JetBrains DataSpell Integrations

Windsurf is a cutting-edge IDE designed for developers to maintain focus and productivity through AI-driven assistance. At the heart of the platform is Cascade, an intelligent agent that not only fixes bugs and errors but also anticipates potential issues before they arise. With built-in features for real-time code previews, automatic linting, and seamless integrations with popular tools like GitHub and Slack, Windsurf streamlines the development process. Developers can also benefit from memory tracking, which helps Cascade recall past work, and smart suggestions that enhance code optimization. Windsurf’s unique capabilities ensure that developers can work faster and smarter, reducing onboarding time and accelerating project delivery.

Docker streamlines tedious configuration processes and is utilized across the entire development lifecycle, facilitating swift, simple, and portable application creation on both desktop and cloud platforms. Its all-encompassing platform features user interfaces, command-line tools, application programming interfaces, and security measures designed to function cohesively throughout the application delivery process. Jumpstart your programming efforts by utilizing Docker images to craft your own distinct applications on both Windows and Mac systems. With Docker Compose, you can build multi-container applications effortlessly. Furthermore, it seamlessly integrates with tools you already use in your development workflow, such as VS Code, CircleCI, and GitHub. You can package your applications as portable container images, ensuring they operate uniformly across various environments, from on-premises Kubernetes to AWS ECS, Azure ACI, Google GKE, and beyond. Additionally, Docker provides access to trusted content, including official Docker images and those from verified publishers, ensuring quality and reliability in your application development journey. This versatility and integration make Docker an invaluable asset for developers aiming to enhance their productivity and efficiency.

Qodo, formerly Codium, analyzes your code to find bugs before you release. Qodo maps the behaviors of your code, identifies edge cases and tags anything suspicious. It then generates meaningful and clear unit tests that match the behavior of your code. You can see how your code behaves and how changes to your code affect the rest of the code. Code coverage is broken. Meaningful tests check functionality and give you the confidence to commit. Spend less time writing questionable tests and more time developing features that are useful to your users. Qodo analyzes your code, docstring and comments to suggest tests as you type. You only need to add them to your suite. Qodo focuses on code integrity. It generates tests that help you understand your code, find edge cases and suspicious behavior; and make your code more robust.

The Jupyter Notebook is a web-based open-source tool that enables users to create and distribute documents featuring live code, visualizations, equations, and written explanations. Its applications are diverse and encompass tasks such as data cleaning and transformation, statistical modeling, numerical simulations, data visualization, machine learning, among others, showcasing its versatility in various fields. Additionally, it serves as an excellent platform for collaboration and sharing insights within the data science community.

Augment Code is an AI agent built to enhance the coding experience for software engineers working with large and complex codebases. It integrates effortlessly into IDEs like Visual Studio Code, IntelliJ IDEA, Node, and Vim, offering a suite of tools for SDK migration, code refactoring, and code documentation. By leveraging machine learning, Augment Code automatically adapts to a developer’s style and memory, improving the quality of code generation and ensuring consistency across multiple repos. The platform is compatible with over 100 native and MCP tools, enabling engineers to debug, explain, and refine code in their familiar environments without needing to switch tools. Augment Code's deep integration with popular collaboration platforms like GitHub and Slack further streamlines workflows, making it easier for teams to collaborate and maintain high-quality code. Trusted by leading software teams, Augment Code helps developers write code like senior engineers, boosting productivity and reducing the complexity of large projects.

Zencoder is a cutting-edge platform that harnesses the capabilities of AI coding agents to enable developers to expedite their product delivery. By utilizing embedded AI agents, Zencoder enhances the process of code generation through comprehensive syntactic and semantic analysis of both your repository and the output code. This innovative approach ensures that our AI coding agents continuously refine the results, allowing you to maintain awareness and expertly navigate the challenges of software development. Experience the transformative potential of AI-enhanced code generation, as Zencoder seamlessly incorporates context-sensitive code into your projects, significantly speeding up your development workflow while maintaining accuracy. With Zencoder, you can interact with a smart coding companion that offers immediate support, insightful responses, and tailored solutions that cater to your specific coding requirements, making the development process smoother and more efficient. This combination of intelligent assistance and advanced technology not only elevates your coding experience but also empowers you to focus more on creativity and innovation.

