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https://github.com/esphome/esphome.git
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merge
This commit is contained in:
J. Nick Koston
@@ -174,7 +174,7 @@ class MemoryAnalyzer:
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self.sections[mapped_section].total_size += size
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except subprocess.CalledProcessError as e:
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_LOGGER.error(f"Failed to parse sections: {e}")
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_LOGGER.error("Failed to parse sections: %s", e)
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raise
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def _parse_symbols(self) -> None:
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@@ -252,7 +252,7 @@ class MemoryAnalyzer:
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seen_addresses.add(address)
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except subprocess.CalledProcessError as e:
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_LOGGER.error(f"Failed to parse symbols: {e}")
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_LOGGER.error("Failed to parse symbols: %s", e)
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raise
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def _categorize_symbols(self) -> None:
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@@ -399,8 +399,9 @@ class MemoryAnalyzer:
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# If batch fails, cache originals
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for symbol in symbols:
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self._demangle_cache[symbol] = symbol
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except Exception:
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except (subprocess.SubprocessError, OSError, UnicodeDecodeError) as e:
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# On error, cache originals
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_LOGGER.debug("Failed to batch demangle symbols: %s", e)
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for symbol in symbols:
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self._demangle_cache[symbol] = symbol
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@@ -424,267 +425,6 @@ class MemoryAnalyzer:
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return "Other Core"
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def generate_report(self, detailed: bool = False) -> str:
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"""Generate a formatted memory report."""
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components = sorted(
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self.components.items(), key=lambda x: x[1].flash_total, reverse=True
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)
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# Calculate totals
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total_flash = sum(c.flash_total for _, c in components)
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total_ram = sum(c.ram_total for _, c in components)
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# Build report
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lines = []
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# Column width constants
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COL_COMPONENT = 29
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COL_FLASH_TEXT = 14
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COL_FLASH_DATA = 14
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COL_RAM_DATA = 12
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COL_RAM_BSS = 12
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COL_TOTAL_FLASH = 15
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COL_TOTAL_RAM = 12
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COL_SEPARATOR = 3 # " | "
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# Core analysis column widths
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COL_CORE_SUBCATEGORY = 30
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COL_CORE_SIZE = 12
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COL_CORE_COUNT = 6
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COL_CORE_PERCENT = 10
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# Calculate the exact table width
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table_width = (
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COL_COMPONENT
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+ COL_SEPARATOR
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+ COL_FLASH_TEXT
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+ COL_SEPARATOR
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+ COL_FLASH_DATA
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+ COL_SEPARATOR
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+ COL_RAM_DATA
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+ COL_SEPARATOR
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+ COL_RAM_BSS
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+ COL_SEPARATOR
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+ COL_TOTAL_FLASH
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+ COL_SEPARATOR
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+ COL_TOTAL_RAM
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)
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lines.append("=" * table_width)
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lines.append("Component Memory Analysis".center(table_width))
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lines.append("=" * table_width)
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lines.append("")
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# Main table - fixed column widths
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lines.append(
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f"{'Component':<{COL_COMPONENT}} | {'Flash (text)':>{COL_FLASH_TEXT}} | {'Flash (data)':>{COL_FLASH_DATA}} | {'RAM (data)':>{COL_RAM_DATA}} | {'RAM (bss)':>{COL_RAM_BSS}} | {'Total Flash':>{COL_TOTAL_FLASH}} | {'Total RAM':>{COL_TOTAL_RAM}}"
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)
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lines.append(
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"-" * COL_COMPONENT
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+ "-+-"
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+ "-" * COL_FLASH_TEXT
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+ "-+-"
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+ "-" * COL_FLASH_DATA
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+ "-+-"
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+ "-" * COL_RAM_DATA
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+ "-+-"
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+ "-" * COL_RAM_BSS
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+ "-+-"
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+ "-" * COL_TOTAL_FLASH
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+ "-+-"
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+ "-" * COL_TOTAL_RAM
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)
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for name, mem in components:
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if mem.flash_total > 0 or mem.ram_total > 0:
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flash_rodata = mem.rodata_size + mem.data_size
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lines.append(
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f"{name:<{COL_COMPONENT}} | {mem.text_size:>{COL_FLASH_TEXT - 2},} B | {flash_rodata:>{COL_FLASH_DATA - 2},} B | "
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f"{mem.data_size:>{COL_RAM_DATA - 2},} B | {mem.bss_size:>{COL_RAM_BSS - 2},} B | "
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f"{mem.flash_total:>{COL_TOTAL_FLASH - 2},} B | {mem.ram_total:>{COL_TOTAL_RAM - 2},} B"
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)
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lines.append(
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"-" * COL_COMPONENT
