Lightweight, minimalist/customizable software for writing?

I work better on paper, however it is wasteful and my wrist resents me.

For notes, I use notepad++ with everything stripped down so its nothing but a blank window, but I dont quite feel compelled to write there. Libreoffice lags the hell off in my pc (3000g,8gbram) past a few dozen pages, and while I like gdocs, specially because it works on the cloud, it also underperforms past a certain point and sometimes also feel a bit clunky.

I dont need a lot of formatting options, what I want is

\- Reliable autosave (notepad++ has failed me more than ocne in several diferent ways)

\- Lightweight (I like how notepad++ allows me to just instantly scroll up and down a txt with several mb under its belt with no issue)

\- Sanity (basically nothing breaking down if I copy paste it from on to it)

\- No distractions/clutter

Any advice?

https://redd.it/1ogx3lf
@r_opensource

Best open source video editor for hierarchical video clip management between multiple subfolders

There are two folders below my main project folder:

Folder01 contains it's own separate project file named “project01” with it's own clips.

Folder02 contains “project02", a separate project file that only contains a few clips and nothing else.

We need to include project01 as part of project02's timeline and integrate that file into our project's timeline before exporting it as one single mp4 file as part of our greater project. Is there a way to do this without having to export project01 first under specific open source video editing programs like shotcut, kdenlive, and openshot?

Which one of these open source video editing programs might help us achieve complex video editing task involving two or more subfolders like these (by importing, I mean being able to include a project file and treat it as it where one single clip from our timeline's perspective)?

https://redd.it/1ogywka
@r_opensource

Project Built a TypeScript validation library with features the market leader doesn't have - MIT licensed

Hi r/opensource! 👋

I've been working on an open source TypeScript validation library called lite-schema-check and wanted to share it with this community.

Why I Built This

I was frustrated with existing validation libraries (mainly Zod) missing key features that developers keep requesting. Their #1 requested feature (FormData validation - 60+ votes) has been open for over a year with no implementation.

So I built it myself, and made it open source from day one.

What Makes It Different

Features the competition doesn't have:

✅ FormData validation with automatic type conversion
✅ Partial validation (return valid data even if some fields fail)
✅ Built-in JSON Schema export (no external packages)
✅ File validation (size, MIME types)
✅ XOR support (exactly one of multiple fields)
✅ Chainable string/number refinements
✅ Schema denoscriptions and metadata
✅ Mixed sync/async validation
✅ Circular/recursive schema support
✅ Reversible transforms (codecs)
✅ Clearer optional/nullable/nullish API

Technical Details:

Zero dependencies
\~3KB minified
Full TypeScript support with type inference
60+ passing tests
Works in Node.js and browsers
MIT licensed

\## Code Example

typenoscript

import { v2 } from 'lite-schema-check';
// Automatic FormData validation with type conversion
const schema = v2.object({
name: v2.string(),
age: v2.number(),
email: v2.string().email(),
avatar: v2.file({ maxSize: 5_000_000, mimeTypes: ['image/jpeg', 'image/png'] })
});
const result = v2.validateFormData(formData, schema);
// All types automatically converted: "25" → 25



\## Project Status

📦 Published on npm: `lite-schema-check`
🔗 GitHub: [https://github.com/YOUR\_USERNAME/lite-schema-check](https://github.com/YOUR_USERNAME/lite-schema-check)
📝 MIT License
🧪 60+ tests passing
📚 Full documentation
🤝 Open to contributions

\## Looking For

**Code reviews** - Always room for improvement
\*Contributors** - Especially for Angular/React integrations
\*Use cases** - What features would you need?
\*Feedback** - Be brutally honest!
\*Security audits** - Fresh eyes welcome

\## Contributing

I've set up:

[CONTRIBUTING.md](http://CONTRIBUTING.md) with guidelines
CODE_OF_CONDUCT.md
Issue templates
PR templates
Clear coding standards

This is a genuine open source project - not a company product, not trying to sell anything. Just solving a problem I had and sharing it.

