@deepnote/runtime-core

@deepnote/runtime-core

Core runtime for executing Deepnote projects.

This project is under active development and is not ready for use. Expect breaking changes.

Installation

npm install @deepnote/runtime-core

Prerequisites

You must have deepnote-toolkit with the server extra installed in your Python environment:

pip install "deepnote-toolkit[server]"

Usage

import { ExecutionEngine } from "@deepnote/runtime-core";

const engine = new ExecutionEngine({
  // Python executable, venv directory, or command in PATH (for example: 'python3')
  pythonEnv: "python",
  workingDirectory: "/path/to/project",
});

try {
  await engine.start();

  const summary = await engine.runFile("./my-project.deepnote", {
    onBlockStart: (block, index, total) => {
      console.log(`Running [${index + 1}/${total}] ${block.type}...`);
    },
    onBlockDone: (result) => {
      console.log(result.success ? "ok" : "failed");
    },
  });

  console.log(
    `Executed ${summary.executedBlocks}/${summary.totalBlocks} blocks in ${summary.totalDurationMs}ms`,
  );
} finally {
  await engine.stop();
}

Runtime config

ExecutionEngine accepts:

• pythonEnv: string - Python executable or environment path used to launch deepnote-toolkit
• workingDirectory: string - Working directory for execution
• serverPort?: number - Optional server port (auto-assigned when omitted)

Execution options

runFile(filePath, options) and runProject(file, options) support:

• Notebook / block filtering: notebookName, blockId, blockIds
• Input injection before execution: inputs
• Database integration metadata for agent block awareness: integrations
• Callbacks: onBlockStart, onBlockDone, onOutput, onAgentEvent, onServerStarting, onServerReady

Result shape

Execution methods return ExecutionSummary:

• totalBlocks
• executedBlocks
• failedBlocks
• totalDurationMs