bhavishyagopesh

Frontend Development

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bhavishyagopesh

/* Update interpreter state based on supplied configuration settings
 *
 * After calling this function, most of the restrictions on the interpreter
 * are lifted. The only remaining incomplete settings are those related
 * to the main module (sys.argv[0], __main__ metadata)
 *
 * Calling this when the interpreter is not initializing, is already
 * initialized or without a valid current thread state is a fatal error.
 * Other errors should be reported as normal Python exceptions with a
 * non-zero return code.

bhavishyagopesh

void
Py_InitializeEx(int install_sigs)
{
    PyInterpreterState *interp;
    PyThreadState *tstate;
    PyObject *bimod, *sysmod;
    char *p;
    char *icodeset = NULL; /* On Windows, input codeset may theoretically
                              differ from output codeset. */
    char *codeset = NULL;

bhavishyagopesh

static PyObject *
run_mod(mod_ty mod, const char *filename, PyObject *globals, PyObject *locals,
         PyCompilerFlags *flags, PyArena *arena)
{
    PyCodeObject *co;
    PyObject *v;
    co = PyAST_Compile(mod, filename, flags, arena);
    if (co == NULL)
        return NULL;
    v = PyEval_EvalCode(co, globals, locals);

bhavishyagopesh

static PyObject *
run_mod(mod_ty mod, PyObject *filename, PyObject *globals, PyObject *locals,
            PyCompilerFlags *flags, PyArena *arena)
{
    PyCodeObject *co;
    PyObject *v;
    co = PyAST_CompileObject(mod, filename, flags, -1, arena);
    if (co == NULL)
        return NULL;
    v = PyEval_EvalCode((PyObject*)co, globals, locals);

bhavishyagopesh

"""
Benchmark threading module.
"""

# FIXME : notify hangs

import perf
from six.moves import xrange
import threading

bhavishyagopesh

"""
Benchmark concurrency.
"""

import perf
from six.moves import xrange
import threading
import multiprocessing

def add_cmdline_args(cmd, args):

bhavishyagopesh

The above script tries to benchmark "Concurrency" implemented using threading and multiprocessing.Actually "threads" in cpython are restricted by "GIL"
,so it's not actually concurrent...On the other hand "multiprocessing" module creates whole different processes but there is substaintial cost involved in 
spawing a whole new process.

So the there is a trade-off involved which is evident as we increase "CRUNCH_NO" variable.

But the benchmark actually tries to compare the same phenomenon in py2 and py3.And py2 looks faster here.

I'm adding two graphs comparing the timings for py2 and py3.

bhavishyagopesh

import perf
from six.moves import xrange
def add_cmdline_args(cmd, args):
    if args.benchmark:
        cmd.append(args.benchmark)

CRUNCH_NO=10000000
def bench_number_crunching(loops):
    range_it = xrange(loops)
    t0 = perf.perf_counter()

bhavishyagopesh

"""
Benchmark zlib module.
"""


import perf
from six.moves import xrange
import zlib
import binascii