Changelog#
All notable changes to CVXlab will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
[Unreleased]#
Changed#
Modified Identity matrix constant: now it accepts one single set as dimensional argument.
Python ≥ 3.11 required: bumped
requires-pythonfrom>=3.8; removedfrom __future__ import annotationsacross the codebase.Frontend package added: new
frontend/package providing a guided CLI for model setup and interaction. Public entry point iscvxlab.frontend.run(), which accepts allModel.__init__, solver, and frontend-only parameters, partitions them into typed groups, and drives an interactive menu loop. Key modules:interface(entry point and menu engine),session(SessionConfig/ModelStatedataclasses),actions(decorator-based@menu_actionregistry buildingMAIN_MENU), anddisplay(terminal UI helpers).Centralized
Defaults.LiteralTypes: sharedLiteraltype aliases consolidated intoDefaults.LiteralTypes, replacing scattered definitions across modules.Integrated-solving convergence refactored: reworked convergence algorithm in
Core.solve_integrated_problems()with newskip_tablesargument for selectively excluding tables from convergence checks.User-defined constants and operators: new template modules (
user_defined_constants.py,user_defined_operators.py) enabling custom symbolic extensions (GitHub issue #109).DataFrame / SQLite data-handling fixes: improved
util.normalize_dataframe()for NaN handling, fixed CSV reading for missing values, and correctedSQLManager.dataframe_to_table()string-type conversion.Pandas 2.3 compatibility: pinned
pandas==2.3.3, removed deprecatederrors='ignore'arguments, fixed boolean-import issues introduced by pandas 3.0.Advancing documentation: new
cvxlab.frontend.run()function auto-documented, …
Planned#
Stable 1.0.1 release.
API stabilization.
Complete documentation coverage.
First interface function to ease user interaction.
[1.0.1b1] - 17 December 2025#
Fixed#
Bug fix following 1.0.0b1 (incremented beta to 1.0.1b1)
[1.0.0b1] - 14 November 2025#
Added#
Modelclass for optimization problem managementSQLite-backed data management via
DatabaseandSQLManagerCVXPY integration for convex optimization solving
Support for independent and integrated (coupled) problem solving
Excel and YAML-based model settings definition
Symbolic expression parsing and validation
Initial set of built-in operators and constants
Basic logging and error handling framework
Documentation#
Initial user guide with workflow steps
API reference documentation
Tutorial: Simple model example
Installation guide
Contributing guidelines
Known Limitations#
Documentation under active development
API subject to change before 1.0.0 stable
Limited tutorial coverage
Limited test converage