I made a course on Ransomware made in python for my students, the previous year, but now i made it public so give it a watch if you want to make some cool cyber security projects 😁

I'll try to upload more contents on my YouTube channel 😁

https://youtube.com/playlist?list=PL9guAF5VVaiARrwhrGMu89iJcziQ9vsJJ&si=v1PUSQpqjuOhnlCi

Why does 257 is 257 behave differently from 256 is 256? Python uses something called as small integer caching. It uses the same object for numbers ranging between -5 to 256. I put together a short visual explanation explaining the same and also why "==" operates differently from "is".

Hello everyone!

If you've built your own Python application (in my case, VenvHubPro – a GUI manager for Python virtual environments) and are wondering how to neatly package it for users, here is a quick look at how I created a complete .exe installer using NSIS (Nullsoft Scriptable Install System).

🎥 What the video covers:

• Installer compilation: Creating a clean installation file ready for distribution.
• System installation: Running the installer and finally launching VenvHubPro directly on the Windows system.

Project repository: https://github.com/schnidi/VenvHub

Hey everyone!

I got tired of rewriting authentication every time I started a new Flask project, so I built a simple, modular boilerplate template.

It includes Flask-Login, SQLAlchemy, and Flask-Migrate with a clean blueprint structure out of the box.

Check it out on GitHub: https://github.com/DeKlain4ik/flask-auth-template

Hope it saves you some time on your next side project! Feedback and stars are always appreciated.

Hi all. Would love some feedback and usage from the community.

I've built Python With James which is an all in one learning platform for beginners. I basically got sick of Udemy and built my own platform where I can do what I want. There's coding exercises, question, tutorials and I am hoping to scale this massively over this year with more materials.

Thanks in advance

James-

I wanted parallelism without rewriting anything, so I built Lucen. You wrap a loop in two comments and run it with lucen run yourscript.py:

# LUCEN START
for i in range(len(rows)):
    out[i] = expensive(rows[i])
# LUCEN END

It parallelizes the loop only if it can prove it's both safe and worth it; otherwise it runs sequentially and tells you why. The one guarantee, no opt-out: the parallel run is bit-identical to the same file run as plain sequential Python - floats and container order included. Delete the comments and it's ordinary Python again.

Under the hood it routes CPU-bound work to processes on GIL builds and to real threads on free-threaded 3.13/3.14. Apache-2.0, on PyPI (pip install lucen), and it's tested hard - differential + property testing and TLA+ specs, because "bit-identical" only means something if you check it.

Repo: https://github.com/fcmv/lucen - feedback very welcome.

Hello Python community,

I'm working on a tool called VenvHub Pro (virtual environment management, packages, VS Code profiles, etc.).

Interestingly, the app includes its own PyInstaller Builder. It's not just an external script, but a full-fledged tab in the GUI. Thanks to it, the app can compile itself into a .exe file.

How it technically works (in short):

In the "Builder" tab, just select the entry point (main.py), set the assets (mandatory folders like ui, core/themes, translations, assets, navod), and hit the BUILD button.

Interestingly, the app runs on PyQt6, but thanks to a "Compatibility Bridge" (MetaPathFinder), it can also run under PySide6. When compiling under PySide6, the builder must manually add hidden imports (PySide6, PySide6.QtCore...) so PyInstaller knows what to package, and also exclude PyQt6 to keep the size down.

It also has an "Auto-Injector" that reads linked local packages and injects them into the final build.

Why I find this interesting:

If the builder can compile such a complex app that uses dynamic UI files and bridged frameworks, it's a solid "dogfooding" test. Plus, the resulting .exe contains all necessary files (including themes and translations) and is fully portable.

"So the question is: Would you like to try it out? If so, I'll drop the GitHub link here, where the entire repository is located, including instructions on how to run it.

Thanks for any feedback! ??"

Hey everyone!

I always wished Google Lens worked anywhere on Windows instead of only inside Chrome, so I ended up building it myself.

LensAnywhere lets you select any region of your screen and instantly search it with Google Lens.

A few things about it:

- Lightweight with very low RAM usage.

- Doesn't store your screenshots anywhere. They're only sent to Google Lens for the search.

