update metrics to support bloaty

This commit is contained in:
hathach
2025-12-08 16:27:39 +07:00
parent 2c78a2dd9c
commit 16c92b50b0
5 changed files with 482 additions and 354 deletions

View File

@ -15,7 +15,7 @@ deps_mandatory = {
'159e31b689577dbf69cf0683bbaffbd71fa5ee10',
'all'],
'tools/linkermap': ['https://github.com/hathach/linkermap.git',
'5f2956943beb76b98fec78d702d8197daa730117',
'23d1c4c84c4866b84cb821fb368bb9991633871d',
'all'],
'tools/uf2': ['https://github.com/microsoft/uf2.git',
'c594542b2faa01cc33a2b97c9fbebc38549df80a',

View File

@ -1,15 +1,14 @@
#!/usr/bin/env python3
"""Calculate average size from multiple linker map files."""
"""Calculate average sizes using bloaty output."""
import argparse
import csv
import glob
import io
import json
import sys
import os
# Add linkermap module to path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'linkermap'))
import linkermap
import sys
from collections import defaultdict
def expand_files(file_patterns):
@ -30,60 +29,105 @@ def expand_files(file_patterns):
return expanded
def combine_maps(map_files, filters=None):
"""Combine multiple map files into a list of json_data.
def parse_bloaty_csv(csv_text, filters=None):
"""Parse bloaty CSV text and return normalized JSON data structure."""
Args:
map_files: List of paths to linker map files or JSON files
filters: List of path substrings to filter object files (default: [])
Returns:
all_json_data: Dictionary with mapfiles list and data from each map file
"""
filters = filters or []
all_json_data = {"mapfiles": [], "data": []}
reader = csv.DictReader(io.StringIO(csv_text))
size_by_unit = defaultdict(int)
symbols_by_unit: dict[str, defaultdict[str, int]] = defaultdict(lambda: defaultdict(int))
sections_by_unit: dict[str, defaultdict[str, int]] = defaultdict(lambda: defaultdict(int))
def _normalize_json(json_data):
"""Flatten verbose linkermap JSON (per-symbol dicts) to per-section totals."""
for row in reader:
compile_unit = row.get("compileunits") or row.get("compileunit") or row.get("path")
if compile_unit is None:
continue
for f in json_data.get("files", []):
collapsed = {}
for section, val in f.get("sections", {}).items():
collapsed[section] = sum(val.values()) if isinstance(val, dict) else val
if str(compile_unit).upper() == "TOTAL":
continue
# Replace sections with collapsed totals
f["sections"] = collapsed
# Ensure total is a number derived from sections
f["total"] = sum(collapsed.values())
return json_data
for map_file in map_files:
if not os.path.exists(map_file):
print(f"Warning: {map_file} not found, skipping", file=sys.stderr)
if filters and not any(filt in compile_unit for filt in filters):
continue
try:
if map_file.endswith('.json'):
with open(map_file, 'r', encoding='utf-8') as f:
vmsize = int(row.get("vmsize", 0))
except ValueError:
continue
size_by_unit[compile_unit] += vmsize
symbol_name = row.get("symbols", "")
if symbol_name:
symbols_by_unit[compile_unit][symbol_name] += vmsize
section_name = row.get("sections") or row.get("section")
if section_name and vmsize:
sections_by_unit[compile_unit][section_name] += vmsize
files = []
for unit_path, total_size in size_by_unit.items():
symbols = [
{"name": sym, "size": sz}
for sym, sz in sorted(symbols_by_unit[unit_path].items(), key=lambda x: x[1], reverse=True)
]
sections = {sec: sz for sec, sz in sections_by_unit[unit_path].items() if sz}
files.append(
{
"file": os.path.basename(unit_path) or unit_path,
"path": unit_path,
"size": total_size,
"total": total_size,
"symbols": symbols,
"sections": sections,
}
)
total_all = sum(size_by_unit.values())
return {"files": files, "TOTAL": total_all}
def combine_files(input_files, filters=None):
"""Combine multiple bloaty outputs into a single data set."""
filters = filters or []
all_json_data = {"file_list": [], "data": []}
for fin in input_files:
if not os.path.exists(fin):
print(f"Warning: {fin} not found, skipping", file=sys.stderr)
continue
try:
if fin.endswith(".json"):
with open(fin, "r", encoding="utf-8") as f:
json_data = json.load(f)
json_data = _normalize_json(json_data)
# Apply path filters to JSON data
if filters:
filtered_files = [
f for f in json_data.get("files", [])
json_data["files"] = [
f
for f in json_data.get("files", [])
if f.get("path") and any(filt in f["path"] for filt in filters)
]
json_data["files"] = filtered_files
elif fin.endswith(".csv"):
with open(fin, "r", encoding="utf-8") as f:
csv_text = f.read()
json_data = parse_bloaty_csv(csv_text, filters)
else:
json_data = linkermap.analyze_map(map_file, filters=filters)
all_json_data["mapfiles"].append(map_file)
if fin.endswith(".elf"):
print(f"Warning: {fin} is an ELF; please run bloaty with --csv output first. Skipping.",
file=sys.stderr)
else:
print(f"Warning: {fin} is not a supported CSV or JSON metrics input. Skipping.",
file=sys.stderr)
continue
