equicompiler-algebraic-portfolio-dsl-to-/README.md

EquiCompiler: Algebraic Portfolio DSL to Verifiable Low-Latency Compiler (MVP)

Overview

• This repository contains a minimal, production-ready MVP for a compiler stack that translates a domain-specific language for market strategies into a portable, verifiable execution graph. The MVP focuses on a small, well-formed core to enable safe extension by additional agents in the swarm.

What you get in this MVP

• A small DSL parser that reads a concise DSL and converts it into a canonical in-memory IR (EquiIR) represented as Python dicts.
• A minimal Python package equicompiler_algebraic_portfolio_dsl_to_ with a core module and a CLI entry point.
• A tiny test suite to validate DSL parsing and IR generation.
• A test runner (test.sh) that executes tests and builds the package to verify packaging metadata.

Usage

• DSL to IR (programmatic): from equicompiler_algebraic_portfolio_dsl_to_.core import parse_dsl_to_ir dsl = "assets: AAPL, MSFT, GOOG\nobjectives: maximize_return\nconstraints: max_drawdown=0.2, var=0.95" ir = parse_dsl_to_ir(dsl) print(ir)

• CLI (Python module): python -m equicompiler_algebraic_portfolio_dsl_to_.cli path/to/dsl_file.txt

Project structure

• AGENTS.md: architecture and testing guidelines for future agents
• README.md: this file
• pyproject.toml: packaging metadata
• equicompiler_algebraic_portfolio_dsl_to_/ (package)
  • init.py
  • core.py: DSL -> IR parser (minimal)
  • cli.py: CLI entry point
• tests/test_core.py: small unit test for DSL parsing
• test.sh: test runner to validate test suite and packaging

Development notes

• The MVP intentionally keeps dependencies minimal to ensure fast iterations and deterministic tests.
• When adding features, try to keep changes small and focused on a single goal.
• Ensure tests cover the new functionality and avoid sensitive data in tests.

Next steps

• Implement a more expressive DSL and a richer IR (EquiIR) representation.
• Add more tests for edge cases and simple integration tests for the CLI.
• Expand packaging metadata and README with a longer developer and user guide.

This README intentionally stays light; the AGENTS.md contains the deeper architectural notes for the SWARM collaborators.