How does a Flask app serve multiple users/requests at once?
How does a Flask/Django app which is synchronous and single threaded serve multiple users at once?
Im learning a bit of JS off a playlist on Youtube and a video discusses async programming and its advantages in context of I/O. This made me wonder: are there certain kinds of web applications which are better suited to being developed using Node.js than a Python framework? Since a lot of the general web apps(read CRUD) need database access, would all such apps be better off being written in Node ?
/r/flask
https://redd.it/cesmvt
How does a Flask/Django app which is synchronous and single threaded serve multiple users at once?
Im learning a bit of JS off a playlist on Youtube and a video discusses async programming and its advantages in context of I/O. This made me wonder: are there certain kinds of web applications which are better suited to being developed using Node.js than a Python framework? Since a lot of the general web apps(read CRUD) need database access, would all such apps be better off being written in Node ?
/r/flask
https://redd.it/cesmvt
reddit
r/flask - How does a Flask app serve multiple users/requests at once?
24 votes and 6 comments so far on Reddit
ELK (Elasticsearch, Logstash & Kibana) stack setup in Django
Hey everyone.. Has anybody worked on ELK stack in their Django project?? If so please help me in integrating in my project.. Its really blowing up my mind and i need to finish the task.. Also if you could show some code that will be great..
I googled it and know what is the use of it but how to integrate it with Django i just couldn't understand.
/r/django
https://redd.it/cf2oxt
Hey everyone.. Has anybody worked on ELK stack in their Django project?? If so please help me in integrating in my project.. Its really blowing up my mind and i need to finish the task.. Also if you could show some code that will be great..
I googled it and know what is the use of it but how to integrate it with Django i just couldn't understand.
/r/django
https://redd.it/cf2oxt
reddit
r/django - ELK (Elasticsearch, Logstash & Kibana) stack setup in Django
2 votes and 2 comments so far on Reddit
The Simplest WSGI Middleware
https://adamj.eu/tech/2019/05/27/the-simplest-wsgi-middleware/
/r/django
https://redd.it/cf5qt3
https://adamj.eu/tech/2019/05/27/the-simplest-wsgi-middleware/
/r/django
https://redd.it/cf5qt3
adamj.eu
The Simplest WSGI Middleware - Adam Johnson
For me, one of the main barriers to the world of deep learning was setting up all the tools. Here's a video that I hope will eliminate this barrier. Hope you guys found it helpful!
https://www.youtube.com/watch?v=Ksu5zZIdfH0
/r/Python
https://redd.it/cf613i
https://www.youtube.com/watch?v=Ksu5zZIdfH0
/r/Python
https://redd.it/cf613i
YouTube
Installations for Deep Learning: Anaconda, Jupyter Notebook, Tensorflow, Keras | Keras #2
Link to download anaconda - https://www.anaconda.com/download/
Create environment ([EnvironmentName] takes place of your environment's name) for Mac and PC -
conda create -n [EnvironmentName]
Activate environment for Mac -
source activate [EnvironmentName]…
Create environment ([EnvironmentName] takes place of your environment's name) for Mac and PC -
conda create -n [EnvironmentName]
Activate environment for Mac -
source activate [EnvironmentName]…
Debugging Flask on a digital ocean droplet server (using ubuntu)
Recently I deployed my first Flask application on a Droplet that uses an Ubuntu with nginx and uWSGI.
Now, I have a problem and I can't use the GET/POST methods to signup and login, at least that is what I hypothesised, because I filled every input for the signup and when I tried to login I couldn't. Furthermore I tried to login with wrong credentials and I got an error, which is normal since I programmed it to output an error if I tried to login as a non-user.
Now if you try to recreate that exact problem follow [this tutorial](https://www.digitalocean.com/community/tutorials/how-to-serve-flask-applications-with-uswgi-and-nginx-on-ubuntu-18-04) and instead of the simple app that it uses just [git clone this repo](https://github.com/anfederico/Flaskex) which is a Flask example that uses an SQLite db (that is what I used as my base app to create the one that I wanted to deploy, so I thought that if it worked my Flask app will work as well).
