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Free, open source disk cleaner and storage analyzer for developers — macOS and Windows

Jharu finds and safely removes the gigabytes that development tools leave behind: machine learning model caches, package manager caches, Docker data, leftovers from uninstalled apps, and forgotten junk files — all from one professional dashboard.

Download

macOS installer is universal (Apple Silicon and Intel). Windows installer is 64-bit.

Current version: v0.2.0 · All releases and release notes

What is Jharu?

Jharu is a desktop disk cleanup app built specifically for software developers and machine learning engineers. Generic disk space analyzers show you folder sizes; Jharu understands what the data actually is. It ships a knowledge base of known cache and data locations, classifies everything it finds, explains each item in plain language, rates how safe it is to delete, and moves removed data to the Trash or Recycle Bin — never a permanent delete.

Typical problems Jharu solves:

Disk full after downloading machine learning models with Hugging Face, Ollama, PyTorch, or Whisper

Gigabytes hidden in npm, pip, uv, yarn, pnpm, conda, Cargo, Go, Gradle, Maven, and NuGet caches

Leftover settings, caches, and support files from apps you uninstalled long ago

Old installers, phone backups, logs, and large files you have not touched in months

Not knowing what is actually using your disk space

Watch the demo

See a scan, a plain-English breakdown, and a click to clean — with the real numbers from a real machine.

▶ Watch on YouTube — reclaiming gigabytes in under a minute

Screenshots

Dev clean — every known cache location, sized and rated

ML models — 21.1 GB of the 21.7 GB here was downloaded and never loaded once

Deep clean — folders sized by what they hold, and an honest notice about what could not be read

Features

ML models — keep what you use, remove what you never loaded. Every downloaded model listed individually, across Hugging Face, Ollama, Whisper, PyTorch and Keras. Jharu distinguishes models you have actually loaded from models that were downloaded once and never opened since, so you can reclaim the second kind without touching the first. Ollama layers shared between models are kept, so removing one model never breaks another. No other cleaner makes this distinction.

Dev clean. Scans 25+ known developer and machine learning cache locations — Hugging Face, Ollama, PyTorch, Whisper, LM Studio, conda, pip, uv, npm, yarn, pnpm, Cargo, Go modules, Gradle, Maven, NuGet, Homebrew, Xcode DerivedData, Docker, JetBrains, Playwright, Puppeteer — with per-item safety ratings and staleness detection.

Python environments. Finds every virtualenv and conda environment, sizes the packages inside them, and shows what duplication costs across environments — the "torch is installed eleven times" problem, quantified.

Deep clean. Full-disk analysis as a treemap or a list. Folders are sized by what they hold and classified as system, applications, your files, app data or developer data. Click a block to go inside it. System locations are protected and can never be cleaned from the app.

Junk files. Non-cache junk: installers and archives in Downloads, old device backups, logs and crash reports, mail attachment copies, large files untouched for six months, and on Windows the temp folders, Windows Update cache, Delivery Optimization files and crash dumps.

Desktop. Screenshots and clutter on your desktop, filterable by type and age. Because these are your own files, archiving them to a folder is the default action rather than deleting.

Browsers. Detects Chrome, Edge, Brave, Arc, Firefox and Safari, and itemizes their caches per profile, separating safe-to-clear cache from data that deserves review.

Uninstaller. Lists installed applications with both their own size and the data they have accumulated across the system. On Windows it reads the registry and runs each program's own uninstaller; on macOS it removes the bundle. Either way it then sweeps the leftovers, with high-confidence matches preselected.

Drive health. Capacity and SMART status per drive, plus a fill forecast built from a daily capacity reading that projects when a drive will run out of space. Wear level, temperature and power-on hours are shown when smartctl is available.

In-app updates. Jharu checks GitHub releases for new versions and downloads and installs them from inside the app — signed, verified, and with a one-click restart.

How Jharu compares

Generic cleaners are built to look busy and sell a subscription. Jharu does one thing deeply: the developer and AI data no general-purpose cleaner understands.

Jharu CleanMyMac CCleaner

Price Free forever $40+/yr Freemium

Open source Yes · Apache 2.0 No No

Understands ML model caches Yes No No

Used vs never-loaded detection Yes No No

Telemetry / tracking None Yes Yes

macOS and Windows Both macOS only Both

Registry "cleaner" Never (it does not work) — Yes

What can Jharu clean?

Category Examples

ML model caches Hugging Face hub (~/.cache/huggingface), Ollama models (~/.ollama/models), PyTorch hub, Whisper, Keras, LM Studio

Python pip cache, uv cache, conda package cache, stale conda environments

JavaScript npm cache (~/.npm/_cacache), yarn cache, pnpm store, Puppeteer and Playwright browser downloads

Build tools Xcode DerivedData and archives, Gradle caches, Maven repository, Cargo registry, Go module cache, NuGet packages

Containers Docker VM data and image storage

IDEs JetBrains caches, editor cache directories

App leftovers Support files, caches, preferences, and logs from uninstalled applications

Junk Installers in Downloads, old device backups, crash reports, mail attachment copies, large stale files

Safety model

Nothing is ever permanently deleted. Every clean action moves data to the Trash or Recycle Bin, where it can be restored.

