rpkbin 0.1.2

Personal collection of small scripts and helpers for work.

rpkbin — Core IC Design & Verification Utilities

rpkbin is a comprehensive toolkit providing essential data types and utilities for hardware design and verification flows.

Core Features

1. MapBV — BitVector with Bidirectional Mapping

MapBV allows you to define a hierarchy of bit-fields that stay synchronized automatically.

• Hierarchical Slicing: Define a 32-bit register and slice it into named fields.
• Bidirectional Linking: Use concat to build a new view from existing variables; updating the view updates the sources.
• Symbolic Evaluation: Use .eval() to test "what-if" scenarios without changing actual values.

Learn more in MapBV Documentation

2. NumBV — Bit-True Fixed-Point Arithmetic

Bit-exact fixed-point simulation for DSP pipeline verification. Pure NumPy, no external dependency.

• Two-layer API: Operator layer (+, *) for convenience; function layer (nbv.add(), nbv.mul()) for explicit pipeline staging.
• Five Rounding Modes: trunc, round, round_half_even (convergent, Xilinx DSP48), ceil, round_to_zero.
• Unified Operations: One NumBV class handles both scalar and array computations. Backed by NumPy by default, with an optional drop-in JAX backend for transparent XLA hardware acceleration.

Learn more in NumBV Documentation

3. Excel Extractor — Template-Based Extraction

Intelligently extract data from complex spreadsheets.

• Layout Description: Define the "shape" of data instead of hardcoded coordinates.
• Fuzzy Matching: Matches headers even with slight spelling variations.
• Merged Cell Support: Correctly resolves values spanning across merged rows/cols.

Learn more in Excel Extractor Documentation

4. Job Manager

A practical, cross-platform job manager for running shell commands and Python callables safely in parallel.

• One API for Common Workloads: Run local functions (FuncJob) and CLI tasks (CmdJob) with the same manager.
• Resource-Aware Scheduling: Limit concurrency by global resources such as GPU count or license tokens.
• Operationally Friendly: Built-in cancellation, retries, live logs, and callbacks for automation pipelines.

Job Manager Documentation

5. Wave — Batch Workflow Orchestration with Live TUI

A workflow layer built on top of Job Manager for declaring and observing long-running batch flows.

• Wave File Pattern: Declare jobs, parsers, and hooks in a plain Python file. Run it with rpk-wave run.
• Live TUI: A full-screen Textual interface with a job dashboard, per-job log/data/event panels, and a built-in command bar.
• Headless REPL: For CI or terminal sessions where a TUI isn't wanted — full inspection and control commands via stdin.
• Hooks & Parsers: React to log output, structured parsed data, elapsed time, or lifecycle events automatically.
• Job Events with Source Tracking: job.emit() records named events; source="system" marks internal errors (parser/hook failures) for easy filtering in the TUI.
• Operational Control: Pause/resume dispatch, gracefully stop jobs, force-cancel jobs, or target active jobs by tag from either the TUI command bar or headless REPL.
• Fast Job Inspection: Open show, logs, data, or events <job> directly in JOB DETAIL, then switch between jobs with [ / ] or between running jobs with { / }.
• Intentional Cancellation Semantics: User-cancelled jobs are reported as cancelled without turning the whole Wave run into a failed exit; real job failures and session timeouts still return a non-zero exit code.

Wave Documentation

Installation

# Core only (zero dependencies)
pip install -e .

# Install specific features
pip install -e .[wave]   # Installs textual, prompt_toolkit, rich
pip install -e .[excel]  # Installs openpyxl, xlrd, rapidfuzz
pip install -e .[cfg]    # Installs networkx

# Install everything
pip install -e .[all]

Testing

Run tests using pytest from the root directory:

pytest tests/ -v

(All tests require only numpy — no optional dependencies needed.)