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+ "-+-"
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+ "-" * COL_FLASH_TEXT
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+ "-+-"
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+ "-" * COL_FLASH_DATA
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+ "-+-"
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+ "-" * COL_RAM_DATA
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+ "-+-"
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+ "-" * COL_RAM_BSS
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+ "-+-"
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+ "-" * COL_TOTAL_FLASH
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+ "-+-"
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+ "-" * COL_TOTAL_RAM
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)
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lines.append(
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f"{'TOTAL':<{COL_COMPONENT}} | {' ':>{COL_FLASH_TEXT}} | {' ':>{COL_FLASH_DATA}} | "
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f"{' ':>{COL_RAM_DATA}} | {' ':>{COL_RAM_BSS}} | "
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f"{total_flash:>{COL_TOTAL_FLASH - 2},} B | {total_ram:>{COL_TOTAL_RAM - 2},} B"
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)
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# Top consumers
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lines.append("")
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lines.append("Top Flash Consumers:")
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for i, (name, mem) in enumerate(components[:25]):
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if mem.flash_total > 0:
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percentage = (
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(mem.flash_total / total_flash * 100) if total_flash > 0 else 0
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)
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lines.append(
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f"{i + 1}. {name} ({mem.flash_total:,} B) - {percentage:.1f}% of analyzed flash"
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)
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lines.append("")
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lines.append("Top RAM Consumers:")
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ram_components = sorted(components, key=lambda x: x[1].ram_total, reverse=True)
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for i, (name, mem) in enumerate(ram_components[:25]):
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if mem.ram_total > 0:
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percentage = (mem.ram_total / total_ram * 100) if total_ram > 0 else 0
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lines.append(
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f"{i + 1}. {name} ({mem.ram_total:,} B) - {percentage:.1f}% of analyzed RAM"
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)
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lines.append("")
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lines.append(
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"Note: This analysis covers symbols in the ELF file. Some runtime allocations may not be included."
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)
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lines.append("=" * table_width)
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# Add ESPHome core detailed analysis if there are core symbols
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if self._esphome_core_symbols:
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lines.append("")
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lines.append("=" * table_width)
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lines.append("[esphome]core Detailed Analysis".center(table_width))
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lines.append("=" * table_width)
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lines.append("")
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# Group core symbols by subcategory
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core_subcategories: dict[str, list[tuple[str, str, int]]] = defaultdict(
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list
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)
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for symbol, demangled, size in self._esphome_core_symbols:
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# Categorize based on demangled name patterns
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subcategory = self._categorize_esphome_core_symbol(demangled)
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core_subcategories[subcategory].append((symbol, demangled, size))
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# Sort subcategories by total size
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sorted_subcategories = sorted(
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[
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(name, symbols, sum(s[2] for s in symbols))
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for name, symbols in core_subcategories.items()
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],
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key=lambda x: x[2],
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reverse=True,
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)
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lines.append(
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f"{'Subcategory':<{COL_CORE_SUBCATEGORY}} | {'Size':>{COL_CORE_SIZE}} | "
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f"{'Count':>{COL_CORE_COUNT}} | {'% of Core':>{COL_CORE_PERCENT}}"
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)
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lines.append(
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"-" * COL_CORE_SUBCATEGORY
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+ "-+-"
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+ "-" * COL_CORE_SIZE
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+ "-+-"
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+ "-" * COL_CORE_COUNT
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+ "-+-"
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+ "-" * COL_CORE_PERCENT
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)
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core_total = sum(size for _, _, size in self._esphome_core_symbols)
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for subcategory, symbols, total_size in sorted_subcategories:
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percentage = (total_size / core_total * 100) if core_total > 0 else 0
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lines.append(
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f"{subcategory:<{COL_CORE_SUBCATEGORY}} | {total_size:>{COL_CORE_SIZE - 2},} B | "
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f"{len(symbols):>{COL_CORE_COUNT}} | {percentage:>{COL_CORE_PERCENT - 1}.1f}%"
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)
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# Top 10 largest core symbols
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lines.append("")
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lines.append("Top 10 Largest [esphome]core Symbols:")
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sorted_core_symbols = sorted(
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self._esphome_core_symbols, key=lambda x: x[2], reverse=True
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)
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for i, (symbol, demangled, size) in enumerate(sorted_core_symbols[:15]):
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lines.append(f"{i + 1}. {demangled} ({size:,} B)")
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lines.append("=" * table_width)
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# Add detailed analysis for top ESPHome and external components
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esphome_components = [
