Why does my Flask /health endpoint show nothing at http://localhost:5000/health?

Hey folks, I’m working on a Flask backend and I’m running into a weird issue.

I’ve set up a simple /health endpoint to check if the server is up. Here’s the code I’m using:

@app.route('/health', methods=['GET'])
def health_check():
return 'OK', 200

The server runs without errors, and I can confirm that it’s listening on port 5000. But when I open http://localhost:5000/health in the browser, I get a blank page or sometimes nothing at all — no “OK” message shows up on Safari while Chrome says “access to localhost was denied”.

What I expected:
A plain "OK" message in the browser or in the response body.

What I get:
Blank screen/access to localhost was denied (but status code is still 200).

Has anyone seen this before? Could it be something to do with the way Flask handles plain text responses in browsers? Or is there something else I’m missing?

Thanks in advance for any help!


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

Should I learn FastAPI? Why? Doesn’t Django or Flask do the trick?

I’ve been building Python web apps and always used Django or Flask because they felt reliable and well-established. Recently, I stumbled on davia ai — a tool built on FastAPI that I really wanted to try. But to get the most out of it, I realized I needed to learn FastAPI first. Now I’m wondering if it’s worth the switch. If so, what teaching materials do you recommend?

/r/Python
https://redd.it/1kou6lc

Is there a module that can dynamically can change all div ids and css ids on each request?

as the title says.

I need that without change all other functions in my flask application.

if it doesn't exist and you just wanna talk bullshit then just don't reply

/r/flask
https://redd.it/1kou68z

Senior Django Developers: Do You Stick with Django for High-Concurrency Async Applications or Transition to Other Frameworks?

Hi everyone, I hope you're all doing well!

I'm exploring the feasibility of using Django for applications that need to handle a massive number of asynchronous operations—things like real-time chat systems, live dashboards, or streaming services. With Django's support for ASGI and asynchronous views, it's now possible to implement async features, but I'm wondering how well it holds up in real-world, high-concurrency environments compared to frameworks that are natively asynchronous.

Given that, I'm curious:

1️⃣ Have you successfully deployed Django in high-concurrency, async-heavy environments?

2️⃣ Did you encounter limitations that led you to consider or switch to frameworks like Node.js, ASP.NET Core, or others?

3️⃣ What strategies or tools did you use to scale Django in such scenarios?

I’m especially interested in hearing about real-world experiences, the challenges you faced, and how you decided on the best framework for your needs.

Thanks in advance for sharing your insights—looking forward to learning from you all!

Warm regards!

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

Should I take a government Data Science job that only uses SAS?

Hey all,
I’ve just been offered a Data Science position at a national finance ministry (public sector). The role sounds meaningful, and I’ve already verbally accepted, but haven’t signed the contract yet.

Here’s the thing:
I currently work in a tech-oriented role where I get to experiment with modern ML/AI tools — Python, transformers, SHAP, even LLM prototyping. In contrast, the ministry role would rely almost entirely on SAS. Python might be introduced at some point, but currently isn’t part of the tech stack.

I’m 35 now, and if I stay for 5 years, I’m worried I’ll lose touch with modern tools and limit my career flexibility. The role would be focused on structured data, traditional scoring models, and heavy audit/governance use cases.

Pros:
• Societal impact
• Work-life balance + flexibility for parental leave
• Stable government job with long-term security
• Exposure to public policy and regulated environments

Cons:
• No Python or open-source stack
• No access to cutting-edge AI tools or innovation
• Potential tech stagnation if I stay long
• May hurt my profile if I return to the private sector at 40

I’m torn between meaning and innovation.

Would love to hear from anyone who’s made a similar move or faced this kind of tradeoff.
Would you take the role and just “keep Python alive” on the side?

/r/Python
https://redd.it/1koy4vw

[P] cachelm – Semantic Caching for LLMs (Cut Costs, Boost Speed)

https://redd.it/1koxlpl
@pythondaily

FRONTEND FRAMEWORK WITH DRF

Hello, writing a drf project and I haven't decided what frontend to use, I've previously written a traditional MVT but first time implementing a frontend with my drf, thinking of using react, but I feel it is kind of stress learning the framework maybe it'll take me a lot of time to get it and since I'm good with django-html and css I feel it's a waste of time or does it worth it?

/r/django
https://redd.it/1kp7yto

Hiding API key

Hi there, I am currently Doing a python application where one of the html pages is a html,css javascript chatbot.


This chatbot relies on an open AI api key. I want to hide this key as an environment variable so I can use it in Javascript and add it as a config var in Heroku. Is it possible to do this.


Thank you.

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

P I built a transformer that skips layers per token based on semantic importance

I’m a high school student who’s been exploring how to make transformers/ai models more efficient, and I recently built something I’m really excited about: a transformer that routes each token through a different number of layers depending on how "important" it is.

