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2to3.py	101 B	-rw-rw-rw-
abitype.py	5.64 KB	-rw-rw-rw-
analyze_dxp.py	4.21 KB	-rw-rw-rw-
byext.py	3.94 KB	-rw-rw-rw-
byteyears.py	1.67 KB	-rw-rw-rw-
checkpip.py	825 B	-rw-rw-rw-
cleanfuture.py	8.69 KB	-rw-rw-rw-
combinerefs.py	4.48 KB	-rw-rw-rw-
copytime.py	689 B	-rw-rw-rw-
crlf.py	655 B	-rw-rw-rw-
db2pickle.py	3.68 KB	-rw-rw-rw-
diff.py	2.26 KB	-rw-rw-rw-
dutree.py	1.66 KB	-rw-rw-rw-
eptags.py	1.6 KB	-rw-rw-rw-
find-uname.py	1.22 KB	-rw-rw-rw-
find_recursionlimit.py	4.03 KB	-rw-rw-rw-
finddiv.py	2.56 KB	-rw-rw-rw-
findlinksto.py	1.09 KB	-rw-rw-rw-
findnocoding.py	2.99 KB	-rw-rw-rw-
fixcid.py	10.24 KB	-rw-rw-rw-
fixdiv.py	14.28 KB	-rw-rw-rw-
fixheader.py	1.38 KB	-rw-rw-rw-
fixnotice.py	3.06 KB	-rw-rw-rw-
fixps.py	923 B	-rw-rw-rw-
generate_opcode_h.py	2.25 KB	-rw-rw-rw-
generate_stdlib_module_names.p...	4.7 KB	-rw-rw-rw-
generate_token.py	7.08 KB	-rw-rw-rw-
get-remote-certificate.py	2.7 KB	-rw-rw-rw-
google.py	526 B	-rw-rw-rw-
gprof2html.py	2.33 KB	-rw-rw-rw-
highlight.py	9.21 KB	-rw-rw-rw-
ifdef.py	3.73 KB	-rw-rw-rw-
import_diagnostics.py	1.01 KB	-rw-rw-rw-
lfcr.py	664 B	-rw-rw-rw-
linktree.py	2.46 KB	-rw-rw-rw-
lll.py	775 B	-rw-rw-rw-
mailerdaemon.py	8.09 KB	-rw-rw-rw-
make_ctype.py	2.32 KB	-rw-rw-rw-
md5sum.py	2.55 KB	-rw-rw-rw-
mkreal.py	1.66 KB	-rw-rw-rw-
ndiff.py	3.86 KB	-rw-rw-rw-
nm2def.py	2.53 KB	-rw-rw-rw-
objgraph.py	6.01 KB	-rw-rw-rw-
parse_html5_entities.py	4.01 KB	-rw-rw-rw-
parseentities.py	1.76 KB	-rw-rw-rw-
patchcheck.py	10.81 KB	-rw-rw-rw-
pathfix.py	6.85 KB	-rw-rw-rw-
pdeps.py	4.07 KB	-rw-rw-rw-
pep384_macrocheck.py	4.75 KB	-rw-rw-rw-
pickle2db.py	4.07 KB	-rw-rw-rw-
pindent.py	17.22 KB	-rw-rw-rw-
ptags.py	1.34 KB	-rw-rw-rw-
pydoc3.py	85 B	-rw-rw-rw-
pysource.py	3.9 KB	-rw-rw-rw-
reindent-rst.py	293 B	-rw-rw-rw-
reindent.py	11.7 KB	-rw-rw-rw-
rgrep.py	1.61 KB	-rw-rw-rw-
run_tests.py	1.83 KB	-rw-rw-rw-
serve.py	1.23 KB	-rw-rw-rw-
smelly.py	5.07 KB	-rw-rw-rw-
stable_abi.py	20.91 KB	-rw-rw-rw-
suff.py	536 B	-rw-rw-rw-
texi2html.py	70.75 KB	-rw-rw-rw-
untabify.py	1.32 KB	-rw-rw-rw-
update_file.py	790 B	-rw-rw-rw-
var_access_benchmark.py	11.92 KB	-rw-rw-rw-
verify_ensurepip_wheels.py	3.21 KB	-rw-rw-rw-
which.py	1.71 KB	-rw-rw-rw-
win_add2path.py	1.68 KB	-rw-rw-rw-

Code Editor : analyze_dxp.py

"""
Some helper functions to analyze the output of sys.getdxp() (which is
only available if Python was built with -DDYNAMIC_EXECUTION_PROFILE).
These will tell you which opcodes have been executed most frequently
in the current process, and, if Python was also built with -DDXPAIRS,
will tell you which instruction _pairs_ were executed most frequently,
which may help in choosing new instructions.

