How can I get IPython hon to indent with a tab character rather than spaces?

I've recently started using spyder and its embedded IPython console. Is there a separate option for the IPython console to change the indentation character?

/r/IPython
https://redd.it/7b535v

Preview of new flask based web framework / CMS - Manhattan
https://youtu.be/p8oAct-RW_0

/r/flask
https://redd.it/7b6vkd

Multiple phone numbers per contact

Hello, I'm trying to make a Customers and a Providers model, which both have almost all fields the same (name, address, email, etc..). Following the DRY concept, I decided to make an abstract class and use it as needed.

How could I add multiple phone numbers to the same Customer/Provider?

### What Have I tried?

Initially I made a phone number model and added a relation to the Abstract class, but that didn't work, so I read about generic foreign keys, which seems to achieve what Im looking for, except, I can't add the phone number model as an _inline_ for my Client class in the admin interface.

This is my models.py:

class Contacto(models.Model):
nombre = models.CharField(max_length=30)
email = models.EmailField(blank=True)
habilitado = models.BooleanField(default=True)

def __str__(self):
return self.nombre
class Meta:
abstract = True
ordering = ['nombre']

class Cliente(Contacto):
direccion_factura = models.CharField(blank=True, max_length=200)


class Proveedor(Contacto):
transportista = models.CharField(max_length=30)

class PhoneModel(models.Model):
content_type = models.ForeignKey(ContentType, on_delete=models.CASCADE)
object_id = models.PositiveIntegerField()
phone_regex = RegexValidator(regex=r'^\+?1?\d{9,15}$', message="Telefono debe ser ingresado en formato: '+999999999'. Permitido hasta 15 digitos.")
phone_number = models.CharField(validators=[phone_regex], max_length=15, blank=True) # validators should be a list
contacto = GenericForeignKey()

My problem is right here in admin.py:

class ContactoInline(admin.TabularInline):
model = PhoneModel
extra = 2

class ClienteAdmin(admin.ModelAdmin):
inlines = [ContactoInline]


admin.site.register(Cliente, ClienteAdmin)
admin.site.register(Proveedor)

Adding phone numbers to my Cliente/Proveedor class fail with:

ERRORS:
<class 'empresa.admin.ContactoInline'>: (admin.E202) 'empresa.PhoneModel' has no ForeignKey to 'empresa.Cliente'.

Ideally I'd like to have unlimited numbers per Client/Provider (because why should I limit the user?) but if that fails, id just hard code like 4 or 5 within the Abstract class.

Thanks

/r/django
https://redd.it/7ayxn1

[D] Machine Learning - WAYR (What Are You Reading) - Week 35

This is a place to share machine learning research papers, journals, and articles that you're reading this week. If it relates to what you're researching, by all means elaborate and give us your insight, otherwise it could just be an interesting paper you've read.

Please try to provide some insight from your understanding and please don't post things which are present in wiki.

Preferably you should link the arxiv page (not the PDF, you can easily access the PDF from the summary page but not the other way around) or any other pertinent links.

Previous weeks :

|1-10|11-20|21-30|31-40|
|----|-----|-----|-----|
|[Week 1](https://www.reddit.com/r/MachineLearning/comments/4qyjiq/machine_learning_wayr_what_are_you_reading_week_1/)|[Week 11](https://www.reddit.com/r/MachineLearning/comments/57xw56/discussion_machine_learning_wayr_what_are_you/)|[Week 21](https://www.reddit.com/r/MachineLearning/comments/60ildf/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 31](https://www.reddit.com/r/MachineLearning/comments/6s0k1u/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 2](https://www.reddit.com/r/MachineLearning/comments/4s2xqm/machine_learning_wayr_what_are_you_reading_week_2/)|[Week 12](https://www.reddit.com/r/MachineLearning/comments/5acb1t/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 22](https://www.reddit.com/r/MachineLearning/comments/64jwde/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 32](https://www.reddit.com/r/MachineLearning/comments/72ab5y/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 3](https://www.reddit.com/r/MachineLearning/comments/4t7mqm/machine_learning_wayr_what_are_you_reading_week_3/)|[Week 13](https://www.reddit.com/r/MachineLearning/comments/5cwfb6/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 23](https://www.reddit.com/r/MachineLearning/comments/674331/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 33](https://www.reddit.com/r/MachineLearning/comments/75405d/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 4](https://www.reddit.com/r/MachineLearning/comments/4ub2kw/machine_learning_wayr_what_are_you_reading_week_4/)|[Week 14](https://www.reddit.com/r/MachineLearning/comments/5fc5mh/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 24](https://www.reddit.com/r/MachineLearning/comments/68hhhb/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 34](https://www.reddit.com/r/MachineLearning/comments/782js9/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 5](https://www.reddit.com/r/MachineLearning/comments/4xomf7/machine_learning_wayr_what_are_you_reading_week_5/)|[Week 15](https://www.reddit.com/r/MachineLearning/comments/5hy4ur/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 25](https://www.reddit.com/r/MachineLearning/comments/69teiz/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 6](https://www.reddit.com/r/MachineLearning/comments/4zcyvk/machine_learning_wayr_what_are_you_reading_week_6/)|[Week 16](https://www.reddit.com/r/MachineLearning/comments/5kd6vd/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 26](https://www.reddit.com/r/MachineLearning/comments/6d7nb1/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 7](https://www.reddit.com/r/MachineLearning/comments/52t6mo/machine_learning_wayr_what_are_you_reading_week_7/)|[Week 17](https://www.reddit.com/r/MachineLearning/comments/5ob7dx/discussion_machine_learning_wayr_what_are_you/)|[Week 27](https://www.reddit.com/r/MachineLearning/comments/6gngwc/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 8](https://www.reddit.com/r/MachineLearning/comments/53heol/machine_learning_wayr_what_are_you_reading_week_8/)|[Week 18](https://www.reddit.com/r/MachineLearning/comments/5r14yd/discussion_machine_learning_wayr_what_are_you/)|[Week 28](https://www.reddit.com/r/MachineLearning/comments/6jgdva/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 9](https://www.reddit.com/r/MachineLearning/comments/54kvsu/machine_lear

