Top 5 Python Sandboxes To Choose From in 2022

Why Do You Need A Developer Sandbox?

A developer sandbox is a safe and isolated environment for developing and testing code. Sandboxes are useful for a number of reasons, few of them are stated below:

1. Testing and Debugging: Sandboxes allow developers to test and debug their code without affecting the rest of their development system. This can be especially useful for experimenting with new libraries or trying out unfamiliar code.
2. Security: Sandboxes can help protect a developer’s system from malicious code by isolating it from the rest of their system. This can be important if they are working with untrusted sources or dealing with sensitive data.
3. Reproducibility: Sandboxes can help ensure that a developer’s code is reproducible, meaning that it will produce the same results every time it is run. This can be important for scientific research and other applications where consistency is critical.
4. Collaboration: Sandboxes can make it easier for developers to share their code with others and collaborate on projects. By running code in a sandbox, developers can avoid conflicts with other people’s code and ensure that everyone is working with the same environment.

Overall, developer sandboxes provide a useful tool for developing and testing code safely and securely. They can help developers write better code, protect their system from potential threats, and collaborate with others more easily.

There are a number of popular tools for running and testing Python code in a sandboxed environment. Jupyter and Repl.it are web-based tools that allow you to run Python code in your web browser, while PyCharm and Visual Studio Code are desktop based code editors that include support for running and debugging Python code. Google Colab is another popular tool that combines the features of a web-based coding environment with the ability to run code on Google’s cloud infrastructure.

While Best Python Hosting is essential for deploying production-grade applications on the wev, Python sandboxes play a crucial role in development, testing, learning and collaboration. Both are important components of the Python ecosystem, catering to different needs and stages of the software development lifecycle.

Let us talk about the top 5 popular Python Sandbox tools:

Jupyter

Jupyter is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is commonly used for data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more.

Jupyter is built on the foundation of the IPython kernel, which allows you to run Python code in a kernel session. This kernel session is what is referred to as a “sandbox” environment, where you can run code without affecting the rest of your system. You can also use Jupyter to run code in other languages, such as R, Julia, and JavaScript, by installing the appropriate kernel for that language.

Jupyter offers a number of useful features for working with Python, such as inline plotting, code completion and interactive debugging. It also supports rich text formatting, allowing you to include equations, images, and other media in your notebooks. Additionally, Jupyter allows you to easily share your notebooks with others, making it a popular tool for collaboration and reproducible research.

Pros:

1. Interactive environment: Jupyter allows you to run code interactively, which can be very useful for testing and debugging. You can also include text and other media in your notebooks, making it a powerful tool for data analysis and exploration.
2. Multiple languages: Jupyter supports many programming languages, including Python, R, Julia, and JavaScript. This allows you to use Jupyter for a wide range of tasks, from numerical simulation to machine learning.
3. Rich outputs: Jupyter notebooks support a wide range of outputs, including plots, tables, and other visualizations. This makes it easy to explore and analyze data in a variety of ways.
4. Sharing and collaboration: Jupyter notebooks are easy to share with others, allowing you to collaborate on projects and reproduce results. This makes Jupyter a popular tool for data science teams and researchers.

Cons:

1. Limited support for large-scale computing: While Jupyter is a powerful tool for data analysis, it is not designed for large-scale computing tasks. If you need to run long-running or resource-intensive jobs, you may be better off using a different tool.
2. Lack of security: Jupyter notebooks are executed in the user’s web browser, which can be a security risk if you are working with sensitive data. It is important to be careful when sharing notebooks and make sure you are using a secure server when running Jupyter.
3. Limited IDE features: Jupyter is not a full-featured integrated development environment (IDE), so it may not have all of the features that you would expect from a traditional code editor. This can make it less convenient to use for some tasks, such as writing long-form code or debugging complex problems.

Repl.it

Repl.it is an online code editor and development environment that allows you to write, run, and share code in a variety of languages, including Python. It is a web-based tool that runs in your web browser, so you don’t need to install any software on your local machine.

Pros:

1. Easy to use: Repl.it is very easy to use, even for people who are new to programming. You can start writing and running code within minutes, without the need to install any software or configure your environment.
2. Multiple languages: Repl.it supports a wide range of programming languages, including Python, Java, C++, and many others. This allows you to use Repl.it for a wide range of projects and tasks.
3. Collaboration: Repl.it allows you to easily share your code with others and collaborate on projects in real-time. This makes it a useful tool for team projects and code review.
4. Cloud-based: Repl.it is cloud-based, so you can access your code and projects from anywhere, on any device. This makes it a convenient option for people who need to work on the go or from multiple computers.

