Reference Manual

• Types and signatures
  • Rationale
  • Signatures
  • Basic types
    • Numbers
    • Arrays
    • Container Types
    • Functions
      • Wrapper Address Protocol - WAP
    • Miscellaneous Types
  • Advanced types
    • Inference
    • NumPy scalars
    • Arrays
    • Optional types
    • Python types
• Just-in-Time compilation
  • JIT functions
  • Generated JIT functions
  • Dispatcher objects
  • Vectorized functions (ufuncs and DUFuncs)
  • C callbacks
• Ahead-of-Time compilation
• Utilities
  • Dealing with pointers
• Environment variables
  • Jit flags
  • Debugging
  • Compilation options
  • Caching options
  • GPU support
  • Threading Control
• Supported Python features
  • Language
    • Constructs
    • Functions
      • Function calls
      • Functions as arguments
      • Inner function and closure
      • Recursive calls
    • Generators
    • Exception handling
      • raise statement
      • try .. except
      • try .. except .. else .. finally
  • Built-in types
    • int, bool
    • float, complex
    • str
    • tuple
    • homogeneous tuples
    • heterogeneous tuples
    • list
      • List Reflection
      • Initial Values
      • Typed List
      • Literal List
      • List comprehension
    • set
    • Typed Set
    • Typed Dict
      • Dictionary comprehension
      • Initial Values
    • Heterogeneous Literal String Key Dictionary
    • None
    • bytes, bytearray, memoryview
  • Built-in functions
    • Hashing
  • Standard library modules
    • array
    • cmath
    • collections
    • ctypes
    • enum
    • math
    • operator
    • functools
    • random
    • heapq
  • Third-party modules
    • cffi
• Supported NumPy features
• Array objects
  • The N-dimensional array (ndarray)
    • Array attributes
      • Memory layout:
      • Data type:
      • Other attributes:
    • Array methods
      • Array conversion:
      • Shape manipulation:
      • Item selection and manipulation:
      • Calculation:
    • Arithmetic, matrix multiplication, and comparison operations
    • Special methods
    • Literal arrays
  • Scalars
    • Built-in scalar types
    • Number
    • Integer types (signed)
    • Integer types (unsigned)
    • Inexact types
  • Array types
    • Array access
    • Structured array access
  • Iterating over arrays
  • Masked arrays
• Universal functions (ufunc)
  • ufunc
    • Limitations
  • Available ufuncs
    • Math operations
    • Trigonometric functions
    • Bit-twiddling functions
    • Comparison functions
    • Floating functions
• Routines
  • Array creation routines
  • Array manipulation routines
  • Datetime support functions
  • Data type routines
  • Indexing routines
  • Linear algebra (numpy.linalg)
  • Logic functions
  • Mathematical functions
  • Miscellaneous routines
  • Polynomials
  • Random sampling (numpy.random)
    • Generator objects
    • RandomState and legacy random number generation
    • Initialization
    • Simple random data
    • Permutations
    • Distributions
  • Set routines
  • Sorting, searching, and counting
  • Statistics
  • Window functions
  • Record subtyping
• Deviations from Python Semantics
  • Bounds Checking
  • Exceptions and Memory Allocation
  • Integer width
  • Boolean inversion
  • Global and closure variables
  • Zero initialization of variables
• Floating-point pitfalls
  • Precision and accuracy
    • Math library implementations
    • Linear algebra
    • Mixed-types operations
  • Warnings and errors
• Deprecation Notices
  • Suppressing Deprecation warnings
  • Deprecation of reflection for List and Set types
    • Reason for deprecation
    • Example(s) of the impact
    • Schedule
    • Recommendations
    • Expected Replacement
  • Deprecation of the numba.pycc module
    • Reason for deprecation
    • Example(s) of the impact
    • Schedule
    • Recommendations
    • Replacement
  • Deprecation and removal of CUDA Toolkits < 11.2 and devices with CC < 5.0
    • Recommendations
    • Schedule
  • Deprecation of the built-in CUDA target
    • Reason for deprecation
    • Impact
    • Recommendations
    • Schedule
• Support Policy
  • Definitions:
  • Support Tiers:
    • Tier 1: Releases that are maintained by the Numba maintainers
    • Tier 1.5: Experimental releases for emerging release configurations
    • Tier 2a: Releases that are built by large software distributors
    • Tier 2b: General community support
  • How to move Tiers?
  • Additional Accelerator and Special Hardware support
• AI Tool Use Policy
  • Policy
  • Details
  • Extractive Contributions
  • Handling Violations
  • Copyright
  • Exceptions
  • References