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VS Code VS PyTorch

Compare VS Code VS PyTorch and see what are their differences

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VS Code logo VS Code

Build and debug modern web and cloud applications, by Microsoft

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • VS Code Landing page
    Landing page //
    2024-10-09
  • PyTorch Landing page
    Landing page //
    2023-07-15

VS Code features and specs

  • Cross-platform
    VS Code works on Windows, macOS, and Linux, providing a consistent development experience across different operating systems.
  • Extensibility
    A vast library of extensions allows users to add functionalities like debuggers, linters, and themes, making it highly customizable.
  • Integrated Git
    Built-in Git integration makes it easy to manage version control tasks directly within the editor.
  • Performance
    Lightweight compared to full-fledged IDEs, ensuring good performance even on systems with limited resources.
  • IntelliSense
    Advanced code completion and refactoring tools help improve coding efficiency and reduce errors.
  • Community Support
    A strong and active community provides extensive support, tutorials, and third-party extensions.
  • Debugging
    Robust debugging tools for various languages and frameworks are available out of the box.
  • Free and Open-Source
    VS Code is completely free to use and open-source, which is beneficial for both individual developers and organizations.

Possible disadvantages of VS Code

  • Limited IDE Features
    While extensible, it may lack some advanced features found in dedicated IDEs out of the box.
  • Extension Management
    Managing and configuring a large number of extensions can become cumbersome and sometimes lead to performance issues.
  • Learning Curve
    Although user-friendly, it has a steeper learning curve for beginners due to its numerous features and customization options.
  • Memory Usage
    Despite being lightweight, it can consume a significant amount of memory when multiple extensions are installed.
  • Update Frequency
    Frequent updates may sometimes introduce bugs or require users to adapt to new changes quickly.
  • Internet Dependency
    Some features and extensions may require an internet connection to function optimally.
  • Telemetry
    By default, VS Code collects usage data, which might be a concern for users sensitive about data privacy. However, this can be disabled.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

VS Code videos

+ Add

My New Favorite Text Editor - Visual Studio Code

More videos:

  • Review - 7 reasons why I switched to Visual Studio Code from Sublime Text

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to VS Code and PyTorch)

VS Code

PyTorch

Text Editors
100 100%
Text Editors
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
IDE
100 100%
IDE
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare VS Code and PyTorch

VS Code Reviews

  1. dksinden
    · Working at SpeechKit ·
Boost Your Productivity with These Top Text Editors and IDEs
Visual Studio Code, commonly known as VS Code, is a powerful and extensible code editor developed by Microsoft. With its rich ecosystem of extensions and features like IntelliSense, debugging, and Git integration, VS Code enhances your coding productivity.
Source: convesio.com
13 Best Text Editors to Speed up Your Workflow
Finally, the Visual Studio Code website has numerous tabs for you to learn about the software. The documentation page walks you through steps like the setup and working with different languages. You’re also able to check out some tips and tricks and learn all of the Visual Studio Code keyboard shortcuts. Along with a blog, updates page, extensions library and API...
Source: kinsta.com
Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Previously, VS Code was more suited to developers or engineers due to its lack of data analysis capabilities, but since 2020, the VS Code team has collaborated with the Jupyter team to create an integrated notebook within VS Code. The end result is a fantastic IDE workbook for data analysis.
Source: lakefs.io
The Best IDEs for Java Development: A Comparative Analysis
Overview: Although not a traditional IDE, VS Code has gained popularity as a lightweight code editor.
Source: dev.to
20 Best Diff Tools to Compare File Contents on Linux
Visual studio code is a code editor made by Microsoft. It supports several development operations like debugging, task running, and version control. It works on Linux, macOS and Windows operating systems.
Source: linuxopsys.com

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, VS Code should be more popular than PyTorch. It has been mentiond 1141 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

VS Code mentions (1141)

  • What's Happening in Developer Tools? (OpenAI Just Bought Windsurf for $3B)
    Microsoft's Visual Studio Code is a free code editor that relies on community plugins for support across various languages and frameworks. It also has an AI offering, Copilot, that provides code completion and it just added its own agent. VSCode supports multiple LLMs, but initially, there seemed to be a preference for ChatGPT, in part given its early lead and no doubt influenced by the fact Microsoft was an early... - Source: dev.to / 2 days ago
  • Your first MCP Server (quick)
    Explore different MCP Clients too! You can continue using ollmcp as we did earlier, or try other clients like Claude Desktop, Visual Studio Code, and more to see how different environments interact with your server. - Source: dev.to / 2 days ago
  • An Introduction to TypeScript for JavaScript Developers
    Better Tooling – Enhanced autocompletion, refactoring, and navigation in IDEs like VS Code. - Source: dev.to / 4 days ago
  • Why Understanding, Not Just Generating Code, Still Matters
    To do this, I used VS Code, an extension called Cline configured in Act mode, and Gemini 2.5 Pro Preview 03-25, which is amazing. I made two attempts. The first one using a simple and very generic prompt, and a second one using a more detailed prompt. Let’s talk about them. - Source: dev.to / 7 days ago
  • 🚀 Your First Setup Win: Python and VS Code on Mac (Beginner Friendly)
    I visited code.visualstudio.com and clicked the big, inviting "Download for Mac" button. After downloading, I opened the .zip file, dragged the VS Code app into my Applications folder, and launched it. - Source: dev.to / 11 days ago
View more

PyTorch mentions (132)

  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 10 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 1 month ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 3 months ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing VS Code and PyTorch, you can also consider the following products

Sublime Text - Sublime Text is a sophisticated text editor for code, html and prose - any kind of text file. You'll love the slick user interface and extraordinary features. Fully customizable with macros, and syntax highlighting for most major languages.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Vim - Highly configurable text editor built to enable efficient text editing

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Notepad++ - A free source code editor which supports several programming languages running under the MS Windows environment.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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