Building Large Flask Apps in the Real World
etscrivner.github.io
etscrivner.github.io
I'm 3 years in to a project where I've taken the approach of having my "app" as its own package. Flask is then a thin wrapper that instantiates the app and then exposes the views to talk to it. I handle validation / sessions / config etc within Flask.
It's extremely flexible. I have some stuff that runs off as worker processes. No problem - the core is the same, the wrapper around it is different. I also have a boot.py that I can call so I'm working directly with the app in ipython (again, it's a wrapper that starts the app).
I'm currently reworking the structure for capacity planning, which is mostly just a matter of splitting the Flask app into 2 apps for handling different parts of the work.
Because my core app is decoupled from the web app it's all really easy to do.
Flask/Web
Deal with sessions, authentication, caching, templating, logging etc here. Fires up an instance of the App and keeps it around for the duration of the life of the Web instance. I actually have an API in here that looks like what you'd expect in most other web apps. It does the validation / error handling etc. In terms of manipluating the data, I'm not a total purist - the API is allowed to load up the SQLA models and make changes. If there's a more complex operation going on though, it will live inside the next layer down.
App
Deal with remote services / data models / db connection. I guess on the outside you might call this a "service layer". A surprisingly large amount of this is data persistance management. The model I use is to put the data access stuff just off to the side at the top level of the app. Nothing in here knows anything about things like web frameworks. This is important. In other places in the system, this same App is used by RQ (worker instances taking on work via a redis queue). There's another web app that uses it for administrative tasks. I can boot it up to work with it in ipython (I do this a lot). Oh, and I don't manage the db life-cycle here. Whichever layer sits above this determines when it's ok to commit transactions. If something goes wrong here we raise app specific expections - the layer above can handle those and relay them as appropriate.
Core
In the very core I have "pure" algorithmic stuff (for context - http://www.countfire.com is effectively an image recognition app). Really this is just one component that the App happens to be using. If the App wants to talk to this, it needs to create the data structures that the core defines. At various borders I often have mappings from the objects in the current local world to versions for the created to talk to the layer below (ps I like namedtuples).
It's a lot more complex than all this, each of these layers has more sub layers etc. And really, what I've called the Core is a sublayer of the App (in my case there's a well definied algorithmic chunk that I think of as the core so it's in its own package - it stands alone as its own library).
There's no real way of knowing where you'll draw lines between the layers when you start but I have a few rules. Any bit of code should be given the bare minimum of data required to do its work. At borders map local data to data for the next layer. Make sure the stuff going into the current layer is really there because it needs to be there. Be a pragmatist - things will change, you'll pull stuff out into submodules. By following the other rules hopefully refactoring won't be too painful.
There are plenty of examples in every language where a web framework turns into a web service + caching + session management + ORM + whatever else you can think of then you use all of those features and now you're inflexible, can't easily add new interfaces without seriously rewriting the old and good luck if you need to move away from that web framework for whatever reason.
If I understand this correctly, how do you define something like a redirect or abort within your own views?
For your specific question - all routing is done from within the top / Flask layer (as is redirecting / aborting). My App layer does not have any Flask stuff in, at all, ever.
Why did you decide to go this way? Is it because the user-facing parts of the app (the bits where Flask helps) are only a small part?
I mean, if I'm developing a CRUD app with small amounts of supporting non-interactive code, I can't see a reason not to use Django (and put the other stuff in manage.py commands).
On the other hand, if I were to write something like an analytics system, which had a web UI for users to inspect and play with results, I can see that I'd feel constrained by Django when writing the non-web parts.
As someone who loved getting started with Flask, but then switched to Django after getting stuck without a good structure, I'd really like to understand whether the choice of Django vs. Flask should be made based on individual preferences (comfort of an imposed structure vs. freedom without it) or based on the type of project (mainly web, or mainly non-web)?
Vanilla is the holy grail. You mention manage.py commands but why not if __name__ == '__main__': do the thing. Or the multitude of tools like invoke (https://github.com/pyinvoke/invoke) and click (http://click.pocoo.org/5/). I digress...
Django is great for a monolith. Stack Django REST Framework on top of it and you're even bigger and nastier. I would never use it again because the amount of time spent bending it to my will often exceeds the time I'd spend building my own system. Fair warning, I have been using Django in production since version 0.96 and have built many companies on it. After ten years of building web apps, using every MVC under the sun, and working with every size/shape team under the sun you really start to appreciate simple things that compose well together. They're easier to reason about. They're easier to replace. They're easier to pull out and turn into a standalone library or shared service. Are you hitting the wall with one tiny part of your app? Replace it with something written in an entirely different language and communicate via JSON, or over a message bus. Not everything can be mapped to a WSGI request/response.
I am so glad aidos has the top comment on this post because his/her style is what we should all be aiming for from the get-go.
