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I am new to Google App Engine. I am building a web app using python and django rest api framework. I am using cloud bigtable, cloud sql and cloud storage for my databases and storage. I wanted to know if I have to use Google App Engine Apis or can I build my own in django to read and write data to the databases and get files from cloud storage? I want to try to keep costs low and not lock in to Google App Engine.
You can use vanilla DjangGAE to do everything you'd mentioned. A good starting point
It's worth mentioning that there are a few notable limitations. Those are also listed in the site I'd linked to.
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After building a flutter web app with
flutter build web
I want to deploy this with dango server, what should i do?
I'm assuming that your backend is an API Rest and does not render the HTML.
The "right" way will be to have a service for the SPA, and another for the API. For example, with docker, droplets, kubernetes, DO and Heroku.
Another way that I'm thinking is... you specified a route (like example.com/) to serve the flutter web project (I mean the HTML), and the other routes can be the endpoints.
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I am thinking of creating a content delivery web application using Django with a MySQL database, and after reading the docs a bit I noted that it is possible to create multiple apps in the same project/site directory.
It may or may not apply to what I want to do, but I was wondering what the motivation behind this architecture is. Why would I want multiple web apps in one site?
For example, Youtube was built around the Django framework, but the entire experience works seamlessly as one application? Is Youtube actually one large web application, or does the project use many applications packaged as one product? If so, why would that be a better option?
There's a good explanation about it in the django docs here and here.
From my own experience: it helps you to organize your code. If you're planning to create a small application it may not need more than one django application. But it you want to create medium or large applications you can take advantages of this approach. Some of useful cases:
Authentication
Blog
Split your RESTFul API based on resources (e.g. clients, invoices, users, etc)
Logging
Chat
Hope that helps a bit.
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i have to develop a Real Time Application that supports thousands of users with Python. The question: decide which framework and architecture use.
The first option is:
Falcon only (Admin and API)
The second:
Tornado manage request, Admin runs Django and API runs Falcon
Another problem is database. Could be one only RethinkDB (1st option), or two, with Postgresql (2nd option).
Which of these option is the best? Should try something different?
PD: One fancy implementation could be with Tornado sockets
I think your question needs to be more specific.
Without more detail about the application my general suggestion would be to not complicate things by using many frameworks, just pick one that does everything you need.
Unless you are planning to design an asynchronous API forget about Tornado. If your application is very small and has a simple API then you could consider Falcon because of it's short learning curve. Otherwise I'd suggest going with Django.
As for the DB, it's nearly impossible to provide a suggestion without understanding what type of data you are planning to store? What is your expected read/write ratio? Do you already have operational experience with any DBs?
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I am currently developing an app that allows people to watch videos. However, these videos are stored in Google Cloud bucket. My back-end is in Python. I can currently grab the credentials in Python then download the video, but cant get the video from Python to the iOS app. Or i could stream the video straight to the phone from the server with a HTTP request, however I need the access token which for the life of me I can not find. What is the best approach for streaming these videos?
Streaming video through your backend is not very efficient - it's slower and you pay for extra instance hours. A better option is to stream directly from the Cloud Storage bucket.
If your videos are not publicly accessible, the best option is to create a signed URL using your backend, and then pass it to the client. The client can use this signed URL to access content directly from the Cloud Storage.
You may find this example useful.
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I have few machine learning models which I have already trained (size in 300MB - 4 GB). Now I want to query them using a rest API. I build my APIs in flask which require these models to be in memory. Is google app engine suitable for it? Or should I use compute engine instead?
it's unsuited for appengine because of reasons like:
appengine does not have instances with so much ram (unless you use flexible which is basically the same as gce option).
even if it did, the instance can go away which requires to reload data to memory constantly (thou it could be on memcached)
time restrictions on frontend instances will make it very unlikely you can even get time to load data to memory, less being able to analyze the data. a backend type of instance could do it, but will be harder than doing it from a regular VM.
good luck loading the libraries you need, as none should write to file storage, even for a temp file.
thus compute engine is the correct place.