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(name, mem)
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for name, mem in components
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if name.startswith("[esphome]") and name != "[esphome]core"
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]
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external_components = [
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(name, mem) for name, mem in components if name.startswith("[external]")
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]
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top_esphome_components = sorted(
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esphome_components, key=lambda x: x[1].flash_total, reverse=True
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)[:30]
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# Include all external components (they're usually important)
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top_external_components = sorted(
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external_components, key=lambda x: x[1].flash_total, reverse=True
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)
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# Check if API component exists and ensure it's included
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api_component = None
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for name, mem in components:
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if name == "[esphome]api":
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api_component = (name, mem)
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break
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# Combine all components to analyze: top ESPHome + all external + API if not already included
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components_to_analyze = list(top_esphome_components) + list(
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top_external_components
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)
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if api_component and api_component not in components_to_analyze:
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components_to_analyze.append(api_component)
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if components_to_analyze:
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for comp_name, comp_mem in components_to_analyze:
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comp_symbols = self._component_symbols.get(comp_name, [])
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if comp_symbols:
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lines.append("")
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lines.append("=" * table_width)
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lines.append(f"{comp_name} Detailed Analysis".center(table_width))
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lines.append("=" * table_width)
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lines.append("")
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# Sort symbols by size
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sorted_symbols = sorted(
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comp_symbols, key=lambda x: x[2], reverse=True
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)
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lines.append(f"Total symbols: {len(sorted_symbols)}")
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lines.append(f"Total size: {comp_mem.flash_total:,} B")
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lines.append("")
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# Show all symbols > 100 bytes for better visibility
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large_symbols = [
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(sym, dem, size)
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for sym, dem, size in sorted_symbols
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if size > 100
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]
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lines.append(
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f"{comp_name} Symbols > 100 B ({len(large_symbols)} symbols):"
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)
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for i, (symbol, demangled, size) in enumerate(large_symbols):
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lines.append(f"{i + 1}. {demangled} ({size:,} B)")
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lines.append("=" * table_width)
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return "\n".join(lines)
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def to_json(self) -> str:
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"""Export analysis results as JSON."""
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data = {
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@@ -707,63 +447,8 @@ class MemoryAnalyzer:
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}
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return json.dumps(data, indent=2)
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def dump_uncategorized_symbols(self, output_file: str | None = None) -> None:
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"""Dump uncategorized symbols for analysis."""
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# Sort by size descending
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sorted_symbols = sorted(
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self._uncategorized_symbols, key=lambda x: x[2], reverse=True
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)
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lines = ["Uncategorized Symbols Analysis", "=" * 80]
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lines.append(f"Total uncategorized symbols: {len(sorted_symbols)}")
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lines.append(
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f"Total uncategorized size: {sum(s[2] for s in sorted_symbols):,} bytes"
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)
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lines.append("")
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lines.append(f"{'Size':>10} | {'Symbol':<60} | Demangled")
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lines.append("-" * 10 + "-+-" + "-" * 60 + "-+-" + "-" * 40)
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for symbol, demangled, size in sorted_symbols[:100]: # Top 100
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if symbol != demangled:
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lines.append(f"{size:>10,} | {symbol[:60]:<60} | {demangled[:100]}")
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else:
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lines.append(f"{size:>10,} | {symbol[:60]:<60} | [not demangled]")
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if len(sorted_symbols) > 100:
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lines.append(f"\n... and {len(sorted_symbols) - 100} more symbols")
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content = "\n".join(lines)
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if output_file:
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with open(output_file, "w") as f:
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f.write(content)
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else:
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print(content)
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def analyze_elf(
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elf_path: str,
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objdump_path: str | None = None,
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readelf_path: str | None = None,
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detailed: bool = False,
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external_components: set[str] | None = None,
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) -> str:
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"""Analyze an ELF file and return a memory report."""
