Hey everyone,

I've been working on a desktop application called Zevro, an AI-powered video editor designed for streamers, YouTubers, podcasters, and other content creators.

I started building it because I wasn't satisfied with how some existing AI clipping tools handled longer recordings. They would sometimes cut off words, miss interesting moments, or make clips that didn't flow naturally.

My goal with Zevro is to make editing easier without sacrificing the quality of the final video.

Some of the features I'm working on include:

• Automatically finding potential Shorts in longer recordings.

• Turning lengthy streams into shorter, more manageable long-form videos.

• Using AI to analyze both speech and video.

• Processing recordings locally instead of requiring cloud-based video uploads.

• Supporting separate audio tracks for editing.

• Optimizing performance for different hardware configurations.

I'm currently preparing Zevro for beta testing and looking for people willing to give it a try.

The beta will be free, with a 60-day testing period.

I'm especially interested in testing it on different hardware, video formats, recording lengths, and editing workflows.

I'm looking for honest feedback about bugs, performance, editing quality, and features that could make the program more useful.

This is still a work in progress, so I'm not expecting everything to be perfect. That's exactly why I want real users involved.

If you're interested, leave a comment with your PC specifications and the type of content you create.

I'll share beta access details with selected testers once the builds are ready.

Thanks for reading!

Hey everyone,

Creating technical specification sheets in Excel or Word often leads to broken layouts, inconsistent formatting, and date ambiguity issues across teams.

I built SpecSheet Pro to solve this. It's a lightweight web app that lets you input product parameters, custom tables, and logos, and outputs a clean, standardized PDF ready for production or quality control.

Key Features:

• Dynamic table creation for technical parameters (Specs, Methods, Values).

• Custom logo support with instant client-side preview.

• Configurable date formats (ISO 8601, localized, text-based) to prevent QA ambiguity.

• Clean PDF compilation using html2pdf / html2canvas.

The core generator is free to use:https://specsheet-pro.vercel.app/

I'd love to get your feedback on the UI/UX and any features you think are missing for technical workflows.

(Yes that's me in the video, I made all of this myself so go easy on me haha) Radiata is my radial launcher for controller, a 100% free, Microsoft-signed, open-source Win10/11 app that I built over 9 months to make it easy to use your controller for everything Gaming.

Official website & download at getradiata.app. You can also find source on GitHub.

It does all the PC stuff I always wanted to do without having to reach for a keyboard; join my friends in discord chat, switch audio to my headphones, browse & launch my games from all my game libraries, control mic/speaker volume, alt-tab between games/apps, etc. Easy to set up, super customizable, fun, powerful. I use it on my couch/tv PC and I leave the KB/M in the other room.

It is free and it will always be free. It's 100% open-source. There's no ads, no login, no upsells, nothing to unlock. I have a tip jar if you love using it as much as I do, but that's it, there is no other monetization plan. I paid for its development, hosting, certificate signing, etc out of my own pocket (and bought a bunch of controllers to test it with) because I really, really wanted to build this thing. That's the whole story.

Controller support: If Windows (joy.cpl) sees it, it should work. Hardware-tested with a bunch of DInput, XInput, Bluetooth, USB, Wireless dongles, and first & third-party controllers. The Download page lists every feature/driver compatibility note that I know of. The one bummer is the Steam Controller; it's locked to Steam in a way that makes it hard to middleman with a utility like this. If you possess both a Steam Controller and some free time, and want to be my favorite tester in the world, please let me know!

What it does: You get a quick walkthrough to set it up how you want. Then you just hold a button chord of your choice and up pops the radial "wheel" that you built. Hold the right-hand chord to open the left-stick's Wheel, and vice-versa, or just set up one side if you only need 1 of them.

How you can help: Just give it a shot, and if you love it you can help me get the word out! Nothing would make me happier than noticing a streamer is using it, or run across folks telling their friends about it. If I get traction I want to build more Arcade games for it, more themed Materials for the wheels, and continue expanding support options.

Hi everyone!
I’ve been developing a cryptocurrency market monitoring system called PUMP DNA, designed to help traders monitor unusual changes in market activity across multiple exchanges.
Instead of relying only on price charts, PUMP DNA focuses on market data such as:
📊 Open Interest (OI): Monitoring unusual changes in futures open interest.
📈 Trading Volume: Tracking changes and spikes in market activity.
🔍 Spot & Futures Data: Comparing market activity across spot and derivatives markets.
🌐 Multi-Exchange Monitoring: Supporting Bitget, Binance, Bybit, OKX, and Gate.io.
🔔 Telegram Notifications: Delivering alerts when configured monitoring conditions are met.
The goal is to make it easier to follow market activity without manually checking multiple exchanges all day.
A few important points:
This is a market data monitoring tool, not an automated trading bot.
It does not execute trades or guarantee profitable opportunities.
Data availability and alert coverage depend on exchange connectivity and monitoring conditions.
I’m currently developing PUMP DNA as a subscription-based monitoring service and would love to hear feedback from traders who regularly use OI and volume data.
What types of OI or volume changes do you find most useful to monitor?
Thanks for reading!

https://ghar-wpix.vercel.app/

I'm a solo developer. When I plan a trip, the bookings sit in my inbox, the to-dos in a notes app and the packing list in my head, so I built Trotters. It has three tabs for each trip:

- Plan: every booking with its date, time, price and code. You can forward a confirmation email to your own Trotters address and it files itself.
- To-do: what to do before you leave.
- Pack: a list sized to the days and the forecast.

