Is it possible to use memorystore with python 3 on GAE standard env? From faq at https://cloud.google.com/memorystore/docs/redis/faq it is clear that it can’t be use with GAE standard but since restrictions are different between python 3 and 2, it might be usable? Python 3 env is not supporting mecache right now and redislab requires another account /subscription managed.
Unfortunately currently it is not possible to access Memorystore from AppEngine Standard environment (even with python 3).
Please see the relevant links: https://cloud.google.com/memorystore/docs/redis/redis-overview#connecting
Also this is being tracked as a feature request here: https://issuetracker.google.com/issues/112411170
It is now available through any standard Redis client, check here https://cloud.google.com/memorystore/docs/redis/redis-overview#connecting
Related
My website was built using Google AppEngine, DataStore and Python2.7. It’s no longer working This site can’t be reached. I need to migrate to Python3 but I cannot identify which migration guide is best suited for me. Can anyone point me to the correct set? I would like to get it running as quickly as possible (I only have one hour a day to try to correct it -- I have an unrelated full-time job).
Migration guide
Google provides a step-by-step migration guide especially for AppEngine which you should follow.
Additionally, you will find lots of useful links there where you can read about the differences between Python 2 and Python 3 and the various migration tools available. Depending on your application those tools might even be able to do the migration (more or less) automatically for you.
Please note: This is the migration guide for the AppEngine standard environment. If you don't know what you're using, you're most likely using the standard environment. While some steps will differ when using the flexible environment, migration of the code base as described in the guide will always be required.
Video: Python 2 to 3: Migration Patterns & Motivators (Cloud Next '19)
There also is a recording of a talk by the Google Cloud Team on migration from Python 2 to 3 on YouTube.
Still having issues?
Migrating from Python 2 to 3 is a well-known problem and there is tons of information available on the internet. Most likely the problems you face have already been solved by someone, so a Google search for a specific problem will likely give you a working solution.
I would like to migrate from vm to app engine with an node.js app.
How can i use session in this case, I know i should use 'google memcache' to make an cross vm session but how should i do it?
I saw that there are some node module that can store the session in memcache db but the google memcache is different.
Is this the best solution? or should i use mysql db ? i care a lot about the performance of this app.
Thank you for the help.
For the reference:
https://github.com/GoogleCloudPlatform/appengine-nodejs
You don't need to use the appengine-nodejs project here. You automagically get a memcached instance with your app running at memcache:11211, and you can use the standard memcached driver to use it. I put together a quick demo of using express and connect-memcached here:
https://gist.github.com/JustinBeckwith/e25983cd50ab21a6b8ad
You can see it running here:
https://express-memcached-demo.appspot.com/
We will work on getting our docs updated. Hope this helps!
Unless you signed up for the Google App Engine flex memcached alpha, the best (or at least most well documented) way to access memcached on App Engine for a Node.js application is documented here: https://cloud.google.com/appengine/docs/flexible/nodejs/using-redislabs-memcache
I set up my Heroku instance to have Memcached, so now I have the MEMCACHE_PASSWORD, MEMCACHE_SERVERS and MEMCACHE_USERNAME env variables. How do I use them with any of the existing node.js memcached libraries? They all seem to take in just a host and port (I'm assuming the port is the default 11211?).
Thanks
As mentioned above, both Memcache addons on Heroku only support the binary protocol. I wrote a library, MemJS, that works with these addons (supports SASL with the binary protocol and recognizes the Heroku environment variables out of the box).
As of today, there is no Node library available that supports this scenario. Heroku's memcached instances use SASL for authentication. None of the currently available libraries support this, and there doesn't seem to be much momentum to add support, either.
If you want to try to implement this yourself, it might be worth taking a look at sasljs, which is a Node binding around GNU SASL. Your best bet would probably be to fork node-memcached and add SASL support there.
https://github.com/elbart/node-memcache
var client = new memcache.Client('11211', 'http://xxxx:xxxxx#mc10.ec2.northscale.net');
I am considering ways to read/modify large Excel spreadsheets with formula support in python, on Google App Engine. I am fairly unfamiliar with how COM works but I was wondering if anyone has successfully implemented pywin32 on GAE - or whether there are inherently problems with doing so, or if it's just a bad idea in general.
It seems like the only possible solution for Python (xlrd has no formula support) but if it doesn't work, I will resort to learning Java and trying JExcel API.
Any insight would be appreciated!
Google's servers are not running Windows, so no, there's no way whatsoever to use any Win32 APIs.
If you have to use GAE then you may process some stuff on a windows machine. You can use Pull Queues to lease tasks from GAE process them and then add them to Push Queues that will store the data in GAE
I wanted to try cloud computing.
I went to PythonInfo Wiki and found links to Google App Engine and PiCloud (which uses Amazon Web Services). However, it turns out that neither of them supports Python 3 (at least at first glance). I would hate to port my code back to Python 2.7.
Does anyone know if there's an easy way to use cloud computing in Python 3 (I don't care who the provider of computing power is)?
With apologies for the self-promotion, my company are working on a cloud-based python environment. We should be able to support all flavours of Python. More info here:
http://www.pythonanywhere.com/