As I configure my Django applications to use containers I'm left with a problem as I try to separate my processes into smaller images. How can I break logic into smaller components that run in their own containers, yet access the same database?
I realize that in a "true" microservices environment I'd want a different database for each service. However, consider a situation where I have a bit of logic that reads data from a database, and produces a CSV file.
I'd like to break out that into a separate type of image, that contains only that logic and gets a special disk mount to write the file to. The rest of the applications remain stateless.
So I'm left with needed two django applications, one that reads and writes data to its database, and another one that I can use to spin up and run reports against that same database.
Option 1: Is that I keep using the same application, where the models have already been defined. I spin up one container for processing, and spin up another container of the same image for use for reporting. While this would work, it seems like it would be a better pattern to isolate the behavior to a specific application.
Option 2: ... What is my option two?
Do you use docker network in your enviroment ?
Suggestion 1: (simple, but fix your situation) duplicate the models.py in two applications. Connect in database using the container database name.
If you need to call a function (def) between containers you can use API's call, using DRF (Django Rest Framework) ou pure Django with JsonResponse.
Do not forget to create tokens to access this "Api's Calls"
Best Regards
Related
I have developed a RESTful API using the Django-rest-framework in python. I developed the required models, serialised them, set up token authentication and all the other due diligence that goes along with it.
I also built a front-end using Angular, hosted on a different domain. I setup CORS modifications so I can access the API as required. Everything seems to be working fine.
Here is the problem. The web app I am building is a financial application that should allow the user to run some complex calculations on the server and send the results to the front-end app so they can be rendered into charts and other formats. I do not know how or where to put these calculations.
I chose Django for the back-end as I expected that python would help me run such calculations wherever required. Basically, when I call a particular api link on the server, I want to be able to retrieve data from my database, from multiple tables if required, and use the data to run some calculations using python or a library of python (pandas or numpy) and serve the results of the calculations as response to the API call.
If this is a daunting task, I at least want to be able to use the API to retrieve data from the tables to the front-end, process the data a little using JS, and send it to a python function located on the server with this processed data, and this function would run the necessary complex calculations and respond with results which would be rendered into charts / other formats.
Can anyone point me to a direction to move from here? I looked for resources online but I think I am unable to find the correct keywords to search for them. I just want a shell code kind of a thing to integrate into my current backed using which I can call some python scripts that I write to run these calculations.
Thanks in advance.
I assume your question is about "how do I do these calculations in the restful framework for django?", but I think in this case you need to move away from that idea.
You did everything correctly but RESTful APIs serve resources -- basically your model.
A computation however is nothing like that. As I see it, you have two ways of achieving what you want:
1) Write a model that represents the results of a computation and is served using the RESTful framework, thus your computation being a resource (can work nicely if you store the results in your database as a way of caching)
2) Add a route/endpoint to your api, that is meant to serve results of that computation.
Path 1: Computation as Resource
Create a model, that handles the computation upon instantiation.
You could even set up an inheritance structure for computations and implement an interface for your computation models.
This way, when the resource is requested and the restful framework wants to serve this resource, the computational result will be served.
Path 2: Custom Endpoint
Add a route for your computation endpoints like /myapi/v1/taxes/compute.
In the underlying controller of this endpoint, you will load up the models you need for your computation, perform the computation, and serve the result however you like it (probably a json response).
You can still implement computations with the above mentioned inheritance structure. That way, you can instantiate the Computation object based on a parameter (in the above case taxes).
Does this give you an idea?
I'm working on a Flask application, in which we will have multiple clients (10-20) each with their own configuration (for the DB, client specific settings etc.) Each client will have a subdomain, like www.client1.myapp.com, www.cleint2.myapp.com. I'm using uWSGI as the middleware and nginx as the proxy server.
There are a couple of ways to deploy this I suppose, one would be to use application dispatching, and a single instance of uwsgi. Another way would be to just run a separate uwsgi instance for each client, and forward the traffic with nginx based on subdomain to the right app. Does anyone know of the pros and cons of each scenario? Just curious, how do applications like Jira handle this?
I would recommend having multiple instances, forwarded to by nginx. I'm doing something similar with a PHP application, and it works very well.