I'd definitely suggest reading up on the SOLID –https://en.wikipedia.org/wiki/SOLID_(object-oriented_design) – principles. Furthermore, the adapter concept is often explained with scary Java code samples, but the core of it is wonderful. Essentially you should consider your API as a vanilla system in your language of choice and you build adapters which then allow for external services to communicate. One adapter could be HTTP (via Flask perhaps) for a front-end website. One adapter could be HTTP but one that only speaks JSON, which you might serve under api.yourdomain.com. Another adapter might be via a queue system which allows for arbitrary commands from an external source to get written to a durable queue, so that they can be replayed later.
I took some melatonin so at this point I feel like I am just babbling and about to fall asleep.
tl;dr build things without frameworks, use your language well, be vanilla, compose tiny things to build big things.
I fall mostly into the second camp. For non-trivial functionality I will (in order of preference) 1. Find a good existing framework or library 2. Refactor something I've already written to be reusable 3. Develop something specifically for the task at hand.
Even when I plump for 3 I'll be thinking about how it could be made reusable - I just postpone actually putting any effort in that direction on the grounds of YAGNI.
I love SQLAlchemy. Maybe things have changed (I'm a jaded Django 0.96 refugee), but as soon as you take away the Django ORM, you lose the admin and then all your advantages just sort of fall away. But really, that's my personal preference with a lot of bias from being there in the early Django days. I think the Django Rest Framework is absolutely awesome, and it almost pulled me back to Django but it just took my first morning of screwing around with some config to remind me of why I prefer the simple frameworks.
And actually, I could already feel with feature creep there. I wanted to have a remote filestore, so there's a Django plugin for doing it. But a) why is my framework in charge of how I store the files for my application (that means I need Django loaded in ipython!) and b) it didn't work quite how I needed and I could see storm clouds brewing.
In terms of general structure, if you know you're building something bigger, I'd suggest at least splitting the web bit and everything else as soon as possible. For me, leaving the web app to handling routing / validation / marshalling / sessions / templating etc feels like the right abstraction.
I look back on any apps I've built / worked on that a) started off as a CRUD system and b) are still going and most of them are a mess. Even if they're clean, the core business logic is mixed up with the standard framework structure. If you really work at it you can separate things out in the code, but my feeling is that by starting with an app that doesn't know about the web, you'll make it much easier to discover where that abstraction lies.
TLDR; use Django if it works for you. Whatever you choose, try to keep the framework out of your application.
A simple (and I think common) situation may illustrate what I took away from your comments:
- You create a CRUD app in Django with two types of users: staff (who use the admin interface to modify anything) and regular (can create/modify their own data, but only read other people's data)
- The staff make a mess via the admin interface, so you decide to add some type of undo thing. You look around for an existing addon that does model versioning, but people still spend time reverting changes back.
- You decide you need some business logic (changes going through some review/approval process) and are scratching your head about how to do that in Django.
I can see then why "I look back on any apps I've built / worked on that a) started off as a CRUD system and b) are still going and most of them are a mess."
In regards to your last question, here are my subjective ways of thinking about this. Firstly, I don't think there are many pre-defined or general rules with software development. I've been lucky to work on a pretty diverse set of projects in my career, and I can tell you success or failure almost always boils down to fundamentals not tools - how well do you understand the space you're working in (for web development - how well do you understand databases, caching, concurrency, scaling strategies) and how well do you understand the abstraction tools provided by your language? If your decision making is grounded in these fundamentals, then the tools you choose are not going to make that big an impact. From this point, tool choice is really about economizing the work you'll have to do and managing risk. If you're gonna be building a bunch of CRUD stuff and non-technical users need to view and modify data - then Django and its admin system makes a ton of sense. If, on the other hand, you're developing JSON APIs that you'll be deploying into high-volume conditions that you'll have to react quickly to, you don't want to pin your ability to scale and move quickly on fundamental decisions made in a large underlying library with many unknowns, in this scenario Flask makes a lot of sense because it's not overly prescriptive and plays nicely with almost everything. For this particular project none of us were very familiar with Django, so there were far too many unknowns for us to be comfortable staking a lot on it.
edit: to be clear, i've read Fowler and understand the idea of a multi-layered application i'm just having a hard time understanding how to achieve it technically.
I've also looked through the Fowler stuff (as well as almost everything else on the subject!). One thing I struggled with a lot was how to handle the DB layer. Fowler has that as the layer right in the middle of the system but I really didn't like that model. All the web frameworks are set up so the db layer is very entangled with the framework and it's quite hard to escape.
Let me put something up on github. Send me an email (in my profile) and then I can let you know once I have something to look at.
- It is both 'out of my way' and flexible enough to scale up. I.e. you can start with a 5 LOC hello world, but it still handles a large app with lots of components well (Blueprints).
