I have a doc project where I have to test a massive number of urls and links.
To do that I was using python 2 linkchecker.
I upgraded to django 2.2 and python 3.6 and I am using a go binary called muffet (https://github.com/raviqqe/muffet).
linkchecker was gentle with the server, muffet on the other hand is more brutal (even with timeout options and other settings).
The problem I have is after some time, the requests timeout and the django local server crashes.
I heard about some kind of queue or cache for the local django server.
Is anyone knows how to increase the django limit in order not to DDOS myself while I am running my tests before deployment (this tool is not running in production).
Or any out of the box thinking to solve this.
Just for you to know, I run the server in background, and call the tool on the localhost url.
(from another terminal)
Thanks
Edit: https://github.com/django/django/blob/fba5d3b6e63fe4a07b1aa133186f997eeebf9aeb/django/core/servers/basehttp.py#L58 this seems something I can play with?
It seems, like using a proper server within the container and runing muffet command like muffet -t 30 -c 30 http://127.0.0.1 solve the issue.
Thanks to #Antwane to point me in the right direction ;)
Related
My team and I have set up an account with Hostinger and have a VPS set up with its own domain. Our current Operating System is CentOS 7 64bit with Webmin/Virtualmin/LAMP and we have Webmin set up as our Cpanel. As of right now we have our HTML pages showing but our Python code is not working.
We used SSH to download Python3, MongoDB, pymongo, and flask, but are still having trouble getting our Python code to work on our web application. From here we are unsure what to do and need guidance on what our next steps should be. Thank you in advance for any help given.
It sounds like what you've gone for on your VPS is a web hosting setup rather than a bare metal VPS setup. I can see why you think you'd want web hosting, but in reality Flask works differently in that it is its own application which needs to run rather than being served like an HTML page.
There is an excellent tutorial on how to do this here. It is designed for Ubuntu (which is a good setup if you are starting fresh) but there are also versions for different linux flavours.
The Issue
I am using my laptop with Apache to act as a server for a local project involving tensorflow and python which uses an API written in Flask to service GET and POST requests coming from an app and maybe another user on the local network.The problem is that the initial page keeps loading when I specifically import tensorflow or the object detection folder within the research folder in the tensorflow github folder, and it never seems to finish doing so, effectively getting it stuck. I suspect the issue has to do with the packages being large in size, but I didn't have any issue with that when running the application on the development server provided with Flask.
Are there any pointers that I should look for when trying to solve this issue? I checked the memory usage, and it doesn't seem to be rising substantially, as well as the CPU usage.
Debugging process
I am able to print basic hello world to the root page quite quickly, but I isolated the issue to the point when the importing takes place where it gets stuck.
The only thing I can think of is to limit the number of threads that are launched, but when I limited the number of threads per child to 5 and number of connections to 5 in the httpd-mpm.conf file, it didn't help.
The error/access logs don't provide much insight to the matter.
A few notes:
Thus far, I used Flask's development server with multi-threading enabled to serve those requests, but I found it to be prone to crashing after 5 minutes of continuous run, so I am now trying to use Apache using the wsgi interface in order to use Python scripts.
I should also note that I am not servicing html files, just basic GET and POST requests. I am just viewing them using the browser.
If it helps, I also don't use virtual environments.
I am using Windows 10, Apache 2.4 and mod_wsgi 4.5.24
The tensorflow module being a C extension module, may not be implemented so it works properly in Python sub interpreters. To combat this, force your application to run in the main Python interpreter context. Details in:
http://modwsgi.readthedocs.io/en/develop/user-guides/application-issues.html#python-simplified-gil-state-api
I understand that this is never to be done. But I have a situation where I need to get something done real quick. I have to do a website where may be 200 people would register for an event. I need to present a simple registration form. Very basic functionality, register and view list of registrants. Very few hits. It would be live for about a month or so.
I know a little bit of Django which can allow me to put together this thing quickly. However, I have only worked with the Django development server.
My problem is setting up Apache to work with Django. I understand that, for Django, I need mod_wsgi installed. I have a VPS but mod_wsgi is not installed. I have asked my hosting provider to install it for me. Even if I can get mod_wsgi installed, it appears that it may take me some time to configure it and it may take a while.
I have the following questions.
Can I run this website on the Django development server? Will it hold up for very light traffic?
If I do, how do I get traffic to go from port 80 to the development server port. From the landing page, I can have the port number added to all the subsequent URLs.
I would also appreciate some guidance on getting Django to work with mod_wsgi.
Thanks
I use cloud9 for development. It is essentially a cloud ubuntu 14 virtual box, so it gives you a real url when django server is running (on port 80). Another use case of cloud 9 is for university classes, which is similar to your event use case. You can go there and setup your django project for free and people can find the page normally. But there are some restarts in your workspace that prevents it to be real server. If you pay 20 bucks per month they give you 2 premium workspaces that they assure that this does not happen ever. But I'm not sure if this is a good idea. I could not even imagine what kind of errors would you get if all 200 people chose to login at the same time, for example.
