"""
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())