Need help for integrating python model to mern stack project

Hello, I am building a ai therapist as my college project and for that I want to integrate python sentiment analysis model into my application.The idea of my webapp is that users can ask a therapy query to ai and the sentiment analysis model will identify the user sentiment and sent the query to gpt model which will then send the response back in chat.Can someone please guide me on the integration.

/r/flask
https://redd.it/1ndbvqa

How to use JWT tokens stored in cookies for evey API requests

I'm using Django template and htmx for the frontend. I'm facing an issue of getting the tokens stored in the cookies to the API. The cookies are stored, but the API doesn't get them. I checked the internet, but I couldn't find one that explains it.

class CustomTokenObtainApiView(TokenObtainPairView):
    def post(self, request, *args, **kwargs):
        serializer = self.get_serializer(data = request.data)
        serializer.is_valid(raise_exception = True)
        tokens = serializer.validated_data

        response = Response({'details': 'login successful'})

        response.set_cookie(
            'access_token', tokens['access'], httponly=True, secure=False, samesite='lax'
        )
        response.set_cookie(
            'refresh_token', tokens['refresh'], httponly=True, secure=False, samesite='lax'
        )
        response["HX-Redirect"] = "/homepage/"
        return response



Here

/r/django
https://redd.it/1ne37xz

detroit: Python implementation of d3js

Hi, I am the maintainer of detroit. detroit is a Python implementation of the library d3js. I started this project because I like how flexible data visualization is with d3js, and because I'm not a big fan of JavaScript.

You can find the documentation for detroit here.

Target Audience

`detroit` allows you to create static data visualizations. I'm currently working on [detroit-live](https://github.com/bourbonut/detroit-live) for those who also want interactivity. In addition, `detroit` requires only [lxml](https://lxml.de/) as dependency, which makes it lightweight.

You can find a gallery of examples in the [documentation](https://detroit.readthedocs.io/en/latest/#gallery). Most of examples are directly inspired by [d3js examples on observablehq](https://observablehq.com/@d3/gallery).

Comparison

The API is almost the same:

// d3js
const scale = d3.scaleLinear().domain(0, 10).range(0, 920);
console.log(scale.domain()) // 0, 10

# detroit
scale = d3.scalelinear().setdomain(0, 10).setrange([0, 920])
print(scale.getdomain()) # 0, 10

The difference between d3js/detroit and matplotlib/plotly/seaborn is the approach to data visualization. With matplotlib, plotly, or seaborn, you only need to write a few lines and that's it - you get your visualization. However, if you want to customize some parts, you'll have to add a couple more lines, and it can

/r/Python
https://redd.it/1ne4t1d

DNVIDIA Blackwell Ultra crushes MLPerf

NVIDIA dropped MLPerf results for Blackwell Ultra yesterday. 5× throughput on DeepSeek-R1, record runs on Llama 3.1 and Whisper, plus some clever tricks like FP8 KV-cache and disaggregated serving. The raw numbers are insane.

But I wonder though . If these benchmark wins actually translate into lower real-world inference costs.

In practice, workloads are bursty. GPUs sit idle, batching only helps if you have steady traffic, and orchestration across models is messy. You can have the fastest chip in the world, but if 70% of the time it’s underutilized, the economics don’t look so great to me. IMO

/r/MachineLearning
https://redd.it/1ndo5md

Django REST Framework: request.version is unknown

👋 Hi everyone,

I’m working on a project using Django REST Framework and I’m trying to switch serializers depending on the API version. My ViewSet looks like this:

class EstudanteViewSet(viewsets.ModelViewSet):

queryset = Estudante.objects.all()

filter_backends = [DjangoFilterBackend, filters.OrderingFilter, filters.SearchFilter]

ordering_fields = ['nome']

search_fields = ['nome', 'cpf']



def get_serializer_class(self):

if self.request.version == 'v2': # the problem is in the "version"

return EstudanteSerializerV2

return EstudanteSerializer

But when I run this, I get an error saying that the attribute version is unknown (or None).

How can I fix this so that versioning works correctly and the serializer changes based on the version?

Thanks!