- It doesn't force a data model / DB onto me - I can just plug in whatever I have (unlike Django).
- It doesn't even force a templating engine onto me - I always use mustache instead of jinja2 (it's extremely tiny, tidy and portable to any language, so it's much easier to port code to other devices / platforms).
- wanna just get started? `sudo pip install Flask && python ./hello.py` --> served on localhost:5000. I recently started a project[1] while in a meeting with someone complaining about some complex app we had - built a prototype with him together that could replace the entire thing and solves problems we had in 2h. Having a foolproof starting point without any configuration and then being able to build up from there is essential.
> It doesn't force a data model / DB onto me - I can just plug in whatever I have (unlike Django).
Django doesn't force a data model onto you anymore than Flask does - nobody is forcing you to use the Django ORM. Any database code you write for a Flask app could be re-used in a Django app.
What the Django ORM does do is allow you to write portable apps and extensions. For example, suppose someone writes an extension for Flask that uses SQLAlchemy. If I'm writing a Flask app and only have a Mongo database available, I can't use that extension. On the other hand, if someone uses the Django ORM to write that extension, as long as I have a Django backend for my database, I can use their extension. It abstracts away the underlying datastore. Besides just which database you are using, you can also write a variety of code that works with Django models. Now granted, this abstraction can be severely leaky and flawed at times, but it's still quite powerful overall. Django provides a conventional, standard way to address the issue of interacting with data in a general way. Again, nobody is forcing you to use it, because you can just bypass the ORM and write your database code directly. It's just a powerful paradigm if you do embrace it.
1) I'm still probably using the ORM. I was just noting that for any data that the ORM doesn't fit well, you don't have to use it.
2) Why is Flask "lighter weight" than Django? From my perspective, as soon as you start writing a real app, you end up reinventing all these basic things like file layout using your own conventions, instead of a standard one that people are familiar with. The mental burden of figuring out your special snowflake conventions makes it 'heavier' weight to me. But again, personal preference :) Flask is obviously much better for really simple stuff, and does provide a great framework for extensions, even if I still lean towards Django.
I think flask is great, like sinatra, for small apps. But I would never consider it for 'big' apps that represented more than half a dozen api endpoints and some sort of in-depth feature set.
Above that size, unless it's super simple, you'll pay the price in tech debt. While our api has worked up until this point, we're gonna scrap it for a Rails api-only app because we need convention + orm + other things to scale not just the app, but the team. There probably is a way to do this in flask, but 95% of our team are Rails guys, so it just makes more sense to go with q company wide maintainable system vs. what's there now.
For small/single devs working on small projects, flask (and sinatra) are great.
It may be because I do not use flask enough either. I spent a little over a year working on a production flask app with a small team and I still feel no where closer in solidifying best practices and design patterns with flask.
In terms of utility and productivity, it all depends on what you want to achieve, of course, and I imagine that Django is a better choice in many cases, but when you already have the wheels you feel like you'd need to re-invent, and those wheels aren't the bells and whistles Django already offers I think I'd prefer using Flask.
When starting with Django the data model is quite inflexible and difficult to work with. Especially the primary key issues.
Anyone looking to get into webscripting/webapps should definitely take a look at flask, its python based, good for prototyping or production apps and has tons of useful documentation.
This is what it always come down to for me. I know that when we can get our app running efficiently with reasonable memory requirements on a single core, then scaling it is really just about launching processes and load balancing them. Scaling out boxes is always easier than scaling out code -- for better or worse.
I'm not talking about load balancing servers mind you, but applications on any given host. Two layers of load balancing. When I'm comfortable with the resource requirements I launch as little or as many of the app in a predictable manner across any number of nodes. It's comforting to know that given X, Y core and ram, I can run N services.
I've used Dancer quite a bit. Some for larger apps (30+ pages)
This is how I typically lay out a Dancer app. Starting with a top level directory of application name, say "MyApp", I put the routes in different directories instead of jumble them all up in one file. As an example, lets use an app that handles and tracks customers and orders. So something like this:
MyApp/
└── Routes
├── API
│ ├── Component
│ │ ├── Customer.pm
│ │ └── Order.pm
│ ├── Customer.pm
│ └── Order.pm
├── API.pm
├── Customer.pm
└── Order.pm
Routes/Customer.pm would handle basic requests like GET /Customer/list and POST or GET Customer/1
While routes handling json/ajax only requests (from jquery ect) would be in Routes/API/Customer.pm. Routes/API.pm would be an api for stuff that doesn't directly involve a Customer or Order object (perhaps returning json from an inventory table or something)
And if you get tired of requesting json just to convert it into html with javascript and you want the power of a template (without a SPA); I fetch that stuff with jquery .load() using the 'Component' routes (dynamic parts of a webpage). For example, perhaps when making a new quote, you select a specific customer and you want open orders to be displayed in a popup or inline div somewhere. Using jquery .load(), you would just easily fetch /API/Component/Customer/Open-Orders/<cust id#>, ect and then just inline the returned html. If you stick to a rule of "components can only return html and not cause a page refresh", you will keep from getting too big of mess with them.
