# Carnets - Jupyter (with scipy)

> Jupyter notebooks, with scipy

Canonical page: [https://chrome-stats.com/d/id1559497253](https://chrome-stats.com/d/id1559497253)

## Overview

- **ID:** `id1559497253`
- **Platform:** Apple
- **Type:** Apple app
- **Status:** Available
- **Publisher:** Nicolas Holzschuch
- **Category:** Developer Tools
- **Rating:** 4.60 / 5 (90 ratings)
- **Version:** 1.9.1
- **Last updated:** 2025-11-26
- **First published:** 2021-05-03
- **Size:** 2.07 GB
- **Data as of:** 2026-09-23
- **Store listing:** [Apple App Store](https://apps.apple.com/us/app/carnets-jupyter-with-scipy/id1559497253)
- **Website:** [https://holzschu.github.io/Carnets\_Jupyter/](https://holzschu.github.io/Carnets_Jupyter/)
- **Privacy policy:** [https://github.com/holzschu/Carnets/blob/master/privacy\_policy.md](https://github.com/holzschu/Carnets/blob/master/privacy_policy.md)

## Description

Carnets lets you run Jupyter notebooks entirely on your iPad. It ships with JupyterLab as an option and includes SciPy, scikit-learn, seaborn, and coremltools for scientific computing and learning. All code runs locally with the embedded Python interpreter, so no internet connection is required.

Write code, mix in Markdown, and share notebooks with other apps. You can install additional pure-Python packages using %pip install, inspect installed packages with %pip list, and manage your environment offline. A broad collection of packages like numpy, pandas, matplotlib, astropy, geopandas, and more are available out of the box. Switch between notebook interfaces in Settings and explore data science workflows on iPad.

## Rankings

- #141,294 — Overall
- #72 — data scraping

## Review summary

Users praise Carnets as a powerful, free iPad Jupyter environment with broad package support and strong on‑the‑go utility, especially for students and remote work. Repeated drawbacks center on data safety (cloud sync/data loss), UX/workflow gaps (no easy notebook creation, unclear use), missing core ML stack (Torch/TF, conda support, SSH), and stability issues (blank screens, install hiccups). Overall, a compelling concept hampered by reliability and usability challenges.

### Pros

- Broad package support and included libraries (Python, Jupyter, SciPy/Seaborn) deliver a full data‑science stack on iPad.
- Free and highly capable Jupyter environment, valued by users who might otherwise pay for similar tooling.
- Great for on‑the‑go ML coding on iPad, especially with iPad Pro and Magic Keyboard.
- Useful for learning and coursework in data science, with many users leveraging it for online courses.
- Ease of file management and handling of notebook/workspace on iPad.

### Cons

- Cloud storage integrations (OneDrive/Dropbox/Google Drive) can wipe notebooks or fail to sync, with no reliable checkpointing.
- No straightforward way to create notebooks or a clear, cohesive UX; feels like an iframe-based wrapper rather than a complete product.
- Missing core ML stack and environment features (no Torch/TF, no conda/miniforge, limited ability to run remote SSH)
- Stability and reliability issues (blank screens on some systems, long installs, cells stopping after extended use)
- Perceived lack of branding/identity and unclear purpose within the App Store (UX/navigation issues)

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Source: [Chrome-Stats](https://chrome-stats.com/d/id1559497253)