Installs a few cmake ingredients, along with a build assistant xo-build
for XO projects such as this one.
$ xo-build --clone --configure --build --install xo-indentlog
$ xo-build --clone --configure --build --install xo-refnct
$ xo-build --clone --configure --build --install xo-subsys
$ xo-build --clone --configure --build --install xo-reflect
$ xo-build --clone --configure --build --install xo-expression
$ xo-build --clone --configure --build --install xo-jit
$ xo-build --clone --configure --build --install xo-pyutil
$ xo-build --clone --configure --build --install xo-pyexpression
note: can use xo-build -n
to dry-run here
$ xo-build --clone xo-pyjit
or equivalently
$ git clone [email protected]:Rconybea/xo-pyjit.git
$ xo-build --configure --build --install xo-pyjit
or equivalently:
$ PREFIX=/usr/local # or preferred install location
$ cmake -DCMAKE_INSTALL_PREFIX=$PREFIX -S xo-pyjit -B xo-pyjit/.build
$ cmake --build xo-pyjit/.build -j
$ cmake --install xo-pyjit/.build
(also see .github/workflows/main.yml)
Assumes xo-pyjit
installed to ~/local2/lib
,
i.e. built with PREFIX=~/local2
.
PYTHONPATH=~/local2/lib:$PYTHONPATH python
>>> from xo_pyreflect import *
>>> from xo_pyjit import *
>>> from xo_pyexpression import *
create a jit from within python
>>> mp=MachPipeline.make()
>>> mp.dump_execution_sesion()
JITDylib "<main>" (ES: 0x0000000000446ee0, State = Open)
Link order: [ ("<main>", MatchAllSymbols) ]
Symbol table:
build an AST from within python
>>> f64_t=TypeDescr.lookup_by_name('double')
>>> x=make_var('x',f64_t) # "x" a variable (context not yet known)
>>> f1=make_sin_pm() # "sin()"
>>> c1=make_apply(f1,[x]) # "sin(x)"
>>> f2=make_cos_pm() # "cos()"
>>> c2=make_apply(f2,[c1]) # "cos(sin(x))"
>>> lm=make_lambda('foo', [x], c2) # "def foo(x): cos(sin(x))"
>>> lm
<Lambda :name foo :argv [x] :body <Apply :fn <Primitive :name cos :type "double (*)(double)" :value 1> :argv "[<Apply :fn <Primitive :name sin :type \"double (*)(double)\" :value 1> :argv \"[<Variable :name x>]\">]">>
generate llvm IR for our AST
>>> code=mp.codegen(lm)
>>> print(code.print())
define double @foo(double %x) {
entry:
%calltmp = call double @sin(double %x)
%calltmp1 = call double @cos(double %calltmp)
ret double %calltmp1
}
generate machine code for our AST, lookup compiled function so we can invoke it directly
>>> mp.machgen_current_module()
>>> mp.dump_execution_session()
JITDylib "<main>" (ES: 0x0000000000446ee0, State = Open)
Link order: [ ("<main>", MatchAllSymbols) ]
Symbol table:
"foo": <not resolved> [Callable] Never-Searched (Materializer 0x646fe0, xojit)
>>> fn=mp.lookup_fn('double (*)(double, double)', 'foo')
>>> mp.dump_execution_session()
JITDylib "<main>" (ES: 0x0000000000446ee0, State = Open)
Link order: [ ("<main>", MatchAllSymbols) ]
Symbol table:
"cos": 0x7ffff7926670 [Data] Ready
"foo": 0x7fffee2b6000 [Callable] Ready
"sin": 0x7ffff7925e50 [Data] Ready
invoke just-compiled code!
>>> fn(22)
0.999960827417674
Limited utility: requires that supporting libraries (e.g. xo_pyexpression
) appear in PYTHONPATH
$ cd xo-pyjit/.build/src/pyjit
$ python
>>> import xo_pyjit
$ cd xo-pyexpression
$ cmake -DCMAKE_BUILD_TYPE=coverage -DENABLE_TESTING=on -S . -B .build-ccov
$ cmake --build .build-ccov -j
LSP looks for compile commands in the root of the source tree; while Cmake creates them in the root of its build directory.
$ cd xo-pyexpression
$ ln -s .build/compile_commands.json # supply compile commands to LSP
-L
list variables-A
include 'advanced' variables-H
include help text
$ cd xo-pyjit/.build
$ cmake -LAH