Another way to go is making a free amazon AWS account (or digital ocean) and doing your deploy there. AWS have 1 year free trial if you run only one microinstance with a particular setup which is plenty of time for your use case. I open the instance on AWS and SSH into it with cloud 9, so it feels like developing even in production. I'm far from a devops expert but I could deploy Nginx, gunicorn, django in AWS following this tutorial. You can do it too for sure, but is a lot of work.
Left my prefered choice for your use case to the end: pythonanywhere. It has free trial and it's really easy to setup. You follow some very basic steps (doing stuff with mod_wsgi that I still dont understand) and make it work in minutes. It's a whole business dedicated to serve python programs.
Hope this helps
I'm trying to develop a database manager in Django and want to develop and deploy it in Docker. As my IDE, I'd like to continue using PyCharm, but I'm having trouble understanding how it interacts with Docker.
I am new to Docker and its integration in PyCharm. My system runs Windows 10 and Docker for Windows.
I already tried using PyCharm's remote interpreter, but I have to activate the port forwarding manually (using Kitematic), since PyCharm does somehow not forward the exposed port automatically.
I also tried using a "Docker Deployment" run configuration. However, I can't get requests to localhost:8000 to get through to the Django server. All I get are empty response errors.
(Note: The bold issue was addressed in the accepted answer.)
It would really help me to have an explanation of how PyCharm's two options (remote interpreter and docker deployment) really work and ideally have an up-to-date tutorial for setting up Django with it. Unfortunately I could only find outdated tutorials and JetBrain's help pages are either outdated or do not explain it in enough detail.
Could someone help me out and guide me through this or point me to good resources?
Assuming you have the latest Docker (for Mac or for Windows) along with an updated version of PyCharm, you could achieve the port forwarding (binding) this way:
Create a new run configuration
Select your Docker server in the Deployment tab. If nothing shows, create a new one. Test that it actually works by clicking View > Tools Windows > Docker and connecting to the docker server. You should see the existing images and running containers.
In the Container tab, make sure to add the right Ports bindings.
An important note
Make sure that you are running your Django server on 0.0.0.0:8000 and not localhost:8000
I am developping a django app on Windows, SQLite and the django dev server . I have deployed it to my host server which is running Linux, Apache, FastCgi, MySQL.
Unfortunately, I have an error returned by the server on the prod while everything ok on the dev machine. I've asked my provider for a pre-production solution in order to be able to debug and understand the problem.
Anyway, what are according to you the most likely errors that can happen when moving a django app from dev to prod?
Best
Update: I think that a pre-prod is the best way to address this kind of problem. But I would like to build a check list of what must be done before to put in production.
Thanks for the very valuable answers that I received until now :)
Update: FYI, I 've implemented the preprod server and the email notification as suggested by shanyu and I can see that the error comes from the smart_if templatetag that I am using on this new version. Any trick with template tags?
Update: I think I've fixed the pb which was caused I think by the Filezilla FTP sending. I was using the "replace if newer" option which I guess is causing some unexpected results. Using the "replace all" option fix the issue. However, it was an opportunity for me to learn more about deployment. Thansk for your answers.
Problems I typically have include:
Misconfigured productions settings, whether in my production localsettings.py, wsgi/cgi, or apache site files in /etc/sites-available
Database differences. I use South for migrations and have run into some subtle issues when performing my migration on PostgreSQL when it worked smoothly in sqlite.
Static file hosting since I cheat and use the Django server in development
Permissions, both on the file system and within the database
Rare, but possible, network issues preventing me from getting my dependencies, whether on PyPi or some 3rd party site
Ways that I have mitigated these issues:
Use the same database in production and development (in your case, MySQL everywhere)
I've found it is useful to have a "test" environment which mimics production in every way possible (it can be on lower end hardware, or even the same machine). This way, if there are any issues in this "production-like" enivornment, I can solve them without taking my production server offline.
Script everything for repeatable deployments. I use fabric, but zc.buildout or Paver would also work. These tools help reduce typos while deploying and reduce the time to deploy my app.
Use version control (mercurial, git, subversion) and a schema migration tool (like South), so if something does go wrong when you deploy to production, you have the possibility of backing out the changes and allowing production to run on the old code with the old database schema.
I haven't set up an "egg proxy" yet, but I am considering it, to avoid issues when downloading dependencies.
I've found pip's freezing dependencies to be useful, in case a new, incompatible change to a library occurred since I downloaded it initially
Use a web testing framework like Windmill or Selenium to test my application in my "test" environment, so that I can get a lot of test coverage of my system very quickly.
Regarding your case, I can think of 2 simple things that may help you:
You can enable Django to send messages when exceptions occur giving details about them. Look at here for details.
You'll be better off if you set up a test environment on the prod server (say, test.example.com) so that you can check if things will go smoothly or not before you deploy the app.
I believe these were the podcasts I listened to recently (from Pycon 2009):
Locate Django in the Real World (PyCon 2009):
http://advocacy.python.org/podcasts/pycon.rss
Parts 1 to 3
Very good introduction to designing your apps for deployment, in particular for reuse and redeployment.
Regs.