Armin explains the Flask globals. I've always wanted to know the reasoning behind this design choice..
https://www.youtube.com/watch?v=1ByQhAM5c1I

/r/Python
https://redd.it/5kqoou

Is Django a good framework for multi-tenancy SaaS app?

I am evaluating difference frameworks right now and it seems like Django is not as mature for building multi-tenancy app. I just tried out django-tenant-schemas today and the repository is not quite caught up with the recent version of Django. I wonder whether anyone have experiences building SaaS app with Django and what do you think of it. Thanks!

/r/django
https://redd.it/5kubzl

donnemartin has a great collection of notebooks on his Git page
https://github.com/donnemartin/data-science-ipython-notebooks

/r/JupyterNotebooks
https://redd.it/47mk4y

Real-time LED strip music visualization written in Python and uses an ESP8266
https://github.com/scottlawsonbc/audio-reactive-led-strip

/r/Python
https://redd.it/5kswq3

Performance comparison of various python clustering implementations
http://nbviewer.jupyter.org/github/lmcinnes/hdbscan/blob/master/notebooks/Benchmarking%20scalability%20of%20clustering%20implementations.ipynb

/r/pystats
https://redd.it/3qcvcz

Highly custom validation?

Ok so I have a model that asks for an event from a dropdown menu and then depending on what event that is a certain number of people, both men and women, have to be entered before submitting.
An example would be event A requires 3 people, at least 2 male and 1 female or 2 female and 1 male. But the rules for each event are different. Is there any way to go about doing this in django? Thank you so much for the help.

Edit* Im using model forms btw if that matters at all

/r/django
https://redd.it/5ksoaf

[Free for Limited Time] Python Fundamentals

https://www.udemy.com/python-fundamentals/

I have also added other development and programming courses at http://meritcoupon.com

/r/Python
https://redd.it/5kupaa

An example machine learning notebook for newcomers
https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects/blob/master/example-data-science-notebook/Example%20Machine%20Learning%20Notebook.ipynb

/r/JupyterNotebooks
https://redd.it/47mqpt

Amazon Machine Learning: use cases and a real example in Python
http://cloudacademy.com/blog/aws-machine-learning/

/r/pystats
https://redd.it/3qbcxh

Embedding IPython example from manual doesn't work (for me)

Hi,
I'm looking to integrate interactive shell to extended unittests framework I work on and I wanted to use IPython for that. But when I tried the example from http://ipython.readthedocs.io/en/stable/interactive/reference.html#embedding-ipython - embed_class_long.py it doesn't seem to work properly - after exiting instance of InteractiveShellEmbed for the first time, next time it should open it just displays both banner and exit messages and no actual shell opens.

Calling IPython.embed() works ok, but I need to set custom banner and new commands (magics in IPython lingo?) which I think isn't possible that way

Any guesses why the manual example doesn't work or what should I change/test/etc?

(I'm using python 2.7 , ipython version 5.0.0, Linux)

/r/IPython
https://redd.it/5kwh3a

How the HDBSCAN clustering algorithm works
http://nbviewer.jupyter.org/github/lmcinnes/hdbscan/blob/master/notebooks/How%20HDBSCAN%20Works.ipynb

/r/pystats
https://redd.it/3pciwv

Simple app that dynamically changes the templates based on domain/subdomain.
https://github.com/linevich/django-mobile-template

/r/django
https://redd.it/5kw0zg

Creating a flask app and thinking of using peewee instead of sqlalchemy...

So, I am creating a flask app and thinking of using peewee instead of sqlalchemy. I have some basic experience with peewee and it seems great to me.

My database will be postgreSQL which I have almost no experience with but I have read that its the recommended Python database for Flask and other web apps.

Are there any glaring problems with using peewee with flask that might cause me problems?

The part of the app I am writing right now is back-end of the back-end. By that I mean that it is the engine that will be running and actually scraping the web and analyzing the data that I want to return to my users. It's the service that the web app will be sending data to and getting results from.

/r/flask
https://redd.it/5kuv7n

Can anyone suggest a good way to handle postal addresses in Python/Django?

I'm currently finishing up an app that relies somewhat heavily on postal addresses - local and international. I'm currently using (a slightly modified version of) https://github.com/furious-luke/django-address. It does a decent job, but the relationships in the DB are set up so every address FK references a locality, every locality fk references a state, and every state fk references a country. I understand the logic behind doing something like this, but if I enter an address that doesn't contain a locality, it won't store a country, because it breaks the FK reference chain. Has anyone ever setup a flat db table that stores all postal address parameters on individual rows? I've been searching all over for something that will at least store international addresses to no avail. Thanks in advance.

