22title : JupyterLab IDE
33---
44
5- JupyterLab Interactive Development Environment - Tailored User Workspace
6-
7- ## JupyterLab overview
5+ ## Overview
86
97The JupyterLab Interactive Development Environment (IDE) capacity within the APEx Project Environments primarily leverages the power
108of the [ JupyterLab] ( #jupyterlab-software-architecture ) software.
@@ -21,12 +19,12 @@ them to harness the computational power of remote servers.
2119Tailored specifically for EO tasks, this environment furnishes developers with an array of tools and libraries fine-tuned
2220for programming languages and productivity plugins or extensions.
2321
24- ## JupyterLab software architecture
22+ ## Software Architecture
2523
2624The JupyterLab setup encapsulates a web-based interactive development environment for Jupyter notebooks, code, and data.
2725It is the user interface for Project Jupyter, offering a flexible user interface and more features than the classic notebook
2826UI. It is a web application providing a development environment in which processing algorithms and services can be developed,
29- tested, and debugged.
27+ tested, and debugged.
3028
3129![ The JupyterLab IDE in the current APEx workspaces offering ] ( images/applicationhub_jupyterlab.png )
3230
@@ -35,7 +33,7 @@ Julia, R, Haskell, Ruby, and Python (via the IPython kernel). It seamlessly adap
3533developers to create, test, and deploy applications within isolated, replicable, and consistent environments, ensuring
3634consistent behaviour across development, staging, and production phases.
3735
38- ### JupyterLab key features
36+ ## Key Features
3937
4038The APEx JupyterLab IDE includes several features that make it suitable for both individual researchers and teams
4139working on EO research and applications.
@@ -53,18 +51,18 @@ various levels of support.
5351Leverage integrated Git support, allowing team members to work on the same project by tracking changes and merging updates,
5452helping to keep the code organized while avoiding conflicting code changes.
5553
56- ## JupyterLab showcase scenarios
54+ ## Showcase Scenarios
5755
5856The APEx JupyterLab IDE supports a variety of use cases, making it an essential tool for developers,
5957researchers, and data scientists within the EO community. Some typical scenarios include:
6058
6159* ** Algorithm Development and Testing** \
6260Researchers and developers can write, test, and debug new algorithms for processing
6361satellite imagery or other EO data. For instance, a user might develop a script to detect deforestation using
64- multi-temporal satellite images. To support the productivity of developers, both the JupyterLab solution use a mechanism of extensions.
62+ multi-temporal satellite images. To support the productivity of developers, both the JupyterLab solution use a mechanism of extensions.
6563
6664::: {.callout-note}
67- There is no GitHub Copilot extension available yet for JupyterLab.
65+ There is no GitHub Copilot extension available yet for JupyterLab.
6866
6967See the [ Code Server IDE] ( ./app_code_server.md ) page for more details on CoPilot extensions.
7068
@@ -86,7 +84,7 @@ working with notebooks, with its native support for data science, data visualisa
8684
8785## Examples
8886
89- @tbl-ide-examples showcases example projects that utilize the APEx JupyterLab IDE.
87+ @tbl-ide-examples showcases example projects that utilize the APEx JupyterLab IDE.
9088
9189It is important to note that a valid APEx account and permissions from the project are required to access an environment.
9290
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