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analyzer = MemoryAnalyzer(elf_path, objdump_path, readelf_path, external_components)
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analyzer.analyze()
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return analyzer.generate_report(detailed)
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if __name__ == "__main__":
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import sys
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from .cli import main
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if len(sys.argv) < 2:
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print("Usage: analyze_memory.py <elf_file>")
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sys.exit(1)
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try:
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report = analyze_elf(sys.argv[1])
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print(report)
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except Exception as e:
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print(f"Error: {e}")
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sys.exit(1)
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main()
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6
esphome/analyze_memory/__main__.py
Normal file
6
esphome/analyze_memory/__main__.py
Normal file
@@ -0,0 +1,6 @@
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"""Main entry point for running the memory analyzer as a module."""
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from .cli import main
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if __name__ == "__main__":
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main()
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338
esphome/analyze_memory/cli.py
Normal file
338
esphome/analyze_memory/cli.py
Normal file
@@ -0,0 +1,338 @@
|
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"""CLI interface for memory analysis with report generation."""
|
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|
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from collections import defaultdict
|
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import subprocess
|
||||
import sys
|
||||
|
||||
from . import MemoryAnalyzer
|
||||
|
||||
|
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class MemoryAnalyzerCLI(MemoryAnalyzer):
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"""Memory analyzer with CLI-specific report generation."""
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|
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def generate_report(self, detailed: bool = False) -> str:
|
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"""Generate a formatted memory report."""
|
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components = sorted(
|
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self.components.items(), key=lambda x: x[1].flash_total, reverse=True
|
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)
|
||||
|
||||
# Calculate totals
|
||||
total_flash = sum(c.flash_total for _, c in components)
|
||||
total_ram = sum(c.ram_total for _, c in components)
|
||||
|
||||
# Build report
|
||||
lines = []
|
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|
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# Column width constants
|
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COL_COMPONENT = 29
|
||||
COL_FLASH_TEXT = 14
|
||||
COL_FLASH_DATA = 14
|
||||
COL_RAM_DATA = 12
|
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COL_RAM_BSS = 12
