.. _cli: 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. .. _cli_usage: Usage ----- 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: :ref:`numba-source-install-check`. 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. .. _cli_help: Help ---- 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] [filename] 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 .. _cli_sysinfo: 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: __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) .. _cli_debug: Debugging --------- 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 @numba.jit def f(x): return 2 * x f(42) 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