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Code Workspaces（Code Workspaces（代码工作空间））

Code Workspaces brings the JupyterLab®, RStudio® Workbench, and VS Code third-party IDEs to Palantir Foundry, enabling users to boost their productivity and accelerate their data science and statistics workflows by using their preferred tools on the high-quality data of the Foundry Ontology. Code Workspaces containers are natively integrated with the rest of the Foundry ecosystem to combine familiar IDEs with the benefits of the Foundry platform, such as data security, branching, build scheduling, and resource management.

Code Workspaces gives platform administrators an easily-deployed, fully-managed, secure, and production-ready way to provide JupyterLab®, RStudio® Workbench, and VS Code to users with Foundry’s data governance and compliance with FedRAMP, GxP, and other standards built-in. With Code Workspaces, users can securely connect to existing internal systems and build analyses, transforms, models, applications, or entire workflows on data with Foundry’s access controls and data permissioning.

Key features

Key features of Code Workspaces include:

  • Security: Code Workspaces is built on the core components of Foundry security that underpin the platform as a whole, like robust permissions and granular access controls. This provides Foundry’s security model to the third-party IDEs available in Code Workspaces. For example, restricting access to a dataset in Foundry will restrict it for Code Workspaces IDEs as well, ensuring consistent permissions across tools.
  • Customizable environments: Code Workspaces allows users to define custom environment profiles and increase or decrease the compute resources of their workspace as desired.
  • Git workflow support: Code Workspaces are backed by the Code Repositories infrastructure, which provides industry-standard version control features like branching, merging, and commit history. These features enable multiple users to operate in the same workspace more easily and safely.
  • Applications: Code Workspaces currently supports Dash ↗ and Streamlit ↗ for Python applications and Shiny® ↗ for R applications. Users can create application workflows directly in Code Workspaces with Foundry’s version control, branching, and data governance features built-in.
  • Model integration: Users can create model assets from within a Code Workspace and track these assets with modeling objectives. Multiple models can be created from the same workspace.
  • Transforms/build integration: Code Workspaces serves as a development environment for transforms. Logic written in Code Workspaces can be published as data transformation pipelines and seamlessly integrates with Foundry's data integration toolkit, including builds, schedules, data lineage, and health checks. Code Workspaces supports both R transforms and Python/Jupyter® transforms.

When to use Code Workspaces

Foundry has a variety of applications you can use for analytical or coding purposes. For example, if you are an analyst, you may be best served by Contour, Foundry’s point-and-click low-code interface for dataset analysis.

If you need to write large-scale data pipelines, set up data connections, or work with streaming data, other Foundry tools have more functionality than Code Workspaces; for these use cases, we recommend using Pipeline Builder, Data Connection, and Foundry Streaming, respectively.

Specifically, Code Workspaces runs on a single node, while other Foundry applications leverage a Spark infrastructure. Thus, we recommend that users performing large-scale data transformations choose Pipeline Builder or Code Repositories instead of Code Workspaces.

Code Workspaces is geared for building machine learning models or those familiar with working in JupyterLab® or RStudio® Workbench.

Learn more

Code Workspaces currently supports three environments: JupyterLab®, RStudio®, and VS Code.

More information about Code Workspaces can be found in the FAQ.

Get started using Code Workspaces with this tutorial.

RStudio® and Shiny® are trademarks of Posit™.

Jupyter®, JupyterLab®, and the Jupyter® logos are trademarks or registered trademarks of NumFOCUS.

All third-party trademarks (including logos and icons) referenced remain the property of their respective owners. No affiliation or endorsement is implied.

中文翻译

Code Workspaces（代码工作空间）

Code Workspaces 将 JupyterLab®、RStudio® Workbench 和 VS Code 等第三方 IDE（集成开发环境）引入 Palantir Foundry，使用户能够利用 Foundry Ontology（本体）的高质量数据，通过其偏好的工具提升生产力并加速数据科学与统计工作流程。Code Workspaces 容器与 Foundry 生态系统的其余部分原生集成，将熟悉的 IDE 与 Foundry 平台的优势（如数据安全、分支管理、构建调度和资源管理）相结合。

Code Workspaces 为平台管理员提供了一种易于部署、完全托管、安全且可直接投入生产的方式，向用户提供 JupyterLab®、RStudio® Workbench 和 VS Code，同时内置 Foundry 的数据治理功能，并符合 FedRAMP、GxP 及其他标准。借助 Code Workspaces，用户可以安全地连接到现有内部系统，并在 Foundry 的访问控制和数据权限管理下，基于数据构建分析、转换、模型、应用或完整的工作流程。

主要功能

Code Workspaces 的主要功能包括：

  • 安全性： Code Workspaces 基于支撑整个平台的 Foundry 安全核心组件构建，例如强大的权限管理和细粒度访问控制。这为 Code Workspaces 中可用的第三方 IDE 提供了 Foundry 的安全模型。例如，限制对 Foundry 中数据集的访问将同时限制对 Code Workspaces IDE 的访问，从而确保跨工具的一致性权限。
  • 可定制环境： Code Workspaces 允许用户定义自定义环境配置文件，并根据需要增加或减少其工作空间的计算资源。
  • Git 工作流支持： Code Workspaces 由 Code Repositories（代码仓库）基础设施提供支持，该基础设施提供行业标准的版本控制功能，如分支、合并和提交历史。这些功能使多个用户能够更轻松、更安全地在同一工作空间中操作。
  • 应用： Code Workspaces 目前支持 Python 应用的 Dash ↗ 和 Streamlit ↗，以及 R 应用的 Shiny® ↗。用户可以直接在 Code Workspaces 中创建应用工作流，并内置 Foundry 的版本控制、分支管理和数据治理功能。
  • 模型集成： 用户可以在 Code Workspaces 中创建模型资产，并通过 modeling objectives（建模目标）跟踪这些资产。同一工作空间可创建多个模型。
  • 转换/构建集成： Code Workspaces 作为转换（transforms）的开发环境。在 Code Workspaces 中编写的逻辑可以发布为数据转换管道，并与 Foundry 的 data integration（数据集成）工具包无缝集成，包括构建、调度、数据血缘和健康检查。Code Workspaces 支持 R 转换和 Python/Jupyter® 转换。

何时使用 Code Workspaces

Foundry 提供了多种可用于分析或编码目的的应用。例如，如果您是分析师，Contour（Foundry 的点击式低代码数据集分析界面）可能最适合您。

如果您需要编写大规模数据管道、设置数据连接或处理流式数据，其他 Foundry 工具比 Code Workspaces 功能更丰富；针对这些用例，我们建议分别使用 Pipeline Builder（管道构建器）、Data Connection（数据连接）和 Foundry Streaming（流式处理）。

具体而言，Code Workspaces 运行在单个节点上，而其他 Foundry 应用则利用 Spark 基础设施。因此，我们建议执行大规模数据转换的用户选择 Pipeline Builder 或 Code Repositories，而非 Code Workspaces。

Code Workspaces 专为构建机器学习模型或熟悉 JupyterLab® 或 RStudio® Workbench 的用户而设计。

了解更多

Code Workspaces 目前支持三种环境：JupyterLab®、RStudio® 和 VS Code。

关于 Code Workspaces 的更多信息，请参阅 FAQ（常见问题解答）。

通过本教程开始使用 Code Workspaces。

RStudio® 和 Shiny® 是 Posit™ 的商标。

Jupyter®、JupyterLab® 及 Jupyter® 标识是 NumFOCUS 的商标或注册商标。

所有第三方商标（包括标识和图标）均归其各自所有者所有。本文不暗示任何关联或认可。