At the heart of extensible programming lies the definition of functions. Python supports both mandatory and optional parameters, keyword arguments, and even allows for arbitrary lists of arguments. Regardless of whether you're just starting out in programming or you have years of experience, Python is accessible and straightforward to learn. This programming language is particularly welcoming for beginners, while still offering depth for those familiar with other programming environments. The subsequent sections provide an excellent foundation to embark on your Python programming journey! The vibrant community organizes numerous conferences and meetups for collaborative coding and sharing ideas. Additionally, Python's extensive documentation serves as a valuable resource, and the mailing lists keep users connected. The Python Package Index (PyPI) features a vast array of third-party modules that enrich the Python experience. With both the standard library and community-contributed modules, Python opens the door to limitless programming possibilities, making it a versatile choice for developers of all levels.

The JetBrains AI Assistant integrates your integrated development environment (IDE) with both third-party and proprietary large language models (LLMs) that are tailored for specific functionalities. This integration allows the AI Assistant to deliver accurate and context-sensitive support, assisting with tasks such as generating code snippets, completing intricate code structures, and developing automated tests efficiently. We prioritize the security of your data and code! JetBrains AI Assistant guarantees that your code snippets remain confidential and are neither stored nor shared, irrespective of whether they come from public repositories, private repositories, or local files. Adhering to the JetBrains AI Terms of Service is fundamental to our practices, ensuring that neither we nor our affiliated service providers utilize your data or code for the purpose of training any generative AI models. Additionally, this commitment to privacy and data integrity fosters a trustworthy environment for developers.

Supermaven enables you to code at twice the speed with the help of artificial intelligence. You can engage in discussions with various advanced models like GPT-4o, Claude 3.5 Sonnet, and GPT-4, among others. Hotkeys make it easy to instantly view differences, implement changes, begin conversations, and toggle between different models. It's simple to attach files you've recently modified to your messages, as Supermaven Chat connects the model's code suggestions to your original code, allowing for easy comparison and updates. Additionally, you can rectify mistakes effortlessly by uploading your code along with compiler error messages with just one click, streamlining the debugging process significantly. This seamless integration of features makes coding not only faster but also more efficient.

Goose, also referred to as codename goose, is an open-source AI agent that operates locally on machines, designed to facilitate the automation of engineering tasks within a terminal or integrated development environment (IDE). By efficiently performing functions such as code creation, debugging, and deployment, it allows developers to shift their focus towards more complex problem-solving activities. Its flexible architecture supports customization with various large language models (LLMs) and the integration of external APIs, which broadens its functionality to meet the unique demands of different projects. By taking on intricate tasks autonomously, Goose simplifies the development workflow, thereby enhancing overall productivity and minimizing the need for manual intervention. Users have expressed appreciation for Goose's capabilities in managing responsibilities like dependency updates, test execution, and code migration automation, underscoring its usefulness in practical scenarios. Furthermore, as the landscape of software development evolves, tools like Goose are becoming increasingly vital for maintaining efficiency in a fast-paced environment.

Project Jupyter is dedicated to the creation of open-source tools, standards, and services that facilitate interactive computing in numerous programming languages. At the heart of this initiative is JupyterLab, a web-based interactive development environment designed for Jupyter notebooks, coding, and data manipulation. JupyterLab offers remarkable flexibility, allowing users to customize and organize the interface to cater to various workflows in fields such as data science, scientific research, and machine learning. Its extensibility and modular nature enable developers to create plugins that introduce new features and seamlessly integrate with existing components. The Jupyter Notebook serves as an open-source web application enabling users to produce and share documents that incorporate live code, mathematical equations, visualizations, and descriptive text. Common applications of Jupyter include data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Supporting over 40 programming languages—including popular ones like Python, R, Julia, and Scala—Jupyter continues to be a valuable resource for researchers and developers alike, fostering collaborative and innovative approaches to computing challenges.

Firebender is an innovative AI-driven tool that aids developers in Android Studio by enhancing the coding experience and boosting overall productivity. This tool automates various aspects of code generation, assists with debugging, and streamlines the Android app development process. Firebender adeptly recognizes coding patterns, proposes effective solutions, and is capable of delivering real-time error corrections, which accelerates the development timeline and reduces the likelihood of errors. Serving as a resourceful assistant, it supports developers in tasks ranging from constructing user interfaces to handling API requests and fine-tuning intricate algorithms by producing code snippets, recommending best practices, and providing documentation help right within the Android Studio environment. This resource is perfect for developers of all skill levels who aim to optimize their workflow and efficiently create top-notch Android applications, ultimately transforming the way coding projects are approached and executed.

