Tailwind v4 problems with Flask

Hey guys I installed Tailwind v4 with CLI to work with Flask but I am having problems in that the UI does not show everything it must show (for example, colors). Anyone with the same issue? By the way v3 works fine!

/r/flask
https://redd.it/1il8x4i

XSS in django-impersonate 1.9.3 and django-gravatar2 1.4.4
https://stsewd.dev/posts/xss-in-djang-impersonate-and-django-gravatar2/

/r/django
https://redd.it/1il713q

IntentGuard - verify code properties using natural language assertions

I'm sharing IntentGuard, a testing tool that lets you verify code properties using natural language assertions. It's designed for scenarios where traditional test code becomes unwieldy, but comes with important caveats.

What My Project Does:

Lets you write test assertions like "All database queries should be parameterized" or "Public methods must have complete docstrings"
Integrates with pytest/unittest
Uses a local AI model (1B parameter fine-tuned Llama 3.2) via llamafile
Provides detailed failure explanations
MIT licensed

✅ Working Today:

Basic natural language assertions for Python code
pytest/unittest integration
Local model execution (no API calls)
Result caching for unchanged code/assertions
Self-testing capability (entire test suite uses IntentGuard itself)

⚠️ Known Limitations:

Even with consensus voting, misjudgments can happen due to the weakness of the model
Performance and reliability benchmarks are unfortunately not yet available

Why This Might Be Interesting:

Could help catch architectural drift in large codebases
Useful for enforcing team coding standards
Potential for documentation/compliance checks
Complements traditional testing rather than replacing it

Next Steps:

1. Measure the performance and reliability across a set of diverse problems
2. Improve model precision by expanding the training data and using a stronger base model

Installation & Docs:

pip install intentguard

GitHub Repository

Comparison: I'm not aware of any direct alternatives.

Target Audience: The tool works but needs rigorous evaluation -

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

Need advice with search functionality design

Hi, I've been developing my first project in Django and one of its features is that users can search for movies/series by title (shouldn't match the exact name) and add them to their watchlist. The problem I ran into is that I'm not sure of how to provide the search results.
The first thing that came to my mind was to use API that I'd found on rapidapi, but the free plan offers only 500 requests per month which might get problematic when the app is used by multiple users. Then I thought I would query a database first and if there are no matches, I'd make an API call and store it into the database.
However, now I can't know for sure if the search query contains any possible match. For example, it can be some nonsense, which won't retrieve any data from the db and I would need to make API request to find out that there are no such movies. Or I can't be certain that the query will get enough data from the db. Like, if the first 3 Jurassic Park movies are in the db and a user searches for 'jurassic', they

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

D Simple Questions Thread

Please post your questions here instead of creating a new thread. Encourage others who create new posts for questions to post here instead!

Thread will stay alive until next one so keep posting after the date in the title.

Thanks to everyone for answering questions in the previous thread!

/r/MachineLearning
https://redd.it/1ilhw29

R LIMO: Less is More for Reasoning

>We present a fundamental discovery that challenges our understanding of how complex reasoning emerges in large language models. While conventional wisdom suggests that sophisticated reasoning tasks demand extensive training data (often >100,000 examples), we demonstrate a striking phenomenon: complex mathematical reasoning abilities can be effectively elicited with surprisingly few examples. This finding challenges not only the assumption of massive data requirements but also the common belief that supervised fine-tuning primarily leads to memorization rather than generalization. Through comprehensive experiments, our proposed model LIMO demonstrates unprecedented performance and efficiency in mathematical reasoning. With merely 817 curated training samples, LIMO achieves 57.1% accuracy on the highly challenging AIME benchmark and 94.8% on MATH, improving the performance of previous strong SFT-based models from 6.5% to 57.1% on AIME and from 59.2% to 94.8% on MATH, while only using 1% of the training data required by previous approaches. Most remarkably, LIMO demonstrates exceptional out-of-distribution generalization, achieving 40.5% absolute improvement across 10 diverse benchmarks, outperforming models trained on 100x more data, directly challenging the prevailing notion that SFT inherently leads to memorization rather than generalization. Synthesizing these pioneering results, we propose the Less-Is-More Reasoning Hypothesis (LIMO Hypothesis): In foundation models where domain knowledge has been comprehensively encoded during pre-training, sophisticated reasoning capabilities can emerge through minimal but precisely orchestrated demonstrations of cognitive processes.