This is just sorta a method I made from various best practices from other frameworks. Perhaps its barftastic, but I haven't been complaining about it.
I'm actually kind of surprised that we haven't seen a return to that style, with more modern sensibilities: each route directly mapping to a file containing the route's procedure body + any view templates for that route; a single "common" file at the project root containing dependency-imports and model declarations, etc.
In the end, it wouldn't actually work like old PHP—you'd still actually have a single entry-point and all the code would be preloaded rather than loaded into an ephemeral request context—but you'd be able to code as if the opposite was true.
Reminds me a bit of the "oldschool sensibilities" of coding with something like Löve2D, actually.
To be clear, Mojolicious advises a layout like above from the beginning for any serious app (and even provides a utility to automatically convert Mojolicious::Lite apps, for the most part), but when it's in production already and Mojolicious lite makes it a little too easy to put that off when it's so easy to just add another route... Well, I have only myself to blame. :/
I'm really interested in well designed route structures,especially for sites that include both HTML and JSON variants of their data. It's API design any way you look at it, which is always a hard problem, but I haven't come up with general rules that I'm quite happy with yet. Guides or example sites are welcome.
Flask-Diamond establishes some common practices so that you are not starting from scratch for each and every new Flask app. In a research context, I might scaffold multiple new apps per month, so this has been a huge time saver for me. This has also made Flask teamwork much easier.
Here's a tldr:
Logging requests to a flat file on a t2.small instance:
Django: 519.93 trans/sec
Falcon: 2083.19 trans/sechttps://gist.github.com/alanhamlett/ecb3656a1d1bfb3feb31 (requirements.txt)
Flask is great for small projects, and also scales to large apps like https://wakatime.com
I've also had good experiences with bottle (http://bottlepy.org/docs/dev/index.html) for building internal apps for companies. The limited amount of users means I don't have to worry much about scaling and bottle with Paste server works pretty nicely. Jinja2 templates can also be used with bottle which is a plus. It's also pretty easy to compile this setup into an executable so it can run off someone's Windows machine and no need for a separate server. This setup makes a really convenient internal-use app which is easy to send to end users for deployment.
(EDIT: fixed autocorrect exe->exercise)
I'm in the process of writing my first webapp, and thses days it's a bit strange seeing a popular framework not being updated (even if it's just for bugfixing) a few times a year.
https://github.com/mitsuhiko/flask/milestones/0.11 https://github.com/mitsuhiko/flask/milestones/1.0
None of the 0.11 blockers are substantial, and 1.0 is mostly about having updated documentation. It just requires someone to actually finish them.
As everyone here knows, it's hard to write software when you don't feel enthused about the programming language.
He has been doing stuff with Rust in particular. Maybe there will be a "Rusty Flask" one day.
It did not stop, it just did not get a release. I'm (very slowly unfortunately) in the process of fixing this by restructuring the github org to get trusted contributors to fix this and to make it easier to have multiple smaller releases instead of a huge one. There is always risk in pushing out releases with a lot of changes which is what would happen which is why I want to have people in place that can push releases without my help to fix things if they are regressing.
I would have done it over Christmas already but life keeps happening and this is something I rather not do without having an action plan :)
Very soon now though.
Disclaimer: You can architect beautiful apps in apps, its just easy todo it wrong.
GLOBALS: Flask has a lot of globals (from flask import g, request, current_user, etc.) A better web handler function looks like this handle(request) -> response. Any other web framework that I know does it like this. Much better. Flask promotes touching the 'request' object everywhere. Example: https://github.com/lepture/flask-wtf/blob/master/flask_wtf/f.... Flask is not functional, its inherently statefull with globals.
MIDDLEWARE: Flask promotes writing middleware as decorators functions, while it looks nice, it not really useable anywhere else, and its not really a standard. At least you can still use WSGI middleware.
BLUEPRINT are nice, but have issues: When you create a blueprint, for a sub app, you cant set error handlers. They only work on app level. Also (small issue) You cant add blueprint specific middleware.
Better way to create 'sub apps': Use a new WSGI App. Or use a sitemap where you bind functions to paths.
SITEMAP @route has disadvantages For big apps, its nice to have a single routes.py file where you can see all urls the app supports, and which methods to handle those. The @route is nice to use initially, but imho for big apps it becomes messy. Also it promotes circular imports:
view.py:
from init import blueprint #circular import!
blueprint.route('/test/')
def f(): pass
init.py:
blueprint = new Blueprint
from . import view
assert view # ensure the handlers are initiallized> GLOBALS: Flask has a lot of globals (from flask import g, request, current_user, etc.) A better web handler function looks like this handle(request) -> response. Any other web framework that I know does it like this.
