ms-markets 0.0.97

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

MainSequence Markets

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. Portfolio and QuantLib-backed pricing capabilities are packaged as separate import surfaces so core msm stays focused on shared markets primitives.

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

import msm

Portfolio workflows import from msm_portfolios. Optional QuantLib-backed pricing imports from msm_pricing.

Project Status

• Status: initial scaffold and SDK extraction
• Current package version: 0.0.18
• Documentation: Documentation Site
• Open issues: GitHub Issues
• Release history: CHANGELOG.md
• License: Apache License 2.0

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.api.accounts: account identity and account target assignment row APIs
• msm.api.calendars: calendar identity, date, session, and event row APIs
• msm.api: user-facing Pydantic row objects and typed class methods for markets MetaTable records
• msm.constants: static built-in keys such as asset type constants used across applications and examples
• msm.client: client-facing Main Sequence market models and API wrappers
• msm.data_nodes: market DataNode contracts, including account holdings, execution events, asset snapshots, and asset pricing details
• msm.api.execution: order managers, target quantities, orders, events, trades, and execution error row APIs
• msm.models: SQLAlchemy market-domain *Table declarations and MetaTable registration order
• msm_portfolios: portfolio configuration, signal weights, rebalance strategies, virtual funds, and portfolio construction workflows
• msm_pricing: optional QuantLib-backed instruments, curves, fixings, pricing helpers, and pure-data analytics installed with pricing or analytics extras
• 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 and SDK-managed MetaTable migration commands

Repository areas:

• docs/: MkDocs documentation, tutorials, knowledge guides, ADRs, and API reference scaffold
• examples/msm/: core assets, accounts, calendars, derived indexes, platform, and row-workflow examples
• examples/msm_portfolios/: single portfolio construction example with index linkage and canonical portfolio DataNodes
• examples/msm_pricing/: optional pricing and QuantLib-backed examples
• .agents/skills/ms_markets/: source agent skills for market-domain workflows
• tests/: automated tests

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:

• Getting Started
• Tutorial
• FastAPI v1
• Command Center
• Knowledge Base
• Architecture Decision Records
• Changelog
• API Reference

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 named analytics surface when working with optional spread analytics:

uv sync --extra analytics

Install portfolio workflow support only when needed:

uv sync --extra portfolios

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

Optional extras provide analytics, documentation, development, portfolio, public API, and pricing tooling. The analytics and pricing-analytics extras reserve the dependency boundary for optional analytics helpers; the current spread helpers use the core numpy and pandas dependencies. The portfolios extra installs portfolio-only helpers such as pandas-market-calendars. The public_api extra installs FastAPI and Uvicorn for the project-level apps/v1 surface. The pricing extra installs QuantLib and the optional pricing runtime exposed as msm_pricing.

Package Metadata

• Distribution name: ms-markets
• Import packages: msm, msm_portfolios, and optional msm_pricing
• Python: >=3.11
• License: Apache-2.0
• Repository: https://github.com/mainsequence-projects/MainSequenceMarkets

Project metadata is defined in pyproject.toml.

License

This project is open source under the Apache License 2.0.