Cons:

1. Limited support for large-scale computing: Repl.it is not designed for large-scale computing tasks, so it may not be suitable for very resource-intensive jobs.
2. Limited IDE features: Repl.it is not a full-featured integrated development environment (IDE), so it may not have all of the features that you would expect from a traditional code editor. This can make it less convenient to use for some tasks, such as writing long-form code or debugging complex problems.
3. Security: Because Repl.it runs code in your web browser, it may not be as secure as running code on your local machine. It is important to be careful when running sensitive code on Repl.it and to use a secure server when sharing code with others.

PyCharm

PyCharm is an integrated development environment (IDE) for Python, developed by JetBrains. It is a standalone code editor that includes support for running and debugging Python code, as well as a number of other useful features for Python development, such as code completion, inline plotting, and refactoring.

Pros:

1. Full-featured IDE: PyCharm is a full-featured IDE, which means that it includes a wide range of tools and features for Python development. This can make it a convenient and powerful option for people who are serious about Python programming.
2. Multiple languages: PyCharm supports a wide range of languages, not just Python. This allows you to use PyCharm for a variety of different tasks and projects.
3. Customization: PyCharm is highly customizable, so you can tailor the interface and settings to your specific needs and preferences. This can make it a more comfortable and efficient tool to use.
4. Support: PyCharm is developed and supported by JetBrains, a well-known and reputable company in the world of software development. This means that you can expect a high level of quality and support for PyCharm.

Cons:

1. Cost: PyCharm is not free, so you will need to purchase a license in order to use it. This can be a significant expense for individuals or small teams.
2. Complexity: PyCharm is a powerful and feature-rich IDE, which can make it overwhelming for people who are new to Python or programming in general. It may take some time to learn how to use all of its features and get the most out of the tool.
3. Memory usage: PyCharm can be a memory-intensive application, so it may not be suitable for people with low-powered machines or limited memory. This can make it less convenient to use on older computers or laptops with limited resources.

Overall, PyCharm is a powerful and feature-rich IDE for Python development. It can be a valuable tool for people who are serious about Python programming, but it may be too complex or expensive for some users.

Visual Studio Code

Visual Studio Code (VSC) is a code editor developed by Microsoft. It is a standalone application that includes support for a wide range of languages, including Python. VSC includes many useful features for Python development, such as code completion, inline plotting, and debugging, as well as support for popular Python libraries and frameworks.

Pros:

1. Multiple languages: VSC supports a wide range of languages, not just Python. This allows you to use VSC for a variety of different tasks and projects.
2. Customization: VSC is highly customizable, so you can tailor the interface and settings to your specific needs and preferences. This can make it a more comfortable and efficient tool to use.
3. Extensibility: VSC has a robust extension ecosystem, which means that you can add new features and functionality to the code editor by installing extensions. This can make VSC a more versatile and powerful tool.
4. Cost: VSC is free to download and use, which makes it a more affordable option than some other code editors.

Cons:

1. Memory usage: VSC can be a memory-intensive application, so it may not be suitable for people with low-powered machines or limited memory. This can make it less convenient to use on older computers or laptops with limited resources.
2. Limited support for large-scale computing: VSC is not designed for large-scale computing tasks, so it may not be suitable for very resource-intensive jobs.
3. Limited IDE features: VSC is not a full-featured integrated development environment (IDE), so it may not have all of the features that you would expect from a traditional IDE. This can make it less convenient to use for some tasks, such as writing long-form code or debugging complex problems.

Overall, VSC is a powerful and versatile code editor for Python development. It is free to use and highly customizable, making it a good option for people who are looking for an affordable and flexible tool for Python programming.

Python Sandbox

Python Sandbox is a platform built to help Python developers share their knowledge in a manner that is more accessible to end users. Whether you’re a back-end web developers dabbling with Django/ Flask all day long, or a Data Scientist working on state-of-the-art models using PyTorch and Tensorflow, or a Data Engineer crunching vast amounts of data using Spark, Python Sandbox is the right platform for you.

The platform helps you create, test, publish, and embed Python code. Python Sandbox enables developers to write better library documentation, and publish tutorials and lists of solutions to common issues without having to establish a development environment.

With PythonSandbox, you can seamlessly:

👉 Access the underlying libraries and tools that a project uses so that you can see how they work and build on top of them.

👉 Teach, learn and take your Python skills to the next level to demonstrate your projects without setting up a local environment.

👉 Get Better at writing documentation, blogs, and StackOverflow answers to stand out and help the community achieve its development dream.