JupyterHub allows users to establish a multi-user environment that can spawn, manage, and proxy several instances of the individual Jupyter notebook server. Developed by Project Jupyter, JupyterHub is designed to cater to numerous users simultaneously. This platform can provide notebook servers for a variety of purposes, including educational environments for students, corporate data science teams, collaborative scientific research, or groups utilizing high-performance computing resources. It is important to note that JupyterHub does not officially support Windows operating systems. While it might be possible to run JupyterHub on Windows by utilizing compatible Spawners and Authenticators, the default configurations are not designed for this platform. Furthermore, any bugs reported on Windows will not be addressed, and the testing framework does not operate on Windows systems. Although minor patches to resolve basic Windows compatibility issues may be considered, they are rare. For users on Windows, it is advisable to run JupyterHub within a Docker container or a Linux virtual machine to ensure optimal performance and compatibility. This approach not only enhances functionality but also simplifies the installation process for Windows users.

R is a comprehensive environment and programming language tailored for statistical analysis and graphical representation. As a part of the GNU project, it shares similarities with the S language, which was originally designed by John Chambers and his team at Bell Laboratories, now known as Lucent Technologies. Essentially, R serves as an alternative implementation of S, and while there are notable distinctions between the two, a significant amount of S code can be executed in R without modification. This versatile language offers a broad spectrum of statistical methods, including both linear and nonlinear modeling, classical statistical tests, time-series analytics, classification, and clustering, among others, and it boasts a high level of extensibility. The S language is frequently utilized in research focused on statistical methodologies, and R presents an Open Source avenue for engaging in this field. Moreover, one of R's key advantages lies in its capability to generate high-quality publication-ready graphics, facilitating the inclusion of mathematical symbols and formulas as needed, which enhances its usability for researchers and analysts alike. Ultimately, R continues to be a powerful tool for those seeking to explore and visualize data effectively.

Markdown enables users to compose content in a straightforward, readable format that can be easily transformed into valid XHTML or HTML. Essentially, "Markdown" refers to two components: (1) a syntax for plain text formatting and (2) a Perl-based software tool that converts this formatted text into HTML. For more information regarding Markdown's formatting syntax, you can refer to the Syntax page. Additionally, you can experiment with it immediately through the online Dingus tool. The primary objective of Markdown’s formatting syntax is to ensure maximum readability, allowing documents to be presented in plain text without the appearance of tags or formatting cues. Although Markdown's syntax draws from various existing text-to-HTML converters, its most significant inspiration stems from the structure of plain text emails. This unique blend of simplicity and functionality makes Markdown a popular choice among writers and developers alike, enhancing their ability to create formatted content effortlessly.

Cody is an advanced AI coding assistant developed by Sourcegraph to enhance the efficiency and quality of software development. It integrates seamlessly with popular Integrated Development Environments (IDEs) such as VS Code, Visual Studio, Eclipse, and various JetBrains IDEs, providing features like AI-driven chat, code autocompletion, and inline editing without altering existing workflows. Designed to support enterprises, Cody emphasizes consistency and quality across entire codebases by utilizing comprehensive context and shared prompts. It also extends its contextual understanding beyond code by integrating with tools like Notion, Linear, and Prometheus, thereby gathering a holistic view of the development environment. By leveraging the latest Large Language Models (LLMs), including Claude Sonnet 4 and GPT-4o, Cody offers tailored assistance that can be optimized for specific use cases, balancing speed and performance. Developers have reported significant productivity gains, with some noting time savings of approximately 5-6 hours per week and a doubling of coding speed when using Cody.

Experience seamless remote development with JetBrains Gateway, a streamlined desktop application that lets you utilize a JetBrains IDE without the need for downloads. This application facilitates a remote development process with ease, allowing you to connect to any remote server via SSH, while JetBrains Gateway manages the deployment of the IDE backend on that server. Enjoy the complete functionality of your IntelliJ-based IDE, making it feel as if you're working on a local project, no matter your location. Importantly, your source code remains secure as it is neither transferred nor stored on your local device. Instantly access fully configured remote environments to begin coding without delay. Benefit from managed and customizable development settings that ensure both security and flexibility for developers. Launch brand new, automated development environments tailored for each task in the cloud within moments, and effortlessly initiate any repository to collaborate in a cloud-based development setup. With JetBrains Gateway, the possibilities for productive remote work are virtually limitless.

