1#!/usr/bin/env python
2"""
3Some helper functions to analyze the output of sys.getdxp() (which is
4only available if Python was built with -DDYNAMIC_EXECUTION_PROFILE).
5These will tell you which opcodes have been executed most frequently
6in the current process, and, if Python was also built with -DDXPAIRS,
7will tell you which instruction _pairs_ were executed most frequently,
8which may help in choosing new instructions.
9
10If Python was built without -DDYNAMIC_EXECUTION_PROFILE, importing
11this module will raise a RuntimeError.
12
13If you're running a script you want to profile, a simple way to get
14the common pairs is:
15
16$ PYTHONPATH=$PYTHONPATH:<python_srcdir>/Tools/scripts \
17./python -i -O the_script.py --args
18...
19> from analyze_dxp import *
20> s = render_common_pairs()
21> open('/tmp/some_file', 'w').write(s)
22"""
23
24import copy
25import opcode
26import operator
27import sys
28import threading
29
30if not hasattr(sys, "getdxp"):
31    raise RuntimeError("Can't import analyze_dxp: Python built without"
32                       " -DDYNAMIC_EXECUTION_PROFILE.")
33
34
35_profile_lock = threading.RLock()
36_cumulative_profile = sys.getdxp()
37
38# If Python was built with -DDXPAIRS, sys.getdxp() returns a list of
39# lists of ints.  Otherwise it returns just a list of ints.
40def has_pairs(profile):
41    """Returns True if the Python that produced the argument profile
42    was built with -DDXPAIRS."""
43
44    return len(profile) > 0 and isinstance(profile[0], list)
45
46
47def reset_profile():
48    """Forgets any execution profile that has been gathered so far."""
49    with _profile_lock:
50        sys.getdxp()  # Resets the internal profile
51        global _cumulative_profile
52        _cumulative_profile = sys.getdxp()  # 0s out our copy.
53
54
55def merge_profile():
56    """Reads sys.getdxp() and merges it into this module's cached copy.
57
58    We need this because sys.getdxp() 0s itself every time it's called."""
59
60    with _profile_lock:
61        new_profile = sys.getdxp()
62        if has_pairs(new_profile):
63            for first_inst in range(len(_cumulative_profile)):
64                for second_inst in range(len(_cumulative_profile[first_inst])):
65                    _cumulative_profile[first_inst][second_inst] += (
66                        new_profile[first_inst][second_inst])
67        else:
68            for inst in range(len(_cumulative_profile)):
69                _cumulative_profile[inst] += new_profile[inst]
70
71
72def snapshot_profile():
73    """Returns the cumulative execution profile until this call."""
74    with _profile_lock:
75        merge_profile()
76        return copy.deepcopy(_cumulative_profile)
77
78
79def common_instructions(profile):
80    """Returns the most common opcodes in order of descending frequency.
81
82    The result is a list of tuples of the form
83      (opcode, opname, # of occurrences)
84
85    """
86    if has_pairs(profile) and profile:
87        inst_list = profile[-1]
88    else:
89        inst_list = profile
90    result = [(op, opcode.opname[op], count)
91              for op, count in enumerate(inst_list)
92              if count > 0]
93    result.sort(key=operator.itemgetter(2), reverse=True)
94    return result
95
96
97def common_pairs(profile):
98    """Returns the most common opcode pairs in order of descending frequency.
99
100    The result is a list of tuples of the form
101      ((1st opcode, 2nd opcode),
102       (1st opname, 2nd opname),
103       # of occurrences of the pair)
104
105    """
106    if not has_pairs(profile):
107        return []
108    result = [((op1, op2), (opcode.opname[op1], opcode.opname[op2]), count)
109              # Drop the row of single-op profiles with [:-1]
110              for op1, op1profile in enumerate(profile[:-1])
111              for op2, count in enumerate(op1profile)
112              if count > 0]
113    result.sort(key=operator.itemgetter(2), reverse=True)
114    return result
115
116
117def render_common_pairs(profile=None):
118    """Renders the most common opcode pairs to a string in order of
119    descending frequency.
120
121    The result is a series of lines of the form:
122      # of occurrences: ('1st opname', '2nd opname')
123
124    """
125    if profile is None:
126        profile = snapshot_profile()
127    def seq():
128        for _, ops, count in common_pairs(profile):
129            yield "%s: %s\n" % (count, ops)
130    return ''.join(seq())
131