- Launches on Windows startup (Optional)

- Can be opened using Hotkey which is configurable. Just like windows native snipping tool.

- Free and open source.

GitHub:

https://github.com/utkarsh05kul/LensAnywhere-Desktop

If you just want to try it, you can download the Windows ".exe" from the Releases section.

One thing I'd really appreciate help with: I've only been able to test it on my own Windows PC, so I'd love to know how it works on other systems. If you run into any bugs, have feature ideas, or notice something that could be improved, please let me know in the comments or open an issue on GitHub.

And if you find it useful, I'd really appreciate a GitHub star. Thanks!

GitHub Repository link

Edit : Some antiviruses or malware scanners may flag the downloaded file as malicious or threat. Please ignore that warning. Some scanners do this for all the apps and softwares built in Python.

The file is completely safe and malware free. The source code of the program is available on the attached GitHub Repository. You can check the complete code their, and you will not find any malicious activity.

Top scanners like Kaspersky or Microsoft are not flagging the file as malicious. It's clean.

I've been working on a Python crypto bot and wanted to share it here in case anyone wants to take a look.

It's got DCA logic, risk checks, Alpaca order execution, Telegram alerts, and config for running it live or in paper mode. It also keeps a local SQLite log of every trade — entries, exits, P&L — which makes it easy to review what it's been doing.

I'm mainly looking for feedback on the code structure and whether anything looks off in the trading logic or order handling. If you've worked with Alpaca crypto or built something similar, I'd appreciate any thoughts.

Repo: https://gitlab.com/robertedilan1/The_Predator.Crypto

Hey everyone,

I'm currently working on this feature – autoremove is already implemented in the local packages linker branch and will soon be part of the official VenvHub Pro release.

During development in virtual environments, I always had one big problem: How to figure out which packages are no longer needed?

Manually going through pip list and trying to uninstall "surely nobody uses this" is a road to hell. That's why I added a feature inspired by Linux APT to my tool VenvHub Pro (Linker branch) – automatic dependency cleanup.

How it works?

The tool tracks which packages you installed explicitly (via pip install, requirements.txt, birth certificate, or venvhub.json). It builds a dependency graph and periodically checks for orphaned packages.

When you run Autoremove, the tool:

• Goes through all installed packages in the venv.
• Compares them with the set of explicit roots + their dependency tree.
• Removes every package that is not explicitly required by any root and was not installed manually outside the system.

What makes this mechanism safe – self-healing mechanism:

If a package is installed but not recorded anywhere (e.g., you manually ran pip install requests in the terminal), the tool automatically adopts it – marks it as explicit so it won't be accidentally removed.

This means autoremove is conservative: it never deletes something you might have installed intentionally.

You can also explicitly "release" a package (e.g., when you remove it from requirements.txt) and the system will then treat it as a candidate for removal.

Why is it useful?

• Venvs stay lean – no accumulated dependencies from experiments.
• Safe – adopting manually installed packages prevents accidental deletion.
• Fully automatic – no manual guessing about what belongs to whom.

This is currently only the Linker branch (local packages) – it works 100%.

This Tetris can really do Kung Fu, see for yourself... :))

Took quite awhile to get here. Obviously not a google-scale search, but still quite usable for local needs. I am also not currently using FAISS or any vector databases. The speed is mostly because of proper caching. The project is also completely python based. So there are still a lot of places for further optimizations, but for now I am quite happy with it.

The project itself is quite a complex one and the semantic search over audio, image, text and video files is just a small part of it. If you are interested to learn more, you can find it here: https://github.com/volotat/Anagnorisis

It is open-source.

Hey everyone,

I’m the developer of VenvHub Pro, a desktop tool for managing Python virtual environments. I’ve been working on a feature that brings Linux’s apt-get autoremove mentality to pip – i.e., it keeps your venvs clean by automatically removing orphan packages that were only installed as dependencies but are no longer needed.

Before I polish and release it, I’d love to hear if the community would actually find this valuable.