ning_wayr_what_are_you_reading_week_9/)|[Week 19](https://www.reddit.com/r/MachineLearning/comments/5tt9cz/discussion_machine_learning_wayr_what_are_you/)|[Week 29](https://www.reddit.com/r/MachineLearning/comments/6m9l1v/d_machine_learning_wayr_what_are_you_reading_week/)||
|[Week 10](https://www.reddit.com/r/MachineLearning/comments/56s2oa/discussion_machine_learning_wayr_what_are_you/)|[Week 20](https://www.reddit.com/r/MachineLearning/comments/5wh2wb/d_machine_learning_wayr_what_are_you_reading_week/)|[Week 30](https://www.reddit.com/r/MachineLearning/comments/6p3ha7/d_machine_learning_wayr_what_are_you_reading_week/)||

Most upvoted papers two weeks ago:

/u/alexbhandari: https://www.nature.com/nature/journal/v550/n7676/full/nature24270.html

/u/hlynurd: http://ccr.sigcomm.org/online/files/p83-keshavA.pdf

/u/cfusting: http://eplex.cs.ucf.edu/papers/morse_gecco16.pdf

Besides that, there are no rules, have fun.

/r/MachineLearning
https://redd.it/7b0av0

[django-rest-framework] How do you guys return error responses?

I started learning DRF recently, and one doubt has popped up. I was using **rest_framework.response.Response** to render the serialized data. However, I want to append a header to the response, so it's easier to check for and debug errors.

I was thinking something like this:

{
"errorCode": int,
"errorMessage": "...",
"payload": # serialized data
}

Would this be a good approach? Is there a way I can do this while remaining compatible with the "formats" option of the serializer? What approach to structuring the response you guys take when designing APIs?


/r/django
https://redd.it/7b85j1

Great tool from Google just released. A Jupyter-based (and Google Drive) now makes easy collaboration and access from any Chrome browser. Thanks Google!
https://research.google.com/colaboratory/unregistered.html

/r/Python
https://redd.it/7b7k1k

Vastly faster Python integration tests
https://medium.com/@boxed/vastly-faster-python-integration-tests-9d8106b3693c

/r/Python
https://redd.it/7b4yvg

Refresh on Django... book recommendations?

So, over the last two years, I became an intermediate Django developer. I felt like I could read and do almost anything in Django, but was way behind on the "right way" to do things. I changed jobs and spent a year away from programming and I feel like my skills are rusty.

I'd like to do a refresh on Django and I'd like to read a different book than I've read before. I've already read Two Scoops of Django and spent a lot of time in Django documentation.

Any recommendations?

/r/django
https://redd.it/7baea5

How to train your own Object Detector with TensorFlow’s Object Detector API
https://medium.com/towards-data-science/how-to-train-your-own-object-detector-with-tensorflows-object-detector-api-bec72ecfe1d9

/r/Python
https://redd.it/7b6ygw

Advice for zero downtime deployments with Django

Hello!

I'm starting a new project where high availability is a priority (meaning no dropped HTTP requests). I was wondering what strategies would you recommend for zero downtime deployments?

I realize that complicated DB migrations would have to done in several steps (like removing a column).

Thank you for your advice.

/r/django
https://redd.it/7bc1tk

Question about building an interactive website with Flask

I'm working on a project with the end goal of providing an interactive dashboard of statistical data from a PostgreSQL database.

* I have the Python scripts working to collect, parse and load the data into the database.
* I have the PostgreSQL code working to take the raw data and create the needed materialized views to present nice "tables" that have all the joins and such already done and the indexes needed for performance.
* I have a Flask+Flask-SQLAlchemy application setup that with the main layout, basic flat pages, and a first draft of the dashboard page that display a nicely formatted table of data from a predefined query hard-coded into the view to initialize the page with the most commonly requested data from the database.