/r/MachineLearning
https://redd.it/1ile9nu

FastAPI Guard - A FastAPI extension to secure your APIs

Hi everyone,

I've published FastAPI Guard some time ago:

Documentation: rennf93.github.io/fastapi-guard/

GitHub repo: github.com/rennf93/fastapi-guard

What is it?
FastAPI Guard is a security middleware for FastAPI that provides:
- IP whitelisting/blacklisting
- Rate limiting & automatic IP banning
- Penetration attempt detection
- Cloud provider IP blocking
- IP geolocation via IPInfo.io
- Custom security logging
- CORS configuration helpers

It's licensed under MIT and integrates seamlessly with FastAPI applications.

Comparison to alternatives:
- fastapi-security: Focuses more on authentication, while FastAPI Guard provides broader network-layer protection
- slowapi: Handles rate limiting but lacks IP analysis/geolocation features
- fastapi-limiter: Pure rate limiting without security features
- fastapi-auth: Authentication-focused without IP management

Key differentiators:
- Combines multiple security layers in single middleware
- Automatic IP banning based on suspicious activity
- Built-in cloud provider detection
- Daily-updated IP geolocation database
- Production-ready configuration defaults

Target Audience:
FastAPI developers needing:
- Defense-in-depth security strategy
- IP-based access control
- Automated threat mitigation
- Compliance with geo-restriction requirements
- Penetration attempt monitoring

Feedback wanted

Thanks!

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

Django REST framework, Django Ninja, FastAPI with Pydantic, and Golang API serialization performance.

A few months ago I wrote a post about comparing the API serialization performance retrieve large amount of records in Django REST Framework, Django Ninja, and Golang. I provided a step-by-step guide in optimization for Django as well as dockerized example for each framework tested. A lot of you liked it, and one common ask was, how does FastAPI compared.

It's taken me a while to sit down and work on this again, but I have now included a dockerized example of FastAPI with SQLAlchemy and Pydantic on the same set of data models with exact same API for comparison. I also added a dockerized example of Locust to do testing now. You can check it out and test it for yourself: https://github.com/oscarychen/building-efficient-api

I gotta say I was expecting FastAPI with Pydantic to perform not far behind Django Ninja, because the serialization of response data mechanism was expected to be similar. I am actually surprised FastAPI is quite a bit faster. Obviously, if we strip parsing response payload through the schema/serializer, Django REST Framework and Django Ninja are a lot faster, but typically on most APIs we would have those mechanism as part of response data parsing, and FastAPI does it significantly

/r/django
https://redd.it/1ilp876

Two Fast Auth - A FastAPI extension to implement 2FA

Hi everyone,

I've published Two Fast Auth:

Documentation: rennf93.github.io/two-fast-auth/

GitHub repo: github.com/rennf93/two-fast-auth

What is it?

Two Fast Auth is a FastAPI middleware that provides seamless two-factor authentication implementation with:

- QR code generation for authenticator apps
- Time-based one-time password (TOTP) verification
- Secure recovery code management
- Optional secret encryption
- Middleware integration for route protection
- Production-ready configuration defaults

MIT licensed and designed specifically for FastAPI applications.

Comparison to alternatives:
- fastapi-jwt-auth: Focuses on JWT authentication without native 2FA
- python-otp: Provides OTP generation but no framework integration
- authlib: General-purpose auth library without FastAPI-specific middleware

Key differentiators:
- Native FastAPI middleware implementation
- Built-in QR code generation endpoint
- Recovery code lifecycle management
- Fernet encryption for secret storage
- Zero-configuration defaults for quick setup
- Active maintenance with production use cases

Target Audience:
FastAPI developers needing:
- Quick 2FA implementation without vendor lock-in
- Compliance with security standards requiring MFA
- Recovery code workflows for end-users
- Encrypted secret storage capabilities
- QR code-based authenticator app setup

Feedback wanted :)

Thanks!

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

Unknown field(s) (usablepassword) specified for CustomUser. Check fields/fieldsets/exclude attributes of class CustomUserAdmin.