|
||||
COL_TOTAL_FLASH = 15
|
||||
COL_TOTAL_RAM = 12
|
||||
COL_SEPARATOR = 3 # " | "
|
||||
|
||||
# Core analysis column widths
|
||||
COL_CORE_SUBCATEGORY = 30
|
||||
COL_CORE_SIZE = 12
|
||||
COL_CORE_COUNT = 6
|
||||
COL_CORE_PERCENT = 10
|
||||
|
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# Calculate the exact table width
|
||||
table_width = (
|
||||
COL_COMPONENT
|
||||
+ COL_SEPARATOR
|
||||
+ COL_FLASH_TEXT
|
||||
+ COL_SEPARATOR
|
||||
+ COL_FLASH_DATA
|
||||
+ COL_SEPARATOR
|
||||
+ COL_RAM_DATA
|
||||
+ COL_SEPARATOR
|
||||
+ COL_RAM_BSS
|
||||
+ COL_SEPARATOR
|
||||
+ COL_TOTAL_FLASH
|
||||
+ COL_SEPARATOR
|
||||
+ COL_TOTAL_RAM
|
||||
)
|
||||
|
||||
lines.append("=" * table_width)
|
||||
lines.append("Component Memory Analysis".center(table_width))
|
||||
lines.append("=" * table_width)
|
||||
lines.append("")
|
||||
|
||||
# Main table - fixed column widths
|
||||
lines.append(
|
||||
f"{'Component':<{COL_COMPONENT}} | {'Flash (text)':>{COL_FLASH_TEXT}} | {'Flash (data)':>{COL_FLASH_DATA}} | {'RAM (data)':>{COL_RAM_DATA}} | {'RAM (bss)':>{COL_RAM_BSS}} | {'Total Flash':>{COL_TOTAL_FLASH}} | {'Total RAM':>{COL_TOTAL_RAM}}"
|
||||
)
|
||||
lines.append(
|
||||
"-" * COL_COMPONENT
|
||||
+ "-+-"
|
||||
+ "-" * COL_FLASH_TEXT
|
||||
+ "-+-"
|
||||
+ "-" * COL_FLASH_DATA
|
||||
+ "-+-"
|
||||
+ "-" * COL_RAM_DATA
|
||||
+ "-+-"
|
||||
+ "-" * COL_RAM_BSS
|
||||
+ "-+-"
|
||||
+ "-" * COL_TOTAL_FLASH
|
||||
+ "-+-"
|
||||
+ "-" * COL_TOTAL_RAM
|
||||
)
|
||||
|
||||
for name, mem in components:
|
||||
if mem.flash_total > 0 or mem.ram_total > 0:
|
||||
flash_rodata = mem.rodata_size + mem.data_size
|
||||
lines.append(
|
||||
f"{name:<{COL_COMPONENT}} | {mem.text_size:>{COL_FLASH_TEXT - 2},} B | {flash_rodata:>{COL_FLASH_DATA - 2},} B | "
|
||||
f"{mem.data_size:>{COL_RAM_DATA - 2},} B | {mem.bss_size:>{COL_RAM_BSS - 2},} B | "
|
||||
f"{mem.flash_total:>{COL_TOTAL_FLASH - 2},} B | {mem.ram_total:>{COL_TOTAL_RAM - 2},} B"
|
||||
)
|
||||
|
||||
lines.append(
|
||||
"-" * COL_COMPONENT
|
||||
+ "-+-"
|
||||
+ "-" * COL_FLASH_TEXT
|
||||
+ "-+-"
|
||||
+ "-" * COL_FLASH_DATA
|
||||
+ "-+-"
|
||||
+ "-" * COL_RAM_DATA
|
||||
+ "-+-"
|
||||
+ "-" * COL_RAM_BSS
|
||||
+ "-+-"
|
||||
+ "-" * COL_TOTAL_FLASH
|
||||
+ "-+-"
|
||||
+ "-" * COL_TOTAL_RAM
|
||||
)
|
||||
lines.append(
|
||||
f"{'TOTAL':<{COL_COMPONENT}} | {' ':>{COL_FLASH_TEXT}} | {' ':>{COL_FLASH_DATA}} | "
|
||||
f"{' ':>{COL_RAM_DATA}} | {' ':>{COL_RAM_BSS}} | "
|
||||
f"{total_flash:>{COL_TOTAL_FLASH - 2},} B | {total_ram:>{COL_TOTAL_RAM - 2},} B"
|
||||
)
|
||||
|
||||
# Top consumers
|
||||
lines.append("")
|
||||
lines.append("Top Flash Consumers:")
|
||||
for i, (name, mem) in enumerate(components[:25]):
|
||||
if mem.flash_total > 0:
|
||||
percentage = (
|
||||
(mem.flash_total / total_flash * 100) if total_flash > 0 else 0
|
||||
)
|
||||
lines.append(
|
||||
f"{i + 1}. {name} ({mem.flash_total:,} B) - {percentage:.1f}% of analyzed flash"
|
||||
)
|
||||
|
||||
lines.append("")
|
||||
lines.append("Top RAM Consumers:")
|
||||
ram_components = sorted(components, key=lambda x: x[1].ram_total, reverse=True)
|
||||
for i, (name, mem) in enumerate(ram_components[:25]):
|
||||
if mem.ram_total > 0:
|
||||
percentage = (mem.ram_total / total_ram * 100) if total_ram > 0 else 0
|
||||
lines.append(
|
||||
f"{i + 1}. {name} ({mem.ram_total:,} B) - {percentage:.1f}% of analyzed RAM"
|
||||
)
|
||||
|
||||
lines.append("")
|
||||
lines.append(
|
||||
"Note: This analysis covers symbols in the ELF file. Some runtime allocations may not be included."