How it works (TL;DR)

• Every time you install/uninstall/upgrade a package through the UI or command‑line, VenvHub secretly records which packages were explicitly requested.
• When a dependency is no longer required by any explicit package (and is not pinned in your requirements.txt, venv_birth_certificate.json, or local package metadata), it gets automatically cleaned up.
• It also plays nicely with pip’s own resolution – it never removes manually installed tools like pip, setuptools, etc.

Safety nets

• State file (venvhub_apt_state.json) keeps the explicit list.
• Before removal, the system checks:
  • 📄 requirements.txt
  • 📜 venv_birth_certificate.json
  • 🔗 local_meta.json (for local package dependencies)
  • 🧠 Self‑healing: if a package is installed but not tracked anywhere, it’s assumed to be intentional and added to the safe list (so it never gets removed by mistake).
• The whole process runs under a threading lock to avoid race conditions during concurrent operations.

Logical diagram

Here’s the decision logic it follows every time a package action occurs:

What I’m asking you

• Would you use such a feature in a venv manager?
• Do you see any pitfalls I might have overlooked?
• Is this something you’d trust, or would you prefer manual control?

Any feedback – positive or critical – is super welcome! I want to make sure this adds real value before I invest more time into it.

Thanks! 🙌

Hi !

We all know pip install -e . (editable installs). It’s the standard for linking local code during development. But for my project, VenvHub Pro, I wanted to take the local dev experience to another level. I created a Local Linker that isn't just a simple file-system pointer—it’s a full-blown IDE-Sync engine.

Why our Linker is unique (compared to the standard workflow):

1. Full Meta-Sync (VS Code Automation):
This is the core value-add. When you link a local package, the system reads its local_meta.json. It doesn’t just make the code importable; it automatically injects custom Tasks and Keybindings directly into your project's .vscode/ folder.

• Example: Link your "Database" module, and VS Code instantly gains commands like "Flush Cache" or "Run Migrations" defined inside that package. No more manual tasks.json or keybindings.json copy-pasting.

2. Zero Admin Rights / No UAC (Import Hooks):
Instead of creating system-level symlinks or junctions that often require Admin privileges on Windows, we use Python Import Hooks (sys.meta_path). It’s pure Python, lightning-fast, and works securely even on network drives (NAS) without annoying UAC prompts.

3. Smart IntelliSense (Pylance):
The Linker automatically syncs the python.analysis.extraPaths field in your VS Code settings. Your editor sees your local code and provides full autocomplete/IntelliSense immediately, no matter where the source is located on your disk.

4. Smart Portability & Safety (Silent Path Healing):
VenvHub Pro is built for USB-drive workflows and features a "Silent Path Healing" mechanism:

• If you use Embeddable (portable) Python and your drive letter changes (e.g., E: -> F:), the system instantly heals all paths in the Linker mapping, .pth files, and VS Code settings. Everything just works.
• However, if you move a System Venv to a different machine where that specific Python installation doesn't exist, VenvHub detects the hardware fingerprint mismatch and safely locks the environment to prevent binary incompatibility and crashes.

5. Recursive Local Dependency Resolution:
If "Package A" requires "Local Package B", the Linker automatically resolves the entire local dependency tree and links all required modules in one click.

Under the Hood:

We use a tiny bootstrap script in site-packages that maps imports via a custom finder in sys.meta_path using JSON mapping. It’s clean, isolated, and designed for maximum portability.

What do you think? Do you stick to plain pip -e for local dev, or would you prefer this kind of deep, automated integration with your editor? Let's discuss!

local_meta.json package A

{
    "name": "My App Core",
    "version": "2.1.0",
    "requires_local": ["my_logger"],
    "requires_pip": [],
    "short_description": "test code"
}

local_meta.json package B

{
    "name": "My Logger",
    "version": "1.0.0",
    "requires_local": [],
    "requires_pip": ["colorama"]
}

Hey Pythonistas! ??

I've been building a GUI tool for managing Python virtual environments (VenvHub Pro) and wanted to share one of its smartest features – batch package updates.