The reason, and benefit of doing it this way is that you can keep everything completely separate, and if one client's setup goes screwy, you can re-instance it and there's no problem for anyone else. Also, no user, even if they manage to break the application level security can access any other user's data.
I keep all clients on their own databases (one mysql instance, multiple dbs), so I can do a complete sqldump (if using mysql, etc) or for another application which uses sqlite rather than mysql: copy the .sqlite database completely for backup.
Going this way means you can also easily set up a 'test' version of a client's site, as well as as live one. Then you can swap which one is actually live just by changing your nginx settings. Say for doing upgrades, you can upgrade the testing one, check it's all OK, then swap. (Also, for some applications, the client may like having their own 'testing' version, which they can break to their hearts content, and know they (or you) can reinstance it in moments, without harming their 'real' data).
Going with application dispatching, you cannot easily get nginx to serve separate client upload directories, without having a separate nginx config per client (and if you're doing that, then why not go for individual uWSGI instances anyway). Likewise for individual SSL certificates (if you want that...).
Each subdomain (or separate domain entirely for some) has it's own logging, so if a certain client is being DOS'd, or hacked otherwise, it's easy to see which one.
You can set up file-system level size quotas per user, so that if one client starts uploading gBs of video, your server doesn't get filled up as well.
The way I'm working is using ansible to provision and set up the server how I want it, with the client specific details kept in a separate host_var file. So my inventory is:
[servers]
myapp.com #or whatever...
[application_clients]
apples
pears
elephants
[application_clients:vars]
ansible_address=myapp.com
then host_vars/apples:
url=apples.myapp.com
db_user=apples
db_pass=secret
then in the provisioning, I set up a two new users & one group for each client. For instance: apples, web.apples as the two users, and the group simply as apples (which both are in).
This way, all the application code is owned by apples user, but the PHP-FPM instance (or uWSGI instance in your case) is run by web.apples. The permissions of all the code is rwXr-X---, and the permissions of uploads & static directories is rwXrwXr-X. Nginx runs as it's own user, so it can access ONLY the upload/static directories, which it can serve as straight files. Any private files which you want to be served by the uWSGI app can be set that way easily. The web user can read the code, and execute it, but cannot edit it. The actual user itself can read and write to the code, but isn't normally used, except for updates, installing plugins, etc.
I can give out a SFTP user to a client which is chroot'd to their uploads directory if they want to upload outside of the application interface.
Using ansible, or another provisioning system, means there's very little work needed to create a new client setup, and if a client (for whatever reason) wants to move over to their own server, it's just a couple of lines to change in the provisioning details, and re-run the scripts. It also means I can keep a development server installed with the exact same provisioning as the main server, and also I can keep a backup amazon instance on standby which is ready to take over if ever I need it to.
I realise this doesn't exactly answer your question about pros and cons each way, but it may be helpful anyway. Multiple instances of uWSGI or any other WSGI server (mainly I use waitress, but there are plenty of good ones) are very simple to set up and if done logically, with a good provisioning system, easy to administrate.
I have a desktop python application whose data backend is a MySQL database, but whose previous database was a network-accessed xml file(s). When it was xml-powered, I had a thread spawned at the launch of the application that would simply check the xml file for changes and whenever the date modified changed (due to any user updating it), the app would refresh itself so multiple users could use and see the changes of the app as they went about their business.
Now that the program has matured and is venturing toward an online presence so it can be used anywhere. Xml is out the window and I'm using MySQL with SQLAlchemy as the database access method. The plot thickens, however, because the information is no longer stored in one xml file but rather it is split into multiple tables in the SQL database. This complicates the idea of some sort of 'last modified' table value or structure. Thus the question, how do you inform the users that the data has changed and the app needs to refresh? Here are some of my thoughts:
Each table needs a last-modified column (this seems like the worst option ever)
A separate table that holds some last modified column?
Some sort of push notification through a server?
It should be mentioned that I have the capability of running perhaps a very small python script on the same server hosting the SQL db that perhaps the app could connect to and (through sockets?) it could pass information to and from all connected clients?
Some extra information:
The information passed back and forth would be pretty low-bandwidth. Mostly text with the potential of some images (rarely over 50k).
Number of clients at present is very small, in the tens. But the project could be picked up by some bigger companies with client numbers possibly getting into the hundreds. Even still the bandwidth shouldn't be a problem for the foreseeable future.