But to summarize my problem; **I can't access the sub directories of my Flask app, using login/signup methods and I don't know how to debug that.**
Can anyone help me with that?
/r/flask
https://redd.it/cf4r9l
Recently I deployed my first Flask application on a Droplet that uses an Ubuntu with nginx and uWSGI.
Now, I have a problem and I can't use the GET/POST methods to signup and login, at least that is what I hypothesised, because I filled every input for the signup and when I tried to login I couldn't. Furthermore I tried to login with wrong credentials and I got an error, which is normal since I programmed it to output an error if I tried to login as a non-user.
Now if you try to recreate that exact problem follow [this tutorial](https://www.digitalocean.com/community/tutorials/how-to-serve-flask-applications-with-uswgi-and-nginx-on-ubuntu-18-04) and instead of the simple app that it uses just [git clone this repo](https://github.com/anfederico/Flaskex) which is a Flask example that uses an SQLite db (that is what I used as my base app to create the one that I wanted to deploy, so I thought that if it worked my Flask app will work as well).
But to summarize my problem; **I can't access the sub directories of my Flask app, using login/signup methods and I don't know how to debug that.**
Can anyone help me with that?
/r/flask
https://redd.it/cf4r9l
Digitalocean
How To Serve Flask Applications with uWSGI and Nginx on Ubuntu 18.04 | DigitalOcean
In this guide, we will be setting up a simple Python application using the Flask microframework on Ubuntu 18.04. The bulk of this article will be about how t…
I made an application which shows a new motivational quote every 2 minutes.
/r/Python
https://redd.it/cf3n3v
/r/Python
https://redd.it/cf3n3v
[P] I made a video review of The Hundred-Page Machine Learning Book
I enjoy learning about machine learning.
And I enjoy making videos.
So I made a video reviewing [The Hundred-Page Machine Learning Book](https://themlbook.com) by Andriy Burkov.
I read it from the perspective of a machine learning engineer and still learned a bunch.
If you haven't checked out the book, it's a great concise read. There's nothing like a complex topic explained simply.
If you do watch the video, any advice on ways to improve or future reviews/topics would be greatly appreciated.
[https://youtu.be/btLxTTkSZuY](https://youtu.be/btLxTTkSZuY)
/r/MachineLearning
https://redd.it/cf4rh5
I enjoy learning about machine learning.
And I enjoy making videos.
So I made a video reviewing [The Hundred-Page Machine Learning Book](https://themlbook.com) by Andriy Burkov.
I read it from the perspective of a machine learning engineer and still learned a bunch.
If you haven't checked out the book, it's a great concise read. There's nothing like a complex topic explained simply.
If you do watch the video, any advice on ways to improve or future reviews/topics would be greatly appreciated.
[https://youtu.be/btLxTTkSZuY](https://youtu.be/btLxTTkSZuY)
/r/MachineLearning
https://redd.it/cf4rh5
YouTube
The Hundred-Page Machine Learning Book Book Review
The Hundred-Page Machine Learning Book. The start here and continue here of machine learning. The book I wish I had when I started learning machine learning.
Buy it on Amazon - https://bit.ly/100pageMLbook
Read it online - https://bit.ly/100pageMLbookhome…
Buy it on Amazon - https://bit.ly/100pageMLbook
Read it online - https://bit.ly/100pageMLbookhome…
[P] Comprehensive Machine Learning Trading Strategies - Google Colab
100+ Machine Learning Trading Strategies
[https://github.com/firmai/machine-learning-asset-management](https://github.com/firmai/machine-learning-asset-management)
​
\- Deep Learning
\- Reinforcement Learning
\- Evolutionary Strategies
\- Stacked Models
/r/MachineLearning
https://redd.it/cf111a
100+ Machine Learning Trading Strategies
[https://github.com/firmai/machine-learning-asset-management](https://github.com/firmai/machine-learning-asset-management)
​
\- Deep Learning
\- Reinforcement Learning
\- Evolutionary Strategies
\- Stacked Models
/r/MachineLearning
https://redd.it/cf111a
GitHub
GitHub - firmai/machine-learning-asset-management: Machine Learning in Asset Management (by @firmai)
Machine Learning in Asset Management (by @firmai). Contribute to firmai/machine-learning-asset-management development by creating an account on GitHub.
