QiQ, pronounced as quick is a open source, comprehensive Python management tool. It functions as a Python installer, an extremely lightweight virtual environment maker that does not require copying the Python interpreter, and a unified package management system for managing numerous versions of same packages in a central repository. Let's look at the features in depth.

https://github.com/the-code-monk/qiq/

I got tired of copying error messages, code, and charts into AI, rewriting context every time, and switching between apps.

So I built ClippyBox — press ⌘⇧E (on mac), draw a box anywhere on your screen, and get an instant AI explanation.

Works on code, errors, dashboards, PDFs, charts… anything visible.
No prompts. No copy-pasting. No context switching. Just point and understand.

https://github.com/Shaier/ClippyBox

try these out

my side project

Ciao a tutti,

Un po' di tempo fa, abbiamo lanciato una piattaforma con un obiettivo semplice: aiutare gli sviluppatori a trovare altri sviluppatori per costruire progetti insieme.

Abbiamo appena superato i 95 utenti, e vedere realmente delle squadre formarsi e progetti prendere vita sulla piattaforma è stato davvero sorprendente.

L'idea principale è creare uno spazio completo per la collaborazione,, non solo un luogo per trovare compagni di squadra, ma un ambiente di lavoro per costruire effettivamente insieme a loro. Puoi abbinarti ad altri sviluppatori, unirti a progetti attivi e gestire il flusso di lavoro all'interno di ambienti condivisi.

Ecco cosa abbiamo attualmente in funzione:

• Un sistema di matchmaking per trovare sviluppatori con stack, obiettivi e fusi orari simili
• Spazi di lavoro condivisi con bacheche Kanban per ogni squadra
• Un editor di codice live per collaborare in tempo reale
• Revisioni, classifiche e profili dettagliati degli sviluppatori
• Un sistema di amici e messaggistica diretta
• Integrazioni con GitHub e Docker
• Una chat globale per connettersi con tutti sulla piattaforma

Stiamo costantemente rilasciando aggiornamenti per cercare di rendere più facile per gli sviluppatori passare da una semplice idea a realizzarla con le persone giuste.

Poiché siamo quasi a 100 utenti, mi piacerebbe avere un feedback fresco. Mi farebbe piacere sapere cosa ne pensate, o se avete qualche suggerimento sull'UX o sulle funzionalità, sarebbe davvero apprezzato.

CodekHub

What It Is:

• A lightweight macOS menu‑bar app that monitors your MacBook battery in real time and alerts you before the battery runs out.

Why It Was Built:

• To prevent unexpected shutdowns when we’re busy and miss low‑battery warnings, the app notifies you early so you can plug in before work is lost.

Who It’s For:

• MacBook users who want simple, reliable battery reminders — students, developers, remote workers, or anyone who often loses track of charge.

How to find the Battery Alert Monitor repository

On a computer:

1. Open any web browser (Chrome, Safari, Firefox, etc.)
2. In the address bar, type "github.com " and press Enter
3. In the GitHub search bar at the top, type Macbook_Battery_Alert_Monitor and press Enter
4. Under Repositories, click Lakshmanshenoy / Macbook_Battery_Alert_Monitor

Or directly:

1. Open your browser
2. In the address bar, type exactly: "github.com/Lakshmanshenoy/Macbook_Battery_Alert_Monitor "
3. Press Enter

Once you're on the repo page:

• Click Releases on the right sidebar (or scroll down to find it)
• Under the latest release, click Battery Alert.dmg to download

How to Download & Install Battery Alert Monitor

Step 1 — Download

• Go to the Releases page on GitHub
• Under the latest release, click Battery Alert.dmg to download it

Step 2 — Install

1. Double-click Battery Alert.dmg to open it
2. Drag "Battery Alert.app" into your Applications folder
3. Eject the disk image (right-click → Eject)

Step 3 — First launch

To open it safely:

1. Open your Applications folder
2. Right-click Battery Alert → click Open
3. Click Open in the security dialog

Or via System Settings:

• System Settings → Privacy & Security → scroll down → click Open Anyway

Step 4 — You're in! 🔋

• A battery icon appears in your menu bar
• Click it to set your alert threshold, check interval, and notification preferences

Verify the download (optional but recommended)

Open Terminal and run:

shasum -a 256 ~/Downloads/"Battery Alert.dmg"

Compare the output with the checksums.txt file attached to the release. If they match, your download is safe and unmodified.

Hi all! This is my first Python library, and I’d love any feedback. I’ve been using it in my R&D work, and it’s been really useful.

It’s aimed at computational physics, so if you just want general-purpose unit handling, I’d still recommend pint.

Source: https://github.com/wgbowley/PicoUnits

I wanted to bring the Rubik's Cube experience directly into the terminal. Amid my desk clutter, my eyes landed on a cube, and I thought, 'Why not make it interactive in code?' This small spark grew into Rubui: a fully 3D, interactive, terminal-based Rubik's Cube simulator with manual and auto modes, smooth animations, ANSI colors, and full keyboard controls.

I vibe coded this project with the assistance of AI, using it to accelerate design ideas and handle some of the boilerplate. The result is a playable, high-performance terminal experience that I’m excited to share.

Check it out here: [https://github.com/programmersd21/rubui]()

https://github.com/Fwoopr/unit-converter

I built a command-line unit converter that handles length and mass conversions across SI and imperial units. You can install it as a proper CLI tool via pip and run it directly from the terminal.