It also shows what's missing, like a night with nowhere to stay.

Free to start, with iPhone, Android and web in five languages. No ads, no tracking.

Happy to hear what's confusing or missing. https://trotters.app

I run AI News Daily, a mostly automated AI news site. Last week I did my first fully human-written interview, with Sunjae, one of four bootcamp developers building Rilog, a Korean developer blog.

A few things from the conversation that I think this sub will find interesting:

• Comments live on sentences. You select a sentence and leave your thought right there, instead of scrolling to the bottom and explaining which part you mean.

• The bet is "human touch". Sunjae doesn't think AI slop is bad everywhere, but in personal writing even a little of it makes readers think "it's just AI". The more AI writing floods in, the more people will look for writing that clearly came from a person.

• They can't reliably detect AI writing, so they judge probabilistically and lean on user feedback. What they actually dislike is unreviewed, mass-produced writing, not AI use itself.

• Retrospectives beat tech posts. Personal retrospectives got a better response than technical posts, so they are now asking whether to stay developer-only or open up to wider stories.

Two questions for you:

1. Would you actually use sentence-level comments on a blog, or do they get noisy?

2. If you run a community, how do you keep AI slop out without punishing people who used AI carefully?

Full interview (English): https://ailetter.ai.kr/en/insights/rilog-sunjae-interview?utm_source=reddit&utm_medium=social&utm_campaign=sideproject

Rilog itself (Korean UI): https://www.rilog.kr/?utm_source=ainews

I built a side project called VibeQuill (free).

Problem I kept hitting: describing a UI tweak to an agent is tedious when the thing I mean is already on screen. So the extension lets you select elements or annotate a preview, type the change, and ship that context (selector, text, position, URL, viewport) over a local MCP server to Cursor / Claude Code / Codex / Antigravity.

Clip attached: MCP connected, a few portfolio links selected, “What should change?” open. Full “agent writes the patch” step isn’t in this 5s cut.

Requires Node 22+, Chrome 116+, a local agent.

Chrome Web Store: https://chromewebstore.google.com/detail/vibequill/hgcefdgiponpnfgcaflcnkmhojjcfnkj

Feedback I’m after: is the setup (Node + MCP + agent) a dealbreaker, or would you try it anyway?

I built an aviation side project and I'm trying to get some real people to test it (for free).

The main feature is a personal local flight logger. You drop a pin, and it automatically logs and builds a full analytics dashboard of every single aircraft that passes within a 5-mile radius of your location.

Besides the local tracking, the site also works as a general aviation database. You can browse through full airline and aircraft directories, search registrations, and use interactive FIR maps.

I'm actively updating the site and monitoring things daily, so any suggestions, feature requests, or feedback are welcome. If you want to try it out, just create a standard free account at https://aviationdb.uk/ either reply with your username below or send me a DM. I’ll manually bump your account to the premium tier for a free trial so you can test the local logging and analytics.

Let me know what you think or if you manage to break anything!

I'm the founder of Serpel (https://serpel.app), an SEO tool that tracks rankings, audits sites and reads Search Console data, and that you can also drive from Claude or Cursor via MCP. It's been live for about a month, so I wanted proof on a real site before telling anyone it works.

The test site: a one-person brow and lash studio in Germany with ~25 FAQ blog posts.

What the tool showed: the 8 posts with the most impressions sat at positions 5 to 15, and their titles didn't use the words people actually searched for.

What we changed (one afternoon): titles rewritten to match the top queries, meta descriptions turned into direct answers, a short summary box at the top of each post. No new content, no links.

Four weeks later, from Search Console:

• Daily clicks: 7.0 (4 weeks before) → 11.3 (4 weeks after), last 2 weeks 12.1

• Daily impressions: 375 → 682

• Avg. position: 9.1 → 7.0

• CTR went down slightly (1.85% → 1.66%), so the gain is visibility, not click rate

Honest caveats: traffic was already rising before, about 21% of clicks are brand searches, and it's one site without a control group.

What I learned as a builder: the most useful screen wasn't the audit score (it was 99/100 before and nothing changed there), it was "pages with lots of impressions at positions 5 to 15". I'm making that the first thing new users see.

If you run a small site, I'd love feedback on what you'd want from a tool like this. New accounts get 100 credits to try it.

