Selling Social Networking App

Hey guys, so heres my story, around a year ago (September) I created a social networking app for my advanced software project class, and it turned out extremely well, and I have been maintaining the app and continuing to consistently update and fix the app as well. I feel confident in my app that people will use it and thoroughly enjoy it as well. I would like to sell the app or at least make some sort of income from it, as I put too much time and effort into making it. Please let me know any ideas or recommendations you might have. Thank you all!

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

Wednesday Daily Thread: Beginner questions

# Weekly Thread: Beginner Questions 🐍

Welcome to our Beginner Questions thread! Whether you're new to Python or just looking to clarify some basics, this is the thread for you.

## How it Works:

1. Ask Anything: Feel free to ask any Python-related question. There are no bad questions here!
2. Community Support: Get answers and advice from the community.
3. Resource Sharing: Discover tutorials, articles, and beginner-friendly resources.

## Guidelines:

This thread is specifically for beginner questions. For more advanced queries, check out our [Advanced Questions Thread](#advanced-questions-thread-link).

## Recommended Resources:

If you don't receive a response, consider exploring r/LearnPython or join the Python Discord Server for quicker assistance.

## Example Questions:

1. What is the difference between a list and a tuple?
2. How do I read a CSV file in Python?
3. What are Python decorators and how do I use them?
4. How do I install a Python package using pip?
5. What is a virtual environment and why should I use one?

Let's help each other learn Python! 🌟

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

I made a Traversible Tree in Python

Comparison
It is inspired from the existing tree command on linux and windows too So basically it is just like the tree command, it shows you a tree of the current directory structure.

What My Project Does
It basically gives you a birds eye view of your dir structure and quickly navigate to the folder you want to without having to know its path or doing cd ../../.. many times.

There are a bunch of command line args such as setting the paths, flags to show dot directories, set head height (no. of parent dirs shown) and tail height (depth).

You can traverse around the tree using various key presses (inspired from vim keybindings) and based on the given argument (-o, -c or --copy) you can output the value (the node to which you traversed), cd into it and have it copied into your clipboard.J

I had created this for my assignment and had a lot of fun with it. Tried to implement as much clean code and good design as I could but its still a mess and active work in progress tbh (added unit tests lol). And the rendering is still a little slow.

Do check it out: pranavpa8788/trav: A Traversible

/r/Python
[https://redd.it/1cxfaph

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/1cvq77y

Programmable Semantics (Eval, Semicolon, Assignment) for Python

I've seen programmable semantics (eval-hacking, macros) in LISPs and in Haskell-likes(Monads/Template Haskell), the overall techinque in OOP languages is called "Aspect Oriented Programming". Has this kind of thing been discussed before, and is it Pythonic it could allow a lot of Python code to be shorter. Python has sys.set_trace that sort of allows some form of programmable semantics but its mostly for debugging.

Programmable assignment(variables) are like setters/getters/properties, but instead of being run on o.x = 5, you could run them on "all local assignments" isnside a context manager or in a decorated function. On every assignment you could do stuff like log the values, update dependencies, notify objects, do a database transaction, do persistance, calculate other values, without having to explicitly do so for every assignment statement.

Programmable semicolons (such as Haskell Monads, or reprogramming Lisp do/progn/let) could allow you to have the same code run either synchronous, async, get undo/history support, break on error, rollback, logging in between lines, changing local/global variables in between each line, database access in between lines, checking values for errors, ignoring certain statements, etc... You can think of a semicolon like an "unrolled for loop"/iterator ran for each code line.

/r/Python
https://redd.it/1cxp7qe

Is there any reason not to use the default database?

Django uses SQLite by default. When would you want to upgrade to a full on SQL database like Postgres?

Is there any reason you would switch to a no-SQL database, like MongoDB? Is the pain this would cause even worth it? I feel like a huge part of the appeal of Django is that you don't have to write your DB queries yourself.

/r/django
https://redd.it/1cxlz6d

D How successful are ML projects?

Our team just deployed our first ML solution. We have several people with DS/ML certificates, and have done ML in side projects and hackathons, but no one has a degree in stats or math or DS and no one's ever done ML professionally. We regularly consulted multiple DS / ML experts, but never had a dedicated DS on our team. It cost us \~$400K to implement, is expected to save $50K a year, and have operational costs of $20K a year.

​

It seems like pursuing this wasn't worth it. Was this a miscalculation on our part? What's the success rate of the projects you work on? How much do you cost the company vs how much money do you generate (or save)?

​

/r/MachineLearning
https://redd.it/1cxtro6

P Fish Speech TTS: clone OpenAI TTS in 30 minutes

While we are still figuring out ways to improve the agent's emotional response to OpenAI GPT-4o, we have already made significant progress in aligning OpenAI's TTS performance. To begin this experiment, we collected 10 hours of OpenAI TTS data to perform supervised fine-tuning (SFT) on both the LLM (medium) and VITS models, which took approximately 30 minutes. After that, we used 15 seconds of audio as a prompt during inference.

Demos Available: here.

As you can see, the model's emotion, rhythm, accent, and timbre match the OpenAI speakers, though there is some degradation in audio quality, which we are working on. To avoid any legal issues, we are unable to release the fine-tuned model, but I believe everyone can tune fish-speech to this level within hours and for around $20.

Our experiment shows that with only 25 seconds of prompts (few-shot learning), without any fine-tuning, the model can mimic most behaviors except details like timbre and how it reads numbers. To the best of our knowledge, you can clone how someone speaks in English, Chinese, and Japanese with 30 minutes of data using this framework.


Repo: https://github.com/fishaudio/fish-speech

/r/MachineLearning
https://redd.it/1cxwqb7

django-import-export v4 released

You may be interested in looking at django-import-export v4.

