#!/usr/bin/env python3

"""
This script reads the input from stdin, extracts all lines starting with
"# FDATA: " (or a given prefix instead of "FDATA"), parses the directives,
replaces symbol names ("#name#") with either symbol values or with offsets from
respective anchor symbols, and prints the resulting file to stdout.
"""

import argparse
import subprocess
import sys
import re

parser = argparse.ArgumentParser()
parser.add_argument("input")
parser.add_argument("objfile", help="Object file to extract symbol values from")
parser.add_argument("output")
parser.add_argument("prefix", nargs="?", default="FDATA", help="Custom FDATA prefix")
parser.add_argument("--nmtool", default="nm", help="Path to nm tool")

args = parser.parse_args()

# Regexes to extract FDATA lines from input and parse FDATA and pre-aggregated
# profile data
prefix_pat = re.compile(f"^# {args.prefix}: (.*)")

# FDATA records:
# <is symbol?> <closest elf symbol or DSO name> <relative FROM address>
# <is symbol?> <closest elf symbol or DSO name> <relative TO address>
# <number of mispredictions> <number of branches>
fdata_pat = re.compile(r"([01].*) (?P<exec>\d+) (?P<mispred>\d+)")

# Pre-aggregated profile:
# {B|F|f} [<start_id>:]<start_offset> [<end_id>:]<end_offset> <count>
# [<mispred_count>]
preagg_pat = re.compile(r"(?P<type>[BFf]) (?P<offsets_count>.*)")

# Replacement symbol: #symname#
replace_pat = re.compile(r"#(?P<symname>[^#]+)#")

# Read input and construct the representation of fdata expressions
# as (src_tuple, dst_tuple, mispred_count, exec_count) tuples, where src and dst
# are represented as (is_sym, anchor, offset) tuples
exprs = []
with open(args.input, 'r') as f:
    for line in f.readlines():
        prefix_match = prefix_pat.match(line)
        if not prefix_match:
            continue
        profile_line = prefix_match.group(1)
        fdata_match = fdata_pat.match(profile_line)
        preagg_match = preagg_pat.match(profile_line)
        if fdata_match:
            src_dst, execnt, mispred = fdata_match.groups()
            # Split by whitespaces not preceded by a backslash (negative lookbehind)
            chunks = re.split(r'(?<!\\) +', src_dst)
            # Check if the number of records separated by non-escaped whitespace
            # exactly matches the format.
            assert len(chunks) == 6, f"ERROR: wrong format/whitespaces must be escaped:\n{line}"
            exprs.append(('FDATA', (*chunks, execnt, mispred)))
        elif preagg_match:
            exprs.append(('PREAGG', preagg_match.groups()))
        else:
            exit("ERROR: unexpected input:\n%s" % line)

# Read nm output: <symbol value> <symbol type> <symbol name>
nm_output = subprocess.run([args.nmtool, '--defined-only', args.objfile],
                           text = True, capture_output = True).stdout
# Populate symbol map
symbols = {}
for symline in nm_output.splitlines():
    symval, _, symname = symline.split(maxsplit=2)
    symbols[symname] = symval

def evaluate_symbol(issym, anchor, offsym):
    sym_match = replace_pat.match(offsym)
    if not sym_match:
        # No need to evaluate symbol value, return as is
        return f'{issym} {anchor} {offsym}'
    symname = sym_match.group('symname')
    assert symname in symbols, f"ERROR: symbol {symname} is not defined in binary"
    # Evaluate to an absolute offset if issym is false
    if issym == '0':
        return f'{issym} {anchor} {symbols[symname]}'
    # Evaluate symbol against its anchor if issym is true
    assert anchor in symbols, f"ERROR: symbol {anchor} is not defined in binary"
    anchor_value = int(symbols[anchor], 16)
    symbol_value = int(symbols[symname], 16)
    sym_offset = symbol_value - anchor_value
    return f'{issym} {anchor} {format(sym_offset, "x")}'

def replace_symbol(matchobj):
    '''
    Expects matchobj to only capture one group which contains the symbol name.
    '''
    symname = matchobj.group('symname')
    assert symname in symbols, f"ERROR: symbol {symname} is not defined in binary"
    return symbols[symname]

with open(args.output, 'w') as f:
    for etype, expr in exprs:
        if etype == 'FDATA':
            issym1, anchor1, offsym1, issym2, anchor2, offsym2, execnt, mispred = expr
            print(evaluate_symbol(issym1, anchor1, offsym1),
                  evaluate_symbol(issym2, anchor2, offsym2),
                  execnt, mispred, file = f)
        elif etype == 'PREAGG':
            # Replace all symbols enclosed in ##
            print(expr[0], re.sub(replace_pat, replace_symbol, expr[1]),
                  file = f)
        else:
            exit("ERROR: unhandled expression type:\n%s" % etype)

#!/usr/bin/env python3

"""
This script reads the input from stdin, extracts all lines starting with
"# FDATA: " (or a given prefix instead of "FDATA"), parses the directives,
replaces symbol names ("#name#") with either symbol values or with offsets from
respective anchor symbols, and prints the resulting file to stdout.
"""

import argparse
import subprocess
import sys
import re

parser = argparse.ArgumentParser()
parser.add_argument("input")
parser.add_argument("objfile", help="Object file to extract symbol values from")
parser.add_argument("output")
parser.add_argument("prefix", nargs="?", default="FDATA", help="Custom FDATA prefix")
parser.add_argument("--nmtool", default="nm", help="Path to nm tool")

args = parser.parse_args()