Anyway, somewhat new territory for me, so what would you do? Thanks in advance!
As I understand this is not a client-server application, but rather an application that has a common remote storage.
One idea would be to change to web services (this would solve most of your problems on the long run).
Another idea (if you don't want to switch to web) is to refresh periodically the data in your interface by using a timer.
Another way (and more complicated) would be to have a server that receives all the updates, stores them in the database and then pushes the changes to the other connected clients.
The first 2 ideas you mentioned will have maintenance, scalability and design uglyness issues.
The last 2 are a lot better in my opinion, but I still stick to web services as being the best.
I want create project wide accessible storage for project/application settings.
What i want to achieve: - Each app has it's own app specific settings stored in db - When you spawn django wsgi process each settings are stored in memory storage and are available project wide - Whenever you change any setting value in db there is a call to regenerate storage from db
So it works very close to cache but I can't use cache mechanism because it's serializing data. I can also use memcache for that purpose but i want to develop generic solution (not always you have access to memcache).
If anyone have any ideas to solve my problem i would be really gratefully for sharing.
Before giving any specific advice to you, you need to be aware of the limitations of these systems.
ISSUES
Architectural Differences between Django and PHP/other popular language.
PHP re-reads and re-evaluates the entire code tree every time a page is accessed. This allows PHP to re-read settings from DB/cache/whatever on every request.
Initialisation
Many django apps initialise their own internal cache of settings and parameters and perform validation on these parameters at module import time (server start) rather than on every request. This means you would need a server restart anyway when modifying any settings for non db-settings enabled apps, so why not just change settings.py and restart server?
Multi-site/Multi-instance and in-memory settings
In Memory changes are strictly discouraged by Django docs because they will only affect a single server instance. In the case of multiple sites (contrib.sites), only a single site will recieve updates to shared settings. In the case of instanced servers (ep.io/gondor) any changes will only be made to a local instance, not every instance running for your site. Tread carefully
PERFORMANCE
In Memory Changes
Changing settings values while the server is running is strictly discouraged by django docs for the reasons outlined above. However there is no performance hit with this option. USE ONLY WITHIN THE CONFINES OF SPECIFIC APPS MADE BY YOU AND SINGLE SERVER/INSTANCE.
Cache (redis-cache/memcached)
This is the intermediate speed option. Reasonably fast lookup of settings which can be deserialised into complex python structures easily - great for dict-configs. IMPORTANT is that values are shared among Sites/Instances safely and are updated atomically.
DB (SLOOOOW)
Grabbing one setting at a time from DB will be very very slow unless you hack in connection pooling. grabbing all settings at once is faster but increases db transfer on every single request. Settings synched between Sites/Instances safely. Use only for 1 or 2 settings and it would be reasonable to use.
CONCLUSION
Storing configuration values in database/cache/mem can be done, but you have to be aware of the caveats, and the potential performance hit. Creating a generic replacement for settings.py will not work, however creating a support app that stores settings for other apps could be a viable solution, as long as the other apps accept that settings must be reloaded every request.
I'm building a website that doesn't require a database because a REST API "is the database". (Except you don't want to be putting site-specific things in there, since the API is used by mostly mobile clients)
However there's a few things that normally would be put in a database, for example the "jobs" page. You have master list view, and the detail views for each job, and it should be easy to add new job entries. (not necessarily via a CMS, but that would be awesome)
e.g. example.com/careers/ and example.com/careers/77/
I could just hardcode this stuff in templates, but that's no DRY- you have to update the master template and the detail template every time.
What do you guys think? Maybe a YAML file? Or any better ideas?
Thx
Why not still keep it in a database? Your remote REST store is all well and funky, but if you've got local data, there's nothing (unless there's spec saying so) to stop you storing some stuff in a local db. Doesn't have to be anything v glamorous - could be sqlite, or you could have some fun with redis, etc.
You could use the Memcachedb via the Django cache interface.
For example:
Set the cache backend as memcached in your django settings, but install/use memcachedb instead.
Django can't tell the difference between the two because the provide the same interface (at least last time I checked).
Memcachedb is persistent, safe for multithreaded django servers, and won't lose data during server restarts, but it's just a key value store. not a complete database.
Some alternatives built into the Python library are listed in the Data Persistence chapter of the documentation. Still another is JSON.