I created a GitHub repository explaining the complete process of gathering data, transforming it, getting insights and making plots using pandas, NumPy, Matplotlib and Seaborn.
https://github.com/PhantomInsights/baby-names-analysis
/r/Python
https://redd.it/cf7y1m
https://github.com/PhantomInsights/baby-names-analysis
/r/Python
https://redd.it/cf7y1m
GitHub
GitHub - PhantomInsights/baby-names-analysis: Data ETL & Analysis on the dataset 'Baby Names from Social Security Card Applications…
Data ETL & Analysis on the dataset 'Baby Names from Social Security Card Applications - National Data'. - PhantomInsights/baby-names-analysis
How to link Flask static files?
I am making a basic blog using HTML,and CSS. I linked my HTML file but I am having trouble linking the CSS.
This is the following code:
from flask import Flask,render_template,url_for
app = Flask(__name__)
@app.route('/')
def hello_world():
return render_template('home.html'), url_for('static', filename='main.css')
Thanks,
/r/flask
https://redd.it/cf7zr4
I am making a basic blog using HTML,and CSS. I linked my HTML file but I am having trouble linking the CSS.
This is the following code:
from flask import Flask,render_template,url_for
app = Flask(__name__)
@app.route('/')
def hello_world():
return render_template('home.html'), url_for('static', filename='main.css')
Thanks,
/r/flask
https://redd.it/cf7zr4
reddit
r/flask - How to link Flask static files?
3 votes and 7 comments so far on Reddit
Is there a tutorial around to make a reddit like site?
I've googled it but keep finding reddit threads about making django sites. I would like to make something like reddit, but not sure where to start. Having a guide or tutorial I could follow would help a lot.
/r/django
https://redd.it/cfbapi
I've googled it but keep finding reddit threads about making django sites. I would like to make something like reddit, but not sure where to start. Having a guide or tutorial I could follow would help a lot.
/r/django
https://redd.it/cfbapi
reddit
r/django - Is there a tutorial around to make a reddit like site?
7 votes and 4 comments so far on Reddit
Pythonanywhere email send does not work
So I just released my site on Pythonanywhere, but one of my features is not working. A user presses a button after filling out a form, and then the data is saved to my admin (which works) and an email is supposed to send to out me and the user. However, the email is not going out. When I try it on my local machine with the same code, it works, but on the pythonanywhere it doesnt.
/r/django
https://redd.it/cfgffy
So I just released my site on Pythonanywhere, but one of my features is not working. A user presses a button after filling out a form, and then the data is saved to my admin (which works) and an email is supposed to send to out me and the user. However, the email is not going out. When I try it on my local machine with the same code, it works, but on the pythonanywhere it doesnt.
/r/django
https://redd.it/cfgffy
reddit
r/django - Pythonanywhere email send does not work
0 votes and 1 comment so far on Reddit
Sales Records API endpoint with Django Rest Framework and Django Filters with Docker
https://github.com/talented/Sales-Records-API
/r/django
https://redd.it/cfcyj7
https://github.com/talented/Sales-Records-API
/r/django
https://redd.it/cfcyj7
GitHub
talented/Sales-Records-API
Sales Records API endpoint with Django Rest Framework and Django Filters with Docker - talented/Sales-Records-API
Updating static files?
So currently, the only way I can get changes to static files to take in my app is to add version numbers to my <link> like so:
<link href="{url_for('static', filename='css/style.css', version='30')}" rel="stylesheet">
But this can get tedious if you're just making incremental changes while testing. So is there a better way to update my static files and have them take effect without constantly changing the version number?
