secondmate 0.11.1

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SecondMate

SecondMate is a modern data catalog and exploration tool built with a high-performance Python backend and a dynamic React frontend. It provides a seamless interface for managing data catalogs, namespaces, and tables, with built-in support for Apache Iceberg and PySpark.

🚀 Key Features

• Dynamic Catalog Browser: Navigate through your data hierarchy (Catalogs -> Namespaces -> Tables) with an intuitive tree view.
• Data Preview: Instantly query and visualize data from your tables.
• Integrated Querying: Built-in support for executing queries against your data lake.
• Iceberg Native: Designed with Apache Iceberg in mind, including automatic sample data initialization.
• Modern UI: Built with React 19, TypeScript, and Vite, featuring a responsive design with resizable panels and a premier dark-mode aesthetic.

🛠️ Tech Stack

Frontend

• Framework: React 19 + TypeScript
• Build Tool: Vite
• State Management: Zustand
• Component: Monaco Editor, React Resizable Panels
• Styling: Lucide React (Icons), CSS Modules

Backend

• Framework: FastAPI
• Data Processing: PySpark 4.0+ (Development build)
• Table Format: Apache Iceberg
• Server: Uvicorn

📦 Installation & Setup

Prerequisites

• Node.js (v18+ recommended)
• Python 3.11+
• Java 17+ (for PySpark)
• uv (recommended for Python dependency management)

1. Development Environment

SecondMate includes a unified development script that starts both the FastAPI backend and Vite frontend together.

# Clone the repository and enter the directory
git clone <repository-url>
cd secondmate

# Install frontend dependencies
npm install

# Create a virtual environment and install backend dependencies using uv
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e .

# Start the development server (runs both backend and frontend)
chmod +x dev.sh
./dev.sh

• The UI will be available at http://localhost:5173.
• The API will be available at http://localhost:8000.
• Automatic API docs at http://localhost:8000/docs.

2. Manual/Separate Setup

Frontend (Vite Server):

npm install
npm run dev

Backend (FastAPI Server):

uv venv
source .venv/bin/activate
uv pip install -e .
uvicorn secondmate.main:app --reload --host 0.0.0.0 --port 8000

3. Production Build

When building for production, the Vite frontend compiles into the Python package (secondmate/static), which is then served by FastAPI.

# Build the frontend (outputs to secondmate/static)
npm run build

# Install the Python package and run the CLI
uv pip install -e .
secondmate --port 4050

The app will be available at http://localhost:4050 serving both UI and API.

4. Verification

Several scripts are available to verify your installation and configuration:

# Ensure frontend is built first
npm run build

# Run asset verification
python verify_assets.py

# Run configuration injection verification
python verify_injection.py

# Run conditional data/provider logic verification
python verify_conditional_data.py

📚 API Endpoints

The backend exposes several key endpoints for metadata and data retrieval:

• GET /health: Service health check.
• GET /info: Spark session and application details.
• GET /catalogs: List all available catalogs.
• GET /catalogs/{catalog_name}/namespaces: List namespaces within a catalog.
• GET /catalogs/{catalog_name}/namespaces/{namespace}/tables: List tables within a namespace.
• GET /query: Execute a sample query (currently fetches user.ipgeo).

🔌 Custom Spark Providers

SecondMate allows you to provide your own Spark session by implementing a custom Spark provider. This is useful for connecting to existing Spark clusters, configuring specific catalogs (like AWS Glue or Hive), or applying custom security settings.

1. Create a Provider Class

Your custom provider must implement the SparkProvider protocol (defined in secondmate/providers/spark_interface.py). It needs a get_session() method that returns a pyspark.sql.SparkSession.

Example my_provider.py:

from pyspark.sql import SparkSession
from secondmate.providers.spark_interface import SparkProvider

class MyCustomSparkProvider(SparkProvider):
    def get_session(self) -> SparkSession:
        return (
            SparkSession.builder
            .appName("SecondMate-Custom")
            .config("spark.sql.catalog.my_catalog", "org.apache.iceberg.spark.SparkCatalog")
            # ... additional configuration ...
            .getOrCreate()
        )

2. Deploying the Provider

To use your custom provider, set the SPARK_PROVIDER_CLASS environment variable to the full import path of your class before starting SecondMate.

export SPARK_PROVIDER_CLASS="my_module.my_provider.MyCustomSparkProvider"
secondmate --port 4050

SecondMate will dynamically load your provider class and use it to obtain the Spark session for all operations.

🧪 Sample Data

On startup, the backend automatically initializes a local Spark Iceberg environment with the following sample tables:

• user.ipgeo (1000 rows)
• user.sales.transactions
• user.finance.budget

Enjoy exploring your data with SecondMate!