DB'] = 'mydb'
app.config['MYSQL_DATABASE_HOST'] = 'localhost'
mysql.init_app(app)
I've tried adding app.config['MYSQL_DATABASE_CURSORCLASS'] = 'DictCursor' but that doesn't work. It instead works with flask-mysqldb from documentation here.
Also am confused about flask-mysql and flask-mysqldb libraries, which one should I be using.
i found other way to config the flask server in flask-mysql(don't confuse with flask-mysqldb),
you can do this:
from flaskext.mysql import MySQL
import pymysql
mysql = MySQL()
mysql = MySQL(app, prefix="mydb", host="localhost",password='password', user="user", db="mydb", cursorclass=pymysql.cursors.DictCursor)