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[Ask Flask] is it possible to POST without moving?

I'm working on a mild app that uses form POST to send data to Flask, but can't figure out if there's a way to post in pure HTML / CSS without moving to the new page, being the POST page.

Is there?

/r/flask
https://redd.it/697mhq
Require login for entire site?

I found [this](http://onecreativeblog.com/post/59051248/django-login-required-middleware#code) blogpost, but it's very old. Is this still a viable approach or are there better alternatives?


/r/djangolearning
https://redd.it/67mjq9
Can Jupyter (or similar) replace Excel?

I hope this question fit's here. If it's a dumb question, tell me and I'll delete it.

1. I don't want to encourage a war.
2. **I admit, that I don't know Jupyter or Excel well!**

Both programs can be used to analyze data.

*As far as I know* Jupyter, it's a bit like Python in the interactive mode, with some extra amenities and easy plotting of graphs. It's mostly used by scientists.

*As far as I know* in Excel, you have files that consist of big tables and in each cell there can either be data, computations, or some explanations like column names. You can probably also connect to dedicated data files/databases and dedicated files with code. You can also use it to make graphs. It's used in "business".

As I said: That is probably not entirely true - that's why I'm asking.

I'm a student of computer science and we learn that you should separate data, metadata, and computation and that having "locations" for data is "bad". In the sense that "goto [line]" commands are bad and pointers are bad if you want maintainability and productivity (of course pointers have their place). To me it seems like Excel makes these errors. (I know that you can give cells names.)

Jupyter can't be used to store and edit structured data (well), I think.

Is anyone of you familiar with both technologies?
What are some good use cases for Excel?
If Jupyter isn't it, do you know other potential replacements for Excel?

…Excel is reactive/"live", which is nice – you don't have to press "run".

/r/IPython
https://redd.it/69nmpa
quickest way to browse web-scraped data?

Hello there.
So, I'm looking for a house, so I wrote a crawler that scrape data from several local real estate agencies and do some filtering (number of rooms, price, etc). All data is currently saved in a sqlite database.

Now, the problem is: what is the quickest way to present the data? I was thinking about making a small Flask-based website to browse the data, deleted records, etc. but that seems a lot of work for an application which will have just two users (me and my GF).

Is there any framework which can help me?

Thanks!

/r/Python
https://redd.it/69mixz
A forensic toolkit in Python

https://github.com/MonroCoury/Forensic-Tools

A project I been working on, a bunch of Python scripts that facilitate digital forensic analysis.


Features:

-Document metadata extraction.

-Image EXIF metadata extraction.

-Firefox database parsing, including extracting cookies, history, form history, Google searches, and downloads. Can limit results to a certain time range.

-Skype database parsing, including Account details, contacts with full details, call log, and messages. Ability to look for messages/calls within a given time range and/or from/to a specific partner.

-Results are saved to html tables with row background highlighting for easier reading.

-I'm trying to make it as simple and easy to use as possible. Firefox scanner attempts to find the default databases across different platforms on its own should the user forget to point it.


Still a work in progress. Planned features:

-Chrome browsing data extraction

-Internet Explorer browsing data extraction

-Network traffic analysis

-Windows registry parsing

-PDF, zip, and rar password cracking

Feedback is most welcome!

/r/Python
https://redd.it/69nc8c
[D] Oxford deep nlp 2017 solutions

My solutions here: https://github.com/mleue/oxford-deep-nlp-2017-solutions

I've recently been going through the lectures of oxford's 2017 deep nlp course (https://github.com/oxford-cs-deepnlp-2017). The course was well presented and I've really deepened my understanding of modern NLP methods.

Naturally I am going through the practicals as well. I've linked to the repo with my current progress but I feel a bit stuck atm.

The main task revolves around a multi-class classification of ~2k transcripts of TED talks. However, the dataset is heavily skewed with one class covering ~50% and some classes only around 3-5% of the data.

Practical 2 wants you to try a basic averaging over word-vectors approach and then pumping that through a single-hidden-layer NN. I've been trying to tweak a lot with preprocessing and tokenization but I can't come beyond ~66% accuracy on the test set.

In Practical 3 you are then supposed to try the same task with a RNN approach. I thought this might get better but I am basically stuck at around the same test set accuracy of ~66%.

Maybe not much more is possible, especially given the fact that there is very little data for some of the classes. Basically I am wondering if anyone else has gone through the course (or even attended the real deal at oxford) so we can get a discussion going.

Thanks in advance! //Michael

/r/MachineLearning
https://redd.it/69pzdg
[AF] FLASK_DEBUG=1 won't start my flask application?

Hello, so I just found out on Windows that I can't run my flask app when I set the debug to true.

I may have done something wrong with config files? Or is it the fault of cmder where I try to tun this app? Or ... I don't have a clue. Pretty new to this.

Log:

D:\Programovani\github\beta-issues (master)
λ set FLASK_APP=flaskr

D:\Programovani\github\beta-issues (master)
λ set FLASK_DEBUG=1

D:\Programovani\github\beta-issues (master)
λ flask run
* Serving Flask app "flaskr"
* Forcing debug mode on
* Restarting with stat
File "C:\Python36\Scripts\flask.exe", line 1
SyntaxError: Non-UTF-8 code starting with '\x90' in file C:\Python36\Scripts\flask.exe on line 1, but no encoding declared; see http://python.org/dev/peps/pep-0263/ for details

D:\Programovani\github\beta-issues (master)
λ set FLASK_DEBUG=0

D:\Programovani\github\beta-issues (master)
λ flask run
* Serving Flask app "flaskr"
* Forcing debug mode off
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)

Without debug the app starts normally.

Edit: The app is modified *Official Flask Tutorial* Flaskr app. [GitHub repo](http://www.github.com/SonGokussj4/beta-issues)

/r/flask
https://redd.it/69kjlg