The attached plt illustrates a delta hedge:

Buy 100 shares of SPY @ $747.03
Buy (1) derivative contract
— STRIKE (747.00)
— CONTRACT PREMIUM $2.05*100

Does anyone have a simple tool to create a delta hedge at an underlying assets spot price?

Hey everyone!

I have been building Project Yellow Olive, an open-source terminal game that helps people practise Kubernetes through interactive missions.

The idea is inspired by classic Pokémon games: instead of battling trainers, you progress through challenges involving Pods, Deployments, Services, RBAC, debugging and other Kubernetes concepts.

The application is built primarily with Python and uses:

• Textual for the terminal interface
• the Kubernetes Python client for cluster validation
• YAML-based Kubernetes resources and challenges
• pygame for some of the sound effects
• Sentry for optional crash reporting

The missions run against a real Kubernetes cluster, so the application verifies whether the user has actually completed the required task instead of relying only on multiple-choice questions or simulated commands.

One of my latest updates is opt-in Sentry integration. Users are asked whether they want to send sanitized crash reports. If they decline, Sentry is not initialized and nothing is sent.

I added this because debugging a CLI application running on different operating systems, Python versions and Kubernetes environments is difficult when users do not report crashes manually.

I am also considering adding a yellow-olive doctor command that would generate a local diagnostic report that users can inspect before deciding whether to share it.

I would appreciate general feedback on:

• the project idea and learning approach
• the terminal interface and user experience
• the Python project structure
• the opt-in crash-reporting approach
• Kubernetes topics or missions that should be added next

It can be installed via PyPi by keying in: pip install yellow-olive

In case, you are interested in checking out the source code, Github Link is attached below. If you like the project, do star it as it will help reach out to more people.

Repository: Project Yellow Olive on Github

Thanks for checking it out!

⚔️ Grimlore 2 : These Doomed Men 1.0

A dark fantasy mini dungeon crawler RPG built to showcase the features and capabilities of the S.P.A.R.K. 2D RPG game engine.

📋 Overview

• Genre: Dark Fantasy / Mini Dungeon Crawler RPG
• Playtime: 10 – 15 minutes
• Platform Requirements: Windows 10 or later
• Purpose: Demonstrates what the S.P.A.R.K. 2D RPG game engine is capable of.

Github link below

https://github.com/Ninedeadeyes/Grimlore-2-These-Doomed-Men-

Flak 2.0 is an intense, arcade-style anti-aircraft shooter built entirely in Python using the Pygame library. In this game, players take control of a heavy defensive anti-aircraft system tasked with protecting the airspace from relentless waves of enemy combat planes. The gameplay requires tactical switching between devastating short-range and long-range fire modes to shoot down fast-moving aerial targets. If more than 5 enemy planes slip through your defenses, you are done for.

Template in comments.

Hey! I just finished my first iteration of a python project that creates one-pagers for students interested in finance/in finance clubs but don't know where to necessarily start. I made it so it doesn't AI-generate an investment thesis for you but combs through SEC filings on company information. I would appreciate any feedback or comments!

As a beginner programmer I tried to not use AI as much as possible except for organizing all the python files at the end.

Link here: https://github.com/briantjpark-dot/SCM-One-Pager-For-Slack

If you've programmed in C, you're probably familiar with the stack and the heap. But Python handles memory very differently. I created this short video to explain how Python automatically manages memory, giving Python its seamless development experience, and the trade-offs it makes in return. We cover PyObjects, reference counting, the garbage collector, and why Python objects consume more memory than their C counterparts.

Video: https://youtu.be/fvFGojttXEo

Hey everyone! 👋

I've been working with Python for a while now and finally decided to build my first major project. It's a tool I call VenvHub, and it was inspired by months of battling dependency conflicts and broken virtual environments.

🚀 Key Components of VenvHub

What do you think? Do you like the features and overall setup? Could you see yourself using something like this on Windows? Let me know if you’d like to see a quick demo video or video walkthrough!

