You are viewing archived documentation from the old Numba documentation site. The current documentation is located at https://numba.readthedocs.io.

Command line interface

Numba is a Python package, usually you import numba from Python and use the Python application programming interface (API). However, Numba also ships with a command line interface (CLI), i.e. a tool numba that is installed when you install Numba.

Currently, the only purpose of the CLI is to allow you to quickly show some information about your system and installation, or to quickly get some debugging information for a Python script using Numba.


To use the Numba CLI from the terminal, use numba followed by the options and arguments like --help or -s, as explained below.

Sometimes it can happen that you get a “command not found” error when you type numba, because your PATH isn’t configured properly. In that case you can use the equivalent command python -m numba. If that still gives “command not found”, try to import numba as suggested here: Dependency List.

The two versions numba and python -m numba are the same. The first is shorter to type, but if you get a “command not found” error because your PATH doesn’t contain the location where numba is installed, having the python -m numba variant is useful.

To use the Numba CLI from IPython or Jupyter, use !numba, i.e. prefix the command with an exclamation mark. This is a general IPython/Jupyter feature to execute shell commands, it is not available in the regular python terminal.


To see all available options, use numba --help:

$ numba --help
usage: numba [-h] [--annotate] [--dump-llvm] [--dump-optimized]
             [--dump-assembly] [--dump-cfg] [--dump-ast]
             [--annotate-html ANNOTATE_HTML] [-s]

positional arguments:
  filename              Python source filename

optional arguments:
  -h, --help            show this help message and exit
  --annotate            Annotate source
  --dump-llvm           Print generated llvm assembly
  --dump-optimized      Dump the optimized llvm assembly
  --dump-assembly       Dump the LLVM generated assembly
  --dump-cfg            [Deprecated] Dump the control flow graph
  --dump-ast            [Deprecated] Dump the AST
  --annotate-html ANNOTATE_HTML
                        Output source annotation as html
  -s, --sysinfo         Output system information for bug reporting

System information

The numba -s (or the equivalent numba --sysinfo) command prints a lot of information about your system and your Numba installation and relevant dependencies.

Remember: you can use !numba -s with an exclamation mark to see this information from IPython or Jupyter.

Example output:

$ numba -s

System info:
__Time Stamp__
2019-05-07 14:15:39.733994

__Hardware Information__
Machine                                       : x86_64
CPU Name                                      : haswell
CPU count                                     : 8
CPU Features                                  :
aes avx avx2 bmi bmi2 cmov cx16 f16c fma fsgsbase invpcid lzcnt mmx movbe pclmul
popcnt rdrnd sahf sse sse2 sse3 sse4.1 sse4.2 ssse3 xsave xsaveopt

__OS Information__
Platform                                      : Darwin-18.5.0-x86_64-i386-64bit
Release                                       : 18.5.0
System Name                                   : Darwin
Version                                       : Darwin Kernel Version 18.5.0: Mon Mar 11 20:40:32 PDT 2019; root:xnu-4903.251.3~3/RELEASE_X86_64
OS specific info                              : 10.14.4   x86_64

__Python Information__
Python Compiler                               : Clang 4.0.1 (tags/RELEASE_401/final)
Python Implementation                         : CPython
Python Version                                : 3.7.3
Python Locale                                 : en_US UTF-8

__LLVM information__
LLVM version                                  : 7.0.0

__CUDA Information__
CUDA driver library cannot be found or no CUDA enabled devices are present.
Error class: <class 'numba.cuda.cudadrv.error.CudaSupportError'>

__ROC Information__
ROC available                                 : False
Error initialising ROC due to                 : No ROC toolchains found.
No HSA Agents found, encountered exception when searching:
Error at driver init:

HSA is not currently supported on this platform (darwin).

__SVML Information__
SVML state, config.USING_SVML                 : False
SVML library found and loaded                 : False
llvmlite using SVML patched LLVM              : True
SVML operational                              : False

__Threading Layer Information__
TBB Threading layer available                 : False
+--> Disabled due to                          : Unknown import problem.
OpenMP Threading layer available              : False
+--> Disabled due to                          : Unknown import problem.
Workqueue Threading layer available           : True

__Numba Environment Variable Information__
None set.

__Conda Information__
conda_build_version                           : 3.17.8
conda_env_version                             : 4.6.14
platform                                      : osx-64
python_version                                : 3.7.3.final.0
root_writable                                 : True

__Current Conda Env__
(output truncated due to length)


As shown in the help output above, the numba command includes options that can help you to debug Numba compiled code.

To try it out, create an example script called myscript.py:

import numba

def f(x):
    return 2 * x


and then execute one of the following commands:

$ numba myscript.py --annotate
$ numba myscript.py --annotate-html myscript.html
$ numba myscript.py --dump-llvm
$ numba myscript.py --dump-optimized
$ numba myscript.py --dump-assembly