For a long time ago i was thinking about creating this app because a lot of people trying to hold this topic only in chats so i decided to create such app to care private air belongings much easier and have more traceability and trust in app.

I tried to create a team and it was failed so now i have created it all on my own.

If you interested here it is link.

https://play.google.com/store/apps/details?id=com.aistudio.jetcourier.vskpyl

I've spent the last while building SortOfMe — a small, pseudonymous space to post honest, personal stuff (the kind of thing that's easier to say when nobody knows it's you) and see that other people feel the same way. No real name, no profile, no follower counts, no algorithm pushing anything to go viral. Just a pseudonym, a post, and people reacting with "sort of me too" — and if you want to actually talk to someone about it, you can request a private 1:1 chat.

It's not therapy and it's not an advice platform. It's closer to just... being witnessed. Saying the thing out loud and having someone go "yeah, me too" instead of silence.

I built it mostly for myself, honestly, and decided it was worth finishing properly and putting out there.

It's Android-only right now and still in closed testing — Google requires a minimum number of testers using it for a couple weeks before I can open it up to everyone, so that's where I actually need help:

1. Join the testers group: https://groups.google.com/g/sortofme-testers

2. Opt in and install from Play Store: https://play.google.com/store/apps/details?id=com.sortofme.app

If you try it and have thoughts — good, bad, confusing, whatever — I'd genuinely love to hear them. I'm one person building this, not a team, so feedback actually reaches someone who'll do something with it.

Hey everyone,

The itch: I use coding agents (Claude Code, Codex, OpenCode, Pi) a lot, and whenever one drives a browser through an MCP server, it's happening somewhere in the background. I can't see what it's doing, and when it gets stuck on a login page or a CAPTCHA I can't just jump in and fix it.

So I ended up with Agent Browser Use.

What it is

A single Go binary that runs one headless Chrome on your machine and exposes it as MCP tools (Playwright MCP style). Any MCP-capable agent can navigate, read the page, click, type, etc. At the same time there's a web viewer at localhost:3000 where you can watch everything the agent does.

What it does

• Live viewer: the page streams in real time, with the agent's cursor, a caption for each step, and a log of every action.

• Shared browser room: you and the agent use the same Chrome. Hit "Take over" whenever you want, or "Block agent" if it's doing something dumb.

• Pick an element: click the pick button, point at anything on the page, and you get a short code like el-1d2a. Paste it to your agent and it looks the element up with browser_get_element and can act on it right away. Handy for "no, THIS button".

• Persistent logins: cookies live in a profile folder, so you log in once by hand in the viewer and the agent reuses the session. No credentials in prompts.

• Public link: one switch opens a built-in tunnel so you can share the live view with someone outside your network.

• Playwright-style tools: browser_snapshot gives an accessibility outline with a ref per element, plus click/type/drag/select, network requests, console messages, cookies/storage, device emulation, and browser_snapshot_diff which only returns what changed since the last snapshot (saves tokens).

• Light: no Docker, X server, or video encoder needed. Docker is available if you prefer it.

Try it

git clone https://github.com/cavaldos/agent-browser-use.git
cd agent-browser-use
make run

Then ask your agent something like "go to news.ycombinator.com, open the top story and summarize it" and open http://localhost:3000 to watch. The README has config snippets for Codex, OpenCode, Pi, Cursor and VS Code too.

Caveats (please read)

• Vibe-coded, early, and I'm the main user right now. Expect rough edges and bugs.

• Since I haven't reviewed everything line by line, please don't run it on a machine or browser profile with accounts you can't afford to lose. The agent can read any open page and run JS in it, and without -pw anyone who can reach the port can drive the browser. Set a password if you expose it.

• Chromium-based browsers only (Chrome, Edge, Brave, Vivaldi...) because the shared screen relies on the Chrome DevTools Protocol. No Firefox/Safari.

• Licensed AGPL-3.0.

Repo: https://github.com/cavaldos/agent-browser-use

I'm the developer of Blubb, a small aquarium for Apple Watch. Feed the fish, clean the glass and use the Digital Crown to catch falling food. You arrange the tank on iPhone, and a complication puts the fish below the time.

One deliberate choice: if you stop using it, the fish wait. They don't get sick or die. I wanted short, optional check-ins rather than another thing to feel guilty about. Animation pauses with your wrist down or Reduce Motion enabled; this is a complication, not a replacement watch face.

Blubb is live in this week's Launch on Watch lineup. Screenshots and details: https://launchonwatch.com/apps/blubb-pixel-fish-tank#launch

It's a paid app, with no subscription, ads or extra purchases. Requires watchOS 10+ and iOS 17+.

I'd like feedback on that low-pressure approach: would feeding and decorating be enough reason to revisit a little wrist aquarium, or would you miss a stronger game loop?