|
||||
)
|
||||
lines.append("=" * table_width)
|
||||
|
||||
# Add ESPHome core detailed analysis if there are core symbols
|
||||
if self._esphome_core_symbols:
|
||||
lines.append("")
|
||||
lines.append("=" * table_width)
|
||||
lines.append("[esphome]core Detailed Analysis".center(table_width))
|
||||
lines.append("=" * table_width)
|
||||
lines.append("")
|
||||
|
||||
# Group core symbols by subcategory
|
||||
core_subcategories: dict[str, list[tuple[str, str, int]]] = defaultdict(
|
||||
list
|
||||
)
|
||||
|
||||
for symbol, demangled, size in self._esphome_core_symbols:
|
||||
# Categorize based on demangled name patterns
|
||||
subcategory = self._categorize_esphome_core_symbol(demangled)
|
||||
core_subcategories[subcategory].append((symbol, demangled, size))
|
||||
|
||||
# Sort subcategories by total size
|
||||
sorted_subcategories = sorted(
|
||||
[
|
||||
(name, symbols, sum(s[2] for s in symbols))
|
||||
for name, symbols in core_subcategories.items()
|
||||
],
|
||||
key=lambda x: x[2],
|
||||
reverse=True,
|
||||
)
|
||||
|
||||
lines.append(
|
||||
f"{'Subcategory':<{COL_CORE_SUBCATEGORY}} | {'Size':>{COL_CORE_SIZE}} | "
|
||||
f"{'Count':>{COL_CORE_COUNT}} | {'% of Core':>{COL_CORE_PERCENT}}"
|
||||
)
|
||||
lines.append(
|
||||
"-" * COL_CORE_SUBCATEGORY
|
||||
+ "-+-"
|
||||
+ "-" * COL_CORE_SIZE
|
||||
+ "-+-"
|
||||
+ "-" * COL_CORE_COUNT
|
||||
+ "-+-"
|
||||
+ "-" * COL_CORE_PERCENT
|
||||
)
|
||||
|
||||
core_total = sum(size for _, _, size in self._esphome_core_symbols)
|
||||
|
||||
for subcategory, symbols, total_size in sorted_subcategories:
|
||||
percentage = (total_size / core_total * 100) if core_total > 0 else 0
|
||||
lines.append(
|
||||
f"{subcategory:<{COL_CORE_SUBCATEGORY}} | {total_size:>{COL_CORE_SIZE - 2},} B | "
|
||||
f"{len(symbols):>{COL_CORE_COUNT}} | {percentage:>{COL_CORE_PERCENT - 1}.1f}%"
|
||||
)
|
||||
|
||||
# Top 10 largest core symbols
|
||||
lines.append("")
|
||||
lines.append("Top 10 Largest [esphome]core Symbols:")
|
||||
sorted_core_symbols = sorted(
|
||||
self._esphome_core_symbols, key=lambda x: x[2], reverse=True
|
||||
)
|
||||
|
||||
for i, (symbol, demangled, size) in enumerate(sorted_core_symbols[:15]):
|
||||
lines.append(f"{i + 1}. {demangled} ({size:,} B)")
|
||||
|
||||
lines.append("=" * table_width)
|
||||
|
||||
# Add detailed analysis for top ESPHome and external components
|
||||
esphome_components = [
|
||||
(name, mem)
|
||||
for name, mem in components
|
||||
if name.startswith("[esphome]") and name != "[esphome]core"
|
||||
]
|
||||
external_components = [
|
||||
(name, mem) for name, mem in components if name.startswith("[external]")
|
||||
]
|
||||
|
||||
top_esphome_components = sorted(
|
||||
esphome_components, key=lambda x: x[1].flash_total, reverse=True
|
||||
)[:30]
|
||||
|
||||
# Include all external components (they're usually important)
|
||||
top_external_components = sorted(
|
||||
external_components, key=lambda x: x[1].flash_total, reverse=True
|
||||
)
|
||||
|
||||
# Check if API component exists and ensure it's included
|
||||
api_component = None
|
||||
for name, mem in components:
|
||||
if name == "[esphome]api":
|
||||
api_component = (name, mem)
|
||||
break
|
||||
|
||||
# Combine all components to analyze: top ESPHome + all external + API if not already included
|
||||
components_to_analyze = list(top_esphome_components) + list(
|
||||
top_external_components
|
||||
)
|
||||