/r/django
https://redd.it/1ndw8pl

Cant use flask run for some reason

I've been trying to run flask in vscode for a while now but I can't get it to work. The error message i get is:

Try 'flask run --help' for help.



Error: Failed to find Flask application or factory in module 'app'. Use 'app:name' to specify one.

I've tried everything. Running export and checking my code for any mistakes but flask run just doesnt work. What do yall suggest

/r/flask
https://redd.it/1ncis3e

How to Build Your Own Bluetooth Scriptable Sniffer using python for Under $25

A Bluetooth sniffer is a hardware or software tool that captures and monitors Bluetooth communication between devices. Think of it as a network traffic analyzer, but for Bluetooth instead of Wi-Fi or Ethernet.
There are high-end Bluetooth sniffers on the market — like those from Ellisys or Teledyne LeCroy — which are powerful but often cost hundreds or thousands of dollars.
You can create your own scriptable BLE sniffer for under $25. the source code is available in this post, you can adjust the code and work further
https://www.bleuio.com/blog/how-to-build-your-own-bluetooth-scriptable-sniffer-for-under-30/

/r/Python
https://redd.it/1ne4z4b

Recommend a good email digest about django

Can someone recommend a good programming digest focused on django, drf? Substack, behive or similar, with interesting topics and good curation.

/r/django
https://redd.it/1neat6h

Friday Daily Thread: r/Python Meta and Free-Talk Fridays

# Weekly Thread: Meta Discussions and Free Talk Friday 🎙️

Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!

## How it Works:

1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.

## Guidelines:

All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.

## Example Topics:

1. New Python Release: What do you think about the new features in Python 3.11?
2. Community Events: Any Python meetups or webinars coming up?
3. Learning Resources: Found a great Python tutorial? Share it here!
4. Job Market: How has Python impacted your career?
5. Hot Takes: Got a controversial Python opinion? Let's hear it!
6. Community Ideas: Something you'd like to see us do? tell us.

Let's keep the conversation going. Happy discussing! 🌟

/r/Python
https://redd.it/1neoksd

What is the quickest and easiest way to fix indentation errors?

Context - I've been writing Python for a good number of years and I still find indentation errors annoying. Also I'm using VScode with the Python extension.

How often do you encounter them? How are you dealing with them?

Because in Javascript land (and other languages too), there are some linters that look to be taking care of that.

/r/Python
https://redd.it/1neno5h

Starting Django, lost now

Started learning Django recently and searched firstly on YouTube for courses, all I found were either project focused courses which I can't understand how people learn from , there aren't many theory-heavy focused courses , I'm searching online rn and I can use any help to direct me to the right path , seriously anything just shoot me.

/r/djangolearning
https://redd.it/1nead8e

fp-style pattern matching implemented in python

I'm recently working on a functional programming library in python. One thing I've really want in python was a pattern matching that is expression and works well with other fp stuff in python. I went through similar fp libs in python such as `toolz` but didn't yet found a handy pattern matching solution in python. Therefore, I implement this simple pattern matching that works with most of objects (through itemgetter and attrgetter), iterables (just iter through), and literals (just comparison) in python.

- target audience

There's [link](https://github.com/BrandenXia/fp-cate) to the github repo. Note that it's still in very early development and also just a personal toy project, so it's not meant to be used in production at all.

