Lets say I created a product database system for different departments of my company. Each department has its own PostgreSQL-databse-instance for various reasons. The schemata of the databases are the same, however the data in them is not. For each of these systems a Python application exists that does some business logic (irrelevant). Each Python app accesses its and only its databases through SQLAlchemy.
I want to create a Supervisior-System that can access all data in all of these databases (readthrough functionality).
Here is an example of what I think about:
Can I do that with SQLAlchemy? If so, what is the best approach for that kind of problem?
Sure you can do that with SQLAlchemy.
All you need to do is create different connection engines, each with their own session maker. Nothing in SQLAlchemy limits you to only one database at a time.
engines = []
sessions = []
for dbconninfo in databases:
engine = create_engine(dbconninfo)
engines.append(engine)
sessions.append(sessionmaker(bind=engine)())
You can use each session to run queries, result objects are attached to the session that produced them, so that changes flow back to the correct database. Do study the session documentation in detail, to see what happens if you were to merge an object from one session into another, for example.
Related
I have a bigquery table about 200 rows, i need to insert,delete and update values in this through a web interface(the table cannot be migrated to any other relational or non-relational database).
The web application will be deployed in google-cloud on app-engine and the user who acts as admin and owner privileges on Bigquery will be able to create and delete records and the other users with view permissions on the dataset in bigquery will be able to view records only.
I am planning to use the scripting language as python,
server(django or flask or any other)-> not sure which one is better
The web application should be displayed as a data-grid like appearance with buttons create,delete or view visiblility according to their roles.
I have not done anything like this in python,bigquery and django. I am already familiar with calling bigquery from python-client but to call in a web interface and in a transactional way, i am totally new.
I am seeing examples only related to django with their inbuilt model and not with big-query.
Can anyone please help me and clarify whether this is possible to implement and how?
I was able to achieve all of "C R U D" on Bigquery with the help of SQLAlchemy, though I had make a lot of concessions like if i use sqlalchemy class i needed to use a false primary key as Bigquery does not use any primary key and for storing sessions i needed to use file based session On Django for updates and create sqlalchemy does not allow without primary key, so i used raw sql part of SqlAlchemy. Thanks to the #mhawke who provided the hint for me to carry out this exericse
No, at most you could achieve the "R" of "CRUD." BigQuery isn't a transactional database, it's for querying vast amounts of data and preparing the results as an immutable view.
It doesn't provide a method to modify the source data directly and even if you did you'd need to run the query again. Also important to note are that queries are asynchronous and require much longer to perform than traditional databases.
The only reasonable solution would be to export the table data to GCS and then import it into a normal database for querying. Alternatively if you can't use another database and since you said there are only 1,000 rows you could perform your CRUD actions directly on that exported CSV.
I am an 11th grade student and I'm learning how to build a web app, with my teammates. Currently, We're making a website showing the school schedule (also to show students' marks) and helping the users to create their to-do lists, of course this web serves students like me. In the backend of the web, we use Python as the main language, Flask as the framework and MySQL to manipulate our database. Now, everything is ok and we're trying to make something like an admin interface for people who host the web. Specifically, it is where teachers can insert their students' grade, and maybe adjust the school timetable. The problem is, we're learning how to use Flask Admin to code that function, and we've found out this tech is only compatible with SQL Server. However, we have a better understand in MySQL therefore we could create multiple tasks, in contrast, we don't know how to use SQL Server to create those funcs. Now I have 2 main questions:
Could we use 2 different SQL in the backend of our web? It is the quickest way we know, however we have to learn how to use SQL Server.
Could we use 2 different Python backend frameworks in the backend of our web? We haven't searched which framework to use yet because we don't know if it's possible to do this.
We don't know any other ways to solve this problem except getting rid of MySQL and use SQL Server instead. However this is not the way we prefer and we hope those 2 questions answered. If there is anything wrong in our knowledge please just straightly comment to let us know, and we greatly welcome any other solutions. Thanks for answering!!
Directly from the flask-admin docs https://flask-admin.readthedocs.io/en/latest/advanced/#using-different-database-backends is the following:
Using Different Database Backends Other than SQLAlchemy… There are
five different backends for you to choose from, depending on which
database you would like to use for your application. If, however, you
need to implement your own database backend, have a look at Adding A
Model Backend.
If you don’t know where to start, but you’re familiar with relational
databases, then you should probably look at using SQLAlchemy. It
is a full-featured toolkit, with support for SQLite, PostgreSQL,
MySQL, Oracle and MS-SQL amongst others. It really comes into its own once you have lots of data, and a fair amount of relations between
your data models. If you want to track spatial data like
latitude/longitude points, you should look into GeoAlchemy, as well.
Regarding the original question, it is possible to use two different frameworks in the backend of a web app. One way to do so would be to set up a reverse proxy server (see https://www.nginx.com/resources/glossary/reverse-proxy-server/#:~:text=A%20reverse%20proxy%20server%20is,traffic%20between%20clients%20and%20servers.), but I would recommend giving SQLAlchemy before doing so.
Why do you think that flask-admin is tied to SqlServer? Flask (and flask-admin) can handle different connections to various databases:
https://github.com/flask-admin/flask-admin#introduction
https://flask-admin.readthedocs.io/en/v1.0.9/db/
My guess is you are currently using SqlAlchemy. As explained here, you can use different backends:
The string form of the URL is dialect[+driver]://user:password#host/dbname[?key=value..], where dialect is a database name such as mysql, oracle, postgresql, etc., and driver the name of a DBAPI, such as psycopg2, pyodbc, cx_oracle, etc.
Alternatively, the URL can be an instance of URL.