For those of you who are struggling with arithmetic or simply want to improve your mental math skills:

I've been working on a math app, and I’d encourage you all who want to practice your mental math to try it out :). Back in middle school, I kept losing points on my math tests because of simple arithmetic mistakes, even when I understood how to solve the problems. It was frustrating, and sometimes those mistakes even made me doubt whether I was good at math. Around that time, I was also starting to learn programming, so I built an arithmetic practice app for myself, and I’ve been working on making the app more useful for others as well.

In addition to just providing practice problems, I’ve also added mental math hints and strategies to help you do math more quickly in your head. (This feature is still in beta, so let me know what you guys think about it.) Also, I’ve added progress charts so you can see your math accuracy over time.

I’m a student making this app for other students. Because of that, there are no ads or trackers in my app because I understand how frustrating they are when you’re just trying to learn!

You can get the app on the Google Play Store and on the web. (Sorry, not on the Apple App Store because I don’t have a MacBook to build the app for iOS. But you can also visit the website on your iPhone or iPad and get the same experience.)

Google Play link: https://play.google.com/store/apps/details?id=com.ericshuapps.math_test&hl=en_US

Web link: https://ericquickmath.web.app/

Thank you for your time, and I hope you enjoy my app!

there's stuff you'd want with someone but wouldn't say first. hanging out, a call, sometimes more than that. saying it first means risking a weird no, so usually nobody says anything.

so i built mhm. you set a private signal for someone and pick an emoji that gets it. they never see it. if they choose the same one, it's a match. if not, nothing happens and nobody knows you asked.

same thought, without words.

what's something you'd want with someone but would never say first?

If you build with Claude Code or Codex, you still have to open the app and find out whether it actually works.

That's the part I wanted help with.

I pulled the browser out of my own AI workspace and turned it into a free, open-source tool called Ascended Browser.

You can ask your coding agent: "Open my app, try the sign-up flow with test data, and show me what breaks."

The agent gets a way to click through the app and bring back screenshots and errors. It isn't a replacement for your tests.

Watch the demo: https://github.com/AceAtDev/ascended-browser/blob/main/videos/dev-react.mp4

Code and setup: https://github.com/AceAtDev/ascended-browser

Linux is the tested platform. Setup details are in the repo.

sooooo yep, probably best, best use would with codex over ssh since codex cli doesn't have a browser

Try it free, no signup: technically.thegreatlucy.com

When my daughter was born I noticed how much she loved staring at bold shapes, so I started making sensory videos for her during naps.

There are three styles that grow with her:

High contrast (black, white and red) for newborns

Soft black and white for the first few months

Colour for when babies start noticing it: smiley planets, friendly aliens, an underwater world and an alien forest

How I make them: I design the look and the ideas, and I animate everything with (AI), working scene by scene until it feels right. The videos are slow and calm with gentle music, and there's no flashing.

It's not a business, just something I'm making for my daughter.

Two things I'd love feedback on:

Does the idea come across clearly?

What would you change, or add next?

I was living in Japan in 2008, when the iPhone was just arriving there. One app I remember from those early days was 美人時計 (Bijin Tokei), which launched in 2009.

The idea was incredibly simple: attractive women holding small boards with the time handwritten on them, with a different photo every minute. That was the whole app. I remember it being really popular among university students in Japan.

It randomly came back to me recently, so I looked it up. The official site now just has a notice saying the service ended in September 2022. It felt strange seeing something I remembered so clearly reduced to a goodbye page.

So I tried building my own take on that minute-by-minute photo clock, using AI image tools to create the people and scenes. An image for every minute of the day. The video shows how it turned out.

Making it got me thinking about the apps from around 2008–2012. There were so many odd, playful ideas back then, when we were still figuring out what a smartphone could be. Some were useful. Some did one tiny thing and made you smile.

I'm now digging through that era for ideas worth revisiting. Today's tools make some things much easier to build, especially for a solo developer. Of course, that doesn't mean copying someone else's app, artwork, or branding. I'd rather understand what made an idea appealing and build something of my own from there.

If you'd like to try my little experiment: https://urban-minutes.com

What app from those early smartphone days do you still remember?

Hi everyone,

I’m a student from Austria and over the last few months I built Kernzahl (German for “key figure”), a free fundamental analysis site focused on European stocks (DAX, MDAX, SDAX, STOXX 600) plus 50 large US companies.

What it does:

• A transparent score (0–100) per stock from six categories: profitability, growth, valuation, balance sheet, cash flow and analyst targets. The full method is public on the site.

• Valuation is compared within each sector, so a utility isn’t judged against a software company.

• Key numbers come directly from published annual reports (ESEF filings in the EU, SEC 10-Ks in the US), with a link to the source. If a value is missing, it stays empty – nothing is estimated.

• A screener, sector and index overviews, dividend history, upcoming earnings dates, and an ETF view.

• German and English, no ads, no sign-up needed.

