mirror of https://github.com/python/cpython
131 lines
4.1 KiB
Python
Executable File
131 lines
4.1 KiB
Python
Executable File
#!/usr/bin/env python
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"""
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Some helper functions to analyze the output of sys.getdxp() (which is
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only available if Python was built with -DDYNAMIC_EXECUTION_PROFILE).
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These will tell you which opcodes have been executed most frequently
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in the current process, and, if Python was also built with -DDXPAIRS,
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will tell you which instruction _pairs_ were executed most frequently,
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which may help in choosing new instructions.
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If Python was built without -DDYNAMIC_EXECUTION_PROFILE, importing
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this module will raise a RuntimeError.
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If you're running a script you want to profile, a simple way to get
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the common pairs is:
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$ PYTHONPATH=$PYTHONPATH:<python_srcdir>/Tools/scripts \
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./python -i -O the_script.py --args
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...
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> from analyze_dxp import *
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> s = render_common_pairs()
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> open('/tmp/some_file', 'w').write(s)
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"""
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import copy
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import opcode
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import operator
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import sys
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import threading
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if not hasattr(sys, "getdxp"):
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raise RuntimeError("Can't import analyze_dxp: Python built without"
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" -DDYNAMIC_EXECUTION_PROFILE.")
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_profile_lock = threading.RLock()
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_cumulative_profile = sys.getdxp()
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# If Python was built with -DDXPAIRS, sys.getdxp() returns a list of
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# lists of ints. Otherwise it returns just a list of ints.
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def has_pairs(profile):
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"""Returns True if the Python that produced the argument profile
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was built with -DDXPAIRS."""
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return len(profile) > 0 and isinstance(profile[0], list)
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def reset_profile():
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"""Forgets any execution profile that has been gathered so far."""
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with _profile_lock:
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sys.getdxp() # Resets the internal profile
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global _cumulative_profile
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_cumulative_profile = sys.getdxp() # 0s out our copy.
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def merge_profile():
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"""Reads sys.getdxp() and merges it into this module's cached copy.
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We need this because sys.getdxp() 0s itself every time it's called."""
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with _profile_lock:
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new_profile = sys.getdxp()
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if has_pairs(new_profile):
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for first_inst in range(len(_cumulative_profile)):
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for second_inst in range(len(_cumulative_profile[first_inst])):
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_cumulative_profile[first_inst][second_inst] += (
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new_profile[first_inst][second_inst])
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else:
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for inst in range(len(_cumulative_profile)):
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_cumulative_profile[inst] += new_profile[inst]
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def snapshot_profile():
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"""Returns the cumulative execution profile until this call."""
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with _profile_lock:
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merge_profile()
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return copy.deepcopy(_cumulative_profile)
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def common_instructions(profile):
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"""Returns the most common opcodes in order of descending frequency.
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The result is a list of tuples of the form
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(opcode, opname, # of occurrences)
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"""
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if has_pairs(profile) and profile:
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inst_list = profile[-1]
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else:
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inst_list = profile
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result = [(op, opcode.opname[op], count)
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for op, count in enumerate(inst_list)
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if count > 0]
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result.sort(key=operator.itemgetter(2), reverse=True)
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return result
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def common_pairs(profile):
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"""Returns the most common opcode pairs in order of descending frequency.
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The result is a list of tuples of the form
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((1st opcode, 2nd opcode),
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(1st opname, 2nd opname),
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# of occurrences of the pair)
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"""
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if not has_pairs(profile):
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return []
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result = [((op1, op2), (opcode.opname[op1], opcode.opname[op2]), count)
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# Drop the row of single-op profiles with [:-1]
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for op1, op1profile in enumerate(profile[:-1])
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for op2, count in enumerate(op1profile)
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if count > 0]
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result.sort(key=operator.itemgetter(2), reverse=True)
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return result
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def render_common_pairs(profile=None):
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"""Renders the most common opcode pairs to a string in order of
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descending frequency.
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The result is a series of lines of the form:
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# of occurrences: ('1st opname', '2nd opname')
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"""
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if profile is None:
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profile = snapshot_profile()
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def seq():
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for _, ops, count in common_pairs(profile):
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yield "%s: %s\n" % (count, ops)
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return ''.join(seq())
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