It offers straightforward, reliable and comprehensive file import / export for your Django application.

django-import-export is an application and library which lets you manage import / export from / to a variety of sources (csv, xlsx, json etc).

It can be run programmatically, or with optional integration with the Django Admin site.

v4 includes lots of fixes and new features.

Please see the README for a full list of features and use-cases.

https://github.com/django-import-export/django-import-export

v4 has been completed by a small group of volunteers. We welcome any comments or feedback.


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

GeoEntropy: A Python Package for Computing Spatial/Geometric Entropy

I look forward to your critical thoughts and ideas about my project GeoEntropy! :-) Meaningful contributions are very welcome.



You can find the source code on Github and the package on PyPi.



Target Audience: Scientists



What My Project Does: GeoEntropy is a Python package designed to compute different entropy measures for spatial data represented in matrices (numpy arrays).



Comparison: GeoEntropy is inspired by the R package SpatEntropy by L. Altieri, D. Cocchi, and G. Roli and provides tools for analyzing the entropy of spatial data.

/r/Python
https://redd.it/1cxyvn2

[D] AI Agents: too early, too expensive, too unreliable

[**Reference: Full blog post**](https://www.kadoa.com/blog/ai-agents-hype-vs-reality)

There has been a lot of hype about the promise of autonomous agent-based LLM workflows. By now, all major LLMs are capable of interacting with external tools and functions, letting the LLM perform sequences of tasks automatically.

But reality is proving more challenging than anticipated.

The [WebArena leaderboard](https://docs.google.com/spreadsheets/d/1M801lEpBbKSNwP-vDBkC_pF7LdyGU1f_ufZb_NWNBZQ/edit#gid=0), which benchmarks LLMs agents against real-world tasks, shows that even the best-performing models have a success rate of only 35.8%.

# Challenges in Practice

After seeing many attempts to AI agents, I believe it's too early, too expensive, too slow, too unreliable.
It feels like many AI agent startups are waiting for a model breakthrough that will start the race to productize agents.

* Reliability: As we all know, LLMs are prone to hallucinations and inconsistencies. Chaining multiple AI steps compounds these issues, especially for tasks requiring exact outputs.
* Performance and costs: GPT-4o, Gemini-1.5, and Claude Opus are working quite well with tool usage/function calling, but they are still slow and expensive, particularly if you need to do loops and automatic retries.
* Legal concerns: Companies may be held liable for the mistakes of their agents. A [recent example](https://www.theguardian.com/world/2024/feb/16/air-canada-chatbot-lawsuit) is Air Canada being ordered to pay a customer who was misled by the airline's

/r/MachineLearning
https://redd.it/1cy1kn9

Django 5.1 alpha 1 released
https://www.djangoproject.com/weblog/2024/may/22/django-51-alpha-1-released/

/r/django
https://redd.it/1cy52tv

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/1cyf892

Flask Stripe Tutorial
https://testdriven.io/blog/flask-stripe-tutorial/

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

Take your Django Serializer game to the next level
https://differ.blog/p/take-your-django-serializer-game-to-the-next-level-b4659a

/r/django
https://redd.it/1cyg4ea

A django rest api key package

Hey everyone,

I've been working on some projects using Django for about five years now. But when I discovered DRF, I've decided to focus on building backend API applications without dealing much with the frontend. But about a year or two ago, I started to build APIs for some SaaS projects, and I realized I needed a robust API key management system.

I initially used https://github.com/florimondmanca/djangorestframework-api-key which is fantastic and has everything you need for API key systems, including great authorization and identification based on Django's password authentication system.

I will say this library shines if you only need API keys for permissions and nothing more.

However, when I wanted to push the package further, I hit some limitations. I needed features like key rotation, monitoring, and usage analytics to help with billing per request and permissions and better performances as the package use passwords hashing algorithms to create api keys.

So, I decided to create my own package. I've been working on it for about nine months to a year now, and it's come a long way. Here are some of the key features:

Quick Authentication and Permission System: You can easily implement authentication and permissions, for example, for organizations or businesses.
Monitoring

/r/django
https://redd.it/1cykl2c

Best practice projects Django + HTMX (+ AlpineJS)

I wan't to dive into Django + HTMX + (AlpineJS) and it would be great to see how others use these tools in projects. Do you know of any projects I could look into? Best practices?

Thanks!

/r/django
https://redd.it/1cyilp8

Do you write many views and paths or have single view for htmx requests?

Do you create view and path for each htmx component or you have single view htmx_request() and then inside that view resolve which template and data to return?

/r/django
https://redd.it/1cy86y3

Is there a way to pass data to redirect() and render the data on template?

Is there way to pass data to redirect() and render it out on templates. I have a static POST form below for sharing post URL. The form is connected to share\_post\_view in the views.py. What I would like to do is pass message='Your message has been sent' to redirect() so that I could render it out on template. Any help will be greatly appreciated. Thank you very much.

return redirect(post.get_absolute_url(), message='Your message has been sent')

views.py

def post_share_view(request, post_id):
post = Post.objects.get(id=post_id)
form = EmailPostForm(request.POST)
if form.is_valid():
name = form.cleaned_data.get('name')
email = form.cleaned_data.get('email')
to = form.cleaned_data.get('to')
comments = form.cleaned_data.get('comments')

message = EmailMultiAlternatives(


/r/django
https://redd.it/1cya1q9

JupyterLab 4.2 and Notebook 7.2 are available!
https://blog.jupyter.org/jupyterlab-4-2-and-notebook-7-2-are-available-b5e6b3c753de

/r/IPython
https://redd.it/1cykkwr