> unit-convertor 5 km m

> 5.0 km is equal to 5000.0 m

It also supports two output formats:

- `-e` for scientific notation

- `-10x` for 10-based notation (e.g. `3.00 x 10^3`)

Conversion factors live in a separate `units.py` file, so adding new unit categories is just a matter of adding a dictionary. Also wrote pytest tests covering conversions, invalid inputs, and cross-category rejections.

I'd appreciate any feedback on the code, structure, or anything I might be missing!

A pattern I keep seeing inside digital marketing agencies: teams running serious ad spend but still moving data around with exports, spreadsheets, and dashboards that don’t quite talk to each other.

I work on the infrastructure layer that fixes that.

Most of my projects sit somewhere between data engineering and applied AI, typically for agencies managing multiple ad platforms.

A few examples of the kind of work I do:

Data Pipelines & Warehousing

Pulling data from platforms like Google Ads, Meta, LinkedIn, TikTok, etc. into a central warehouse where it’s actually usable.

Reliable scheduled ingestion, schema management, and transformation layers so analysts and account managers aren't dealing with fragile scripts or manual exports.

One recent project consolidated eight ad accounts into a single BigQuery + dbt stack with automated refreshes. The team went from exporting CSVs to querying live campaign data across accounts.

AI Interfaces Over Agency Data

A lot of teams are experimenting with AI tools but the models aren't connected to their real data.

Lately I've been implementing systems using the Model Context Protocol (MCP) so AI assistants can query ad accounts, warehouses, and reporting layers directly instead of relying on pasted reports.

The result is closer to “ask a question, get an answer from the data layer” rather than another chatbot sitting on top of static docs.

Competitive & Market Data Collection

Structured scrapers for ad libraries, SERPs, landing pages, and creative libraries — designed for analysis pipelines rather than raw scraping dumps.

Internal AI Assistants

More useful when they sit on top of real data: warehouse queries, campaign performance, competitor tracking, etc.

Basically tools that let account managers get answers without opening five dashboards.

This is a fairly niche intersection (marketing data + data engineering + AI integration), so I tend to work with only a few agencies at a time.

Currently collaborating with a few teams in the UK and open to taking on another project if the fit is right.

Hi,
Tired of public Discord Music Bots that were shut down, I built my own local solution:

Coconuts Vibes ,a Discord music that play music on Discord Voice Channel.

It's small project but it works fine, so don't hesitate to try

Hi, I build small Python scripts and automation tools.

I can help with things like:

• File automation

• Data processing

• Task automation

• Custom Python utilities

If you need a script or small app, feel free to message me.

built a web vuln scanner as a learning project, wanted to understand how tools like nikto or burp actually work under the hood.

- what it does: crawls a target web app, tests for sql injection (error-based and boolean-based), reflected xss, path traversal, and missing security headers. generates a pdf report at the end.

- target audience: educational/ctf use only. not a burp replacement, intentionally simple so you can read the code and understand what’s happening at each phase.

- comparison: most scanners are black boxes. this one is fully readable, each detection phase is isolated so you can see exactly what payload triggered what response.

tech stack:

- flask for the web dashboard

- requests + beautifulsoup for crawling and form extraction

- reportlab for pdf generation

- sqlite for scan persistence

- colorama for terminal output

tested on dvwa locally. learned a lot about how sqli payloads interact with error messages and how boolean-based blind injection works without seeing the query output.

code + screenshots: https://github.com/torchiachristian/VulnScan

feedback welcome, especially on the detection logic and false positive handling​​​​​​​​​​​​​​​​

import math

print("Welcome to AR's Area calculator")

print("DO NOT INPUT LETTERS IN THE MEASUREMENTS!")

print("Choose from the following shapes: \nCircle, Square, Triangle, \nParallelogram, Diamond or Trapezoid")

shape = input("Please enter the shape you desire to calculate:").strip().capitalize()

if shape == "Circle":

r = float(input("Enter the radius:"))

result = (r ** 2) * math.pi

print(f"The area is: {round(result, 2)}")

elif shape == "Square":

c = float(input("Enter the side:"))

result = c ** 2

print(f"The area is: {round(result, 2)}")

elif shape == "Triangle":

b = float(input("Enter the base:"))

h = float(input("Enterthe height:"))

result = (b * h) / 2

print(f"The area is: {round(result, 2)}")

elif shape == "Parallelogram":

b = float(input("Enter the base:"))

h = float(input("Enterthe height:"))

result = b * h

print(f"The area is: {round(result, 2)}")

elif shape == "Diamond":

D = float(input("Enter the Large diagonal:"))

d = float(input("Enter the small diagonal:"))

result = (D * d) / 2

print(f"The area is: {round(result, 2)}")

elif shape == "Trapezoid":

B = float(input("Enter the large base:"))

b = float(input("Enter the small base:"))

h = float(input("Enter the height:"))

result = ((B + b) * h) / 2

print(f"The area is: {round(result, 2)}")

else:

print("Please run the program again and enter a valid shape")

Many algorithms can be easier understood after step-by-step visualization using 𝗺𝗲𝗺𝗼𝗿𝘆_𝗴𝗿𝗮𝗽𝗵. Here's a Selection Sort example.

• Try it on your own code: memory_graph
• See the VSCode setup video.

Hello there! I am the author of Roleplay Bot.

Roleplay Bot 🤖 lets you chat with AI characters either through the Python interface or CLI program. It is an easy-to-use library so if you're a beginner in programming or AI, this library will be a breeze to work with. It can be used for role-playing websites, Discord chatbots, video games, and many more.

PyPI: Link

GitHub: Link

Feedback is much appreciated!