/r/django
https://redd.it/5klhbd

[AF] Please share advice for testing with existing database

I am new to flask and marginally familiar with databases and testing. I am working on a project that mainly deals with an Oracle database and it isn't clear to me how I should to test my project. I need help getting my mindset right.

Currently the application draws a chart of selected data, the user categorizes points in the chart and saves the categories to another table. The site is then updated in a way so other uses know that group of data has been examined.

At the moment the dev database is a full copy with hundreds of thousands of rows in the main table. At the moment relations are simple and I know exactly which tables I need and their relation to one another.

What advice or resources do you all have?

The popular advice from just searching is that I should build a new version of the database up for each test, but that seems unwieldy for the amount of data. Do I take a subset? Are there established ways of copying the database's schema using sql-alchemy so it can be regenerated quickly? Even then what do I test, that I get the correct data from the database?

The other advice I have seen is to avoid CRUD tests altogether and just test data manipulation using mocks or example data. This seems like the easy way out as almost all the business logic will live in the database.

Thanks






/r/flask
https://redd.it/5kuxfn

Jinja 2.8.1 Released with a Security Fix for str.format in Sandbox Mode
https://www.palletsprojects.com/blog/jinja-281-released/

/r/Python
https://redd.it/5kwvr6

Flask author Armin Ronacher: "Flask for Fun and Profit" at PyBay2016
https://www.youtube.com/watch?v=1ByQhAM5c1I&index=24&list=WL

/r/flask
https://redd.it/5kynb4

Notebook Gallery -- Most Viewed Notebooks!
http://nb.bianp.net/sort/views/

/r/JupyterNotebooks
https://redd.it/47mjzk

The Iterator Protocol: How for Loops Work in Python
http://treyhunner.com/2016/12/python-iterator-protocol-how-for-loops-work/

/r/Python
https://redd.it/5kzopj

[D] r/MachineLearning's 2016 Best Paper Award!

Hi guys!

Welcome to /r/MachineLearning's 2016 Best Paper Award!

The idea is to have a community-wide vote for the best papers of this year.

I hope you find this to be a good idea, mods please tell me if this breaks any rules/if you had something like this in store.

---

## How does it work?

**Nominate** by commenting on the dedicatd top level comments. Please provide a (paywall free) link. Feel free to justify your choice. Also if you're one of the author, be courteous and indicate it.

**Vote** by upvoting the nominees.

The **results** will be announced **by the end of next week** (6-7th of Jan.). Depending on the participation/interest I might change it.

It's that simple!

There are some simple rules to make sure everything runs smoothly, you can find them below, please read them before commenting.

---

## Categories

- [Best Paper of the year](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrapti/)

> No rules! Any research paper you feel had the greatest impact/had top writing, any criterion is good.

- [Best student paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbraqkv/)

> Papers from a student, grad/undergrad/highschool, everyone who doesn't have a phd and goes to school. The student must be first author of course. Provide evidence if possible.

- [Best paper name](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrar08/)

> Try to beat [this](http://www.oneweirdkerneltrick.com/spectral.pdf)

- [Best paper from academia](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbraroz/)

> Papers where the first author is from a university / a state research organization (eg INRIA in France).

- [Best paper from the industry](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrasnz/)

> Great paper from a multi-billion tech company (or more generally a research lab sponsored by privat funds, eg. openai)

- [Best rejected paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrat9t/)

> A chance of redemption for good papers that didn't make it trough peer review. Please provide evidence that the paper was rejected if possible.

- [Best unpublished preprint](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbratyb/)

> A category for those yet to be published (e.g. papers from the end of the year). This may or may not be redundant with the rejected paper category, we'll see.

- [Best theoretical paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrauan/)

> Keep the math coming

- [Best non Deep Learning paper](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbraumv/)

> Because gaussian processes, random forests and kernel methods deserve a chance amid the DL hype train

---

## Rules

1. Only one nomination by comment. You can nominate multiple papers in different comments/categories.
2. Nominations should include a **link to the paper**. In case of an arxiv link, please link to the arxiv page and not the pdf directly. Please do not link paywalled articles.
3. Only **research paper** are to be nominated. This means no book, no memo or no tutorial/blog post for instance. This could be adressed in a separate award or category if there is enough demand.
4. For the sake of clarity, there are some rules on commenting :
- ***Do NOT comment on the main thread***. For discussion, use the [*discussion* thread](https://www.reddit.com/r/MachineLearning/comments/5kxfkb/d_rmachinelearnings_2016_best_paper_award/dbrap6u/)
- ***Please ONLY comment the other threads with nominations***. You can discuss individual nominations in child comments. However 1rst level comments on each thread should be nominations only.