I inherited a CustomUser class from AbstractUser like this:

class CustomUser(AbstractUser):
passclass CustomUser(AbstractUser):
pass

Here is the admin for this class:

from django.contrib import admin
from django.contrib.auth import getusermodel
from django.contrib.auth.admin import UserAdmin

from .forms import CustomUserChangeForm, CustomUserCreationForm

CustomUser = getusermodel()


class CustomUserAdmin(UserAdmin):
addform = CustomUserCreationForm
form = CustomUserChangeForm
model = CustomUser
listdisplay = [
"email",
"username",
"issuperuser",
]


admin.site.register(CustomUser, CustomUserAdmin)

The forms only define email and username:

class

/r/djangolearning
https://redd.it/1ile16j

[R] Your AI can’t see gorillas: A comparison of LLMs’ ability to perform exploratory data analysis
https://chiraaggohel.com/posts/llms-eda/

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

Critique this Django App
http://afteractions.com

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

Monday Daily Thread: Project ideas!

# Weekly Thread: Project Ideas 💡

Welcome to our weekly Project Ideas thread! Whether you're a newbie looking for a first project or an expert seeking a new challenge, this is the place for you.

## How it Works:

1. **Suggest a Project**: Comment your project idea—be it beginner-friendly or advanced.
2. **Build & Share**: If you complete a project, reply to the original comment, share your experience, and attach your source code.
3. **Explore**: Looking for ideas? Check out Al Sweigart's ["The Big Book of Small Python Projects"](https://www.amazon.com/Big-Book-Small-Python-Programming/dp/1718501242) for inspiration.

## Guidelines:

* Clearly state the difficulty level.
* Provide a brief description and, if possible, outline the tech stack.
* Feel free to link to tutorials or resources that might help.

# Example Submissions:

## Project Idea: Chatbot

**Difficulty**: Intermediate

**Tech Stack**: Python, NLP, Flask/FastAPI/Litestar

**Description**: Create a chatbot that can answer FAQs for a website.

**Resources**: [Building a Chatbot with Python](https://www.youtube.com/watch?v=a37BL0stIuM)

# Project Idea: Weather Dashboard

**Difficulty**: Beginner

**Tech Stack**: HTML, CSS, JavaScript, API

**Description**: Build a dashboard that displays real-time weather information using a weather API.

**Resources**: [Weather API Tutorial](https://www.youtube.com/watch?v=9P5MY_2i7K8)

## Project Idea: File Organizer

**Difficulty**: Beginner

**Tech Stack**: Python, File I/O

**Description**: Create a script that organizes files in a directory into sub-folders based on file type.

**Resources**: [Automate the Boring Stuff: Organizing Files](https://automatetheboringstuff.com/2e/chapter9/)

Let's help each other grow. Happy

/r/Python
https://redd.it/1ilt1is

Inviting Collaborators for a Differentiable Geometric Loss Function Library

Hello,
I am a grad student at Stanford, working on shape optimization for aircraft design.

I am looking for collaborators on a project for creating a differentiable geometric loss function library in pytorch.

I put a few initial commits on a repository here to give an idea of what things might look like:
Github repo

Inviting collaborators on twitter

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

Question about store environment variables

I am trying to store secret environment variables. All the tutorials I have checked tell me to download python-datoenv and create a .env file. My file is called .flaskenv. Is that technically wrong? I followed Miguel's mega tutorial and he told me to call that file .flaskenv.

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

I made Versioneer work with Hatchling and pdm build backends

version-pioneer is a fork of Versioneer that supports Hatchling and pdm build backends.

The reason I hesitated for so long to switch from setuptools to hatchling etc. was Versioneer. I believe versioning system should be independent from the backend you use so you can easily migrate. Not only that you have to learn a new system, but also they don't work the same way. For example, I noticed other VCS versioning systems do not support dynamic version resolution in editable installs, which means while developing you will often get incorrect version.