Amazon Q Developer is an advanced AI assistant built for professional developers, combining coding intelligence with deep AWS expertise. It’s designed to handle every stage of development—from writing and refactoring code to performing upgrades and automating documentation. Integrated with major IDEs and the AWS Management Console, it empowers developers to code faster and operate smarter using secure, context-aware assistance. Its agentic automation can autonomously implement features, test applications, and perform large-scale migrations like .NET to Linux or Java 8 to Java 17 in minutes. Developers can chat directly with Amazon Q inside Slack, Microsoft Teams, GitHub, and GitLab, where it provides architectural recommendations and incident resolution guidance. The tool also supports CLI autocompletions and AWS resource management to streamline workflows from the terminal to the cloud. Offering enterprise-grade access controls and IAM integration, it ensures that organizational data and permissions remain protected. Available on the AWS Free Tier, Amazon Q Developer enables up to 50 monthly AI interactions and 1,000 lines of code transformation at no cost, helping teams start building smarter right away.

Latta AI is a cutting-edge platform aimed at optimizing the software development workflow through automated bug detection and resolution. By capturing user sessions and employing AI-based solutions, Latta AI empowers developers, project managers, and testers to concentrate on creating new features, which ultimately enhances productivity and speeds up release timelines. The platform is designed to integrate effortlessly with widely-used version control systems such as GitHub and GitLab while ensuring robust security measures to safeguard code integrity and confidentiality. In addition, Latta AI provides a plugin for JetBrains IDEs, which permits developers to utilize its bug-fixing capabilities directly within their coding environment. This seamless integration allows for rapid identification and resolution of problems without having to exit the IDE. Furthermore, Latta AI's objective is to cut down the time developers dedicate to debugging by as much as 40%, significantly improving overall efficiency and enabling teams to prioritize innovation and creativity in their projects. By minimizing the burden of bug fixing, Latta AI plays a crucial role in transforming the software development landscape.

Code With Me is an innovative service designed for collaborative coding and pair programming. It allows you to seamlessly invite others into your Integrated Development Environment (IDE) project, enabling real-time collaboration. You and your teammates can address issues, review code, and work on coding tasks together instantly, making it easier to develop, debug, and resolve problems as a cohesive unit within a single remote collaborative IDE. By inviting others to your project, you can effectively demonstrate and clarify your code, making it an excellent resource for educational settings and online coding interviews. Simply click the link provided by the host to get started—no need to download repositories or pull changes from different branches. You'll no longer waste time setting up environments, tackling compile-time errors, or dealing with dependency issues just to access a project. Moreover, as a guest, you won’t even need to have a JetBrains IDE installed, eliminating barriers to entry for collaboration. This streamlined approach enhances productivity and fosters a more efficient coding experience for everyone involved.

Conda serves as an open-source solution for managing packages, dependencies, and environments across various programming languages, including Python, R, Ruby, Lua, Scala, Java, JavaScript, C/C++, Fortran, and others. This versatile system operates seamlessly on multiple platforms such as Windows, macOS, Linux, and z/OS. With the ability to swiftly install, execute, and upgrade packages alongside their dependencies, Conda enhances productivity. It simplifies the process of creating, saving, loading, and switching between different environments on your device. Originally designed for Python applications, Conda's capabilities extend to packaging and distributing software for any programming language. Acting as an efficient package manager, it aids users in locating and installing the packages they require. If you find yourself needing a package that depends on an alternate Python version, there’s no need to switch to a different environment manager; Conda fulfills that role as well. You can effortlessly establish an entirely separate environment to accommodate that specific version of Python, while still utilizing your standard version in your default environment. This flexibility makes Conda an invaluable tool for developers working with diverse software requirements.

SQL is a specialized programming language designed specifically for the purpose of retrieving, organizing, and modifying data within relational databases and the systems that manage them. Its use is essential for effective database management and interaction.

Engage in discussions about your codebase while allowing your AI coding assistant to make updates across numerous files directly within your preferred IDE! With the capability to automatically include all files currently opened in your editor, you can leverage up to 128,000 tokens within the AI's context memory. The AI will handle the coding tasks, and you can either approve the multi-file patch, select parts of it, or request adjustments as needed. Codebuddy is designed to scan your entire repository and create a vector database, enabling it to choose appropriate files for you or provide insights about your codebase, especially if you're not entirely familiar with it. This AI coding assistant possesses an in-depth understanding of your repository, allowing you to create new files or modify several existing ones with a single command. Codebuddy will automatically insert code in a format that resembles a unified patch (diff), enhancing your coding experience with unparalleled multi-file support. By incorporating these features, you can significantly streamline your coding process and improve overall productivity.

