Atención al Cliente de Juno

APP FEATURES

- Navigate and manage files and folders, quickly preview documents and media
- Browse and view Jupyter notebooks with quick and beautifully rendered previews
- Run code in Jupyter notebooks and Python sources locally on your device with a built-in Python 3.10 interpreter, entirely offline
- Write and execute Python code in a full-fledged development environment, featuring snappy, intelligent code completion and a console with full terminal emulator support
- Navigate through code sources, scripts, JSON, XML, and other text-based formats with rich previews and syntax highlighting
- Add quick access bookmarks for file system locations outside the app's sandbox, or simply open documents in place
- Access all Jupyter features in a modern, powerful and customizable notebook editor
- Leverage powerful data analysis, machine learning and developer tools: NumPy, Matplotlib, SciPy, Scikit-learn, Pandas, LXML, and more
- View and edit any file as text in a built-in versatile plain text editor with syntax highlighting
- Enjoy painless package management: easily install any pure Python package with an intuitive package manager

PYTHON SCRIPTS

Python scripts are plain-text Python source code files with a .py extension. Juno lets you work on these with snappy code completion, a console with full terminal emulator support, a built-in media viewer for code-generated images, plots, web apps, and more. Juno will execute the code using an embedded Python interpreter, locally on your iPhone or iPad and completely offline.

JUPYTER NOTEBOOKS

A Jupyter notebook is a versatile document format that enables you to store live code, markdown text, plots, images, and LaTeX equations — all within a single notebook file with a .ipynb extension. Notebooks serve as excellent Python coding playgrounds for data manipulation and experimentation, and Juno makes working with them a breeze!

Notebook documents keep a record of all inputs and outputs from an interactive programming session, and the rich output generated by running Python scripts (including HTML, images, video, and plots) is embedded within the Jupyter notebook document. They are particularly convenient for coding in Python for data analysis, machine learning, or computational science in general.