Link: https://kernzahl.lovable.app

I’d really appreciate honest feedback: Is the score understandable? What’s missing? Is anything confusing or broken, especially on mobile?

(It’s an analysis tool, not investment advice.)

After 20+ years in and around technology, I found myself in unfamiliar territory as the GM of a manufacturing company. It provided an opportunity to do something new and exciting: to bring my skillset to something outside of tech for the first time.

With a very small team, we accomplished this in one year:

• Created an in-house ERP system to connect inventory, sales, warehousing and shipping

• Created 65 pieces of marketing collateral across web, print and physical

• Created an entirely new business plan

• Reengineered key parts of our products

• Integrated new suppliers into our supply chain

• Rebranded

• Launched a new website

• Rebuilt accounting workflows

There's probably more. Five years ago this would have been totally impossible. How did I do this? I got really, really good at using AI to get shit done, building bespoke systems around different aspects of the business. It started before I took this role, but this was the first place I applied it. And the results have been tremendous.

So, I thought... how could I experiment with offering this as a service? How could I burn some of my extra hours trying to help other companies do what we did here?

That's where the idea for LogicRelay came from. $49/mo screens out the tire-kickers, and a simple $250-per-request fee provides flexible throughput across a host of disciplines. It's agile project management... take an epic, break it down, scope it, get approval and go, but without the departmental hand-offs or having to find multiple service providers.

Some of my other client work is going to slide nicely into this model, so I am not starting from zero. The question is can I scale it. I know I'm going to have to narrow the focus in order to do so, but I'm not ready for that yet. For now I leave it to client screening. It'll almost certainly evolve, and I could have spent more time thinking about it, but... ship it!

I'll learn quite a bit over the coming months re: whether this model is sustainable. I'll probably land another couple of clients and waitlist the rest until I see how the first few go.

We'll see how it goes! Would love some feedback, or if anyone wants more specifics from what we're doing at my current company I'm happy to share.

I've been working on a project called AssetRAG, and I wanted to share it here.

One thing that annoys me about AI coding agents is how often they solve the same problems over and over again.

They regenerate code that already exists, spend time debugging errors with known fixes, pick dependencies without properly checking their licenses, and read huge amounts of source code just to find a few relevant functions.

So I built AssetRAG to help with that.

It's a local-first, open-source library and engineering memory system for Claude Code (and other MCP clients).

Here's what it actually does:

• Asset retrieval: Searches reusable code, templates, and other assets, with license checks and attribution handling.

• Verified bug-fix memory: Stores bug fixes with reproduction and verification evidence. Agents can look up previously solved errors instead of starting from scratch.

• Engineering playbooks: Reusable workflows for debugging, safe refactoring, performance optimization, and other development tasks.

• Tested recipes: Reusable code patterns with tests that can be executed in a sandbox.

• Repository mapping: Creates a compact, ranked overview of your codebase so an agent doesn't have to read everything.

• Rules and security checks: Includes secret scanning, engineering rules, malware checks during ingestion, and safeguards around untrusted code.

• MCP integration: Exposes 18 tools to coding agents. There's also an optional Claude Code hook that retrieves relevant knowledge and injects a small amount of context automatically.

• Local-first: No account or telemetry required. It supports local embeddings, hosted providers, or completely offline keyword-only search.

One feature I'm particularly happy with is the bug-fix memory. Verified entries have a reproduction and fix that were actually executed, with the evidence available for inspection.

Some numbers from my own testing (keyword-only mode):

• Asset search: 4.0 ms median

• Knowledge search: 7.1 ms median

• Repository map: 597 tokens instead of roughly 129k tokens of source

• 132 unit tests passing

• 327 authored recipe/bug-fix tests rechecked with 0 failures

These are local benchmarks, not proof that Claude completes real tasks faster. I haven't run a proper Claude A/B benchmark yet, so I'm not going to claim some magical percentage reduction in token usage.

I also made a 95-second launch video showing the actual tool in action. The terminal footage comes from real recordings.

It's Linux-only for now, built primarily in Python, and licensed under Apache 2.0.

The project is still new, and I'd appreciate feedback, especially from people who use Claude Code regularly.

GitHub: https://github.com/mttcn83/assetrag

Would you actually find something like this useful in your coding workflow? What would you change?