EasyCode is an AI tool designed to comprehend your codebase. It empowers developers by providing immediate answers to their inquiries. Benefit from context-aware code recommendations, gain insights into legacy projects, and effortlessly locate the pertinent code. Integrate ChatGPT directly into your IDE for seamless access. This enables contextual responses and suggestions that streamline the developer's workflow. Maintain a uniform coding style while receiving instantaneous feedback on the quality of your code. By reducing time spent on monotonous tasks, developers can dedicate more time to impactful coding assignments. Additionally, it promotes enhanced context and knowledge sharing within teams, fostering collaboration and efficiency. This ultimately leads to a more productive development environment.

The JetBrains IDEs have integrated a new CSV Editor plugin that designates CSV (Comma-Separated Values) as a formal language, complete with a defined syntax, structured language components, and relevant file extensions (.csv/.tsv/.psv). This functionality enables standard editor capabilities such as syntax validation, highlighting, and inspections for files that resemble CSV formats. Users can enjoy customizable text and table editors, along with versatile table editing options, syntax validation, and tailored syntax highlighting and formatting. Additionally, it offers quick-fix inspections and useful intentions like quoting and unquoting text or shifting columns as needed. The plugin is designed to handle various value separators, including tab characters, and it permits the use of custom separators and line comments for enhanced flexibility. With the table editor, users can easily add or remove rows and columns through context menus, and it also supports keyboard shortcuts for smoother navigation and management of data. This makes working with CSV files more intuitive and efficient for developers.

Lingma serves as Alibaba Cloud's AI-driven coding assistant, aimed at enhancing the efficiency of software development processes. Featuring capabilities such as line and function-level real-time code completion, natural language-based code generation, and smart troubleshooting, it allows developers to articulate their requirements in simple language, resulting in automatically generated code within the editor. Supporting an extensive array of over 200 programming languages, Lingma also offers in-depth code explanations accompanied by visual flow charts. Furthermore, it can assess codebases to produce unit tests, automatically compile and execute code, and rectify issues to boost test coverage. Users can even upload images for contextual analysis, which aids in generating code or delivering bug fixes based on specified requirements. For corporate users, Lingma seamlessly integrates with private data sources, such as documents and repositories, to refine its model outputs and ensure they adhere to company standards, thereby maximizing its utility in professional environments. Additionally, this integration fosters a collaborative atmosphere for development teams, promoting a more streamlined workflow across projects.

The leading open-source AI assistant. You can create custom autocomplete experiences and chats by connecting any models to any context. Remove the barriers that hinder productivity when developing software to remain in flow. Accelerate your development with a plug and play system that is easy to use and integrates into your entire stack. Set up your code assistant so that it can evolve with new capabilities. Continue autocompletes entire sections of code or single lines in any programming languages as you type. Ask questions about files, functions, the entire codebase and more by attaching code or context. Highlight code sections, then press the keyboard shortcut to convert code into natural language.

Mistral Code is a cutting-edge AI coding assistant tailored for enterprise software engineering teams that need frontier-grade AI capabilities combined with security, compliance, and full IT control. Building on the proven open-source Continue project, Mistral Code delivers a vertically integrated solution that includes state-of-the-art models like Codestral, Codestral Embed, Devstral, and Mistral Medium for comprehensive coding assistance—from autocomplete to agentic coding and chat support. It supports local, cloud, and serverless deployments, allowing enterprises to choose how and where to run AI-powered coding workflows while ensuring all code and data remain within corporate boundaries. Addressing key enterprise pain points, Mistral Code offers deep customization, broad task automation beyond simple suggestions, and unified SLAs across models, plugins, and infrastructure. The platform is capable of reasoning over code files, Git diffs, terminal output, and issues, enabling engineers to complete fully scoped development tasks with configurable approval workflows to keep senior engineers in control. Enterprises such as Spain’s Abanca, France’s SNCF, and global integrator Capgemini rely on Mistral Code to boost developer productivity while maintaining compliance in regulated industries. The system includes a rich admin console with granular platform controls, seat management, and detailed usage analytics for IT managers. Mistral Code is currently in private beta for JetBrains IDEs and VSCode, with general availability expected soon.