(https://docs.sqlalchemy.org/en/13/core/engines.html#sqlalchemy.create_engine)
More on Engine here
Flask-admin is a admin view on your database tables - you cannot run it on a "different" db then the tables it should modify. It needs to have access to the database tables you want it to modify, so you cannot run "admin" on MS and "your data backend" on another database(-connection).
Some other things to think about:
MS-(T-)Sql and MySql are infrastructural choices, language wise they are very closely related so adapting MySql knowledge to T-SQL Syntax should be possible. Choosing SqlServer may force you to license it - and afaik that comes with fees (eiter on premise or as a azure subscription wich might or might not be free for schools (no idea - but you should check that)).
This sounds like an ambitious project for school - depending on where you live, privat data protection laws come into play especially considering you connect names with schedules with grades which would need you to implement a lot more to comply.
For first question, I checked flask-admin documentation and found that the framework already included serval built-in ORM library, i.e. SQLAlchemy, MongoEngine, pymongo and Peewee. This means you can just directly import the ORM library from the flask-admin package and use it to access your database. For your case, you should look for SQLAlchemy as you are using SQL Database. Both SQL Server and MySQL are supported by SQLAlchemy.
The Adding Model Views section in their official doc also mentioned it as well:
https://flask-admin.readthedocs.io/en/latest/introduction/#getting-started
For the second question, it is technically not possible to apply two different frameworks in one single backend application.
I'm currently developing a Python Flask app that will allow users to write out paragraphs and store them in a MySQL database. Are there any Python libraries that will let users have the benefits of version control? Ideally users would be able to track edits so that users can revert to previous versions of the text they've written.
If you're using SQL Alchemy, checkout: sqlalchemy-continuum.
Features:
Does not store updates which don’t change anything
Supports alembic migrations
Can revert objects data as well as all object relations at given transaction even if the object was deleted
Transactions can be queried afterwards using SQLAlchemy query syntax
Querying for changed records at given transaction
Querying for versions of entity that modified given property
Querying for transactions, at which entities of a given class changed
History models give access to parent objects relations at any given point in time
Or check versioning-objects in SQLAlchemy documentation.
I also found this tutorial Database Content Versioning Using SQLAlchemy by Googling: sqlalchemy history table, you may find other solutions.
I need to write a complex query, which retrieves a lot of data from a bunch of tables. Basically I need to find all instances of the models
Customer
Payment
Invoice
where relationships intersect in a specific way. In SqlAlchemy, I would be able to do something like
for c, p, i in session.query(Customer, Payment, Invoice).\
filter(User.id==Payment.customer_id).\
filter(Invoice.id==Payment.invoice_id).\
filter(Payment.date==...).\
filter(Customer.some_property==...)
all():
# Do stuff ...
This would allow me to set several constraints and retrieve it all at once. In Django, I currently do something stupid like
customers = Customer.objects.filter(...)
payments = Payment.objects.filter(customer=customer)
invoices = Invoice.objects.filter(customer=customer, payment_set=payments)
Now, we already have three different queries (some details are left out to keep it simple). Could I reduce it to one? Well, I could have done something like
customers = Customer.objects.filter(...).prefetch_related(
'payments', 'payments__invoices'
)
but now I have to traverse a crazy tree of data instead of having it all laid out neatly in rows, like with SqlAlchemy. Is there any way Django can do something like that? Or would I have to drop through to custom SQL directly?
After reading up on different solutions, I have decided to use SqlAlchemy on top of my Django models. Some people try to completely replace the Django ORM with SqlAlchemy, but this almost completely defeats the purpose of using Django, since most of the framework relies on the ORM.
Instead, I use SqlAlchemy simple for querying the tables defined by the Django ORM. I follow a recipe similar to this
# Setup sqlalchemy bindings
import sqlalchemy as s
from sqlalchemy.orm import sessionmaker
engine = s.create_engine('postgresql://<user>:<password>#<host>:<port>/<db_name>')
# Automatically read the database tables and create metadata
meta = s.MetaData()
meta.reflect(bind=engine)
Session = sessionmaker(bind=engine)
# Create a session, which can query the tables
session = Session()
# Build table instances without hardcoding tablenames
s_payment = meta.tables[models.Payment()._meta.db_table]
s_allocation = meta.tables[models.Allocation()._meta.db_table]
s_customer = meta.tables[models.Customer()._meta.db_table]
s_invoice = meta.tables[models.Invoice()._meta.db_table]
report = session.query(s_payment.c.amount, ...).all()
There is room for a few improvements on this recipe, e.g. it is not very elegant to create an empty instance of Django models in order to find their table name, however, with a few lines of code, I get the full flexibility of SqlAlchemy without compromising with the Django ORM layer. This means both can live happily alongside each other.
One caveat is that SqlAlchemy will not use the same connection as the Django ORM, which means that the view of things may not appear consistent if I use both approaches in the same context. This won't be a problem for me though, since I just want to read a bunch of data from the database.
I tried a few different things but I could not succeed, so maybe it's just not possible.
When I create a sqlalchemy engine with
create_engine('mysql://user#host/database')
it looks like the database is compulsory, while it's not using the sqlite backend.
But since I have to manipulate many different databases on the same server, I would like to avoid creating multiple engines..
Is there a way?
Otherwise what I could is to create a superengine that creates all the needed engines and then redirect to the right engine depending on the database name requested...
One engine pretty much equals one connectable database. See SQLAlchemy docs. You can have as many engines as you want, or you can throw away the engines that you do not need anymore.
Creating the engine one time for each of your databases would be the way I would do it. The you will be able to access them as needed instead of creating an engine then destroying it then recreating etc.