/r/flask
https://redd.it/cf9lrp
So currently, the only way I can get changes to static files to take in my app is to add version numbers to my <link> like so:
<link href="{url_for('static', filename='css/style.css', version='30')}" rel="stylesheet">
But this can get tedious if you're just making incremental changes while testing. So is there a better way to update my static files and have them take effect without constantly changing the version number?
/r/flask
https://redd.it/cf9lrp
reddit
r/flask - Updating static files?
7 votes and 10 comments so far on Reddit
Pure Python Implementation of 100+ Stock Trading Strategies - Google Colab
I have always held the belief that one of the best ways to learn about data-science/python is to find problems to solve in finance where the data is plentiful.
I will add the list here so that you won't have to go to GitHub or the SSRN file. It is a list of a few strategies and some portfolio optimisation techniques. They all have an ML bent. Like before any criticism and feedback is highly appreciated.
Source: [https://github.com/firmai/machine-learning-asset-management](https://github.com/firmai/machine-learning-asset-management)
**1. Tiny CTA**
*Resources*:
See this [paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2695101) and [blog](https://www.linkedin.com/pulse/implement-cta-less-than-10-lines-code-thomas-schmelzer/) for further explanation.
[Data](http://drive.google.com/open?id=12BB8KpFYJSx41yvHhtoLYE_ZZOHNamP8), [Code](https://drive.google.com/open?id=1EwbHhBZL_PRTphR25EbMQA9dV7jC4CjT)
**2. Tiny RL**
*Resources*:
See this [paper](http://cs229.stanford.edu/proj2006/Molina-StockTradingWithRecurrentReinforcementLearning.pdf) and/or [blog](https://teddykoker.com/) for further explanation.
[Data](https://drive.google.com/open?id=1k7J5y1xCssIna45d_Xw78d2frgzD94Li), [Code](https://drive.google.com/open?id=1IRrR6kWjunERzZqrszJ9_q-C1Yj5L0Qj)
**3. Tiny VIX CMF**
*Resources*:
[Data](https://drive.google.com/open?id=1Yv2_mTjZMANoL9fM0ajOsOFEc9MJZAMU), [Code](https://drive.google.com/open?id=186j-gtkXCgzj06WCWDAU9yhYXP9SfgLu)
**4. Quantamental**
*Resources*:
[Web-scrapers](https://drive.google.com/drive/folders/12aZ7vg_3HIdPYZ4GavYY7BjptlAPGFtc?usp=sharing), [Data](https://drive.google.com/open?id=1b0OXiSKnacEDftYKgov619SCfXwpcUWT), [Code](https://drive.google.com/open?id=1PqtFfcr1ejreGr6XIoZCs8jsD7AccuL7), [Interactive Report](https://github.com/firmai/interactive-corporate-report), [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420490).