# Regexes to extract FDATA lines from input and parse FDATA and pre-aggregated
# profile data
prefix_pat = re.compile(f"^# {args.prefix}: (.*)")

# FDATA records:
# <is symbol?> <closest elf symbol or DSO name> <relative FROM address>
# <is symbol?> <closest elf symbol or DSO name> <relative TO address>
# <number of mispredictions> <number of branches>
fdata_pat = re.compile(r"([01].*) (?P<exec>\d+) (?P<mispred>\d+)")

# Pre-aggregated profile:
# {B|F|f} [<start_id>:]<start_offset> [<end_id>:]<end_offset> <count>
# [<mispred_count>]
preagg_pat = re.compile(r"(?P<type>[BFf]) (?P<offsets_count>.*)")

# Replacement symbol: #symname#
replace_pat = re.compile(r"#(?P<symname>[^#]+)#")

# Read input and construct the representation of fdata expressions
# as (src_tuple, dst_tuple, mispred_count, exec_count) tuples, where src and dst
# are represented as (is_sym, anchor, offset) tuples
exprs = []
with open(args.input, 'r') as f:
    for line in f.readlines():
        prefix_match = prefix_pat.match(line)
        if not prefix_match:
            continue
        profile_line = prefix_match.group(1)
        fdata_match = fdata_pat.match(profile_line)
        preagg_match = preagg_pat.match(profile_line)
        if fdata_match:
            src_dst, execnt, mispred = fdata_match.groups()
            # Split by whitespaces not preceded by a backslash (negative lookbehind)
            chunks = re.split(r'(?<!\\) +', src_dst)
            # Check if the number of records separated by non-escaped whitespace
            # exactly matches the format.
            assert len(chunks) == 6, f"ERROR: wrong format/whitespaces must be escaped:\n{line}"
            exprs.append(('FDATA', (*chunks, execnt, mispred)))
        elif preagg_match:
            exprs.append(('PREAGG', preagg_match.groups()))
        else:
            exit("ERROR: unexpected input:\n%s" % line)

# Read nm output: <symbol value> <symbol type> <symbol name>
nm_output = subprocess.run([args.nmtool, '--defined-only', args.objfile],
                           text = True, capture_output = True).stdout
# Populate symbol map
symbols = {}
for symline in nm_output.splitlines():
    symval, _, symname = symline.split(maxsplit=2)
    symbols[symname] = symval

def evaluate_symbol(issym, anchor, offsym):
    sym_match = replace_pat.match(offsym)
    if not sym_match:
        # No need to evaluate symbol value, return as is
        return f'{issym} {anchor} {offsym}'
    symname = sym_match.group('symname')
    assert symname in symbols, f"ERROR: symbol {symname} is not defined in binary"
    # Evaluate to an absolute offset if issym is false
    if issym == '0':
        return f'{issym} {anchor} {symbols[symname]}'
    # Evaluate symbol against its anchor if issym is true
    assert anchor in symbols, f"ERROR: symbol {anchor} is not defined in binary"
    anchor_value = int(symbols[anchor], 16)
    symbol_value = int(symbols[symname], 16)
    sym_offset = symbol_value - anchor_value
    return f'{issym} {anchor} {format(sym_offset, "x")}'

def replace_symbol(matchobj):
    '''
    Expects matchobj to only capture one group which contains the symbol name.
    '''
    symname = matchobj.group('symname')
    assert symname in symbols, f"ERROR: symbol {symname} is not defined in binary"
    return symbols[symname]

with open(args.output, 'w') as f:
    for etype, expr in exprs:
        if etype == 'FDATA':
            issym1, anchor1, offsym1, issym2, anchor2, offsym2, execnt, mispred = expr
            print(evaluate_symbol(issym1, anchor1, offsym1),
                  evaluate_symbol(issym2, anchor2, offsym2),
                  execnt, mispred, file = f)
        elif etype == 'PREAGG':
            # Replace all symbols enclosed in ##
            print(expr[0], re.sub(replace_pat, replace_symbol, expr[1]),
                  file = f)
        else:
            exit("ERROR: unhandled expression type:\n%s" % etype)

#!/usr/bin/env python3 This script reads the input from stdin, extracts all lines starting with "# FDATA: " (or a given prefix instead of "FDATA"), parses the directives, replaces symbol names ("#name#") with either symbol values or with offsets from respective anchor symbols, and prints the resulting file to stdout. # Regexes to extract FDATA lines from input and parse FDATA and pre-aggregated # profile data # {args.prefix}: (.*)") # FDATA records: # <is symbol?> <closest elf symbol or DSO name> <relative FROM address> # <is symbol?> <closest elf symbol or DSO name> <relative TO address> # <number of mispredictions> <number of branches> # Pre-aggregated profile: # {B|F|f} [<start_id>:]<start_offset> [<end_id>:]<end_offset> <count> # [<mispred_count>] # Replacement symbol: #symname# #]+)#") # Read input and construct the representation of fdata expressions # as (src_tuple, dst_tuple, mispred_count, exec_count) tuples, where src and dst # are represented as (is_sym, anchor, offset) tuples # Split by whitespaces not preceded by a backslash (negative lookbehind) # Check if the number of records separated by non-escaped whitespace # exactly matches the format. # Read nm output: <symbol value> <symbol type> <symbol name> # Populate symbol map # No need to evaluate symbol value, return as is # Evaluate to an absolute offset if issym is false # Evaluate symbol against its anchor if issym is true Expects matchobj to only capture one group which contains the symbol name. # Replace all symbols enclosed in ##