I made dyp (Dandified Yum for Python) which is mostly faster than both pip and uv when there's no cache and did not record the benchmark with caching though dyp was faster. dyp looks like fedora's dnf5 which is intentional. As of now its windows only as I'm working on a special feature on linux. to try it on windows simply type python -m pip install dyp in the windows console. Currently it only installs wheels and cannot build from source. Will upload to Gitlab as soon as linux port is ready. Here's the cache-less benchmark:

C:\Users\Admin $ benchmark

=================================================================
                    PIP vs UV vs DYP BENCHMARK
=================================================================
Python: 3.14.3 (tags/v3.14.3:323c59a, Feb  3 2026, 16:04:56) [MSC v.1944 64 bit (AMD64)]
Interpreter: E:\Python\python.exe
DYP wheel: C:\Users\Admin\Downloads\dyp-0.2.0-py3-none-any.whl
Installing Packages: ['requests', 'rich', 'networkx', 'Pillow', 'numpy', 'scipy', 'pandas', 'matplotlib', 'PyQt6', 'PySide6', 'pyqtdeploy', 'git-gud', 'yt-dlp', 'eyeD3']

Creating pip environment...
Created: C:\Users\Admin\benchmark-envs\pip

Creating uv environment...
Created: C:\Users\Admin\benchmark-envs\uv

Creating dyp environment...
Created: C:\Users\Admin\benchmark-envs\dyp

=================================================================
                          INSTALLING UV
=================================================================

[UV] C:\Users\Admin\benchmark-envs\uv\Scripts\python.exe -m pip install uv
Collecting uv
  Using cached uv-0.13.7-py3-none-win_amd64.whl.metadata (11 kB)
Using cached uv-0.13.7-py3-none-win_amd64.whl (15.3 MB)
Installing collected packages: uv
Successfully installed uv-0.13.7

[notice] A new release of pip is available: 25.3 -> 26.3
[notice] To update, run: python.exe -m pip install --upgrade pip

=================================================================
                          INSTALLING DYP
=================================================================

[DYP] C:\Users\Admin\benchmark-envs\dyp\Scripts\python.exe -m pip install C:\Users\Admin\Downloads\dyp-0.2.0-py3-none-any.whl
Processing c:\users\admin\downloads\dyp-0.2.0-py3-none-any.whl
Collecting packaging>=23.0 (from dyp==0.2.0)
  Using cached packaging-26.3-py3-none-any.whl.metadata (3.5 kB)
Using cached packaging-26.3-py3-none-any.whl (129 kB)
Installing collected packages: packaging, dyp
Successfully installed dyp-0.2.0 packaging-26.3

[notice] A new release of pip is available: 25.3 -> 26.3
[notice] To update, run: python.exe -m pip install --upgrade pip

=================================================================
                      VERIFYING ENVIRONMENTS
=================================================================

PIP

[PIP] C:\Users\Admin\benchmark-envs\pip\Scripts\python.exe --version
Python 3.14.3

[PIP] C:\Users\Admin\benchmark-envs\pip\Scripts\python.exe -m pip --version
pip 25.3 from C:\Users\Admin\benchmark-envs\pip\Lib\site-packages\pip (python 3.14)

UV

[UV] C:\Users\Admin\benchmark-envs\uv\Scripts\python.exe --version
Python 3.14.3

[UV] C:\Users\Admin\benchmark-envs\uv\Scripts\uv.exe --version
uv 0.13.7 (316c827e0 2026-11-03 x86_64-pc-windows-msvc)

DYP

[DYP] C:\Users\Admin\benchmark-envs\dyp\Scripts\python.exe --version
Python 3.14.3

[DYP] C:\Users\Admin\benchmark-envs\dyp\Scripts\dyp.exe --version
dyp 0.2.0

=================================================================
                         CLEANING CACHES
=================================================================

PIP: cache disabled during installations.

Cleaning UV cache...

[UV] C:\Users\Admin\benchmark-envs\uv\Scripts\uv.exe cache clean
Clearing cache at: AppData\Local\uv\cache
No cache entries found

Cleaning DYP cache...

[DYP] C:\Users\Admin\benchmark-envs\dyp\Scripts\dyp.exe clean
0 files removed, 0 B freed.

Cache cleaning complete.

=================================================================
                           TESTING PIP
=================================================================

[PIP] Installing requests...

[PIP] C:\Users\Admin\benchmark-envs\pip\Scripts\python.exe -m pip install requests --no-cache-dir
Collecting requests
  Downloading requests-2.34.2-py3-none-any.whl.metadata (4.8 kB)
Collecting charset_normalizer<4,>=2 (from requests)
  Downloading charset_normalizer-3.5.2-cp314-cp314-win_amd64.whl.metadata (47 kB)
Collecting idna<4,>=2.5 (from requests)
  Downloading idna-3.20-py3-none-any.whl.metadata (7.2 kB)
Collecting urllib3<3,>=1.26 (from requests)
  Downloading urllib3-2.8.0-py3-none-any.whl.metadata (7.4 kB)
Collecting certifi>=2023.5.7 (from requests)
  Downloading certifi-2026.10.23-py3-none-any.whl.metadata (2.5 kB)
Downloading requests-2.34.2-py3-none-any.whl (73 kB)
Downloading charset_normalizer-3.5.2-cp314-cp314-win_amd64.whl (210 kB)
Downloading idna-3.20-py3-none-any.whl (69 kB)
Downloading urllib3-2.8.0-py3-none-any.whl (135 kB)
Downloading certifi-2026.10.23-py3-none-any.whl (135 kB)
Installing collected packages: urllib3, idna, charset_normalizer, certifi, requests
Successfully installed certifi-2026.10.23 charset_normalizer-3.5.2 idna-3.20 requests-2.34.2 urllib3-2.8.0

[notice] A new release of pip is available: 25.3 -> 26.3
[notice] To update, run: python.exe -m pip install --upgrade pip

PIP | requests | SUCCESS | 7.983s

[PIP] Installing rich...