**5. Earnings Surprise**
*Resources*:
[Code](https://drive.google.com/open?id=1KtGauKizS8QISuDCW0SwIxbYPeBwTQxF), [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420722)
**6. Bankruptcy Prediction**
*Resources*:
[Data](https://drive.google.com/open?id=1UAIZBNHag-AdWZ4z7nd_y5THQ89D-IQh), [Code](https://drive.google.com/open?id=1Z2ZyvEoWsRfHSa1f7g0m1O-JiXedUdb_), [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420889)
**7. Filing Outcomes**
*Resources*:
[Data](https://drive.google.com/open?id=1cDhrrAp07e-2TgrPQginXUNQpdbTpq-u)
**8. Credit Rating Arbitrage**
*Resources:*
[Code](https://drive.google.com/open?id=1i_yERL4i6qp57C0LdSWEV8iYv_rtAZLF)
**9. Factor Investing:**
*Resources:*
[Paper](https://docplayer.net/120877135-Industry-return-predictability-a-machine-learning-approach.html), [Code](https://drive.google.com/open?id=1O0LQ_khTfsbFG5aN3-AqV6DEIRWQ6UuP), [Data](https://drive.google.com/open?id=1cc43729RyOPCsDJ3r46SdHcJJp1AUmaA)
**10. Systematic Global Macro**
*Resources:*
[Data](https://drive.google.com/open?id=1ePKFtfjBrfg3xDtg_dbssykeSd8ZmA1z), [Code](https://drive.google.com/open?id=10bN3kNjl9EMDB5Tt1ArXO8IaxLiPh_Zd)
**11. Mixture Models**
*Resources*:
[Data](https://drive.google.com/open?id=1jmR2Jlk6Hy7J7c2jZFEK1oXptOHbDYLK), [Code](https://drive.google.com/open?id=1tRIt7lIJErWKwoHIuBS6rZbZo2EYBNTN)
**12. Evolutionary**
*Resources*:
[Code](https://drive.google.com/open?id=116Aj9kbZcrCyR5MDu58HkWE53lacAE52)
**13. Agent Strategy**
*Resources*:
[Code](https://drive.google.com/open?id=1qCvIeui5dJKMXnjUm9_wiPf65VVHdWwz)
**14. Stacked Trading**
*Resources*:
[Code](https://drive.google.com/open?id=11SG9KIWUxV9fgrrpAs0QifgGrcdzk2dh), [Blog](https://www.kdnuggets.com/2017/02/stacking-models-imropved-predictions.html)
**15. Deep Trading**
*Resources*:
/r/Python
https://redd.it/cfevn9
I have always held the belief that one of the best ways to learn about data-science/python is to find problems to solve in finance where the data is plentiful.
I will add the list here so that you won't have to go to GitHub or the SSRN file. It is a list of a few strategies and some portfolio optimisation techniques. They all have an ML bent. Like before any criticism and feedback is highly appreciated.
Source: [https://github.com/firmai/machine-learning-asset-management](https://github.com/firmai/machine-learning-asset-management)
**1. Tiny CTA**
*Resources*:
See this [paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2695101) and [blog](https://www.linkedin.com/pulse/implement-cta-less-than-10-lines-code-thomas-schmelzer/) for further explanation.
[Data](http://drive.google.com/open?id=12BB8KpFYJSx41yvHhtoLYE_ZZOHNamP8), [Code](https://drive.google.com/open?id=1EwbHhBZL_PRTphR25EbMQA9dV7jC4CjT)
**2. Tiny RL**
*Resources*:
See this [paper](http://cs229.stanford.edu/proj2006/Molina-StockTradingWithRecurrentReinforcementLearning.pdf) and/or [blog](https://teddykoker.com/) for further explanation.
[Data](https://drive.google.com/open?id=1k7J5y1xCssIna45d_Xw78d2frgzD94Li), [Code](https://drive.google.com/open?id=1IRrR6kWjunERzZqrszJ9_q-C1Yj5L0Qj)
**3. Tiny VIX CMF**
*Resources*:
[Data](https://drive.google.com/open?id=1Yv2_mTjZMANoL9fM0ajOsOFEc9MJZAMU), [Code](https://drive.google.com/open?id=186j-gtkXCgzj06WCWDAU9yhYXP9SfgLu)
**4. Quantamental**
*Resources*:
[Web-scrapers](https://drive.google.com/drive/folders/12aZ7vg_3HIdPYZ4GavYY7BjptlAPGFtc?usp=sharing), [Data](https://drive.google.com/open?id=1b0OXiSKnacEDftYKgov619SCfXwpcUWT), [Code](https://drive.google.com/open?id=1PqtFfcr1ejreGr6XIoZCs8jsD7AccuL7), [Interactive Report](https://github.com/firmai/interactive-corporate-report), [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420490).