If Python was built without -DDYNAMIC_EXECUTION_PROFILE, importing
this module will raise a RuntimeError.

If you're running a script you want to profile, a simple way to get
the common pairs is:

$ PYTHONPATH=$PYTHONPATH:<python_srcdir>/Tools/scripts \
./python -i -O the_script.py --args
...
> from analyze_dxp import *
> s = render_common_pairs()
> open('/tmp/some_file', 'w').write(s)
"""

import copy
import opcode
import operator
import sys
import threading

if not hasattr(sys, "getdxp"):
    raise RuntimeError("Can't import analyze_dxp: Python built without"
                       " -DDYNAMIC_EXECUTION_PROFILE.")

_profile_lock = threading.RLock()
_cumulative_profile = sys.getdxp()

# If Python was built with -DDXPAIRS, sys.getdxp() returns a list of
# lists of ints.  Otherwise it returns just a list of ints.
def has_pairs(profile):
    """Returns True if the Python that produced the argument profile
    was built with -DDXPAIRS."""

return len(profile) > 0 and isinstance(profile[0], list)

def reset_profile():
    """Forgets any execution profile that has been gathered so far."""
    with _profile_lock:
        sys.getdxp()  # Resets the internal profile
        global _cumulative_profile
        _cumulative_profile = sys.getdxp()  # 0s out our copy.

def merge_profile():
    """Reads sys.getdxp() and merges it into this module's cached copy.

We need this because sys.getdxp() 0s itself every time it's called."""

with _profile_lock:
        new_profile = sys.getdxp()
        if has_pairs(new_profile):
            for first_inst in range(len(_cumulative_profile)):
                for second_inst in range(len(_cumulative_profile[first_inst])):
                    _cumulative_profile[first_inst][second_inst] += (
                        new_profile[first_inst][second_inst])
        else:
            for inst in range(len(_cumulative_profile)):
                _cumulative_profile[inst] += new_profile[inst]

def snapshot_profile():
    """Returns the cumulative execution profile until this call."""
    with _profile_lock:
        merge_profile()
        return copy.deepcopy(_cumulative_profile)

def common_instructions(profile):
    """Returns the most common opcodes in order of descending frequency.

The result is a list of tuples of the form
      (opcode, opname, # of occurrences)

"""
    if has_pairs(profile) and profile:
        inst_list = profile[-1]
    else:
        inst_list = profile
    result = [(op, opcode.opname[op], count)
              for op, count in enumerate(inst_list)
              if count > 0]
    result.sort(key=operator.itemgetter(2), reverse=True)
    return result

def common_pairs(profile):
    """Returns the most common opcode pairs in order of descending frequency.

The result is a list of tuples of the form
      ((1st opcode, 2nd opcode),
       (1st opname, 2nd opname),
       # of occurrences of the pair)

"""
    if not has_pairs(profile):
        return []
    result = [((op1, op2), (opcode.opname[op1], opcode.opname[op2]), count)
              # Drop the row of single-op profiles with [:-1]
              for op1, op1profile in enumerate(profile[:-1])
              for op2, count in enumerate(op1profile)
              if count > 0]
    result.sort(key=operator.itemgetter(2), reverse=True)
    return result

def render_common_pairs(profile=None):
    """Renders the most common opcode pairs to a string in order of
    descending frequency.

The result is a series of lines of the form:
      # of occurrences: ('1st opname', '2nd opname')

"""
    if profile is None:
        profile = snapshot_profile()
    def seq():
        for _, ops, count in common_pairs(profile):
            yield "%s: %s\n" % (count, ops)
    return ''.join(seq())

${this.title}

Code Editor : analyze_dxp.py