CVXPY is a Python-embedded domain-specific language (DSL) for convex optimization, designed to simplify the process of formulating and solving convex optimization problems. It allows users to express problems in a natural, math-like syntax, which is then automatically converted into the standard form required by generic solvers. CVXPY supports high-level Python features such as parallelism and object-oriented design, making it easy to integrate with other Python tools. The language is based on CVX but introduces new features like signed disciplined convex programming (DCP) analysis and parameters. CVXPY interfaces with open-source cone solvers such as CVXOPT, ECOS, and SCS, each with different characteristics. The language also supports object-oriented approaches to constructing optimization problems, enabling more flexible and reusable code. CVXPY has been widely used and has been the subject of multiple courses and extensions, including an extension for stochastic optimization.CVXPY is a Python-embedded domain-specific language (DSL) for convex optimization, designed to simplify the process of formulating and solving convex optimization problems. It allows users to express problems in a natural, math-like syntax, which is then automatically converted into the standard form required by generic solvers. CVXPY supports high-level Python features such as parallelism and object-oriented design, making it easy to integrate with other Python tools. The language is based on CVX but introduces new features like signed disciplined convex programming (DCP) analysis and parameters. CVXPY interfaces with open-source cone solvers such as CVXOPT, ECOS, and SCS, each with different characteristics. The language also supports object-oriented approaches to constructing optimization problems, enabling more flexible and reusable code. CVXPY has been widely used and has been the subject of multiple courses and extensions, including an extension for stochastic optimization.