Flask's request is not global. I have had this discussion with someone else before:
https://news.ycombinator.com/item?id=6662623
FWIW, flask's "from flask import request" never had been a blocker for me, whereas django's injected request variable had made me write middleware to preseve requests as thread locals so that I can access it elsewhere. Werkzeug does the same thing, except it does it more robustly.
> MIDDLEWARE: Flask promotes writing middleware as decorators functions, while it looks nice, it not really useable anywhere else, and its not really a standard. At least you can still use WSGI middleware.
I don't see an issue. If you can solve it using simple python(decorators), solve it using Python.
> BLUEPRINT are nice, but have issues: When you create a blueprint, for a sub app, you cant set error handlers. They only work on app level. Also (small issue) You cant add blueprint specific middleware.
Rather than calling app.before_request, you can call blueprint.before_request and it will work only for that blueprint.
> SITEMAP @route has disadvantages For big apps, its nice to have a single routes.py file where you can see all urls the app supports, and which methods
Then don't use the decorator. Have a routes.py and call app.add_url_rule
I have had a template with all of this from some time back
In my experience, any sufficiently large Flask project contains an ad hoc, bug-ridden, slow implementation of half of Django.
What JS framework do you tie it to, if you use Flask to just create an API/manage sessions?
The trick with that is having to host them from separate domains and deal with CORS, however it also allows you to distribute your SPA via CDN instead of using Flask app servers to serve up that static content. This is what we do at my full-time gig, but same holds for Flask.
We are using webpack and it seems hard to do it.
ETags is not viable for this kind of a setup - it pretty much means triggering a nginx reload which is what a cache-busting signature avoids.
And why should Flask be used instead of asynchronous Tornado or Node.js?
In terms of async Tornado / etc, it serves a different need. Like all wsgi servers, it is best to optimize Flask such that you serve a small number of concurrent requests that are fast to prevent a long queue waiting to serve web requests. With Tornado you have more flexibility in that particular area, but also another layer of complexity. Different tools for different use cases.
Well, most (or all) web applications I've worked with make database calls to serve a response, which (in case of Flask) locks the whole thread, and there's always the possibility that the database request is slow. That's why I prefer asynchronous web servers where I don't need to worry about this particular problem.
Modern web applications tend to be more like light proxies between the database and other (micro)services. Most logic has been transferred to the client, including templating. Serving static files should be done by Nginx in any case. Therefore I think it's rather critical that the web application does the serving of multiple requests well, and why I think the async architecture is the way going forward.
I don't get this, when did Flask start connecting to databases? The only point of Flask is that it only provides an HTTP layer, nothing more. If you want to connect to a database, you have to import some other library (or use something from Python's standard library), which may or may not be blocking.
That said, the default development server built-in (which uses werkzeug's underneath) is multi-threaded - just pass threaded=True to app.run(...) - and in production, you can deploy a Flask app using an evented framework like Tornado or Gevent: http://flask.pocoo.org/docs/0.10/deploying/wsgi-standalone/#...
To answer your first question: you use something like uWSGI. Flask, by default, stores sessions entirely client-side. You'll have to use something like Redis if you want to use more than one server (properly, anyway), but a Python app like this should easily be able to scale. It won't be Flask that stops you, anyway.
uWSGI allows for brokering requests across multiple application processes and/or threads, and also allows for more interesting and complex scenarios such as zero-downtime deploys, "automatic" scaling of processes/threads based on load characteristics, to name a few.
> And why should Flask be used instead of asynchronous Tornado or Node.js?
Tornado's asynchronous request handling is quite nice, but it also forces you to ensure that every 3rd party system you interact with has an equivalent async-compatible library; otherwise you end up blocking a request while waiting for a response, thus defeating the whole purpose of Tornado. Most systems (e.g. Postgresql[1]) have async-compatible drivers, but it's not always the case.
As for why not node.js, well, perhaps a better question would be: How would Node be an improvement over Flask+uwsgi? What are the associated infrastructure/architecture/cultural costs?
How is this done in detail? In the case of Flask does it create new processes or threads? How quickly does it create a new Flask process/thread to serve a new request?
EDIT: This website documents configuration settings for autoscaling: http://uwsgi-docs.readthedocs.org/en/latest/Cheaper.html - looks like it's based on various heuristics and algorithms, and in practice it's too slow to create a new process for each request, thus wasting resources
I would think that ideally the number of processes/threads would exactly match the number of live requests, otherwise you're either having too few instances to handle all the requests as fast as possible or having too many instances which means that more resources are used than necessary, thus increasing costs.
I think Node.js is an improvement because the architecture is better suited for scaling and all the dependencies are asynchronous by default. Of course, I think there are other reasons for Node.js (e.g. isomorphism, easier full-stack development etc.), but I guess that's another discussion, really.
