Rebuilt my Bible search tool with Django + Tailwind: multi-version, case toggle, logical operations
https://aaronjs.pythonanywhere.com/

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

Tuples vs Dataclass (and friends) comparison operator, tuples 3x faster

I was heapifying some data and noticed switching dataclasses to raw tuples reduced runtimes by \~3x.

I got in the habit of using dataclasses to give named fields to tuple-like data, but I realized the dataclass wrapper adds considerable overhead vs a built-in tuple for comparison operations. I imagine the cause is tuples are a built in CPython type while dataclasses require more indirection for comparison operators and attribute access via __dict__?

In addition to dataclass , there's namedtuple, typing.NamedTuple, and dataclass(slots=True) for creating types with named fields . I created a microbenchmark of these types with heapq, sharing in case it's interesting: https://www.programiz.com/online-compiler/1FWqV5DyO9W82

Output of a random run:

tuple : 0.3614 seconds
namedtuple : 0.4568 seconds
typing.NamedTuple : 0.5270 seconds
dataclass : 0.9649 seconds
dataclass(slots) : 0.7756 seconds

/r/Python
https://redd.it/1kggyg0

Flask is driving me crazy

ok so i started learning flask as part of a course im in. At first, it felt like it was easy with some all-in-one code ive made. Like managing the routes, using url_for, creating the connection with the database. Then i tried to make the flask tutorial from their website, now i feel the more dumb than i used to, lol. i think they just throw code on the screen and you gotta copy, i mean, i can totally understand what the code does by reading it, but i cant imagine me learning anything from it. I dont know if i am going to be able to get all of this stuff in my head.


Is there any other place i can learn flask or Python webdev thats does it slowly and/or in a better way?

/r/flask
https://redd.it/1kgq62e

How Big Softwares are planned and executed.

Hi,

This is a long post. Thanks for Reading.

Honestly, I need some senior with whom I can talk.


Backend: Django , Frontend: React + Typescript , Database: postgres , Cloud: AWS


So, basically I work in a company which has been in business for more then 20 years, It's a medium sized organization. But they never integrated tech into their system. They are not going to sell any software, they just want everything for themselves.


I have been hired as a Team lead here, I hired the others guys as well. So, right now we have core frontend and backend devs . We work very closely. They have hired us so that we can automate their internal processes.


None of us is much experienced, Actually honestly I am just a fresher. And others here are just 1yr-2yr experienced.


Others just code, they aren't really that interested into designing and planning.


Now, I am facing a lot of issues, I am desperate to know how these things are handled in Big Enterprises , Large tech companies. None of our project is small, All of the projects are quite complex

/r/djangolearning
https://redd.it/1kf9ccd

Django security releases issued: 5.2.1, 5.1.9 and 4.2.21
https://www.djangoproject.com/weblog/2025/may/07/security-releases/

/r/django
https://redd.it/1kgz64x

GitHub - mithunchak/Train-Booking-Microservice-System
https://github.com/mithunchak/Train-Booking-Microservice-System.git

/r/flask
https://redd.it/1kgt5uh

Am on the 3rd part of Django tutorial and got stuck.

How do I access this part : polls/templates/polls/detail.html ?

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

Django Guardian v3 released!

Here you go, djangonauts, it's what you've all been waiting for: A bang-up-to-date version of django-guardian. Compatible with the latest and greatest django/python versions, equipped with improved docs, static typing, an overhauled library framework and dev tools and a range of performance improvements.

All you need to do is use it! But please check the release notes first!

/r/django
https://redd.it/1kh77wl

Absolute Zero: Reinforced Self-play Reasoning with Zero Data [R]
https://www.arxiv.org/abs/2505.03335

/r/MachineLearning
https://redd.it/1kgylx3

Authentication Methods

I am getting into web dev and am confused on the different types of authentication methods and how they works and what their pros and cons are. Could anyone link to a resource where I could learn about these. so far, the two I know are using JWT and using cookies but am not too sure how they work so I don’t know which I should use. I am using DRF to make an API if that changes anything. Thank you!

/r/django
https://redd.it/1kh8nie

introduction of flasky ! Free Flask AI chatbot.

hi folks! Today I'm writing to you after a few weeks of development to introduce Flasky. Flasky is a modified version of qwen coder 2.5 that I trained on flask data, basically I took the basic model and provided it with a tone of flask related data.

It's not as powerful as claude 3.7 etc. but it gets the job done! I host it totally locally on 2 4060 loll.. i got them for dirt cheep so. Oh and you can access it to ask for help at any time on flask wiki it's 100% and NO i dont collect any data, it's litterally just going trought my Ollama API then trought my custom model. No data collection and will never have any.

https://flaskwiki.wiki/ai-assistant

Hope you enjoy hehe, don't hesitate to let me know of any problems or potential improvements. This is my first real experience with AI I've already fuck arround a bit with Ollama, lm studio in the past or copilot, but I never really got far.