**5. Earnings Surprise**
*Resources*:
[Code](https://drive.google.com/open?id=1KtGauKizS8QISuDCW0SwIxbYPeBwTQxF), [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420722)
**6. Bankruptcy Prediction**
*Resources*:
[Data](https://drive.google.com/open?id=1UAIZBNHag-AdWZ4z7nd_y5THQ89D-IQh), [Code](https://drive.google.com/open?id=1Z2ZyvEoWsRfHSa1f7g0m1O-JiXedUdb_), [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3420889)
**7. Filing Outcomes**
*Resources*:
[Data](https://drive.google.com/open?id=1cDhrrAp07e-2TgrPQginXUNQpdbTpq-u)
**8. Credit Rating Arbitrage**
*Resources:*
[Code](https://drive.google.com/open?id=1i_yERL4i6qp57C0LdSWEV8iYv_rtAZLF)
**9. Factor Investing:**
*Resources:*
[Paper](https://docplayer.net/120877135-Industry-return-predictability-a-machine-learning-approach.html), [Code](https://drive.google.com/open?id=1O0LQ_khTfsbFG5aN3-AqV6DEIRWQ6UuP), [Data](https://drive.google.com/open?id=1cc43729RyOPCsDJ3r46SdHcJJp1AUmaA)
**10. Systematic Global Macro**
*Resources:*
[Data](https://drive.google.com/open?id=1ePKFtfjBrfg3xDtg_dbssykeSd8ZmA1z), [Code](https://drive.google.com/open?id=10bN3kNjl9EMDB5Tt1ArXO8IaxLiPh_Zd)
**11. Mixture Models**
*Resources*:
[Data](https://drive.google.com/open?id=1jmR2Jlk6Hy7J7c2jZFEK1oXptOHbDYLK), [Code](https://drive.google.com/open?id=1tRIt7lIJErWKwoHIuBS6rZbZo2EYBNTN)
**12. Evolutionary**
*Resources*:
[Code](https://drive.google.com/open?id=116Aj9kbZcrCyR5MDu58HkWE53lacAE52)
**13. Agent Strategy**
*Resources*:
[Code](https://drive.google.com/open?id=1qCvIeui5dJKMXnjUm9_wiPf65VVHdWwz)
**14. Stacked Trading**
*Resources*:
[Code](https://drive.google.com/open?id=11SG9KIWUxV9fgrrpAs0QifgGrcdzk2dh), [Blog](https://www.kdnuggets.com/2017/02/stacking-models-imropved-predictions.html)
**15. Deep Trading**
*Resources*:
/r/Python
https://redd.it/cfevn9
GitHub
GitHub - firmai/machine-learning-asset-management: Machine Learning in Asset Management (by @firmai)
Machine Learning in Asset Management (by @firmai). Contribute to firmai/machine-learning-asset-management development by creating an account on GitHub.
[book] Django for Professionals - Learn how to build production-ready websites with Python & Django
https://djangoforprofessionals.com/
/r/django
https://redd.it/cfkrl7
https://djangoforprofessionals.com/
/r/django
https://redd.it/cfkrl7
Learndjango
LearnDjango | LearnDjango.com
LearnDjango is a platform for learning Django, a popular Python web framework for building web applications. It offers tutorials and courses to help you master your craft and boost your career.
Receiving and then Serving image files
So I get an image file with the following sample URL (http://localhost:8096/image/blah). I would like to then serve this image via a flask route.
So I have at the moment
@app.route('/image/blah')
def __blahimage():
import requests
r = requests.get('http://localhost:8096/image/blah')
#Response 200
return send_file(r.text)
This does not seem to be the correct way. I'm new to Python in general and the reason I'm doing this is because the images are available on a local server only. The flask is a wrapper essentially.
/r/flask
https://redd.it/cfka7t
So I get an image file with the following sample URL (http://localhost:8096/image/blah). I would like to then serve this image via a flask route.
So I have at the moment
@app.route('/image/blah')
def __blahimage():
import requests
r = requests.get('http://localhost:8096/image/blah')
#Response 200
return send_file(r.text)
This does not seem to be the correct way. I'm new to Python in general and the reason I'm doing this is because the images are available on a local server only. The flask is a wrapper essentially.