Of course, this doesn't change your app and its dependencies to work in an async-friendly way, but then again, Node.js callbacks are hardly transparent either.
If you're hitting enough load where async really matters, just skip Python altogether. And please, please, don't use Node. Just use Golang or Scala for true multithreading, and you'll save yourself the headaches Javascript will bring for something that's not truly parallelized.
In terms of the ideal number of processes/threads, I'm not so sure number if live visitors is correct. It's going to depend on your various resource constraints but if requests are quick to service there's no problem with having other requests waiting in a queue.
I once was called in to fight a fire where the team said, "we don't understand, we have horizontal scalability, but adding more machines seems to be making things run slower!" - Erm, yeah, because your single db server is on its knees :-)
[0] http://uwsgi-docs.readthedocs.org/en/latest/asyncio.html
Edit to add that I've just looked through the cheaper docs you mentioned and that behaviour all looks pretty sane. You can have a good default number of workers and expand as required. Also, uWSGI forks workers after the app is loaded in memory so you get fast copy-on-write behaviour during worker start.
https://www.digitalocean.com/community/tutorials/how-to-serv...
Flask/Python blows Node out of the water where performance is concerned. That shouldn't be a surprise to anyone.
Flask has a significantly faster ramp up time than Tornado as it is designed to be simple.
As far as load balancing/performance, you front end it with something like NginX.
You can process things out of band easily enough with Flask, but I wouldn't evangelize it so much to say that it's the best solution for every problem.
Personally, I like to keep things as simple and as logically separated as possible until it's absolutely necessary to change. Flask is one of those frameworks that doesn't present a lot of mystery.
My biggest problem with node isn't performance - for that it's fine for most use cases that I deal with. It's that you can get perl-level convoluted and sloppy very quickly and easily.
https://www.techempower.com/benchmarks/#section=data-r11&hw=...
And my experience is generally also that V8 beats the pants off CPython in performance.
I suspect that part of the problem is that the node ecosystem encourages you to just "npm install" whenever you have a problem, and so you have 3-4 layers of third-party libraries doing minimal work (but consuming lots of CPU cycles) on top of your problem space. But if that's the problem - don't do that. Flask is a microframework; it's trivially easy to build a small microframework on top of the Node.js stdlibs. Node was meant as a scriptable high-performance C++ server, after all, and there's nothing stopping you from using it as one.
It has a range of 723 requests (CherryPy) for a plaintext hello world to 6.8Million (ulib) for plaintext. I looked at the Flask numbers and they don't compare with my own - I got between 3 and 4 times that when I benchmarked it myself on hardware that I'm sure was older and less powerful (and I didn't bother to turn off logging).
I looked at the node code and it does not use express - which could very well be the difference I am experiencing.
I'll tell you what though... I'm going to have a look at ulib for static files!
I'm a huge fan of Flask and Python in general, and despise server-side Javascript (or Javascript anything, really). But I'm curious how you can make this claim. CPython lacks JIT, and gunicorn + Flask is going to run a process pool by default, with each process being single threaded and under GIL.
What's your set up then? PyPy and gevent gunicorn workers? Otherwise I don't see how CPython+Flask+gunicorn could beat Node performance wise out of the box. At best PyPy + gevent would approximate NodeJS performance, unless you can tell me otherwise.
Nodejs performs very well in synthetic benchmarks. In the real world, slow clients and large queries just kill that initial performance.
Then there's the further load balancing you can do behind something like an ELB instance in AWS to control load across multiple servers.
http://blog.miguelgrinberg.com/post/easy-websockets-with-fla...
It was also among first python frameworks that supported py3.
Also the debugtool bar is excellent for tracking down defects.
The last time I check the Pyramid code base had 100% test coverage.
I look to the documentation as a work of art and a standard for all of my opensource libraries.
Can anyone provide a few good open source flask projects worth reading?
Given hexagonal architecture (i.e. your model + business rules existing as a "service component" library project, that your webapp consumes as a dependency), if all you need is to expose that service with an API, Flask and/or Sinatra lets you do so with nothing more than a flat file of 3–6-line controller stanzas. It's really quite lovely; gets to the core of what it means for something to be a "microservice."
The next realisation you'll come to is that all that stuff has already been written by someone else as addons. So you try that but eventually you'll find you are in so much pain from problems with integrating addons that you will realise that you would be best off with something that has all the basic functionality "batteries included". So then you'll try to find projects on github that have already baked together Flask plus all the plugins into a boilerplate project. Then you'll find that there's many ways to bake all that stuff together and start to wonder if maybe you're now using a framework. But the boilerplate Flask with addons integration doesn't feel like it has a really well thought out consistent overarching model.
