4. Developer Manual

• 4.1. Contributing to Numba
  • 4.1.1. Communication
    • 4.1.1.1. Mailing-list
    • 4.1.1.2. Bug tracker
  • 4.1.2. Getting set up
    • 4.1.2.1. Build environment
    • 4.1.2.2. Building Numba
    • 4.1.2.3. Running tests
  • 4.1.3. Development rules
    • 4.1.3.1. Code reviews
    • 4.1.3.2. Coding conventions
    • 4.1.3.3. Stability
    • 4.1.3.4. Platform support
  • 4.1.4. Documentation
    • 4.1.4.1. Main documentation
    • 4.1.4.2. Web site homepage
• 4.2. Numba Architecture
  • 4.2.1. Introduction
  • 4.2.2. Contexts
  • 4.2.3. Compiler Stages
    • 4.2.3.1. Stage 1: Analyze Bytecode
    • 4.2.3.2. Stage 2: Generate the Numba IR
    • 4.2.3.3. Stage 3: Macro expansion
    • 4.2.3.4. Stage 4: Infer Types
    • 4.2.3.5. Stage 5a: Generate No-Python LLVM IR
    • 4.2.3.6. Stage 5b: Generate Object Mode LLVM IR
    • 4.2.3.7. Stage 6: Compile LLVM IR to Machine Code
• 4.3. Notes on generators
  • 4.3.1. Terminology
  • 4.3.2. Function analysis
  • 4.3.3. The generator structure
    • 4.3.3.1. Layout
    • 4.3.3.2. Allocation
  • 4.3.4. Compiling to native code
    • 4.3.4.1. The next() function
• 4.4. Extending the Numba Frontend
  • 4.4.1. Overview
    • 4.4.1.1. Numba Types
    • 4.4.1.2. Type Inference Mechanism
  • 4.4.2. Tutorial
    • 4.4.2.1. Creating a New Numba Type
    • 4.4.2.2. Organizing Type Signatures with a Registry
    • 4.4.2.3. Adding an Attribute Value Type Signature
    • 4.4.2.4. Adding a Function Type Signature
    • 4.4.2.5. Overloading Elementary Operations
    • 4.4.2.6. Installing the Registry in a Typing Context
    • 4.4.2.7. Enabling Type Inference for Function Arguments and Globals
  • 4.4.3. Conclusion
• 4.5. Extending the Numba backend
  • 4.5.1. Helper Lib
  • 4.5.2. Python API
  • 4.5.3. Target Interval Objects
  • 4.5.4. Base Target