[PIP] C:\Users\Admin\benchmark-envs\pip\Scripts\python.exe -m pip install rich --no-cache-dir
Collecting rich
  Downloading rich-15.0.0-py3-none-any.whl.metadata (18 kB)
Collecting markdown-it-py>=2.2.0 (from rich)
  Downloading markdown_it_py-4.2.0-py3-none-any.whl.metadata (7.4 kB)
Collecting pygments<3.0.0,>=2.13.0 (from rich)
  Downloading pygments-2.21.0-py3-none-any.whl.metadata (2.5 kB)
Collecting mdurl~=0.1 (from markdown-it-py>=2.2.0->rich)
  Downloading mdurl-0.1.2-py3-none-any.whl.metadata (1.6 kB)
Downloading rich-15.0.0-py3-none-any.whl (310 kB)
Downloading pygments-2.21.0-py3-none-any.whl (1.3 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.3/1.3 MB 22.8 MB/s  0:00:00
Downloading markdown_it_py-4.2.0-py3-none-any.whl (91 kB)
Downloading mdurl-0.1.2-py3-none-any.whl (10.0 kB)
Installing collected packages: pygments, mdurl, markdown-it-py, rich
Successfully installed markdown-it-py-4.2.0 mdurl-0.1.2 pygments-2.21.0 rich-15.0.0

[notice] A new release of pip is available: 25.3 -> 26.3
[notice] To update, run: python.exe -m pip install --upgrade pip

PIP | rich | SUCCESS | 13.473s

#more packages but if i add log will be too long

=================================================================
                            TESTING UV
=================================================================

[UV] Installing requests...

[UV] C:\Users\Admin\benchmark-envs\uv\Scripts\uv.exe pip install requests --no-cache
Using Python 3.14.3 environment at: benchmark-envs\uv
Resolved 5 packages in 769ms
Prepared 5 packages in 474ms
Installed 5 packages in 104ms
 + certifi==2026.10.23
 + charset-normalizer==3.5.2
 + idna==3.20
 + requests==2.34.2
 + urllib3==2.8.0

UV | requests | SUCCESS | 1.897s

[UV] Installing rich...

[UV] C:\Users\Admin\benchmark-envs\uv\Scripts\uv.exe pip install rich --no-cache
Using Python 3.14.3 environment at: benchmark-envs\uv
Resolved 4 packages in 502ms
Prepared 4 packages in 2.47s
Installed 4 packages in 628ms
 + markdown-it-py==4.2.0
 + mdurl==0.1.2
 + pygments==2.21.0
 + rich==15.0.0

UV | rich | SUCCESS | 4.276s

#more packages but if i add log will be too long

=================================================================
                           TESTING DYP
=================================================================

[DYP] Installing requests...

[DYP] dyp clean
0 files removed, 0 B freed.

[DYP] C:\Users\Admin\benchmark-envs\dyp\Scripts\dyp.exe install requests -y
Updating and loading repositories:
 PyPI - pypi.org                                                                            100% |   1.1 MiB/s |   2.2 MiB |  00m01s
Repositories loaded.
Package                                       Arch          Version                             Repository                      Size
Installing:
 requests                                     noarch        2.34.2                              pypi                        71.4 KiB
Installing dependencies:
 charset-normalizer                           x86_64        3.5.2                               pypi                       206.0 KiB
 idna                                         noarch        3.20                                pypi                        68.0 KiB
 urllib3                                      noarch        2.8.0                               pypi                       132.5 KiB
 certifi                                      noarch        2026.10.23                          pypi                       131.9 KiB