So you'll then look at full featured integrated frameworks like Django where it's all integrated according to an architectural vision (perfect or otherwise is a matter of opinion) and although you might mot like some of the components, at least its all built in. Flask still carries of cruft and mental model though, because it is from earlier days of web development when you built the front end in the back end using things like Jinja templates.
And then one day you'll need to build just a simple REST API without all the bells and whistles needed in a web application. So you can then look at Falcon which is extremely minimalist for developer who know they don't want any extra web application stuff at all including things like back end UI generation with templates. It's a sharp knife because there's almost nothing in it, and never attempted to provide the features needed to build user oriented web applications, so it has a very small mental model to grasp.
TLDR:
Bottle and Flask are great for finding your feet in web development without being forced to learn too many concepts all at the same time.
Django or Pyramid or something full featured for web application development
Falcon for REST API development
If you are willing to take on the cognitive load of going straight to your destination, I would recommend beginners start with Django or Pyramid or Falcon. If (and this is entirely reasonable) you need to get going in Python web development without being overwhelmed by the concepts, go to Bottle or Flask but move on as soon as you can.
If you love Flask and have the skills and competence to craft your own architecture and carefully selected from a menu of addons that suit you and know how to whittle out unneeded functionality, then Flask is the right choice for you.
I'd take those benchmarks with a massive pinch of salt. 338µs per request for Flask is the bad case. 0.5ms of the request is spent in the framework, that's not even noise. The fastest framework I've used is one I wrote for coldfusion and that's the only time I've expected all my requests to be sub 100ms. And even then, the network latency turns that into noise.
Look at features before performance - both in the case of frameworks and version of Python to use (Python 3 is a lot nicer).
Lies, damn lies and benchmarks - I'm not saying the benchmarks are made up but you know - the benchmark thing.
Falcon for REST API development. Django/Pyramid for full featured web application development.
And regarding speed, well how does its Python 3 performance compare to the Python 2 performance of other Python web servers? And any does speed matter that much? In many cases "fast enough is good enough" and the bottle necks are more likely to be other parts of your system and if speed matter that much then you should be horizontally scaling.
And if I may raise the ugly topic - who cares about Python 2 under any circumstances? For me - and I know many people do not think this way - Python 2 is dead so who gives a rats arse anything about it. Python 3 is the future and I'm not looking back for any gripes or grumbles about it.
Don't get me wrong, I think ruby-rails-slow is a bad thing, but Falcon fast should be good enough.
And if speed really matters to you then you shouldn't be using Python for web application development.
In all my research over the years Pyramid is the framework that looks the most interesting. The docs are amazing (I more or less read them cover to cover, even though I haven't tried the framework) and the whole thing seems very well thought out.
I'd love any insights from people who have worked with it.
Falcon gives you less than Flask, not more.
For me the big thing is that Falcon has none of the stuff needed for building web apps. Flask has all that stuff cause it was built when back end servers also built the HTML pages. There's alot of stuff associated with that functionality in Flask that is not there in Falcon. It makes it much cleaner.
Personally, I'm excited to explore flask more, since it seems to put the ball entirely in your court. I like the concept behind flask a lot -- for some projects I'm willing to sacrifice additional framework features in exchange for a more careful understanding of everything I am adding to my app.
The problem as I see it is that Pyramid has a lot of extra interfaces and support for things in the core by default (and some concepts that are completely missing from most frameworks like context). So much is there that it's easy to lose sight of how little is actually required. Fundamentally you can write Pyramid apps in 10 lines of code exactly as you would with Flask but that's less interesting for bigger apps and so the docs focus on all the extra features.
I mean if you take the example at the top of http://docs.pylonsproject.org/projects/pyramid/en/latest/ and add in the pyramid_jinja2 library via config.include('pyramid_jinja2') then you basically have views and jinja2 rendering fully baked.
As in the previous example if you get right down to it Pyramid doesn't even have a templating engine! Flask comes with jinja2 built-in! So scaling DOWN to APIs where this is not necessary is an interesting thing..
By saying "it's not a particularly opinionated framework", I mean to say that it allows you to add, easily, whatever you want to it. However, there is a fair amount of conceptual load in doing so. The difference between a flask app and a pyramid app with pyramid jinja2 built in is that one of them takes about 20 seconds to understand.
Don't get me wrong -- I think pyramid is fantastic. But it it is disingenuous to suggest that there are not differences in complexity between the two frameworks.
I'm interested in the present.
You of course may use whichever software you want but I don't have enough time to learn anything but what is currently being developed.
I worked on a pretty big Flask codebase (certainly bigger than the one mentioned in the article, though obviously it depends on how you define it, how you structure your codebase, etc). We didn't really use much in terms of third party add-ons, but we did fork and add various useful features, conveniences, etc. I don't personally think the lack of (eg) sessions is very painful, because it's trivial to implement, and there's something to be said for having a code path that you understand. Yes, we spent some time building some pretty generic stuff... but it was a tiny fraction of overall development time, and we gained wins from the fact that we understood our codebase very well thanks to it.