The idea came from noticing how every token, even simple ones like “the” or “of”, gets pushed through every layer in standard transformers. But not every token needs the same amount of reasoning. So I created a lightweight scoring mechanism that estimates how semantically dense a token is, and based on that, decides how many layers it should go through.

It’s called SparseDepthTransformer, and here’s what it does:

Scores each token for semantic importance
Skips deeper layers for less important tokens using hard gating
Tracks how many layers each token actually uses
Benchmarks against a baseline transformer

In my tests, this reduced memory usage by about 15% and cut the average number of layers per token by \~40%, while keeping output quality the same. Right now it runs a bit slower because the skipping is done token-by-token, but batching optimization is next on my list.

Here’s the GitHub repo if you’re curious or want to give feedback:
https://github.com/Quinnybob/sparse-depth-transformer

Would love if you

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

Sunday Daily Thread: What's everyone working on this week?

# Weekly Thread: What's Everyone Working On This Week? 🛠️

Hello /r/Python! It's time to share what you've been working on! Whether it's a work-in-progress, a completed masterpiece, or just a rough idea, let us know what you're up to!

## How it Works:

1. Show & Tell: Share your current projects, completed works, or future ideas.
2. Discuss: Get feedback, find collaborators, or just chat about your project.
3. Inspire: Your project might inspire someone else, just as you might get inspired here.

## Guidelines:

Feel free to include as many details as you'd like. Code snippets, screenshots, and links are all welcome.
Whether it's your job, your hobby, or your passion project, all Python-related work is welcome here.

## Example Shares:

1. Machine Learning Model: Working on a ML model to predict stock prices. Just cracked a 90% accuracy rate!
2. Web Scraping: Built a script to scrape and analyze news articles. It's helped me understand media bias better.
3. Automation: Automated my home lighting with Python and Raspberry Pi. My life has never been easier!

Let's build and grow together! Share your journey and learn from others. Happy coding! 🌟

/r/Python
https://redd.it/1kp6wqf

FastAPI + React Front - Auth0, build from scratch?

I have a fastapi backend with a react front end. I’m trying to figure out the best way to manage my users login, credentials, permissions, etc. I keep finding myself just defaulting to building it all myself. Am I missing a different option? What are most people using?

/r/Python
https://redd.it/1kpby44

D Can we possibly construct an AlphaEvolve@HOME?

Today, consumer grade graphics cards are getting to nearly 50 TeraFLOPS in performance. If a PC owner is browsing reddit, or their computer is turned off all night, the presence of an RTX 50XX idling away is wasted computing potential.

When millions of people own a graphics card, the amount of computing potential is quite vast. Under ideal conditions, that vast ocean of computing potential could be utilized for something else.

> AlphaEvolve is a coding agent that orchestrates an autonomous pipeline of computations including queries to LLMs, and produces algorithms that address a userspecified task. At a high level, the orchestrating procedure is an evolutionary algorithm that gradually develops programs that improve the score on the automated evaluation metrics associated with the task.


Deepmind's recent AlphaEvolve agent is performing well on the discovery -- or "invention" -- of new methods. As Deepmind describes above, AlphaEvolve is using an evolutionary algorithm in its workflow pipeline. Evolutionary algorithms are known to benefit from large-scale parallelism. This means it may be possible to run AlphaEvolve on the many rack servers to exploit the parallelism provided by a data center.

Or

/r/MachineLearning
https://redd.it/1kp4nxq

Lets make visualizations of 3D images in Notebooks just as simple as for 2D images

# Target Audience

Many of us who deal with image data in their everyday life and use Python to perform some kind of analysis, are used to employ Jupyter Notebooks. Notebooks are great, because they permit to write a story of the analysis that we perform: We sketch the motivation of our investigation, we write the code to load the data, we explore the data directly inside the Notebooks by embedding images, we write the code for the analysis, we inspect the results (more images!), make observations and we draw conclusions.

Thanks to matplotlib, visualization of 2D images inside Notebooks—be it for exploration or for inspection—is absolutely trivial. Notebooks are a paradise of an ecosystem, for 2D image data. However, things get more complicated when you move to 3D.

>LibCarna is an attempt to make the visualization of 3D image data in Jupyter Notebooks just as simple as it is for 2D images.

In a nutshell: If you ever wanted to visualize 3D images in Notebooks, then LibCarna might be for you.

# What My Project Does

LibCarna started off more than a decade ago (see "Scope of the Project" section below, if you're interested) and was developed with an emphasis on simplicity and flexibility. Under

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

Dashboard Panel for Django

I am looking into creating a dashboard like SaaS project. Instead of creating everything from the beginning and I looking into using premade components and UI for the MVP. My platform is not too complex at the moment.

