Top 10 VS Code Extensions For Data Science

Visual Studio Code is a popular integrated development environment. It provides plugin support, is able to run the code, has functionalities and is also used to debug the code. It is very famous among developers and among data scientists.

Visual Studio Code (VS Code) is an IDE which is a streamlined code editor used for building, task running and debugging the cloud and website applications. Therefore, in this article, we will discuss the Top 10 VS Code Extensions for Data Science which are used by the developers for adding different languages, tools and debugging facilities.

Top 10 VS Code Extensions for Data Science

Some of the Top 10 VS code extensions for data science are mentioned below:

1. Github copilot
2. Pylance
3. Python
4. Python Indent
5. R
6. Indent-rainbow
7. Julia
8. Jupyter
9. DVC
10. GitLens

1. Github Copilot

Github copilot is a cloud-based AI pair programmer which helps to assist VS Code users. It was developed by OpenAI and GitHub. It helps the users by offering autocomplete suggestions as we code. Github Copilot is a free AI tool for verified teachers, programmers and open-source maintainers.

Key Features:

• The key feature is it is used to analyse the context of the file while users are editing.
• They also offer suggestions from the text editor.
• It is trained on multiple languages which appear on the public repositories.

Advantages:

• It accelerates unit testing and also is robust with multiple synthetic data.
• For remote work they consist of good pair programmers.

Disadvantages:

• For new programmers it can lead to bad programming habits.

Pricing: It is free for the verified students, teachers and the open source maintainers. But for others the pricing starts from $10/month.

2. Pylance

Pylance is another extension of Vs code which is a python language server used in data science. As it is a python language server it means it offers some features such as syntax highlighting, package import resolution and so on.

Key Features:

• It supports recursive type aliases.
• It has a feature of auto-imports which add and remove import code actions.
• It has multi-root workspace and type checking support.

Advantages:

• It offers enhancements to IntelliSense and syntax highlighting.
• It consists of package import resolution and also used to write code faster and accurately.
• It configures and utilises both the remote and local debugging.

Disadvantage:

• Some bugs need to be resolved and also needs to improve the performance of Pylance extension.

Pricing: However, it is a closed source but it is free to use.

3. Python

Python extension is used for debugging, code formatting and code navigation, unit tests and refactoring purposes.

Key Features:

• It supports testing with the unit test, nose test and pytest.
• Syntax checking, auto-completion and auto activation are the features present in this extension.
• It analyses code for the potential errors.

Advantages:

• It can switch between different environments.
• It supports Jupyter Notebooks.
• It is used for code formatting.

Disadvantage:

• The only disadvantage it has is that it requires more configuration.

Pricing: It is a completely free extension.

4. Python Indent

The Python Indent extension is used by the python developers to add closing brackets automatically when they press the Tab key. It is also used to maintain proper python indentation in the Vs code.

Key Features:

• The python developers use this extension to streamline their coding process.
• This python extension automates the indentation in python code.
• It always ensures that all the dedents and the indents conform to the python style guide (PEP8).

Advantages:

• This extension is accurate in correcting and detecting the indentation errors.
• It also adjusts the level of indentation according to the previous line syntax.
• It is also a customizable extension which allows the users to adjust the setting to their linkings.

Disadvantages:

• The main disadvantage of Python Indent is the mixing spaces for indentation can cause syntax errors. Thus it makes code debugging tough.

Pricing: It is a freeware Python VS code extension.

5. R Extension

R extension in Visual Studio Code provides support to R programming language and it is used to support the extended syntax highlighting, linting formatting, viewing data, help pages, managing the packages, code completion and working with the R Markdown documents.

Key Features:

• This VS Code extension provides support to the R programming language.
• It has features such as code completion, syntax highlighting and so on.
• It also works with the R Markdown documents.

Advantages:

• R extension is a service based on code analysis, it interacts with R terminals.
• It also helps to view data, plots and manage several packages in vs code.

Disadvantage:

• If the extension is not added to the directory containing R and Rscript to the PATH variable it will show errors.

Pricing: It is free to use.

6. Indent-rainbow

Indent rainbow is an extension in VS code which is used to colourize the indentation in the front text alternating in four different colours in each step. It is useful for writing code in Nim, Python, Yami and so on.

Key Features:

• The main features of this indent rainbow is to colour the indentation in the front text.
• This extension creates a rainbow palette within the closing and opening of elements, brackets or tags.

Advantages:

• With the help of this extension it is easier to read the multi-step indentation by adding the multiple colours on each step.
• Indentation improves code readability and also uses the present tab size users have set in the editor.

Disadvantages:

• Whenever odd numbered tags are written in vue template indentation appears in red which indicates an error.

Pricing: It is a freeware extension in VS code.

7. Julia

The Julia extension for Visual Studio is a free editor for the Julia language which provides a fully featured integrated development environment for profiling, debugging and linting.

Key Features:

• It includes the built-in dynamic autocompletion, plot pane and inline results features in it.
• This extension also has variable view, code navigation, syntax highlighting and advanced navigation features in it.

Advantages:

• It is an usable real-time feedback therefore consists of a completely live environment.
• It has ease to ease performance and is also beginner friendly.

Disadvantage:

• Sometimes the syntax highlighting feature breaks.

Pricing: The Julia extension is free to use.

8. Jupyter

Jupyter is visual studio code extension which is used to provide notebook support for any of the language kernels which is supported in Jupyter Notebooks nowadays. It lets the user edit, run and also save the Python Jupyter notebooks within the VS code.

Key Features:

• It supports working with the Jupyter Notebooks and also through the python code files.
• It can easily combine the executable python source and the markdown text on one canvas which is known as notebook.

Advantages:

• When code execution is finished these extensions can display a browser message and also provide information when the cell is running.
• Jupyter extension can auto format the code and also combines functionalities of Jupyter with VS code extension to provide the python development experience.

Disadvantage:

• These extensions are not good for big projects.

Pricing: Jupyter extension can be used freely.

9. DVC

The DVC extension is used to run, track and visualise the machine learning experiments with the VS code.

Key Features:

• This extension provides editors and manages the experiments to display the plots in IDE tabs.
• Visualisation and live tracking features are available in this extension.
• Big datasets, models and files are handled effectively.

Advantages:

• No need for external databases, subscriptions and servers are required.
• In DVC extension the data is under the control.

Disadvantage:

• Sometimes this extension works a bit slowly.

Pricing: This is a free extension and can be used by anyone.

10. GitLens

GitLens is a VS code extension used to show the commit details and includes the most recents commits. They also show author information and number of authors. They let the developer compare, explore and navigate each of the commits.

Key Features:

• The visualisations of the commit tree are good.
• Some of the main features are inline hover for getting the commit details and help users in debugging.
• This extension also has heatmaps, work tree and file blame features.

Advantages:

• It provides interactive views of the user’s code history.
• It allows the users to get insights into the code change over time.
• After each commit it displays the important information.

Disadvantage:

• The pro features such as the visualisation features come under paid pricing and sometimes the extension takes time to load.

Pricing: The GitLens extension is free to use but some of its features are paid.

Conclusion

Therefore, these are the Top 10 Visual Studio Code extensions for Data science which are used by the developers. The VS code extensions are used to add multiple languages, tools for installation and to add debuggers. This article covers the key features, advantages, disadvantages and pricing of the mentioned 10 extensions which are used in the field of Data science.