Numba documentation

This is the Numba documentation. Unless you are already acquainted with Numba, we suggest you start with the User manual.

• 1. User Manual
  • 1.1. Overview
  • 1.2. Getting started
  • 1.3. Compiling Python code with @jit
  • 1.4. Flexible specializations with @generated_jit
  • 1.5. Creating Numpy universal functions
  • 1.6. Compiling python classes with @jitclass
  • 1.7. Creating C callbacks with @cfunc
  • 1.8. Compiling code ahead of time
  • 1.9. Automatic parallelization with @jit
  • 1.10. Troubleshooting and tips
  • 1.11. Frequently Asked Questions
  • 1.12. Examples
• 2. Reference Manual
  • 2.1. Types and signatures
  • 2.2. Just-in-Time compilation
  • 2.3. Ahead-of-Time compilation
  • 2.4. Utilities
  • 2.5. Environment variables
  • 2.6. Supported Python features
  • 2.7. Supported NumPy features
  • 2.8. Deviations from Python semantics
  • 2.9. Floating-point pitfalls
• 3. Numba for CUDA GPUs
  • 3.1. Overview
  • 3.2. Writing CUDA Kernels
  • 3.3. Memory management
  • 3.4. Writing Device Functions
  • 3.5. Supported Python features in CUDA Python
  • 3.6. Supported Atomic Operations
  • 3.7. Random Number Generation
  • 3.8. Device management
  • 3.9. The Device List
  • 3.10. Examples
  • 3.11. Debugging CUDA Python with the the CUDA Simulator
  • 3.12. GPU Reduction
  • 3.13. CUDA Ufuncs and Generalized Ufuncs
  • 3.14. Sharing CUDA Memory
  • 3.15. CUDA Frequently Asked Questions
• 4. CUDA Python Reference
  • 4.1. CUDA Host API
  • 4.2. CUDA Kernel API
  • 4.3. Memory Management
• 5. Numba for HSA APUs
  • 5.1. Overview
  • 5.2. Writing HSA Kernels
  • 5.3. Memory management
  • 5.4. Writing Device Functions
  • 5.5. Supported Atomic Operations
  • 5.6. Device management
  • 5.7. Examples
• 6. Extending Numba
  • 6.1. High-level extension API
  • 6.2. Low-level extension API
  • 6.3. Example: an interval type
• 7. Developer Manual
  • 7.1. Contributing to Numba
  • 7.2. Numba architecture
  • 7.3. Polymorphic dispatching
  • 7.4. Notes on generators
  • 7.5. Notes on Numba Runtime
  • 7.6. Using the Numba Rewrite Pass for Fun and Optimization
  • 7.7. Live Variable Analysis
  • 7.8. Listings
• 8. Numba Enhancement Proposals
  • 8.1. Implemented proposals
  • 8.2. Other proposals
• 9. Glossary
• 10. Release Notes
  • 10.1. Version 0.34.0
  • 10.2. Version 0.33.0
  • 10.3. Version 0.32.0
  • 10.4. Version 0.31.0
  • 10.5. Version 0.30.1
  • 10.6. Version 0.30.0
  • 10.7. Version 0.29.0
  • 10.8. Version 0.28.1
  • 10.9. Version 0.28.0
  • 10.10. Version 0.27.0
  • 10.11. Version 0.26.0
  • 10.12. Version 0.25.0
  • 10.13. Version 0.24.0
  • 10.14. Version 0.23.1
  • 10.15. Version 0.23.0
  • 10.16. Version 0.22.1
  • 10.17. Version 0.22.0
  • 10.18. Version 0.21.0
  • 10.19. Version 0.20.0
  • 10.20. Version 0.19.2
  • 10.21. Version 0.19.1
  • 10.22. Version 0.19.0
  • 10.23. Version 0.18.2
  • 10.24. Version 0.18.1
  • 10.25. Version 0.17.0
  • 10.26. Version 0.16.0
  • 10.27. Version 0.15.1
  • 10.28. Version 0.15
  • 10.29. Version 0.14
  • 10.30. Version 0.13.4
  • 10.31. Version 0.13.3
  • 10.32. Version 0.13.2
  • 10.33. Version 0.13.1
  • 10.34. Version 0.13
  • 10.35. Version 0.12.2
  • 10.36. Version 0.12.1
  • 10.37. Version 0.12
  • 10.38. Version 0.11
  • 10.39. Version 0.10
  • 10.40. Version 0.9
  • 10.41. Version 0.8
  • 10.42. Version 0.7.2
  • 10.43. Version 0.7.1
  • 10.44. Version 0.7
  • 10.45. Version 0.6.1
  • 10.46. Version 0.6
  • 10.47. Version 0.5
  • 10.48. Version 0.4
  • 10.49. Version 0.3.2
  • 10.50. Version 0.3
  • 10.51. Version 0.2