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- """
- 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())
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