Would love to hear your thoughts, especially on:

1. Is the API intuitive?
2. What features would make it more useful?
3. Any concerns about the approach?

Thanks for reading! 🙏



Links:

\- GitHub: https://github.com/toozuuu/lite-schema-check
\- npm: [https://www.npmjs.com/package/lite-schema-check](https://www.npmjs.com/package/lite-schema-check)
\- License: MIT

https://redd.it/1oh2mna
@r_opensource

🌍 GlobalCVE — Unified CVE Data from Around the World

Hey folks 👋

If you track vulnerabilities across multiple CVE databases, check out GlobalCVE.It aggregates CVE data from NVD, MITRE, CNNVD, JVN, CERT-FR, and more — all in one searchable feed.

It’s open-source (GitHub), API-friendly, and built to reduce duplication and blind spots across fragmented CVE listings.

Not flashy — just a practical tool for researchers, analysts, and anyone who wants a clearer view of global vulnerability data.

https://redd.it/1oh4buo
@r_opensource

What's your favorite OPEN SOURCE Chromium-based browser with MV3 and vertical tabs?

Hi r/opensource, I've been a heavy user of the zen browser ever since it came out, and as such I really want a browser with similar features (proper ad block, vertical tabs, containerized workspaces) BUT I want it to be chromium-based, as just in the past week I ran into five websites that did not work on firefox (broken dropdowns, registration buttons doing nothing, important elements not appearing), and it is hard to continue using it.

https://redd.it/1ognl7j
@r_opensource

Built a package manager to compile & install packages directly from their git repository
https://github.com/phukon/sprout

https://redd.it/1ogsynu
@r_opensource

Lightweight Python Implementation of Shamir's Secret Sharing with Verifiable Shares

Hi r/opensource!

I built a lightweight Python library for Shamir's Secret Sharing (SSS), which splits secrets (like keys) into shares, needing only a threshold to reconstruct. It also supports Feldman's Verifiable Secret Sharing to check share validity securely.

**What my project does**

Basically you have a secret(a password, a key, an access token, an API token, password for your cryptowallet, a secret formula/recipe, codes for nuclear missiles). You can split your secret in n shares between your friends, coworkers, partner etc. and to reconstruct your secret you will need at least k shares. For example: total of 5 shares but you need at least 3 to recover the secret). An impostor having less than k shares learns nothing about the secret(for context if he has 2 out of 3 shares he can't recover the secret even with unlimited computing power - unless he exploits the discrete log problem but this is infeasible for current computers). If you want to you can not to use this Feldman's scheme(which verifies the share) so your secret is safe even with unlimited computing power, even with unlimited quantum computers - mathematically with fewer than k shares it is impossible to recover the secret

Features:

* Minimal deps (pycryptodome), pure Python.
* File or variable-based workflows with Base64 shares.
* Easy API for splitting, verifying, and recovering secrets.
* MIT-licensed, great for secure key management or learning crypto.

Comparison with other implementations:

* pycryptodome - it allows only 16 bytes to be split where mine allows unlimited(as long as you're willing to wait cause everything is computed on your local machine). Also this implementation does not have this feature where you can verify the validity of your share. Also this returns raw bytes array where mine returns base64 (which is easier to transport/send)
* [This](https://github.com/thedanhub/shamir-secret-sharing) repo allows you to share your secret but it should already be in number format where mine automatically converts your secret into number. Also this repo requires you to put your share as raw coordinates which I think is too technical.
* Other notes: my project allows you to recover your secret with either vars or files. It implements Feldman's Scheme for verifying your share. It stores the share in a convenient format *base64* and a lot more, check it out for docs

**Target audience**

I would say it is production ready as it covers all security measures: primes for discrete logarithm problem of at least 1024 bits, perfect secrecy and so on. **Even so, I wouldn't recommend its use for high confidential data(like codes for nuclear missiles) unless some expert confirms its secure**