But I think AI can honestly help so much in solving stupid little problems that we get stuck on sometimes... Anyway! hope it can help you :)!

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

R Cracking 40% on SWE-bench with open weights (!): Open-source synth data & model & agent

We all know that RL & FTing works great to get good agent models. But creating swe-bench style training data for software engineering agents is difficult! Until now.

Introducing SWE-smith: Generate 100s to 1000s of task instances for any GitHub repository.

Using this, we've generated 50k+ task instances for 128 popular GitHub repositories, then trained our own LM for SWE-agent.

The result? SWE-agent-LM-32B achieve 40% pass@1 on SWE-bench Verified.

Now, we've open-sourced everything, and we're excited to see what you build with it!

That means you get an open source LM, a big finetuning dataset, the framework that was used to create it, and our agent has been open source for a long time!

In addition, we share lots of insides about synthetic data, finetuning, and agent behavior in our paper.

/r/MachineLearning
https://redd.it/1kh18td

R Process Reward Models That Think

TLDR: Tackles the challenge of expensive step-level supervision required for training PRMs via ThinkPRM, a generative PRM fine-tuned with only 8K process labels, enabling it to verify reasoning using long chains-of-thought.


🔗 Paper : https://arxiv.org/abs/2504.16828

Github: https://github.com/mukhal/thinkprm
Verifiers: ThinkPRM-14B, ThinkPRM-1.5B
Data: https://huggingface.co/datasets/launch/thinkprm-1K-verification-cots



/r/MachineLearning
https://redd.it/1kgya52

Thursday Daily Thread: Python Careers, Courses, and Furthering Education!

# Weekly Thread: Professional Use, Jobs, and Education 🏢

Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.

---

## How it Works:

1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.

---

## Guidelines:

- This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
- Keep discussions relevant to Python in the professional and educational context.

---

## Example Topics:

1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?

---

Let's help each other grow in our careers and education. Happy discussing! 🌟

/r/Python
https://redd.it/1khchg7

Why wagtail over plain django?

Isn't embracing and extending in this way exactly the worst possible thing. Why not make it a library that you can add to a django project instead? They have zero information in their FAQ about maintenance - which is exactly my main concern.

/r/django
https://redd.it/1khjx7h

Wagtail 7.0 released
https://docs.wagtail.org/en/latest/releases/7.0.html

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

Ty: An extremely fast Python type checker and language server, written in Rust.

Astral just released a stand alone repository of their new typer checker ty on their github: https://github.com/astral-sh/ty

/r/Python
https://redd.it/1kgzxs0

Help me with oauth

Anyone have implemented oauth sign in with google in flask, can you share the code with me for reference.

/r/flask
https://redd.it/1khh53h

P Introducing the Intelligent Document Processing (IDP) Leaderboard – A Unified Benchmark for OCR, KIE, VQA, Table Extraction, and More

The most comprehensive benchmark to date for evaluating document understanding capabilities of Vision-Language Models (VLMs).

What is it?
A unified evaluation suite covering 6 core IDP tasks across 16 datasets and 9,229 documents:

Key Information Extraction (KIE)
Visual Question Answering (VQA)
Optical Character Recognition (OCR)
Document Classification
Table Extraction
Long Document Processing (LongDocBench)
(Coming soon: Confidence Score Calibration)

Each task uses multiple datasets, including real-world, synthetic, and newly annotated ones.

Highlights from the Benchmark

Gemini 2.5 Flash leads overall, but surprisingly underperforms its predecessor on OCR and classification.
All models struggled with long document understanding – top score was just 69.08%.
Table extraction remains a bottleneck — especially for long, sparse, or unstructured tables.
Surprisingly, GPT-4o's performance decreased in the latest version (gpt-4o-2024-11-20) compared to its earlier release (gpt-4o-2024-08-06).
Token usage (and thus cost) varies dramatically across models — GPT-4o-mini was the most expensive per request due to high token usage.

Why does this matter?
There’s currently no unified benchmark that evaluates all IDP tasks together — most leaderboards (e.g., OpenVLM, Chatbot Arena) don’t deeply assess document understanding.

Document Variety
We evaluated models on a wide range of documents: Invoices, forms, receipts,

/r/MachineLearning
https://redd.it/1khpwl3

I actually used Python practically the first time today!

I had to copy and paste a long sentence that was in all caps into a google doc, but didn't feel manually retyping the whole thing to be lower case, so I just wrote:

sentence = "Blah blah blah"

print(sentence.lower())

and voila, I have the long ass sentence in full lower case. Just wanted to share my milestone with some fellow python enthusiasts.

/r/Python
https://redd.it/1kh3uz7

Just out of curiosity, has anyone here ever used flask as the backend to a mobile app?

Started learning flask and the ease of certain things such as getting a development server up and running has me hooked. I eventually will like to build a mobile app for the saas web application I will begin working on soon as I get more experience.

/r/flask
https://redd.it/1kf72vx