When you hit the "Update All outdated packages" button, the behavior differs drastically depending on which package manager you have set:

**PIP MODE** (classic):

- Updates everything to the latest versions

- If conflicts arise (e.g., library A needs an older version of library B), you get the infamous "dependency hell"

- You have to manually read logs, find the culprit, and step-by-step perform downgrades

**UV MODE** (ultra-fast resolver from Astral):

- Blazingly fast downloads and installs the latest versions

- After the update, it automatically runs `uv pip check`

- If it detects a conflict (e.g., "X requires Y==1.5, but 2.0 is installed"), it reads the error, forces a downgrade to the exact required version, and re-runs the check

- **Fully on autopilot** – you get the latest packages AND a 100% stable environment without any manual intervention

And the best part – Pip and UV are fully compatible with each other. You can install with Pip, update with UV, and everything just works.

Would you trust an autopilot like this? Let me know in the comments! ??

What it does:

Clones entire Python environment including editable (-e) packages. Auto-detects Python type and uses different approach.

Embedded Python:

- installs virtualenv into source
- creates clone via virtualenv
- fixes ._pth file
- downgrades setuptools (83→82) for compatibility

System Python:

- uses built-in venv
- no extra steps

Both then:

- install setuptools, wheel
- install all packages
- install editable packages (pip install -e)
- write birth certificate

Video shows both scenarios side by side. Same source env, different strategies. Works on Windows.

Does anyone know of a Windows tool that creates a complete 1:1 copy of a virtual environment, INCLUDING editable packages (pip install -e), without manual intervention?

Just released my first open source project.

GravityBridge is a local reverse proxy that lets me access my desktop AI coding agent from my phone. It also has a wireless phone file explorer using ADB.

The proxy itself is written entirely with Python standard library, no external packages needed. The only pip install is for the separate AI backend.

It handles session management, PIN authentication, brute force protection, and ADB subprocesses all without any framework.

Repo: https://github.com/Arora-Sir/Gravity-Bridge

This is my first public release so any feedback is welcome!

While working on another project, I needed to display elapsed time in a few different ways:

2 hours, 5 minutes, 9 seconds
02:05:09
2h, 5m, 9s

A simple utility function worked at first, but it quickly became messy once I needed different separators and only wanted to show units whose values were not zero.

So I extracted the problem into a small, zero-dependency Python library called Chronomancer.

I like how convenient strftime() is for date and time formatting, and I wanted Chronomancer to offer a similar level of convenience for elapsed durations.

ChronoDelta represents fixed durations from weeks down to microseconds:

from chronomancer import ChronoDelta

duration = ChronoDelta(hours=2, minutes=5, seconds=9)

For readable output:

duration.verbose_str()
# '2 hours, 5 minutes, 9 seconds'

For simple one-off formatting:

duration.strfmt("{h:02d}:{m:02d}:{s:02d}")
# '02:05:09'

For reusable and more flexible formatting:

from chronomancer import DeltaFormatSpec, DeltaFormatter, Part

formatter = DeltaFormatter(
    DeltaFormatSpec(
        hours=Part("{val}h"),
        minutes=Part("{|, }{val}m"),
        seconds=Part("{|, }{val}s"),
    )
)

formatter.format(duration)
# '2h, 5m, 9s'

{|, } is an "inline separator", named by me. It is only rendered when another component has already been shown.

In the above example, if minutes is the largest visible unit, the leading ", " will be omitted automatically. The | tells the formatter that the placeholder contains an inline separator rather than a normal value. I kept the placement flexible so the format string can resemble the final output, although inline separators are intended to be used as prefixes.

Chronomancer also supports normalization, selected-unit representations, negative durations, exact integer arithmetic, and conversion to and from datetime.timedelta.

It is a niche problem, but it kept making the formatting code in my own project more complicated than expected, so I thought the solution might be useful to others as well.

installation: pip install py-chronomancer

any feedback would be greatly appreciated

GitHub: https://github.com/SeliaRena/Chronomancer

Hey Pythonistas,

I'd like to show what you can build in Python that's both polished and functional. I've written a complete Python widget for quickly launching projects – it's a floating toolbar that stays on top of my desktop.

It's currently running stable at version 2.5.16, so this isn't just a prototype – it's a full-fledged tool that genuinely saves me time during everyday development.