Check it out:

* PyPI: [https://pypi.org/project/shamir-lbodlev/](https://pypi.org/project/shamir-lbodlev/) (pip install shamir-lbodlev)
* GitHub: [https://github.com/lbodlev888/shamir](https://github.com/lbodlev888/shamir-lbodlev) (README with examples)

\-Feedback or feature ideas? Let me know [here](https://github.com/lbodlev888/shamir/issues)!

https://redd.it/1oh925h
@r_opensource

Unlocking the Sony PSP's Second CPU

Hey all!

The PSP may be an old device, but it still holds plenty of mysteries and possibilities for tinkering!

So I started this open-source project earlier this year with the goal of taking advantage of the Sony PSP's Media Engine, specifically its second MIPS CPU core, which has essentially the same capabilities as the main one.

However, it has no direct access to main system functions. It runs its own 'factory' core with functions stored in a kernel memory space, which hasn't been fully reverse-engineered yet.

- This project comes as a library that maps as many functions as possible from the Media Engine's core to make them accessible to homebrew developers

- It provides a custom initialization system and utility functions to simplify working with the Media Engine.

- It handles interrupts, suspend events, stack and local memory optimization, and thread management which is in WIP.

It's designed to make it easier for PSP homebrew developers to ease the integration and communication with the Media Engine. It's a work in progress, and contributions are welcome!

Available on GitHub: mcidclan/psp-media-engine-custom-core

Enjoy !

https://redd.it/1oh9qzv
@r_opensource

I built Flowcraft, a lightweight, zero-dependency alternative to heavy workflow platforms like Temporal/Airflow/Vercel
https://github.com/gorango/flowcraft

https://redd.it/1ohbuza
@r_opensource

What if Goldman Sachs made Slang open source?
https://youtube.com/shorts/wm5-vujv0FQ

https://redd.it/1ohej5z
@r_opensource

[R] Adaptive Sparse Training on ImageNet-100: 92.1% Accuracy with 61% Energy Savings (Open-source, zero degradation)

**TL;DR**: Implemented **Adaptive Sparse Training (AST)** on ImageNet-100 with a pretrained ResNet-50. Trains on \~37–39% of samples per epoch, cuts energy by \~61–63%, gets **92.12%** top-1 (baseline **92.18%**) with **no meaningful drop**; a faster “efficiency” variant reaches **2.78×** speedup with \~1–2 pp accuracy drop. **Code + noscripts open-source** (links below).

# Key Results

**Production (best accuracy)**

* **Top-1:** 92.12% (baseline: 92.18%) → Δ = **+0.06 pp**
* **Energy:** **–61.49%**
* **Speed:** **1.92×** over baseline
* **Activation rate:** 38.51% of samples/epoch

**Efficiency (max speed)**

* **Top-1:** 91.92%
* **Energy:** **–63.36%**
* **Speed:** **2.78×**
* **Activation rate:** 36.64%

# Method: Adaptive Sparse Training (AST)

At each step, select only the most informative samples using a significance score combining **loss magnitude** and **prediction entropy**:

significance = 0.7 * loss_magnitude + 0.3 * prediction_entropy
active_mask = significance >= dynamic_threshold # selects top K%


* Trains on **\~10–40%** of samples per epoch after warmup.
* **PI controller** keeps the target activation rate stable over training.