Every finding carries a safety rating: safe to clear, re-downloadable, or review first.

Operating system locations are protected and excluded from cleaning entirely.

Every clean is confirmed by a dialog that states the actual consequence — a cache rebuilds itself, a model is re-downloaded, an environment must be recreated, your own files are gone for good.

A location Jharu cannot read is reported, never hidden. A folder needing elevated rights measures 0 B, which looks exactly like an empty one; Jharu flags these as partly unreadable instead of quietly leaving them out. A cleaner that hides what it cannot see is worse than one that admits it.

No registry cleaner, and Windows prefetch is listed but never cleaned. Both are widely marketed and neither does anything useful; prefetch is how Windows starts your apps quickly, and clearing it makes the next launches slower.

Installation

Prebuilt installers for macOS (Apple Silicon and Intel) and Windows are published on the releases page. Once installed, Jharu updates itself in-app.

Build from source

Prerequisites: Rust (stable) and Node.js 20+.

git clone https://github.com/riponcm/Jharu.git cd Jharu npm install npm run tauri dev # run in development npm run tauri build # produce installers for your platform

On macOS, grant Full Disk Access (System Settings, Privacy and Security) for complete scan coverage. Jharu detects missing access and offers to open the right settings pane.

Opening Jharu the first time

Jharu is not yet signed with a paid developer certificate (see Support Jharu below), so your operating system shows a one-time warning the first time you open it. This is expected for open source apps and does not mean anything is wrong — the download is verified by a cryptographic signature on every in-app update.

macOS: if you see "Jharu cannot be opened because Apple cannot verify it", right-click (or Control-click) the app and choose Open, then confirm. You only do this once.

Windows: if SmartScreen shows "Windows protected your PC", click More info, then Run anyway.

Frequently asked questions

How do I clear the Hugging Face model cache? Open Jharu's Dev clean tab. It lists your Hugging Face hub cache (~/.cache/huggingface) with its exact size and lets you explore it or move it to the Trash. Models are re-downloaded automatically the next time a library requests them.

Is it safe to delete npm, pip, or other package manager caches? Yes. These caches only speed up reinstalls and are rebuilt automatically on the next install. Jharu marks them "Safe to clear". Deleting an active project's node_modules or a conda environment you still use is different — Jharu rates those "Review first".

Does Jharu permanently delete my files? No. Every clean action moves data to the macOS Trash or Windows Recycle Bin, where it can be restored. Jharu never bypasses the Trash.

Is Jharu a free alternative to CleanMyMac or CCleaner? Yes. Jharu is free and open source under the Apache 2.0 license, with no subscription, telemetry, or upsell. Its focus is narrower and deeper: developer and machine learning data that general-purpose cleaners do not understand.

How do I find out what is taking up disk space on my Mac or Windows PC? Jharu's Deep clean tab analyzes the whole disk and shows every folder's real size, classified by what it is — system files, applications, your documents, app data, or developer data — so you can tell junk from data that matters.

How do I completely uninstall an app, including leftover files? Jharu's Uninstaller lists every installed app together with the data it has accumulated. Uninstalling removes the app and its leftover support files, caches, and preferences in one step.

Architecture

Layer Technology

Scanner Rust with parallel directory walking (jwalk)

Safety OS trash integration (trash), never permanent deletion

Rules Per-platform knowledge base of cache and data locations

UI React and TypeScript, Tauri 2 WebView

Updates tauri-plugin-updater with signed GitHub release artifacts

Drive info sysinfo, with SMART via diskutil and optional smartctl

Windows winreg for the uninstall keys; per-platform paths throughout

Trend A daily capacity reading stored locally, fitted by least squares

Roadmap

Orphaned-data detection by comparing leftover folders against installed applications

Duplicate file detection

Detailed drive health on Windows, which currently reports capacity only

Localized UI, starting with Bengali and Hindi

Shipped in 0.2.0: per-model ML intelligence, Python environment analysis, the desktop cleaner, Windows uninstaller and junk rules, the deep clean treemap and the fill forecast. See the changelog.

Support Jharu

Jharu is free, open source, and has no ads, telemetry, or paid tier — and it always will. But shipping a desktop app that users can install without scary security warnings costs real money every year, and that is the one thing an individual developer cannot absorb alone:

What it unlocks Cost

Apple notarization — removes the "Apple cannot verify this app" warning on every Mac 99 USD / year (Apple Developer Program)

Windows code signing — removes the "Windows protected your PC" SmartScreen warning ~100–400 USD / year (code

[truncated for AI cost control]