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rosterops

A deterministic, configurable, Polars-based pharma roster processing and validation engine.

rosterops ingests a baseline roster (or a single snapshot) plus optional movement files — transfers, promotions, terminations, leave, hires/rehires, temporary coverage — normalizes them into a canonical model, reconstructs the expected roster as of a requested date, applies configurable business rules, and returns validated Polars DataFrames with audit-ready reports.

It is a local-first data-processing library and CLI. It never writes back to a CRM, HR system, or database, requires no network access, and never fabricates historical events from a single snapshot.

rosterops architecture and workflow

Status

Beta (Phases 0–8 complete). process and validate commands are implemented (Modes A/B), rules execute end-to-end, outputs include CSV/Parquet/JSON and rosterops_report.xlsx, reconciliation and movement metrics are computed, and the example scenario runs. See IMPLEMENTATION_PHASES.md for the full tracker and REQUIREMENTS.md for the operative specification.

Install

pip install -e ".[dev]"          # development
pip install -e ".[excel]"        # with Excel read/write support
pip install -e ".[pandas]"       # with pandas interop

Requires Python 3.10+. Core dependencies: polars, pydantic, PyYAML.

Quick look

rosterops --help
rosterops --version
rosterops rules list
rosterops rules describe TRF-002
rosterops validate-inputs --config examples/config/scenario.yaml
from rosterops import RosterConfig

config = RosterConfig.from_file("examples/config/scenario.yaml")
print(config.data.grain)

Documentation

  • REQUIREMENTS.md — operative requirements: modes, domain model, effective-date semantics, the 86-rule catalogue, outputs, security, testing.
  • IMPLEMENTATION_PHASES.md — phase-by-phase progress tracker with acceptance criteria, test matrices, and backlog.

Development

ruff check . && ruff format --check .
mypy src
pytest

License

MIT — see LICENSE.

Metadata

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