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Setup for running simple python scripts on (Nginx) web server?

I would like to run a couple of very simple Python 3 scripts on the web. As an example, say, the script just reads certain parameters from the URL, sends an email and prints out a simple HTML page saying "success".
I have a virtual private server with Nginx, so I am free to setup the best framework.
My question is: what is the state-of-the-art setup to do this?
More particularly: what do I need to install on my server for Nginx and what do I use in my Python scripts for e.g. reading the URL content? My idea is, that once the server setup is done, I can just put any new script_xy.py file into some directory and it can be accessed using the URL of the script, without a full blown deployment for each script.
Flask If I were to use Flask (or Django), each new script would need its own, continuously running process and its own Nginx setup. That seems like a total overkill to me. Another alternative is web2py, is it the same here or would that be an idea?
CGI 20 years ago I used to program such simple things as Perl scripts using CGI. I read this can be done in principle with Python, but CGI is slow. Then there is Fast CGI. However, my impression was that this is still a bit outdated?
WSGI WSGI seems to be the state-of-the-art alternative to CGI for Python. What python modules would I need to import in my script and what would be the setup for Nginx?
Something else? As you see, I might just need a few hints on what to search for. I am not even sure if I need to search for "Python web framework" or "Python server" etc.
Any help is greatly appreciated.
Thanks a lot for your ideas!
juxeku

Need advice on how to incorporate Python into an Azure, specifically an ASP.NET web application environment

Need advice on how to incorporate Python into an Azure ASP.NET web application environment. Please excuse this question but I am new to Azure and I'm not clear on how to proceed. Every option that I look into looks promising but they all seem to have their own issues. Below is a more thorough explanation but the deal is that I have an Azure account with all kinds of goodies, a full fledged ASP.NET (C#) web app running via App Service, I am new to Azure (but not Python), and I'm hoping to add Python functionality to this whole setup. In short:
I want to add Python to this setup mainly to run scheduled jobs and also to trigger Python code from ASP.NET web form submissions
ideally I want a solution that resembles a non-cloud setup. I know this sounds silly but I'm finding the cloud/Azure functionality to be nuanced and not straightforward. I want a place to put a bunch of Python scripts, run, edit, schedule and trigger them from ASP.NET
for example: I created a WebJob that runs manually and from the documentation it wasn't clear how it should be called. I just figured out that you need to POST with Basic Auth (and the credentials provided).
!Also, Azure CMD does NOT like files with 'underscore _' in them! You cannot submit a Web Job with a py file with an underscore nor can you write output with a file with an underscore
!Also, I don't see an option for this Web Job to run Python 3.6.4 (which I installed via extension). Right now it is using 2.7.15...
!Also, CRON expression in Azure has six *, not five plus a command. Again, more weird stuff to worry about
I tried these instructions but the updates to the web page's Web.config file breaks the ASP.NET web pages
ideally the most cost effective option
Any info is greatly appreciated
MORE DETAILED EXPLANATION
Currently I have an ASP.NET site running via Azure App Service and I would like to add Python scripts and possibly Flask/Rest functionality. Note that I am not expecting to serve any content via Python and will largely be running Python scripts either on a scheduled basis or call them from ASP.NET. As a matter of fact, and this is an important point, I'm hoping to have ASP.NET trigger/run a Python script when a web form is submitted. I realize that I could get a similar effect if I make a web call to a Rest api that is running Python. In any event, I can't tell if I should:
add a Python extension to the current App Service running the web page (I tried this) OR
I did install Python 3.6.4 and some packages via pip
These instructions were useful, however the updates to the web page's Web.config file breaks the ASP.NET web pages
set up a VM that will have all of the Python code (but how can I have the .NET web page(s) call the Python in the VM?) OR
use Azure functions (I'm completely new to this and must admit that I prefer to have my old school Python environment instead although I see the benefit of using functions. But how do you deal with logging and debugging?)
or what about a custom windows container (Docker)?
This requires installing VS Code and that is OK but I'm looking for a solution that another user can get into with as few interruptions as possible
The idea is to ramp up the use of Python although, like I said, I don't expect Python to be serving any of the web content. It will be used to run in the background and to run scheduled jobs. What is the most robust and hopefully easiest way to add Python functionality to Azure (most importantly in a way to be able to trigger/use Python from an App Service running .NET?)? I've searched online and stack overflow so far with interesting finds but nothing to my liking.
For example, the following link discusses how to schedule WebJobs. I just created a manual one and when I called the webhook I got the message: "No route registered for '/api/triggeredwebjobs/TestPython/run'" How to schedule python web jobs on azure
The Docker method looks very promising, however, I'm looking for a simple solution as there is another person who will be involved in all of this and he's busy with other projects
Thank you very much!

I found a solution, though I'm open to more info. Like I mentioned in my post, I used the 'add extension' tool to add Python 3.6.4 to my Azure (installed in D:\home\python364x64).
Then I installed a bunch of packages via pip, these installed into D:\home\python364x64\Lib\site-packages.
I created a Python folder in webpages\Python where I put my scripts.
Finally, in ASP.NET I used the Diagnostics.Process call to run my code in ~\webpages\Python\somecode_2.py
The main issue is that Azure came with Python 2.7.15 installed. And for some reason when my Python code got executed it was using 3.4 (where that version came from beats me). So for each script, I had to create an _2.py version where I simply did the following in order to call the original script via Python 3.6.4. Looks a little nasty but it works. So like I said, I would welcome more info for ways to do this better...
--
import os<br>
os.system("D:\\home\python364x64\python.exe SomePython.py {0}".format(add arguments here)

How to expose an NLTK based ML(machine learning) Python Script as a Web Service?

