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	svn+ssh://pythondev@svn.python.org/python/trunk ........ r69811 | collin.winter | 2009-02-20 13:30:41 -0600 (Fri, 20 Feb 2009) | 2 lines Issue 5176: special-case string formatting in BINARY_MODULO implementation. This shows a modest (1-3%) speed-up in templating systems, for example. ........ r69947 | jeffrey.yasskin | 2009-02-24 16:48:34 -0600 (Tue, 24 Feb 2009) | 3 lines Tools/scripts/analyze_dxp.py, a module with some helper functions to analyze the output of sys.getdxp(). ........
		
			
				
	
	
		
			129 lines
		
	
	
	
		
			4.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			129 lines
		
	
	
	
		
			4.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
"""
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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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