There's some example I wrote using this library. I'd like to get some advice and suggestions about possible features and improvements I make for this functionality :)

```py
from dataclasses import dataclass

from fp_cate import pipe, match, case, matchV, _any, _rest, default


# works with any iterables
a = "test"
print(
matchV(a)(
case("tes") >> (lambda x: "one"),
case(["a", _rest]) >> (lambda x, xs: f"list starts with a, rest is {xs}"),


/r/Python
https://redd.it/1nem1ty

Best way to install python package with all its dependencies on an offline pc. -- Part 2

This is a follow up post to https://www.reddit.com/r/Python/comments/1keaeft/best\_way\_to\_install\_python\_package\_with\_all\_its/
I followed one of the techniques shown in that post and it worked quite well.
So in short what i do is
first do
python -m venv . ( in a directory)
then .\Scripts\activate
then do the actual installation of the package with pip install <packagename>
then i do a pip freeze > requirements.txt
and finally i download the wheels using this requirements.txt.
For that i create a folder called wheel and then I do a pip download -r requirements.txt
then i copy over the wheels folder to the offline pc and create a venv over there and do the install using that wheel folder.

So all this works quite well as long as there as only wheel files in the package.
Lately I see that there are packages that need some dependencies that need to be built from source so instead of the whl file a tar.gz file gets downloaded in the wheel folder. And somehow that tar.gz doesn't get built on the offline pc due to lack of dependencies or sometimes buildtools or setuptools version mismatch.

Is there a way

/r/Python
https://redd.it/1ner9mj

html2pic: transform basic html&css to image, without a browser (experimental)

Hey everyone,

For the past few months, I've been working on a personal graphics library called [PicTex](https://github.com/francozanardi/pictex). As an experiment, I got curious to see if I could build a lightweight HTML/CSS to image converter on top of it, without the overhead of a full browser engine like Selenium or Playwright.

**Important**: this is a proof-of-concept, and a large portion of the code was generated with AI assistance (primarily Claude) to quickly explore the idea. It's definitely not production-ready and likely has plenty of bugs and unhandled edge cases.

I'm sharing it here to show what I've been exploring, maybe it could be useful for someone.

Here's the link to the repo: [https://github.com/francozanardi/html2pic](https://github.com/francozanardi/html2pic)

---

### What My Project Does

`html2pic` takes a subset of HTML and CSS and renders it into a PNG, JPG, or SVG image, using Python + Skia. It also uses BeautifulSoup4 for HTML parsing, tinycss2 for CSS parsing.

Here’s a basic example:

```python
from html2pic import Html2Pic

html = '''
<div class="card">
<div class="avatar"></div>
<div class="user-info">
<h2>pictex_dev</h2>
<p>@python_renderer</p>
</div>
</div>
'''

css = '''
.card {
font-family: "Segoe UI";
display: flex;
align-items: center;
gap: 16px;
padding: 20px;


/r/Python
https://redd.it/1neuyit

D Math foundations to understand Convergence proofs?

Good day everyone, recently I've become interested in proofs of convergence for federated (and non-federated) algorithms, something like what's seen in appendix A of the FedProx paper (one page of it attached below)

I managed to go through the proof once and learn things like first order convexity condition from random blogs, but I don't think I will be able to do serious math with hackjobs like that. I need to get my math foundations up to a level where I can write one such proof intuitively.

So my question is: What resources must I study to get my math foundations up to par? Convex optimization by Boyd doesn't go through convergence analysis at all and even the convex optimization books that do, none of them use expectations over the iteration to proof convergence. Thanks for your time

https://preview.redd.it/481lxdf47lof1.png?width=793&format=png&auto=webp&s=6771d3ffe8a533155aa145b2ec691181a30968b9



/r/MachineLearning
https://redd.it/1nehy84

16 reproducible bugs every Django learner hits (and how to fix them before they grow)

when i was learning Django and tried to connect it with modern AI workflows (RAG, embeddings, async tasks), i kept hitting weird bugs. each time i patched one, another came back in a different form.

so i built a Problem Map: a catalog of 16 reproducible failure modes. it’s written as a learning tool — you can open any item, see the minimal diagnosis, and apply a fix without needing extra SDKs or infra.

### why it matters for Django learners

* early projects often fail silently: OCR splits headers wrong, pgvector returns “nearest” but semantically wrong, or Celery starts before your index is ready.
* with this map, you can see the bug class before it happens. the fix is small but structural, and once applied, the same bug never reappears.
* it’s not a black box — each page is a step-by-step explainer, so you understand *why* the fix works.

### before vs after

* before: patch after output, firefight each bug, add regex, rerankers, tool hacks. ceiling \~70–80% stability.
* after: run acceptance checks before output (ΔS, λ, coverage). only stable states generate. ceiling moves to 90–95%+, and fixes stay permanent.

### quick use

you don’t need to read everything at once. just keep the map bookmarked.