Let me explain what I'm trying to achieve. In the past while working on Java platform, I used to write Java codes(say, to push or pull data from MySQL database etc.) then create a war file which essentially bundles all the class files, supporting files etc and put it under a servlet container like Tomcat and this becomes a web service and can be invoked from any platform.
In my current scenario, I've majority of work being done in Java, however the Natural Language Processing(NLP)/Machine Learning(ML) part is being done in Python using the NLTK, Scipy, Numpy etc libraries. I'm trying to use the services of this Python engine in existing Java code. Integrating the Python code to Java through something like Jython is not that straight-forward(as Jython does not support calling any python module which has C based extensions, as far as I know), So I thought the next option would be to make it a web service, similar to what I had done with Java web services in the past. Now comes the actual crux of the question, how do I run the ML engine as a web service and call the same from any platform, in my current scenario this happens to be Java. I tried looking in the web, for various options to achieve this and found things like CherryPy, Werkzeug etc but not able to find the right approach or any sample code or anything that shows how to invoke a NLTK-Python script and serve the result through web, and eventually replicating the functionality Java web service provides. In the Python-NLTK code, the ML engine does a data-training on a large corpus(this takes 3-4 minutes) and we don't want the Python code to go through this step every time a method is invoked. If I make it a web service, the data-training will happen only once, when the service starts and then the service is ready to be invoked and use the already trained engine.
Now coming back to the problem, I'm pretty new to this web service things in Python and would appreciate any pointers on how to achieve this .Also, any pointers on achieving the goal of calling NLTK based python scripts from Java, without using web services approach and which can deployed on production servers to give good performance would also be helpful and appreciable. Thanks in advance.
Just for a note, I'm currently running all my code on a Linux machine with Python 2.6, JDK 1.6 installed on it.

One method is to build an XML-RPC server, but you may wish to fork a new process for each connection to prevent the server from seizing up. I have written a detailed tutorial on how to go about this: https://speakerdeck.com/timclicks/case-studies-of-python-in-parallel?slide=68.

NLTK based system tends to be slow at response per request, but good throughput can be achieved given enough RAM.

How to embed a Python interpreter on a website

I am attempting to build an educational coding site, similar to Codecademy, but I am frankly at a loss as to what steps should be taken. Could I be pointed in the right direction in including even a simple python interpreter in a webapp?

One option might be to use PyPy to create a sandboxed python. It would limit the external operations someone could do.
Once you have that set up, your website would take the code source, send it over ajax to your webserver, and the server would run the code in a subprocess of a sandboxed python instance. You would also be able to kill the process if it took longer than say 5 seconds. Then you return the output back as a response to the client.
See these links for help on a PyPy sandbox:
http://doc.pypy.org/en/latest/sandbox.html
http://readevalprint.com/blog/python-sandbox-with-pypy.html
To create a fully interactive REPL would be even more involved. You would need to keep an interpreter alive to each client on your server. Then accept ajax "lines" of input and run them through the interp by communicating with the running process, and return the output.
Overall, not trivial. You would need some strong dev skills to do this comfortably. You may find this task a bit daunting if you are just learning.

There's more to do here than you think.
The major problem is that you cannot let people run arbitrary Python code on your webserver. For example, what happens if they do
import os
os.system("rm -rf *.*")
So clearly you have to run this Python code securely. But then you have the problem of securing Python, which is basically impossible because of how dynamic it is. And so you'll probably have to run the Python shell in a virtual machine, which comes with its own headaches.
Have you seen e.g. http://code.google.com/p/google-app-engine-samples/downloads/detail?name=shell_20091112.tar.gz&can=2&q=?

One recent option for this is to use repl.
This option is awesome because the compilers are made using JavaScript so the compilation and execution is made in the user-side, meaning that the server is free of vulnerabilities.
They have compilers for: Python3, Python, Javascript, Java, Ruby, PHP...
I strongly recommend you to check their site at http://repl.it

Look into LXC Containers. They have a pretty cool api that you can use to create lightweight linux containers. You could run the subprocess commands inside that container that way the end user could not mess with your main server.

Deploying matlab app on the web using python

Hi I want to deploy a matlab application on the web using python. Is there a way to do it.I have converted my application into jar files (java classes) as per the documentation on math works site. Can someone point me in the right direction to go ahead

The fact that your Matlab code is packaged up as Jars may not help that much here, at least not with pure Python.
There are a few ways you can take code written in Java and expose it to Python.
Jython
If you are willing to give Jython a shot this may be a really easy way to provide a Django interface to your jars.
Basically you'll get to write a normal Django App and also use Jython to work natively with your Jars. This could be the best of both worlds assuming you aren't tied to CPython.
Django-Jython
Java Compatibility Interfaces
On CPYTHON either of the following projects will help you work with the code in your Jar files:
JCC: Create a Python extension module that wraps your Jar file
JPype: Provides an API for running the JVM and calling into code running in that JVM from Python.
Separate Process:
If you have a standalone program written in Matlab (really any language) you could execute it as a child process of your Django application. You'd look into a simple web form in Django that allowed you to submit values to be inputs to this process and then in your view (after validating the form) you'd do something like:
command = "mymatlabprogram.exe %s"%(arg1,)
process = subprocess.Popen(command.split())
stdout, stderr = process.communicate()
Assuming that worked you could pull answers out of stdout or error messages out of stderr. You could serve an image created by that process, etc. Once something like this is working you could look into celeryd to extract the subprocess stuff from your web app.
The advantage of working with a separate process is that you isolate bugs in your Matlab code from breaking your web application and vice versus. The disadvantage is you have to serialize everything and work with multiple times between the client's browser and your web app, between the web app and the executable, and back to the client.