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2.1. Numba Types
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2. Reference Manual
¶
2.1. Numba Types
2.1.1. Basic Types
2.1.1.1. Numbers
2.1.1.2. Arrays
2.1.2. Advanced Types
2.1.2.1. Numpy scalars
2.1.2.2. Arrays
2.1.2.3. Optional types
2.2. Compilation
2.2.1. JIT functions
2.2.2. Vectorized functions (ufuncs)
2.3. Environment variables
2.3.1. Errors and warnings display
2.3.2. Debugging
2.3.3. Compilation options
2.3.4. GPU support
2.4. Supported Python features
2.4.1. Language
2.4.1.1. Constructs
2.4.1.2. Function calls
2.4.1.3. Generators
2.4.2. Built-in types
2.4.2.1. int, bool
2.4.2.2. float, complex
2.4.2.3. tuple
2.4.2.4. None
2.4.2.5. bytes, bytearray, memoryview
2.4.3. Built-in functions
2.4.4. Standard library modules
2.4.4.1.
array
2.4.4.2.
cmath
2.4.4.3.
ctypes
2.4.4.4.
math
2.4.4.5.
operator
2.4.4.6.
random
2.4.5. Third-party modules
2.4.5.1.
cffi
2.5. Supported Numpy features
2.5.1. Scalar types
2.5.2. Array types
2.5.2.1. Operations
2.5.2.2. Attributes
2.5.2.3. Methods
2.5.3. Functions
2.5.4. Modules
2.5.4.1.
random
2.5.4.1.1. Initialization
2.5.4.1.2. Simple random data
2.5.4.1.3. Permutations
2.5.4.1.4. Distributions
2.5.5. Standard ufuncs
2.5.5.1. Limitations
2.5.5.2. Math operations
2.5.5.3. Trigonometric functions
2.5.5.4. Bit-twiddling functions
2.5.5.5. Comparison functions
2.5.5.6. Floating functions
2.6. Deviations from Python semantics
2.6.1. Integer width
2.6.2. Global and closure variables