/r/djangolearning
https://redd.it/1nd8xr5

D Larry Ellison: “Inference is where the money is going to be made.”

In Oracle’s recent call, Larry Ellison said something that caught my attention:

“All this money we’re spending on training is going to be translated into products that are sold — which is all inferencing. There’s a huge amount of demand for inferencing… We think we’re better positioned than anybody to take advantage of it.”

It’s striking to see a major industry figure frame inference as the real revenue driver, not training. Feels like a shift in narrative: less about who can train the biggest model, and more about who can serve it efficiently, reliably, and at scale.

Not sure if the industry is really moving in this direction? Or will training still dominate the economics for years to come?

/r/MachineLearning
https://redd.it/1nfav96

Update: Should I give away my app to my employer for free?

Link to original post - https://www.reddit.com/r/Python/s/UMQsQi8lAX

Hi, since my post gained a lot of attention the other day and I had a lot of messages, questions on the thread etc. I thought I would give an update.

I didn’t make it clear in my previous post but I developed this app in my own time, but using company resources.

I spoke to a friend in the HR team and he explained a similar scenario happened a few years ago, someone built an automation tool for outlook, which managed a mailbox receiving 500+ emails a day (dealing/contract notes) and he simply worked on a fund pricing team and only needed to view a few of those emails a day but realised the mailbox was a mess. He took the idea to senior management and presented the cost saving and benefits. Once it was deployed he was offered shares in the company and then a cash bonus once a year of realised savings was achieved.

I’ve been advised by my HR friend to approach senior management with my proposal, explain that I’ve already spoken to my manager and detail the cost savings I can make, ask for a salary increase to provide ongoing

/r/Python
https://redd.it/1nf57hb

Saturday Daily Thread: Resource Request and Sharing! Daily Thread

# Weekly Thread: Resource Request and Sharing 📚

Stumbled upon a useful Python resource? Or are you looking for a guide on a specific topic? Welcome to the Resource Request and Sharing thread!

## How it Works:

1. Request: Can't find a resource on a particular topic? Ask here!
2. Share: Found something useful? Share it with the community.
3. Review: Give or get opinions on Python resources you've used.

## Guidelines:

Please include the type of resource (e.g., book, video, article) and the topic.
Always be respectful when reviewing someone else's shared resource.

## Example Shares:

1. Book: "Fluent Python" \- Great for understanding Pythonic idioms.
2. Video: Python Data Structures \- Excellent overview of Python's built-in data structures.
3. Article: Understanding Python Decorators \- A deep dive into decorators.

## Example Requests:

1. Looking for: Video tutorials on web scraping with Python.
2. Need: Book recommendations for Python machine learning.

Share the knowledge, enrich the community. Happy learning! 🌟

/r/Python
https://redd.it/1nfiys8

Flowfile - An open-source visual ETL tool, now with a Pydantic-based node designer.

Hey r/Python,

I built Flowfile, an open-source tool for creating data pipelines both visually and in code. Here's the latest feature: Custom Node Designer.

# What My Project Does

Flowfile creates bidirectional conversion between visual ETL workflows and Python code. You can build pipelines visually and export to Python, or write Python and visualize it. The Custom Node Designer lets you define new visual nodes using Python classes with Pydantic for settings and Polars for data processing.

# Target Audience

Production-ready tool for data engineers who work with ETL pipelines. Also useful for prototyping and teams that need both visual and code representations of their workflows.

# Comparison

* **Alteryx**: Proprietary, expensive. Flowfile is open-source.
* **Apache NiFi**: Java-based, requires infrastructure. Flowfile is pip-installable Python.
* **Prefect/Dagster**: Orchestration-focused. Flowfile focuses on visual pipeline building.

# Custom Node Example

import polars as pl
from flowfile_core.flowfile.node_designer import (
CustomNodeBase, NodeSettings, Section,
ColumnSelector, MultiSelect, Types
)

class TextCleanerSettings(NodeSettings):
cleaning_options: Section = Section(
title="Cleaning Options",


/r/Python
https://redd.it/1nff4dw