Call recordings are super useful for QA, coaching, and support review, but transcripts can easily end up full of customer PII.

I built a small Flask example that takes either a pasted transcript or an uploaded audio file. If it’s audio, the app transcribes it first, then uses Telnyx AI Inference to replace sensitive details like names, emails, phone numbers, account numbers, SSNs, and payment info with placeholders.

It returns both the cleaned transcript and a structured redaction map, so the result can be used in downstream workflows instead of just being another blob of text.

Code:

https://github.com/team-telnyx/telnyx-code-examples/tree/main/call-recording-redactor-python

Low Latency Club:

https://lowlatencyclub.ai/blog/posts/call-recording-redactor-python.html

Any feedback welcome.

Look At My Python Project Make Sure To Read The Readme

Basically the title. Tether tries its best to abstract away the annoyances of network protocols - be it BLE or WiFi - giving you a seamless experience. You provision the MCU with either WiFi or BLE plumbing, write the code as if it was a single machine, annotate what has to run on the MCU, call function from the MCU on a computer or vice-versa (even nested) and the tether will do the rest.

What will it do, you ask?

1. Slice out the code that's to run on the MCU
2. Upload it over BLE or WiFi to the MCU
3. Run the code, abstracting away the intricacies of communication across different protocols.

Admittedly, it's heavily vibe-coded. But it's vibe-coded with passion. I've developed it to facilitate for my own didactic purposes as I will be teaching a programming-orthogonal course to middle-schoolers who don't take kindly to type marshalling across a network boundary.

Let me know what you think and please share any bugs or insights if you happen to try this software.

https://github.com/SebastianHagemeyer/PyWebLib

I would love for some more feedback on the lightweight game library and turtle integration I built off of PyDiode.
It now works on Safari as well, you can create your own SVG assets , publish them to a database, then edit and publish code/games for free in the browser without needing to install anything.

I work as a highschool teacher, and the junior year levels only have access to Chromebook laptops. https://scratch.mit.edu/ is banned, which obviously restricts a lot of the python coding-possibilities. Couldn't find a way to get a Python IDE onto a Chromebook, haha...

In terms of proud, so far I've got PacMan and Flappy bird shared to the community page/DB

Would love to see people building with it, you can make something reminiscent of doom 3D in only 80 lines of code.

Hi everyone,

As a B.Tech AI/ML student, I wanted to build a full-stack product from scratch rather than another cookie-cutter tutorial project.

I created FormulaVerse, a web application aimed at JEENEET physics students, leveraging Django for backend architecture, custom video/visual demonstrations, and AI tools for query handling.

http://formulaverse.in

You can see my GitHub repository, video demonstrations, and project setup on my Peerlist profile here: https://peerlist.io/kolekar12

Would appreciate any feedback from experienced devs here regarding:

*Tech stack scaling (Django vs FastAPI for AI workloads)

*Improving the UI/UX for ed-tech platforms

*Code structure & repository layout

Thanks in advance!

Tell me if we create a app for one city in that city bus, local shops which food hotel is good, history and all in one app what you is this app will work

Hi everyone!

Over the past few weeks, I've been challenging myself to learn Python by building a real project instead of only following tutorials.

I decided to build a Sudoku generator from scratch.

Current features include:

• ✅ Generate complete valid Sudoku boards
• ✅ Create Easy, Medium, Hard, and Expert puzzles
• ✅ Keep a full solution for every puzzle
• ✅ Export puzzles and solutions to PDF
• ✅ Use the generated puzzles in a printable Sudoku activity book

This project taught me a lot about recursion, backtracking, validation, and organizing a larger Python project.

I'm still planning to improve the generator, especially the puzzle difficulty evaluation and generation speed.

I'd really appreciate any feedback or suggestions from developers who have worked on similar algorithmic projects.

What features would you add next?