What sparsediff is | Building an expression graph | Assembling a problem and its derivative oracle | Evaluating value and derivatives | Parameters and fast re-evaluation | Where to go next

Introduction | The mathematical setup | What the package computes | Example 1: a linear program | Example 2: a second-order-cone program | Example 3: a small semidefinite program | A practical sensitivity-analysis example | Forward versus adjoint: when to use each | Choosing dense versus lsqr | Conventions | Connection to CVXR | Citation

What sparsediff is | Building an expression graph | Assembling a problem and its derivative oracle | Evaluating value and derivatives | Parameters and fast re-evaluation | Where to go next

Introduction | Example 1: A Production Planning LP | Example 2: The Knapsack Problem | Example 3: N-Queens Problem | Example 4: Circle Packing (Quadratic Constraints) | Example 5: Facility Location (Mixed-Integer) | Example 6: Indicator Constraints | Solver Controls | References

Introduction | 1. Basic Quadratic Program Example | 1.1. Objective function | 1.2. Constraints | 1.3. Solution | 2. Basic Second-order Cone Programming Example | 2.1. Objective function | 2.2. Constraints | 2.3. Solution | 3. Semidefinite Cone Programming | 3.1. Example | 4. Updating Problem Data (Warm Starts) | 4.1. Example: SDP with a changed constraint | 5. Cone Specifications | 6. Control parameters

1. Introduction | 2. The Problem Solver Interface | 3. The Solver Model Object | Updating problem data and re-solving | 4. Dense and Sparse Interfaces | 5. Another Example | 6. Solver parameters

Introduction | Migrating from osqp < 1.0 | Setup and Solve | Convenience Function | Updating Problem Data | Updating Vectors | Updating Matrices | Warm Starting | Solver Settings | Key Settings | Updating Settings | Retrieving Problem Dimensions | Result Object | Status Values | Example: Lasso Regression | Example: Portfolio Optimization | Sparse Matrix Input | References