### What My Project Does:

- Highly customisable: It's an easy-to-read script. Literally a simple Python script in which you can customise the version format or anything you need.
- 🐍 Runs with Python 3.8+
- ❌📦 No dependencies like package, config file etc. It runs with one Python file.
- ⭕ Works with any build backend with hooks. (Supports setuptools, hatchling, pdm)
- 🦀 Works with any language, not just Python.
- Version format "digits" generates digits-only version string which is useful for multi-language projects, Chrome Extension, etc. because their versioning standard is different.
- CLI makes it easy to compute the version without vendoring anything in the

/r/Python
https://redd.it/1im12r8

P Inviting Collaborators for a Differentiable Geometric Loss Function Library

Hello,
I am a grad student at Stanford, working on shape optimization for aircraft design.

I am looking for collaborators on a project for creating a differentiable geometric loss function library in pytorch.

I put a few initial commits on a repository here to give an idea of what things might look like:
Github repo

Inviting collaborators on twitter

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

HTTP queries parameters to MongoDB Query Language converter

I did develop a Python module for my company based on Regex to convert HTTP queries parameters sent from frontend app (React & Angular mainly) to our backend (FastAPI) in MongoDB Query Language (MQL). This way, frontend devs can easilly make specific queries without asking the backend devs.

It is working pretty well for a couple of years but it became pretty hard to maintain and update. I'm also asking myself, can I improve it ? Here is a couple of exemple that I've build over the years:

http://localhost:8000/api/v1/company?filter=category==507f1f77bcf86cd799439011^createdat=BETWEEN(2024-01-01,2025-06-30)^nbemployee>10

# Output in Python
from query import MongoQueryManager as mqm

query = mqm(filter="category==507f1f77bcf86cd799439011^createdat=BETWEEN(2024-01-01,2025-06-30)^nbemployee>10", page=0, limit=100, orderdir="asd", orderby="createdat", excludedkeys=)
print(query.mongoargs)

{'filter': {'$and': [{'category': '507f1f77bcf86cd799439011'}, {'createdat': {'$gte': 1704063600.0, '$lte': 1751234400.0}}, {'nbemployee': {'$gt': 10}}]}, 'sort': [('createdat', -1)], 'skip': 0}

Note : 507f1f77bcf86cd799439011 is an ObjectId (specific to MongoDB).

There is some limitation, we can only put 3 logical operator if there is AND and OR at the same time. Example : arg1=1 AND arg2=2 AND arg3=3 OR arg4=4. I never find a way to code something stable

/r/Python
https://redd.it/1im5i4s

SQLalchemy is driving me nuts

I want to set all timestamps in DB with timezone utc, but my DB uses its own local time as timezone instead. Can anyone spot what I am doing wrong?

My sqlalchemy defs looks like this.

import sqlalchemy as sa
import sqlalchemy.orm as so
from datetime import datetime, timezone

timestamp: so.Mapped[datetime] = so.mapped_column(sa.DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))

When I pull the data from the DB I get something like this, where timezone seems to be the server timezone:

datetime.datetime(2025, 2, 9, 23, 33, 59, 666407, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600)))

While I would want something like this:

datetime.datetime(2025, 2, 10, 12, 31, 56, 422389, tzinfo=datetime.timezone.utc)


/r/flask
https://redd.it/1im57ij

A Modern Python Repository Template with UV and Just

Hey folks, I wanted to share a Python repository template I've been using recently. It's not trying to be the ultimate solution, but rather a setup that works well for my needs and might be useful for others.

What My Project Does

It's a repository template that combines several modern Python tools, with a focus on speed and developer experience:

\- UV for package management

\- Just as a command runner

\- Ruff for linting and formatting

\- Mypy for type checking

\- Docker support with a multi-stage build

\- GitHub Actions CI/CD setup

The main goal was to create a clean starting point that's both fast and maintainable.

Target Audience

This template is meant for developers who want a production-ready setup but don't need all the bells and whistles of larger templates.

Comparison

The main difference from other templates is the use of Just instead of Make as the command runner. While this means an extra installation step, Just offers several advantages, such as a cleaner syntax, better dependency handling and others.

I also chose UV over pip for package management, but at this point I don't consider this as something unusual in the Python ecosystem.

You can find the template here: https://github.com/GiovanniGiacometti/python-repo-template

Happy to hear your thoughts and suggestions for improvement!

/r/Python
https://redd.it/1ime8ja