# Setup

* **Model:** ResNet-50 (pretrained on ImageNet-1K, 23.7M params)
* **Data:** ImageNet-100 (126,689 train / 5,000 val; 100 classes)
* **Hardware:** Kaggle P100 GPU (free tier) — fully reproducible

**Two-stage schedule**

1. **Warmup (10 epochs):** 100% samples (adapts features to 100-class subset)
2. **AST (90 epochs):** adaptive selection, 10–40% active

**Optimizations**

* **Gradient masking** → single forward pass (vs double) for \~3× reduction in overhead
* **AMP (FP16/FP32)** on both baseline and AST
* Dataloader tuning (prefetch, 8 workers)

# Why it matters

* **Sustainability**: \~61–63% less training energy
* **Iteration speed**: **1.9–2.8×** faster ⇒ more experiments per GPU-hour
* **Accuracy**: Production variant matches/slightly outperforms baseline (transfer setting)
* **Drop-in**: Works with standard pretrained pipelines; no exotic components

# Notes & comparisons

* **Baseline parity**: Same ResNet-50, optimizer (SGD+momentum), LR schedule, and aug as AST; only sample selection differs.
* **Overhead**: Significance scoring reuses loss/entropy; <1% compute overhead.
* **Relation to prior ideas**:
* Random sampling: no model-aware selection
* Curriculum learning: AST is **fully automatic**, no manual ordering
* Active learning: selection **per epoch** during training, not one-shot dataset pruning
* **From scratch?** Not tested (this work targets transfer setups most common in practice).

# Code & Repro

* **Repo**: [https://github.com/oluwafemidiakhoa/adaptive-sparse-training](https://github.com/oluwafemidiakhoa/adaptive-sparse-training)
* **Production noscript (best acc)**: `KAGGLE_IMAGENET100_AST_PRODUCTION.py`
* **Efficiency noscript (max speed)**: `KAGGLE_IMAGENET100_AST_TWO_STAGE_Prod.py`
* **Guide**: `FILE_GUIDE.md` (which version to use)
* **README**: complete docs and commands

# Discussion

1. Experiences with **adaptive sample selection** at larger scales (ImageNet-1K / beyond)?
2. Thoughts on **warmup→AST** vs training from scratch?
3. Interested in collaborating on **ImageNet-1K** or **LLM fine-tuning** evaluations?
4. Suggested **ablations** (e.g., different entropy/loss weights, alternative uncertainty metrics)?

**Planned next steps**: full ImageNet-1K runs, extensions to BERT/GPT-style fine-tuning, foundation-model trials, and curriculum-learning comparisons.

https://redd.it/1ohj0tf
@r_opensource

FlexingUSB is a New, Blazing-Fast, & Safe Terminal Utility for Creating Bootable USBs on macOS (Faster than dd/Etcher)
https://github.com/Goenvim/FlexingUSB

https://redd.it/1ohltje
@r_opensource

The OSI is seeking its next Executive Director, responsible for advancing its mission, growing and diversifying its funding base, and fostering a global, inclusive community of stakeholders.
https://opensource.org/blog/open-source-initiative-now-accepting-your-application-for-executive-director

https://redd.it/1ohm13j
@r_opensource

So OpenObserve is ‘open-source’… until you actually try using it

I’ve been exploring OpenObserve lately — looked promising at first, but honestly, it feels like another open-core trap.

RBAC, SSO, fine-grained access — all locked behind “Enterprise.” The OSS version is fine for demos, but useless for real production use. If I can’t run it securely in production, what’s even the point of calling it open source?

I maintain open-source projects myself, so I get the need for sustainability. But hiding basic security and access control behind a paywall just kills trust.

Even Grafana offers proper RBAC in OSS. OpenObserve’s model feels like “open-source for marketing, closed for reality.” Disappointing.

Obviously I can build a wrapper its just some work, but opensource things should actually be production-ready

https://redd.it/1ohmsso
@r_opensource

Cooklang Federation: A decentralized, GitOps-based recipe sharing platform (no ads, no tracking, just recipes)

I've spent 4 years building Cooklang - an open-source markup language for recipes (think Markdown for cooking). Today I'm launching the Cooklang Federation, a decentralized recipe search platform.

The Problem: Recipe sites optimize for ads and SEO, not quality. They modify copied recipes to make them "unique," creating an arms race that produces absurdities like dishwasher salmon. Good recipes are harder to find despite abundance.