But now I'm confused on how to make the website interactive to allow the user to, for example, select from icons in the sidebar to update the table of data based on what they want to see from the database.

I'd appreciate some pointers on different ways to provide this interactivity.

Searching Google isn't helping much because I don't know what to search for in the first place. All I'm finding is how to use Flask as a REST API with SPA frameworks like Angular/React doing all the front-end - not Flask specific solutions.

Edit: As a clarification - by interactivity I mean making choices that would set the parameters to use in the query of the data. The data is historical and read-only, so there won't be any user input forms.



/r/flask
https://redd.it/7b8y4n

[Help] Python KNN weighting during .predict()?

I'm using a KNN algorithm for a class (instructed to use this algorithm, may not what you'd expect for application, see below)

Essentially, we have a raspberry pi set up to collect the signal strengths of 6 local WIFI router Mac addresses. At different locations on a floor of our building we've recorded these signal strengths in .csv files.

Using python I've created a script which uses the functions on [this page](http://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html).

I fit a knn as below:

from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClassifier(n_neighbors=1, algorithm = 'auto')
knn.fit(strengths, labels)

where strengths is a nested array like this:

[[Loc1strengths],[Loc2strengths],[Loc3strengths],[Loc4strengths],[Loc5strengths],[Loc6strengths]]

labels is set up like this:

[Loc1, Loc2, Loc3, Loc4, Loc5, Loc6]



Later in the script, I collect the signal strengths of the 6 local WIFI router Mac addresses and try to predict the location of my pi using knn.predict() and hope to get the location of the pi, Location1 for example.

The results aren't great, it does a relatively poor job of figuring out where it is.

I was wondering if there was a way to weight the function of knn.predict() so that the neighbors of the most recent location are weighted more heavily, the pi won't move to the other side of the floor without crossing the other points.

Any help would be appreciated!


/r/pystats
https://redd.it/7baulc

RISE 5.1.0 is out! This is the reveal.js interactive slideshow environment for the Jupyter notebook!
http://www.damian.oquanta.info/posts/rise-510-is-out.html

/r/IPython
https://redd.it/7bcszh

How can I use a rich text editor in a django blog admin?

I am creating a dynamic blog using Django. I would like to enable the user of this blog to format the blog posts very easily using a rich text editor. How can I implement it with this Django blog admin?

/r/djangolearning
https://redd.it/7b6p83

What's everyone working on this week?

Tell /r/python what you're working on this week! You can be bragging, grousing, sharing your passion, or explaining your pain. Talk about your current project or your pet project; whatever you want to share.


/r/Python
https://redd.it/7bddxy

Interfacing Python and C: Advanced “ctypes” Features
https://dbader.org/blog/python-ctypes-tutorial-part-2#intro

/r/Python
https://redd.it/7bdiye

Practical Python List Comprehension Tutorial
https://www.datacamp.com/community/tutorials/python-list-comprehension?utm_source=reddit&utm_campaign=python_list

/r/Python
https://redd.it/7bemz6

How does a beginner learn Machine Learning?

I usually use R for my work and have a tiny bit of experience with Python. What's the best way for me to go about getting Python under my belt with the goal of mastering basic concepts in machine learning?
Specifically, I'm asking for suggestions in online courses, but also how should I think about this? Any advice is welcome. Thanks!

/r/Python
https://redd.it/7bextj

Trying to get a template/link working in Mezzanine

Hey all,

I'm working on a Mezzanine project. I made a `ProjectLinkPage` class that inherits from Mezzanine's Displayable class. I logged into the Admin section and added a `ProjectLinkPage` object with the slug "some-content." I want to open the template `some-content.html` by going to "http://127.0.0.1:8000/projects/some-content." This does not work. I get a 404 error.

Here's how my directory looks.

myProject/
- myProject/
-- urls.py
- theme/
-- models.py
-- views.py
-- templates/
--- pages/
---- project_pages/
----- project_base.html
----- projects/
------ some-content.html

My `models.py` looks like this:

class ProjectLinkPage(Displayable)
# Fields and `class Meta`, etc...
@models.permalink
def get_absolute_url(self):
return ("project_detail", (), {"slug": self.slug})

`views.py`:

def project_detail(request, slug, template="project_pages/project_base.html", extra_context=None):
project = get_object_or_404(Project, slug=slug, status=2)
context = {
"project": project,
"editable_obj": project
}
context.update(extra_context or {})

templates = [u"project_pages/projects/%s.html" % str(slug), template]
return TemplateResponse(request, templates, context)

`urls.py`:

`url("^projects/(?P<slug>.*)%s$" % _slash, project_detail, name="project_detail"),`.

Have I missed something in these files? What must I change for my browser to correctly locate the `some-content.html` template when I go to "http://127.0.0.1:8000/projects/some-content?"


/r/django
https://redd.it/7bfvm3