What are good options? I have found AdminLTE or Jazzmin. What else would you recommend?

/r/django
https://redd.it/1kpga8h

Best GUI library with fast rendering times for data visualization

Hey everyone! I'm looking for a lightweight Python library to develop a graphical user interface (GUI) for a data science project. This GUI application involves rendering a lot of points at once — on average, more than a 100,000. One of the core features of the application is switching between batches of those 100,000 data points by clicking buttons. This needs to be fast — when I switch to another batch of a 100,000 data points, due to the nature of the application, I require that it doesn't take too long to completely render — an ideal rendering time would be less than a second. Now, I don't really have to render all of those points on a single window at once — typically, only \~1000 points will be shown on the window at once. If loading and rendering all points at once does not take too long (should happen in less than a second), I would just have all the points rendered at once; if rendering all the points at once causes performance issues, I would only load the ones that will be seen on the screen and load more as the window is navigated forward. What is the

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

Hiring 6 REMOTE Full Stack Devs who has the following experience ($75 AUD / hr)

We recently got funding to develop a music sharing platform similar to Soundcloud. If you have experience building something like this, YOU'RE A PERFECT FIT!

Skills you should be familiar with (As long as you have most of these, you should be fine):

\- REACT JS for the frontend

\- Preferably NodeJS experience or any other backend framework experience.

\- Tailwind CSS + any component library that you have experience using

\- State Management

\- Any DB. SQL is fine.

\- Python and also Typescript

\- AWS, Docker and Vercel (or similar alternatives)

\- Metadata Processing

\- User authenticaion (login, signup etc...)

Pay and hours

$48 / hr USD REMOTE full stack dev role. Must be available ASAP and should be able to work at least 5 - 6 hours per day.

We need 4 - 6 devs at the moment. Must have whatsapp as that's what we use to communicate.

If you are in AUS, we pay via payroll direct to bank. If elsewhere, then paypal and Remitly are 2 other options.

Email me - admin@outreachaddict.com if interested. You MUST include why you think you will be a good fit. Show me some of your past side projects etc....

Thanks



/r/django
https://redd.it/1kpmp15

Automated Python CLI Tool for Converting PDFs to Kindle-Compatible eBooks and Sending via USB/Email

**What My Project Does**

This is a Python CLI tool that converts PDF files into Kindle-compatible eBook formats—AZW3 for USB transfers and EPUB for email delivery. It adds metadata like title, author, and cover images, automates USB Kindle detection on Windows, and sends EPUB files to your Kindle via email using SMTP with Gmail app passwords. The tool manages file compatibility and automates the entire workflow from conversion to delivery.

**Target Audience**

This project is intended for intermediate to advanced Python users who want to automate their eBook workflow for Kindle devices. It's practical for frequent readers who want their documents properly formatted and organized, and for developers interested in building CLI automation around eBook management. The tool is designed for everyday use, not just as a hobby or experiment.

**Comparison**

While Calibre offers GUI tools for ebook conversion and management, this script provides a streamlined command-line interface for batch processing, automation, and remote usage. Unlike generic PDF converters, it enforces Kindle-specific format rules, detects connected Kindle devices for direct USB transfers, and supports sending files via email with secure authentication. This fills a gap for users who want to script and automate their ebook handling beyond what GUI tools allow.

**Additional Details**

* Built with Python

/r/Python
https://redd.it/1kpn02i

audiobackend - Python library for advanced audio playback with custom buffering and resampling

Hey r/Python!

I'm excited to share my first "serious" Python library, audiobackend, which I've been working on to get more control over audio playback than what's typically offered by simpler libraries. I'd love to get your feedback!

GitHub: https://github.com/Niamorro/audiobackend

---

### What My Project Does

audiobackend is a Python library designed to provide a flexible backend for playing audio files. It handles the complexities of decoding, resampling, buffering, and outputting audio, allowing developers to focus on their application logic.

Key Features:

File Loading & Decoding: Uses PyAV (FFmpeg bindings) to load and decode a wide variety of audio formats.
Playback Control: Standard play, pause, stop, and volume control.
Seeking: Allows seeking to specific positions within the audio track.
Advanced Threaded Buffering: Implements a multi-threaded buffering system to ensure smooth playback. It dynamically fills a buffer in a separate thread, with configurable thresholds and sizes to manage latency and prevent underflows.
Audio Resampling: Can resample audio on-the-fly to a preferred sample rate or adapt to the original file's rate using PyAV's `AudioResampler`. It also handles very high sample rates by downsampling to a supported maximum if necessary.
Callbacks: Provides callbacks for position updates, playback state

/r/Python
https://redd.it/1kpprn7