The Solution: A federated, decentralized platform where creators maintain full control of their recipes while making them discoverable to the community.

# Key Features

Decentralized Architecture:
- Recipes hosted on your own domain or GitHub repo
- No central authority or platform lock-in
- You control your data completely

GitOps Workflow:
- All feeds version-controlled in GitHub
- Changes require pull request review
- Full audit trail and transparency
- Community-governed feed list

Open Standards:
- RSS/Atom feed support
- GitHub repository indexing
- Plain text recipe format
- Open API (coming soon)

Currently indexing: 60+ active feeds, 3,500+ recipes

Try it: https://recipes.cooklang.org

# Technical Architecture

The federation uses a crawl-index-search pattern:

1. Feed Registry: YAML file listing all RSS/Atom feeds and GitHub repos
2. Automated Crawler: Periodically fetches and parses recipes from registered feeds
3. Full-Text Search: Indexes recipes for fast, powerful search
4. Decentralized Hosting: Recipes stay on creator's infrastructure

Think "GitHub Pages for recipes" or "RSS reader meets recipe search."

# Cooklang Format

Recipes are written in a simple markup language:

---
servings: 4
time: 30 minutes
---

Add @bacon{200%g} to a pan and fry until crispy.

Add @onions{2} and cook until soft.

Mix in @tomatoes{400%g} and simmer for ~{15%minutes}.

Serve with @pasta{400%g}.

Benefits:
- Human-readable plain text
- Machine-parseable for tooling
- Version control with git
- No vendor lock-in
- Easy migration and backup

# Contributing

As a Recipe Creator:
1. Write recipes in Cooklang format
2. Host them (blog, GitHub, static site)
3. Add your feed to feeds.yaml
4. Submit a PR to the federation repo

As a Developer:
- Federation repo: https://github.com/cooklang/federation
- Cooklang spec: https://github.com/cooklang/spec
- Parser libraries: Rust, JavaScript, TypeScript available
- Draft federation spec: https://github.com/cooklang/federation/blob/main/spec.md

# The Ecosystem

Cooklang has grown to 30+ repositories on GitHub:
- CLI tools for recipe management
- Mobile apps (iOS/Android)
- Parser libraries in multiple languages
- Editor extensions (VSCode, Vim, Emacs)
- Static site generators

All open source, all community-driven.

# Why This Matters

Recipe sites are the poster child for how ad-driven incentives corrupt content quality. The federation provides a sustainable alternative:
- Creators maintain control and ownership
- No ads, no tracking, no paywalls
- Community-curated, not algorithm-driven
- Built on open standards and protocols

# Get Involved

Search recipes: https://recipes.cooklang.org
Contribute: https://github.com/cooklang/federation
Learn more: https://cooklang.org
Spec: https://github.com/cooklang/federation/blob/main/spec.md

I'm happy to answer questions about the architecture, the format, or the roadmap. Looking forward to your feedback!

https://redd.it/1ohpn7w
@r_opensource

My Spotify student deal is expiring

Hi r/opensource, I've been building this project just for myself, but then thought it might be cool to share if anyone is interested or has a similar problem as myself. It's pretty much an audio archival tool, and it's completely self-hosted and hopefully easily installable (only requires Python) so the only cost is leaving my laptop plugged in at home when I'm out, and the storage audio files take up.

I've been using it when I drive and go to the gym now so I feel a bit more comfortable talking about it, and it has a lot of stuff that makes it baseline functional at this point:

Search and download
Regular audio controls (play, pause, skip, scrub, queue, shuffle, loop, loop one)
Queue and queue to front via one swipe
Playlists, and importing from the green app
Renaming playlists and audio metadata
Backgrounded playback (yes, even on iOS Safari!!)

Obviously I'm no UI designer and there is still quite some work to make this what I envisioned, but I think I would need way more time and money to commit to that (audio editing, recommendations, listening stats, moutning existing audio folders).

