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Main Sequence SDK

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Main Sequence Python SDK

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The Main Sequence Python SDK is the client and development toolkit for the Main Sequence platform.

The Main Sequence platform allows you to:

  1. rapidly build and deploy data products and data workflows as a unified API with a normalized structure through DataNodes
  2. rapidly deploy RBAC-enabled dashboards on the platform
  3. rapidly deploy agents using the Google Agent SDK

The key idea is that you can focus on development and deployment, while the platform handles the DevOps layer.

Project Status

What this repository contains

This repository contains the SDK and the documentation used to build and operate Main Sequence projects.

Main package areas:

  • mainsequence.tdag: data orchestration, DataNodes, update workflows, and persistence
  • mainsequence.client: API client models for projects, jobs, data node storages, assets, sharing, and platform resources
  • mainsequence.virtualfundbuilder: portfolio construction and portfolio time series workflows
  • mainsequence.instruments: pricing-oriented market data and instrument tooling
  • mainsequence.dashboards.streamlit: reusable Streamlit scaffolding and dashboard helpers
  • mainsequence.cli: the mainsequence command-line interface

Repository areas:

  • docs/: tutorials, knowledge guides, CLI docs, and generated reference docs
  • examples/: worked examples and usage patterns
  • tests/: automated tests

Documentation map

The documentation is organized into four reading modes:

  1. Tutorial: the guided learning path
  2. Knowledge: deeper conceptual guides
  3. CLI: command-focused operational documentation
  4. Reference: generated API reference

Recommended entry points:

Quick start

Install the package:

pip install mainsequence

Authenticate:

mainsequence login

Check that you can see your projects:

mainsequence project list

Create a new project:

mainsequence project create my-first-project

Set it up locally:

mainsequence project set-up-locally <PROJECT_ID>
cd my-first-project
mainsequence project build_local_venv --path .

From there, the normal learning path is:

  1. create your first DataNode
  2. model app-facing data with SimpleTable when needed
  3. add an API or another application surface
  4. understand sharing and RBAC
  5. schedule jobs
  6. build dashboards or downstream consumers
  7. package the project as an agent-facing surface when the repository is ready

Installation for development

This repository uses pyproject.toml and a development dependency group.

With uv:

uv sync --group dev

Or with pip, install the package and the docs/test tools you need separately.

Common development commands

Run the CLI:

mainsequence --help

Run tests:

pytest

Serve the docs locally:

mkdocs serve

Build the docs:

mkdocs build

Lint the code:

ruff check .

Format the code:

black .

How to read this repository

If you are evaluating the platform:

  • start with the tutorial in docs/tutorial/

If you are building a feature and already know the area:

  • go straight to the relevant guide in docs/knowledge/

If you are operating projects day to day:

  • use docs/cli/ and the mainsequence --help command tree

If you need the exact SDK surface:

  • use docs/reference/

Package metadata

  • Package name: mainsequence
  • Python: >=3.11
  • CLI entry point: mainsequence

Project metadata is defined in pyproject.toml.

License

This repository is distributed under the terms described in LICENSE.

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