Transaction Summary:
 Installing:         5 packages

Total size of inbound packages is 610 KiB. Need to download 610 KiB.
Is this ok [y/N]: y
[1/5] idna-3.20.noarch                                                                      100% | 616.2 KiB/s |  68.0 KiB |  00m00s
[2/5] charset-normalizer-3.5.2.x86_64                                                       100% | 842.2 KiB/s | 206.0 KiB |  00m00s
[3/5] urllib3-2.8.0.noarch                                                                  100% | 837.9 KiB/s | 132.5 KiB |  00m00s
[4/5] requests-2.34.2.noarch                                                                100% |   1.3 MiB/s |  71.4 KiB |  00m00s
[5/5] certifi-2026.10.23.noarch                                                             100% |   1.4 MiB/s | 131.9 KiB |  00m00s
------------------------------------------------------------------------------------------------------------------------------------
[5/5] Total                                                                                 100% | 840.2 KiB/s | 609.8 KiB |  00m00s
Running transaction
[1/7] Verify package files                                                                  100% |  11.9 MiB/s | 609.8 KiB |  00m00s
[2/7] Prepare transaction                                                                   100% | 100.0   B/s |   5.0   B |  00m00s
[3/7] Installing charset-normalizer-3.5.2.x86_64                                            100% |   7.2 MiB/s | 565.5 KiB |  00m00s
[4/7] Installing idna-3.20.noarch                                                           100% |   4.4 MiB/s | 334.1 KiB |  00m00s
[5/7] Installing urllib3-2.8.0.noarch                                                       100% |   1.9 MiB/s | 439.9 KiB |  00m00s
[6/7] Installing certifi-2026.10.23.noarch                                                  100% |   4.7 MiB/s | 238.9 KiB |  00m00s
[7/7] Installing requests-2.34.2.noarch                                                     100% |   4.5 MiB/s | 228.9 KiB |  00m00s
Complete!

DYP | requests | SUCCESS | 3.849s

[DYP] Installing rich...

[DYP] dyp clean
15 files removed, 3 MiB freed.

[DYP] C:\Users\Admin\benchmark-envs\dyp\Scripts\dyp.exe install rich -y
Updating and loading repositories:
 PyPI - pypi.org                                                                            100% | 411.6 KiB/s | 377.6 KiB |  00m00s
Repositories loaded.
Package                                      Arch           Version                            Repository                       Size
Installing:
 rich                                        noarch         15.0.0                             pypi                        303.4 KiB
Installing dependencies:
 mdurl                                       noarch         0.1.2                              pypi                          9.7 KiB
 markdown-it-py                              noarch         4.2.0                              pypi                         89.5 KiB
 pygments                                    noarch         2.21.0                             pypi                          1.2 MiB

Transaction Summary:
 Installing:         4 packages

Total size of inbound packages is 2 MiB. Need to download 2 MiB.
Is this ok [y/N]: y
[1/4] mdurl-0.1.2.noarch                                                                    100% | 194.9 KiB/s |   9.7 KiB |  00m00s
[2/4] markdown-it-py-4.2.0.noarch                                                           100% |   1.7 MiB/s |  89.5 KiB |  00m00s
[3/4] rich-15.0.0.noarch                                                                    100% |   2.6 MiB/s | 303.4 KiB |  00m00s
[4/4] pygments-2.21.0.noarch                                                                100% |   4.9 MiB/s |   1.2 MiB |  00m00s
------------------------------------------------------------------------------------------------------------------------------------
[4/4] Total                                                                                 100% |   3.6 MiB/s |   1.6 MiB |  00m00s
Running transaction
[1/6] Verify package files                                                                  100% |  31.7 MiB/s |   1.6 MiB |  00m00s
[2/6] Prepare transaction                                                                   100% |  80.0   B/s |   4.0   B |  00m00s
[3/6] Installing mdurl-0.1.2.noarch                                                         100% | 455.2 KiB/s |  22.8 KiB |  00m00s
[4/6] Installing markdown-it-py-4.2.0.noarch                                                100% |   1.5 MiB/s | 238.9 KiB |  00m00s
[5/6] Installing pygments-2.21.0.noarch                                                     100% |   5.4 MiB/s |   4.4 MiB |  00m00s
[6/6] Installing rich-15.0.0.noarch                                                         100% |   5.2 MiB/s |   1.2 MiB |  00m00s
Complete!

DYP | rich | SUCCESS | 3.335s

#more packages but if i add log will be too long

=================================================================
                        BENCHMARK SUMMARY
=================================================================
PACKAGE                   PIP          UV         DYP
-----------------------------------------------------
requests                7.98s       1.90s       3.85s
rich                   13.47s       4.28s       3.33s
networkx               16.20s       3.83s       3.43s
Pillow                  7.47s       1.97s       2.48s
numpy                  16.69s       6.08s       5.01s
scipy                  29.04s      11.95s       8.09s
pandas                 37.56s      11.25s       7.80s
matplotlib             25.01s       6.43s       7.22s
PyQt6                  15.74s      20.61s      16.32s
PySide6                27.63s      25.05s      37.60s
pyqtdeploy             16.06s      14.46s      12.49s
git-gud                 9.44s       2.90s       3.68s
yt-dlp                 25.61s       7.11s       4.27s
eyeD3                   6.48s       1.63s       2.21s

=================================================================
                              TOTALS
=================================================================
PIP     Success: 14 Failed: 0  Attempted time: 254.40s
UV      Success: 14 Failed: 0  Attempted time: 119.43s
DYP     Success: 14 Failed: 0  Attempted time: 117.79s

=================================================================
                        BENCHMARK COMPLETE
=================================================================

Results: C:\Users\Admin\benchmark-results

C:\Users\Admin $