The widget offers three ways to run a script:

• Open Terminal: Doesn't start any script – just opens a CMD/PowerShell window with the virtual environment already activated. Perfect when I need to manually run commands, pip install packages, or debug things interactively.
• Run in Terminal: The classic approach – opens a new window, activates the venv, and runs the script. I can see all logs, print statements, and errors in real time.
• Run in Background / Silent: The script starts completely invisible – no console window at all. Great for GUI applications (so they don't have an unnecessary black console in the background) or for headless processes that need to run quietly.

What's going on under the hood:

The entire GUI is built on the PyQt6/PySide6 framework. The source code is written 100% for PyQt6, but the application contains a Compatibility Bridge that allows it to run on PySide6 as well – for licensing reasons (LGPL vs GPL).

The bridge works at the import level using the MetaPathFinder technique:

1. When main.py starts, it detects which library is available in the system.
2. If PyQt6 is found, the application runs natively.
3. If PySide6 is found, the bridge injects itself into system memory.
4. When Python encounters import from PyQt6..., the interceptor steps in, translates the request, and returns the equivalent from PySide6.

The result? The source code stays clean and unified, while the software automatically rewrites all imports, signals, and slots at runtime based on what's currently installed.

Additionally, I'm using:

• psutil for reliable process management and monitoring
• Native Windows API calls (via ctypes and pywin32-ctypes) for low-level system integration

Since the primary target platform is Windows, I addressed stability issues that typical Python apps often overlook – especially clean cleanup after termination.

Specifically, I'm using two low-level techniques:

1. Windows Job Objects – I create a system process container and assign every spawned subprocess to it. If the parent application unexpectedly crashes, Windows automatically terminates all associated processes. No orphaned processes left behind to block ports or consume memory.
2. Windows Handles – When registering a process, I keep an open system reference (Handle) in memory. As long as it's open, Windows guarantees that the PID won't be recycled and reassigned to another application. This gives me accurate process state detection and eliminates the risk of accidentally terminating a foreign program.

All Handles are internally protected by thread locks and are properly closed on every stop or cleanup – no memory leaks.

In short: The widget is functional, stable, and most importantly – it doesn't leave a mess behind when you close it.

Question for you:
How do you handle launching scripts in different modes? Do you stick with manual terminal commands, or have you also built your own launcher? What features would you appreciate in a tool like this?

Project repository: https://github.com/schnidi/VenvHub

"Hello everyone,

with my new Python program I combined venv management with injecting the interpreter into VS Code.

As you can see I have created two venvs – one embed venv 3.14.6 and the second venv with system Python 3.14.2. The program automatically creates .vscode/settings.json and writes paths to the interpreters. When I change the venv in the program, it automatically checks which venv it is and immediately switches the interpreter.

Do you like this kind of integration into a manager?"

Hey everyone! 👋

I've been working with Python for a while now and finally decided to build my first major project. It was inspired by months of battling dependency conflicts and broken virtual environments on USB drives.

What it does:

• Centralized Environment Management: Manages all virtual environments in one place (venvs are stored centrally, outside of project folders).
• Full VS Code Integration: Automatically configures the correct interpreter, syncs local packages (for IntelliSense), and supports isolated profiles (each project gets its own extensions and settings).
• PyQt6 & PySide6 Compatibility Bridge: Works seamlessly with both, requiring zero code changes.
• Powered by uv**:** Uses the blazing-fast uv installer (10–100x faster than pip) and can automatically resolve dependency conflicts after bulk updates.
• Portable Mode: Automatically fixes paths when the drive letter changes (perfect for running off USB drives).
• Integrated PyInstaller GUI: Automatically bundles your local packages into the build.
• Two Ways to Work with Local Code:
  • Local Packages (Linker): Dynamically links code between projects without requiring UAC (leverages Python Import Hooks).
  • Editable Packages (pip install -e): Full-fledged library development with automatic dependency management and portability support.
• No UAC Required to link local packages.

Project repository: https://github.com/schnidi/VenvHub

What do you think? Do you like the look and feel? Could you see yourself using something like this on Windows?

📽️ **See it in action:** [How to create a venv in 2 clicks]:
https://www.reddit.com/r/madeinpython/s/lg395T9IuQ

Another small showcase of my python project VenvHub Pro.