Definitely a balance to be struck, but I really appreciate that the surface area of Flask is small enough that provided you accept the basic conceptual model (request per thread, entry point is a function, etc), you have a lot of freedom to do what you will, and there's very little bias in the system pulling you away from that. Whereas if you don't want to do something the Django way... well, there's some cost to that choice, usually.
I don't think that this is doing what you think it is doing (assuming that 'import logging' is importing the Python logging package, and not relying on broken Python 2 package name resolution quirks to import a local module).
The `logging.{LEVEL}` functions always log in the root logger. The loggers that you initialize have a tree structure. There is a nice package for inspecting that here:
https://pypi.python.org/pypi/logging_tree
Several different 3rd party libraries that you might be using will all have their own loggers that are initialized at their level. By separating things out like this, you can set different log levels for different loggers. For example, you might not want Component A logging at DEBUG level, while you want Component B logging at DEBUG level. This is why one would initialize things per package like this:
import logging
logger = logging.getLogger(__name__)
* Flask-CORS: When I first started using this it's default logging level was really noisy.
* factory (aka Factory Boy): You can turn in DEBUG level to get a deluge of information about what is happening with your test data.
* SQLAlchemy: The 'echo' option to create_engine isn't the only way that you can control logging. E.g.:
import logging
logging.basicConfig()
logging.getLogger('sqlalchemy.engine').setLevel(logging.INFO)
This fork is currently active: https://github.com/teracyhq/flask-classy
[1] https://code.google.com/archive/p/webapp-improved/source/def...
I also probably didn't formulate my question well. I didn't ask whether to use it or not, but how it compares to Flask - .
http://flask.pocoo.org/docs/0.10/
the snippets page is really helpful
http://flask.pocoo.org/snippets/
also, I've some boilerplate
https://github.com/ransomw/catalog-flask
even though it hasn't gotten attn in a while
Flask is plagued with abandoned plugins from a cesspool of weekend contributors which you rely on for basic things such as authentication and ORM. Tough enough as it is with all the outdated documentation for each of the plugins you need.
So my recommendation based on 2 years of working with Flask is don't fucking do it, unless your product doesn't extend beyond couple of HTTP endpoints served over uwsgi + nginx for your internal applications.
I really wish I'd spent all that time I spent on Flask on Node.js, python was the wrong medium to distance myself from PHP frameworks.
All in all, 4 years have passed since my search of alternatives to LAMP. And finally, it wasn't some open source framework or asynchronous javascript to save the day, it was Amazon Lambda + API Gateway.
Gone are the need to spin up Vagrant, docker, mysql/postgresql. I just upload the specific script I want and bam. Npm modules and pip modules too.
I've in the process of migrating to AWS and leaving Flask. Great initiative, ruined by abandonware plugins and modules, certainly not attractive to entice developers to build their own wheels.
The biggest mistake you could do is basing speed and agility as basis for going with Flask. It is the complete opposite. I think using Laravel or even CodeIgniter will significantly cut development time.
Regardless, I'm done with the whole server/client frameworks and have migrated to AWS without any servers to maintain or setup. There's even frameworks for "Serverless" architecture now which makes me shake my head.
Jumping on the lambda bandwagon seems pretty risky, and in any case how does it protect you against abandonware? To me it's a bit like saying "I don't like outdated python packages, so I'll switch to nginx instead of Apache!".
They blame Python for issues they perceived with Flask, I doubt they're going to be too open to Django.
I really did wish I was using django and it's a great framework, however, I would still choose a php based framework over django, my whole point of using Flask was buying into the "microframework" experience, it hasn't been stellar nor worth the extra effort.
I do have to say that I rather liked doing things in Flask until it came time to do the less fun plumbing code that Flask conveniently leaves out for you to implement and rely on other Flask plugin contributors....it's literally npm world but far far fewer in volume....I really did not expect using Flask would become a minefield
About Lambda, yes there is a platform risk, but I don't think it's a huge one because the code you write on Lambda are largely self sufficient on their own. At most if AWS Lambda shut down, you'd moving them to a queue based architecture with EC2 workers chewing away at the queue.
All in all I don't think AWS Lambda is a hugely different than any other webhosting...I'm more worried that digitalocean is going to sell out and I'm stuck with dozen of snapshot images that won't work anywhere else.
What Node frameworks are you using?
If your requirements are more involved than that, Flask is an obstacle. The way it gives each request its own context makes it hard to have any kind of communication between them, without some kind of "spawn a gevent to wait for a signal" hackery.
Also, Flask comes with Jinja but they should totally be separate. Why should a network protocol layer come with a frontend templating system?