I've been contributing to a few projects like free code camp on my personal accounts, and it would honestly be incredible if I could one day contribute to something goated like ffmpeg.

I'm grateful for any advice or feedback from the open source community, as it's my first project that I feel kind of proud of and want to share with others. If you decide to check it out or drop a star, thank you!

Link to project: https://github.com/whimsypingu/scuttle

Screenshots:

1. https://imgur.com/a/6lcYP1w
2. https://imgur.com/a/EVM4SrW

https://redd.it/1ohjlcr
@r_opensource

AGPL questions: API calls with proprietary services and commercialization ?

I’m evaluating the AGPL for a new open-source project and want to sanity-check my understanding.

Hypothetical questions:

AGPL -> Proprietary API: Can someone fork and Integrate it with Proprietary products such as Auth0 over API/HTTP? Obviously they can't open source Auth0 as well as it's a product that's not in their control.
Proprietary service -> AGPL : Can Proprietary products such as Auth0/stripe call back to AGPL product over the network? The constraint is we can't open source Auth0/stripe which are not in the control of forker.
ElasticSearch Style Forks? If something like ElasticSearch had been AGPL, would that stop an AWS-style fork/hosted service for commercialization? AWS also shared the source of OpenSearch. My current read is: AGPL wouldn’t prevent forking or commercialization per se, but it would require the host to publish their fork’s source (and subsequent changes) to users of the network service, which AWS did. I am trying to understand what could have been implications for AWS had it been AGPL?
If the about screen has copyright , can the fork change that?

https://redd.it/1ohtf9o
@r_opensource

yasr - a minimal no bloat web screen recorder under 1000 lines
https://unixextremist.github.io/yasr/

https://redd.it/1ohtqpv
@r_opensource

Pimo — tiny always-on-top Windows popup notes (auto-save + drag/drop images) — made this for myself, open-sourced it

Hi everyone — I made a tiny Windows app called Pimo for quick popup notes. It’s intentionally minimal: always-on-top, frameless, auto-saves every 5s (and Ctrl+S), supports drag/drop images and thumbnails, and packages as a single NSIS installer. I built it in Electron and shipped a v1 installer.

Why I built it

I wanted a note that just pops up, saves instantly, and hides away without cluttering my taskbar.
Dragging screenshots into a note felt essential, so I handled browser/Explorer/URL drags gracefully.
I kept the UI small and focused — no heavy feature bloat.

What I’d love from you

Try the app or the source and tell me what’s annoying or missing.
If you have a quick idea (UX or tiny feature), drop it here and I’ll consider it for v1.1.
If you find a bug, please open an issue and I’ll investigate.

Link
https://github.com/higgn/pimo-popup-notes

Small notes

Installer SHA256: B2217BF3BE3BAEDF6F50B5A644376C170635FF05371A8392065881F579E8E2F0
I know unsigned EXEs trigger SmartScreen; signing is on the roadmap — feedback on install flow is especially helpful.

https://redd.it/1ohkmck
@r_opensource

Would you say Mozilla is a good starting point to contribute to open source

I am a student with a bit of experience developing and would like to start contributing to open source. From what I read they assign you a mentor for each ticket you take on. What do you think?

https://redd.it/1ohye7o
@r_opensource

Open-source MBOX → EML → PST toolkit (Outlook, Python, no paid libs)

I was hired to back up old Google Workspace mailboxes to PST. Most mailboxes were 50–100 GB, and the tools I tried were either paid or just didn’t work. So I built my own and I’m sharing it here.

Step 1: MBOX → EML (year/month/flat layout, year filters, folder size/file limits)
Step 2: EML → PST (Outlook via pywin32), split by year or evenly by size, PST cap (15–20 GB), progress + optional flush so Windows updates file size

GitHub: https://github.com/madsonrick/mbox-to-pst-toolkit

Tested on Windows + Outlook 2016/M365. Requires Python and pywin32

https://redd.it/1ohy0sg
@r_opensource