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Financial markets ORM, engines, and application management extensions for Main Sequence.

Project description

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MainSequence Markets

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ms-markets is the financial markets extension layer for the Main Sequence platform. It provides reusable market-domain ORM models, market DataNodes, portfolio construction utilities, repository operations, and application-facing helpers for building financial systems on top of Main Sequence. QuantLib-backed pricing is an optional package surface, not part of the core msm import package.

The Python distribution is named ms-markets. The import package is intentionally short:

import msm

Project Status

The initial core package was migrated from mainsequence-sdk/mainsequence/markets into this repository under src/msm. Architecture and implementation decisions are tracked in Architecture Decision Records.

What This Repository Contains

Main package areas:

  • msm.accounts: account identity, holdings, virtual funds, and account target assignments
  • msm.api: user-facing Pydantic row objects and typed class methods for markets MetaTable records
  • msm.client: client-facing Main Sequence market models and API wrappers
  • msm.data_nodes: market DataNode contracts, including asset snapshots and asset pricing details
  • msm.execution: order managers, target quantities, orders, events, trades, and execution errors
  • msm.models: SQLAlchemy market-domain *Table declarations and MetaTable registration order
  • msm.portfolios: portfolio configuration, signal weights, rebalance strategies, and Virtual Fund Builder workflows
  • msm_pricing: optional QuantLib-backed instruments, curves, fixings, and pricing helpers installed with the pricing extra
  • msm.repositories: compiled persistence operations over market-domain models
  • msm.services: application-level orchestration over repositories, including asset lookup and OpenFIGI service helpers
  • msm CLI: package maintenance helpers such as explicit agent-skill copying

Repository areas:

  • docs/: MkDocs documentation, tutorials, knowledge guides, ADRs, and API reference scaffold
  • examples/: migrated market examples from the SDK
  • .agents/skills/ms_markets/: source agent skills for market-domain workflows
  • tests/: automated tests
  • src/msm/.agents/ms_markets/: packaged agent-skill bundle installed with the wheel

Documentation Map

The documentation is organized into four reading modes:

  1. Tutorial: guided learning material
  2. Knowledge: concept-oriented guides for each msm package area
  3. Architecture: ADRs that record implementation decisions
  4. Reference: generated API reference scaffold

Recommended entry points:

Quick Start

Install the package from this repository in editable mode:

python -m pip install -e ".[dev]"

Or with uv:

uv sync --extra dev

Install pricing support only when needed:

uv sync --extra pricing

Install the project-level FastAPI surface only when needed:

uv sync --extra public_api

Verify the core import:

python -c "import msm; print(msm.__version__)"

After installing the pricing extra, verify the optional pricing import:

python -c "import msm_pricing; print(msm_pricing.FixedRateBond)"

Copy the packaged ms-markets skills into a host Main Sequence project only when you explicitly want them available to agents in that project:

msm copy-msm-skills --path /path/to/project

Importing msm never mutates the current directory or auto-copies skills. The command writes only to <project>/.agents/skills/ms_markets/ and leaves unrelated .agents content alone. Use --dry-run or --json to inspect the copy plan.

Common Development Commands

Run tests:

pytest

Run focused linting for optional pricing:

ruff check src/msm_pricing

Serve the docs locally:

mkdocs serve

Build the docs:

mkdocs build --strict

Build the package:

uv build

Publish a tagged release to PyPI:

git tag v0.0.2
git push origin v0.0.2

Pushing a v* tag triggers .github/workflows/publish-to-pypi.yml, which builds the distribution and publishes it to PyPI through GitHub Actions using trusted publishing for the repository pypi environment.

Core Dependencies

Runtime dependencies are declared in pyproject.toml. The core stack starts with:

  • mainsequence for platform integration
  • SQLAlchemy for market-domain ORM models
  • pydantic for typed configuration and serialized row contracts
  • pandas and numpy for tabular market data and portfolio workflows

Optional extras provide documentation, development, portfolio, public API, pricing, and Streamlit UI tooling. The public_api extra installs FastAPI and Uvicorn for the project-level apps/v1 surface. The pricing and pricing-streamlit extras install QuantLib and the optional pricing runtime exposed as msm_pricing.

Package Metadata

Project metadata is defined in pyproject.toml.

License

This project is open source under the Apache License 2.0.

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