/r/flask
https://redd.it/cfka7t
reddit
r/flask - Receiving and then Serving image files
2 votes and 8 comments so far on Reddit
Is Flask a good fit for this kind of service ?
Hi everyone,
I'm in the very early stages of evaluating the technical options available for an online tool. So far my research showed me that yes, Flask is a good solution. I've always heard good things about it, but I'd like to get some reinsurance from people who work with it on a daily basis.
I play a bit with Python myself but I'm nowhere near a technical guy. I'm probably unaware of the best ways to handle, store, feed and serve large data stream. Pardon in advance any incongruous consideration.
​
Here's the big picture : get data from APIs/scraping > do some data wrangling > serve that to a pretty font-end.
Flask can do that as far as I know.
Now at first the features should be basic:
Pull data from APIs > do some parsing & statistical stuff with it (Pandas, Geopandas), feed some dashboards with tables / dynamic graphs, add vector layers to maps.
​
From what I understand, for the earlier, more basic phase, I should do fine with a good fullstack dev and a good server and that should be enough to get the thing up and running (+ maintenance), right ?
​
Later on some additional tasks could be added, such as:
* scrape
/r/flask
https://redd.it/cflc3p
Hi everyone,
I'm in the very early stages of evaluating the technical options available for an online tool. So far my research showed me that yes, Flask is a good solution. I've always heard good things about it, but I'd like to get some reinsurance from people who work with it on a daily basis.
I play a bit with Python myself but I'm nowhere near a technical guy. I'm probably unaware of the best ways to handle, store, feed and serve large data stream. Pardon in advance any incongruous consideration.
​
Here's the big picture : get data from APIs/scraping > do some data wrangling > serve that to a pretty font-end.
Flask can do that as far as I know.
Now at first the features should be basic:
Pull data from APIs > do some parsing & statistical stuff with it (Pandas, Geopandas), feed some dashboards with tables / dynamic graphs, add vector layers to maps.
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From what I understand, for the earlier, more basic phase, I should do fine with a good fullstack dev and a good server and that should be enough to get the thing up and running (+ maintenance), right ?
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Later on some additional tasks could be added, such as:
* scrape
/r/flask
https://redd.it/cflc3p
reddit
r/flask - Is Flask a good fit for this kind of service ?
4 votes and 3 comments so far on Reddit
How to build a File Manager Storage web app with Django Rest Framework and Vue.js with Vuex and Ag-grid integration
https://medium.com/js-dojo/how-to-build-a-file-manager-storage-web-app-with-django-rest-framework-and-vue-js-e89a83318e9c
/r/django
https://redd.it/cfnglh
https://medium.com/js-dojo/how-to-build-a-file-manager-storage-web-app-with-django-rest-framework-and-vue-js-e89a83318e9c
/r/django
https://redd.it/cfnglh
Medium
Part 1 — How to build a File Manager Storage web app with Django Rest Framework and Vue.js with Vuex and Ag-grid integration
Since beginning of this year, I have been attending an online course. We have a platform that enables us to store and share files…
My Website (Audio Converter) which has a Flask/Python backend.
This is a non-profit website that I work on in my free time. Many formats are supported. No software to download and easy to use.
You can access my website via either of the following URLs:
https://onlineaudioconverter.net
https://freeaudioconverter.net
Feedback is welcome :)
/r/flask
https://redd.it/cfol51
This is a non-profit website that I work on in my free time. Many formats are supported. No software to download and easy to use.
You can access my website via either of the following URLs:
https://onlineaudioconverter.net
https://freeaudioconverter.net
Feedback is welcome :)
/r/flask
https://redd.it/cfol51
onlineaudioconverter.net
Convert Audio Files or Extract Audio from Video. No software download!
Convert audio files to MP3, WAV, AAC, FLAC, Opus, Vorbis, and more! You can also extract the audio from a video and save it as an audio file.