System Requirements Document (SRD)

Project Name: sonic-jupyterlab

1. Introduction

The sonic-jupyterlab project aims to create a customized JupyterLab environment tailored for interactive data analysis, coding, and work-related tasks. This project is designed to enhance productivity by providing a seamless, efficient, and user-friendly interface for professionals like Faisol Rosikin in Singapore. The system will incorporate specific features and integrations to meet the unique needs of its users, ensuring a robust and scalable solution for data-heavy workflows.

This document outlines the system requirements for sonic-jupyterlab, including functional and non-functional requirements, user personas, design concepts, and technical specifications.

2. System Overview

sonic-jupyterlab is a web-based interactive development environment (IDE) designed for data scientists, analysts, and developers. It will provide a highly customizable workspace with pre-installed libraries, support for multiple programming languages, and integrations with popular tools like Git. The system will focus on:

• Streamlining workflows for data analysis and coding.
• Offering a visually appealing and intuitive interface.
• Supporting collaboration and version control.
• Ensuring compatibility with modern technologies and frameworks.

The system will be deployed in a containerized environment using Docker and Kubernetes for scalability and reliability.

3. Functional Requirements

• As a User, I should be able to create and manage Jupyter notebooks.
• As a User, I should be able to install and use pre-configured libraries.
• As a User, I should be able to customize the theme and layout of the JupyterLab interface.
• As a User, I should be able to integrate Git for version control.
• As a User, I should be able to collaborate with other users in real-time.
• As a User, I should be able to access the JupyterLab environment from any device.
• As a User, I should be able to visualize data using built-in tools and extensions.
• As a User, I should be able to manage resources efficiently using a dashboard.

4. User Personas

4.1 Data Scientist

• Description: A professional working with large datasets, requiring tools for data cleaning, analysis, and visualization.
• Goals: Efficiently process and analyze data, create visualizations, and share insights with the team.
• Pain Points: Slow processing speeds, lack of collaboration tools, and difficulty in managing dependencies.

4.2 Developer

• Description: A programmer using JupyterLab for prototyping, testing, and debugging code.
• Goals: Write, test, and debug code efficiently with access to necessary libraries and tools.
• Pain Points: Limited customization options and lack of integration with version control systems.

4.3 Team Collaborator

• Description: A team member collaborating on shared projects within JupyterLab.
• Goals: Work collaboratively in real-time, track changes, and maintain version control.
• Pain Points: Difficulty in real-time collaboration and managing shared resources.

5. Visuals Colors and Theme

The sonic-jupyterlab project will feature a unique and modern color palette to enhance user experience and align with the project's identity.

• Background: #1E1E2F (Deep Midnight Blue)
• Surface: #2A2A3B (Charcoal Gray)
• Text: #E8E8F2 (Soft White)
• Accent: #FF6F61 (Coral Red)
• Muted Tones: #A6A6B3 (Muted Lavender)

This palette is designed to provide a professional yet visually appealing environment, reducing eye strain during long work sessions.

6. Signature Design Concept

The sonic-jupyterlab homepage will feature an interactive galaxy map that represents the user's projects, notebooks, and tools as celestial bodies.

Key Features:

• Dynamic Animations: Stars and planets will gently orbit, creating a sense of motion and exploration.
• Interactive Elements: Clicking on a star will zoom into a specific project or notebook, while hovering will display a tooltip with details.
• Color Shifts: The galaxy's background will transition between shades of blue and purple, creating a calming and futuristic atmosphere.
• Micro-Interactions: Subtle animations, such as twinkling stars and orbiting satellites, will respond to user actions like mouse movements.
• Customizable Themes: Users can personalize the galaxy's appearance, including star colors and background gradients, to suit their preferences.

This design will make the sonic-jupyterlab homepage an unforgettable experience, blending functionality with a sense of wonder and creativity.

7. Non-Functional Requirements

• The system must support at least 100 concurrent users.
• The system must load the homepage within 3 seconds on a standard broadband connection.
• The system must comply with Singapore's data protection regulations (PDPA).
• The system must be accessible on both desktop and mobile devices.
• The system must support integration with third-party tools like Git and cloud storage services.

8. Tech Stack

Frontend

• React for Web

Backend

• Python
• FastAPI

Database

• MySQL (using Alembic for migrations)

AI Models

• GPT 5.4 for user-friendly responses
• Claude 4.6 Opas for academic or coding work

AI Tools

• Litellm for LLM Routing
• Langchain

Local Orchestration

• Docker
• docker-compose

Server-Side Orchestration

• Kubernetes

9. Assumptions and Constraints

Assumptions

• Users will have basic knowledge of JupyterLab and its functionalities.
• The system will be hosted on a cloud platform with sufficient resources to handle the expected user load.
• Users will have stable internet connections to access the platform.

Constraints

• The system must adhere to Singapore's Personal Data Protection Act (PDPA).
• The project must be completed within the allocated budget and timeline.
• The system must be compatible with the latest versions of major web browsers.

10. Glossary

• JupyterLab: A web-based interactive development environment for notebooks, code, and data.
• PDPA: Personal Data Protection Act, a data protection law in Singapore.
• Docker: A platform for developing, shipping, and running applications in containers.
• Kubernetes: An open-source system for automating deployment, scaling, and management of containerized applications.
• FastAPI: A modern, fast web framework for building APIs with Python.
• Alembic: A lightweight database migration tool for usage with SQLAlchemy.
• Litellm: A tool for routing large language models.
• Langchain: A framework for developing applications powered by language models.