if api_component and api_component not in components_to_analyze:
|
||||
components_to_analyze.append(api_component)
|
||||
|
||||
if components_to_analyze:
|
||||
for comp_name, comp_mem in components_to_analyze:
|
||||
comp_symbols = self._component_symbols.get(comp_name, [])
|
||||
if comp_symbols:
|
||||
lines.append("")
|
||||
lines.append("=" * table_width)
|
||||
lines.append(f"{comp_name} Detailed Analysis".center(table_width))
|
||||
lines.append("=" * table_width)
|
||||
lines.append("")
|
||||
|
||||
# Sort symbols by size
|
||||
sorted_symbols = sorted(
|
||||
comp_symbols, key=lambda x: x[2], reverse=True
|
||||
)
|
||||
|
||||
lines.append(f"Total symbols: {len(sorted_symbols)}")
|
||||
lines.append(f"Total size: {comp_mem.flash_total:,} B")
|
||||
lines.append("")
|
||||
|
||||
# Show all symbols > 100 bytes for better visibility
|
||||
large_symbols = [
|
||||
(sym, dem, size)
|
||||
for sym, dem, size in sorted_symbols
|
||||
if size > 100
|
||||
]
|
||||
|
||||
lines.append(
|
||||
f"{comp_name} Symbols > 100 B ({len(large_symbols)} symbols):"
|
||||
)
|
||||
for i, (symbol, demangled, size) in enumerate(large_symbols):
|
||||
lines.append(f"{i + 1}. {demangled} ({size:,} B)")
|
||||
|
||||
lines.append("=" * table_width)
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def dump_uncategorized_symbols(self, output_file: str | None = None) -> None:
|
||||
"""Dump uncategorized symbols for analysis."""
|
||||
# Sort by size descending
|
||||
sorted_symbols = sorted(
|
||||
self._uncategorized_symbols, key=lambda x: x[2], reverse=True
|
||||
)
|
||||
|
||||
lines = ["Uncategorized Symbols Analysis", "=" * 80]
|
||||
lines.append(f"Total uncategorized symbols: {len(sorted_symbols)}")
|
||||
lines.append(
|
||||
f"Total uncategorized size: {sum(s[2] for s in sorted_symbols):,} bytes"
|
||||
)
|
||||
lines.append("")
|
||||
lines.append(f"{'Size':>10} | {'Symbol':<60} | Demangled")
|
||||
lines.append("-" * 10 + "-+-" + "-" * 60 + "-+-" + "-" * 40)
|
||||
|
||||
for symbol, demangled, size in sorted_symbols[:100]: # Top 100
|
||||
if symbol != demangled:
|
||||
lines.append(f"{size:>10,} | {symbol[:60]:<60} | {demangled[:100]}")
|
||||
else:
|
||||
lines.append(f"{size:>10,} | {symbol[:60]:<60} | [not demangled]")
|
||||
|
||||
if len(sorted_symbols) > 100:
|
||||
lines.append(f"\n... and {len(sorted_symbols) - 100} more symbols")
|
||||
|
||||
content = "\n".join(lines)
|
||||
|
||||
if output_file:
|
||||
with open(output_file, "w", encoding="utf-8") as f:
|
||||
f.write(content)
|
||||
else:
|
||||
print(content)
|
||||
|
||||
|
||||
def analyze_elf(
|
||||
elf_path: str,
|
||||
objdump_path: str | None = None,
|
||||
readelf_path: str | None = None,
|
||||
detailed: bool = False,
|
||||
external_components: set[str] | None = None,
|
||||
) -> str:
|
||||
"""Analyze an ELF file and return a memory report."""
|
||||
analyzer = MemoryAnalyzerCLI(
|
||||
elf_path, objdump_path, readelf_path, external_components
|
||||
)
|
||||
analyzer.analyze()
|
||||
return analyzer.generate_report(detailed)
|
||||
|
||||
|
||||
def main():
|
||||
"""CLI entrypoint for memory analysis."""
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: analyze_memory.py <elf_file>")
|
||||
sys.exit(1)
|
||||
|
||||
try:
|
||||
report = analyze_elf(sys.argv[1])
|
||||
print(report)
|
||||
except (subprocess.CalledProcessError, FileNotFoundError, OSError) as e:
|
||||
print(f"Error: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user