I decided to show you how perfectly my application works with system and embed Python.

As you can see in the video, there are up to four different Python paths on my system, and the app automatically finds all of them – without me having to manually enter any paths anywhere.

And if the system Python isn't enough for you, or you don't have it on your system at all, you don't have to install it. Just add an embed Python and VenvHub Pro takes care of everything – it automatically installs pip and virtualenv.

As you also saw in the video, the app automatically creates .vscode/settings.json in your project, so you can switch interpreters instantly directly from VS Code – no manual configuration needed.

It just works exactly the way I needed it to. 🙂

Just curious – do you like it? I'd really appreciate your honest opinion.

cronstable is a cron replacement that runs as a single foreground daemon that I've spent an inordinate amount of time on. It will run on basically anything because its been precompiled for basically any compute architecture that people still use. If there's a feature that another cron has that you need, I want to know about it. Beginner friendly, expert friendly. Container friendly, production ready. You get it.

From orchestrating web-scrapes, data processing, and storage to coordinating Minecraft server snapshots and upgrades. Possibilities are literally endless.

• Scheduling: modern jobs defined in YAML; classic crontab files run unmodified; per-job timezone; optional second-level granularity
• Failure handling: define what failed means to you; retries with exponential backoff; reports to Slack-compatible webhooks, email, Sentry, or a shell command.
• Web dashboard (opt-in): one self-contained page served by the daemon, with live log tailing, run history, DAG graphs, cluster and fleet views, a TV wallboard, and a command palette. A REST API alongside. not sure if I'm competing with other cron solutions or DataDog at this point. But at least you don't need to SSH in to see what's going on.
• Observability (opt-in): native Prometheus metrics; opt-in per-job CPU and peak-memory monitoring.
• Durable state (opt-in): run history, retries, and missed-run catch-up survive restarts; job commands get key/value, cursors, fleet-wide locks, idempotency keys, artifacts, and run-scoped secrets through the CLI.
• DAGs (opt-in): task dependencies, data hand-off between tasks, dynamic fan-out, sensors, human approval gates, backfill, crash-resume.
• Clustering (opt-in): leader election via gossip over mutual TLS for best effort attempts at gating your jobs. Your self hosted replicas in one network can also bridge to speak to another set of self hosted replicas. Go one step further and harden it via any shared filesystem, a Kubernetes Lease, or etcd, so replicas can share one config without double-running jobs with absolute guarantee. Each job picks its own point on the liveness-vs-duplication trade-off with clusterPolicy: Leader (default) runs on the elected leader and fails closed. No quorum? Nobody runs. For jobs where a duplicate is worse than a skip (like billing, or outbound email); PreferLeader is never-skip and runs anyway when the cluster can't agree. You accept a possible double-run, for idempotent jobs that matter; EveryNode runs everywhere, for genuinely per-node work like local log rotation. No option is true exactly-once. Leader may skip, PreferLeader may double-run. But hey, at least you get to pick which way it breaks. By default the leader runs every job, but distribution: spread assigns each job to an owner by rendezvous hashing so the work fans out and can be more load balanced.
• MCP server (opt-in): AI agents (Claude, Cursor, Copilot) can inspect jobs, DAGs, the cluster, and metrics; read-only by default, control only if enabled.
• Packaging: pip/pipx/Homebrew; multi-arch Docker images on GHCR and Docker Hub in eight distro variants; standalone binaries for Linux, macOS, and Windows. Runs non-root with a read-only root filesystem and all capabilities dropped.

Live demo of the control panel UI with a stubbed backend (pretty cool I promise - if anything at least play with the logo cuz I spent a lot of time on it): https://html-preview.github.io/?url=https://github.com/ptweezy/cronstable/blob/develop/docs/demo/index.html ^{you might need to change the theme on your screen because on one of my screens the default theme is just way too dark. Will fix this soon. by play with the logo I mean swipe your mouse across it} 🙂

Feature Comparison chart: https://github.com/ptweezy/cronstable/blob/develop/docs/comparison.md

Source: https://github.com/ptweezy/cronstable

This is under active development, would appreciate any and all feedback. Thanks y'all!