Code Editor vs Juno – Python and Jupyter Usage & Stats

Introducing the Visual Code Editor for iOS, the ultimate solution for coding on-the-go. This powerful app is designed to provide you with a seamless coding experience that is both efficient and convenient. The Visual Code Editor features a sleek and intuitive user interface that allows you to easily create, edit and manage your code. The app provides support for multiple programming languages, including Python, Java, JavaScript, HTML, CSS, and many more, so you can work on projects across a wide range of coding languages. With the app's advanced suggestion and highlighting features, coding becomes even easier. The app's intelligent code completion system provides suggestions for code snippets as you type, while its syntax highlighting feature highlights syntax errors and other important code elements, making it easy to spot issues and correct them quickly. The Visual Code Editor also offers a wide range of customization options, allowing you to choose your preferred color scheme and font size, making it easier to work on your code for extended periods of time. With the ability to work with multiple files simultaneously, the Visual Code Editor is perfect for working on complex projects that involve multiple files and directories. You can easily switch between files, preview your code, and share your work with others, all from within the app. Overall, the Visual Code Editor is an essential tool for any developer looking to code on-the-go. With its advanced features, multiple language support, and intuitive interface, coding has never been easier or more convenient. Try it out today and take your coding experience to the next level!

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Juno – Python and Jupyter

Zero-setup Python environment and developer toolbox in a first-class citizen app for iPad and iPhone. Juno is designed to cover all your Python coding needs, and will work seamlessly with all source code formats. Juno supports both Python scripts (.py) and Jupyter notebooks (.ipynb) — a document format focused on applying Python to data analysis and computational science. FREE FEATURES - Navigate and manage files and folders, quickly preview documents and media - Browse and view Jupyter notebooks with quick and beautifully rendered previews - 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 PRO FEATURES - 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 - 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.