# Drop any fake TOTAL entries that slipped in as files
json_data["files"] = [
f for f in json_data.get("files", [])
if str(f.get("file", "")).upper() != "TOTAL"
]
all_json_data["file_list"].append(fin)
all_json_data["data"].append(json_data)
except Exception as e:
print(f"Warning: Failed to analyze {map_file}: {e}", file=sys.stderr)
except Exception as e: # pragma: no cover - defensive
print(f"Warning: Failed to analyze {fin}: {e}", file=sys.stderr)
continue
return all_json_data
@ -93,7 +137,7 @@ def compute_avg(all_json_data):
"""Compute average sizes from combined json_data.
Args:
all_json_data: Dictionary with mapfiles and data from combine_maps()
all_json_data: Dictionary with file_list and data from combine_files()
Returns:
json_average: Dictionary with averaged size data
@ -101,128 +145,133 @@ def compute_avg(all_json_data):
if not all_json_data["data"]:
return None
# Collect all sections preserving order
all_sections = []
for json_data in all_json_data["data"]:
for s in json_data["sections"]:
if s not in all_sections:
all_sections.append(s)
# Merge files with the same 'file' value and compute averages
file_accumulator = {} # key: file name, value: {"sections": {section: [sizes]}, "totals": [totals]}
file_accumulator = {} # key: file name, value: {"sizes": [sizes], "totals": [totals], "symbols": {name: [sizes]}, "sections": {name: [sizes]}}
for json_data in all_json_data["data"]:
for f in json_data["files"]:
for f in json_data.get("files", []):
fname = f["file"]
if fname not in file_accumulator:
file_accumulator[fname] = {"sections": {}, "totals": [], "path": f.get("path")}
file_accumulator[fname]["totals"].append(f["total"])
for section, size in f["sections"].items():
if section in file_accumulator[fname]["sections"]:
file_accumulator[fname]["sections"][section].append(size)
else:
file_accumulator[fname]["sections"][section] = [size]
file_accumulator[fname] = {
"sizes": [],
"totals": [],
"path": f.get("path"),
"symbols": defaultdict(list),
"sections": defaultdict(list),
}
size_val = f.get("size", f.get("total", 0))
file_accumulator[fname]["sizes"].append(size_val)
file_accumulator[fname]["totals"].append(f.get("total", size_val))
for sym in f.get("symbols", []):
name = sym.get("name")
if name is None:
continue
file_accumulator[fname]["symbols"][name].append(sym.get("size", 0))
sections_map = f.get("sections") or {}
if isinstance(sections_map, list):
sections_map = {
s.get("name"): s.get("size", 0)
for s in sections_map
if isinstance(s, dict) and s.get("name")
}
for sname, ssize in sections_map.items():
file_accumulator[fname]["sections"][sname].append(ssize)
# Build json_average with averaged values
files_average = []
for fname, data in file_accumulator.items():
avg_total = round(sum(data["totals"]) / len(data["totals"]))
avg_sections = {}
for section, sizes in data["sections"].items():
avg_sections[section] = round(sum(sizes) / len(sizes))
files_average.append({
"file": fname,
"path": data["path"],
"sections": avg_sections,
"total": avg_total
})
avg_size = round(sum(data["sizes"]) / len(data["sizes"])) if data["sizes"] else 0
symbols_avg = []
for sym_name, sizes in data["symbols"].items():
if not sizes:
continue
symbols_avg.append({"name": sym_name, "size": round(sum(sizes) / len(sizes))})
symbols_avg.sort(key=lambda x: x["size"], reverse=True)
sections_avg = {
sec_name: round(sum(sizes) / len(sizes))
for sec_name, sizes in data["sections"].items()
if sizes
}
files_average.append(
{
"file": fname,
"path": data["path"],
"size": avg_size,
"symbols": symbols_avg,
"sections": sections_avg,
}
)
totals_list = [d.get("TOTAL") for d in all_json_data["data"] if isinstance(d.get("TOTAL"), (int, float))]
total_size = round(sum(totals_list) / len(totals_list)) if totals_list else (
sum(f["size"] for f in files_average) or 1)
for f in files_average:
f["percent"] = (f["size"] / total_size) * 100 if total_size else 0
for sym in f["symbols"]:
sym["percent"] = (sym["size"] / f["size"]) * 100 if f["size"] else 0
json_average = {
"mapfiles": all_json_data["mapfiles"],
"sections": all_sections,
"files": files_average
"file_list": all_json_data["file_list"],
"TOTAL": total_size,
"files": files_average,
}
return json_average
def compare_maps(base_file, new_file, filters=None):
"""Compare two map/json files and generate difference report.
Args:
base_file: Path to base map/json file
new_file: Path to new map/json file
filters: List of path substrings to filter object files
Returns:
Dictionary with comparison data
"""
def compare_files(base_file, new_file, filters=None):
"""Compare two CSV or JSON inputs and generate difference report."""
filters = filters or []
# Load both files
base_data = combine_maps([base_file], filters)
new_data = combine_maps([new_file], filters)
if not base_data["data"] or not new_data["data"]:
return None
base_avg = compute_avg(base_data)
new_avg = compute_avg(new_data)
base_avg = compute_avg(combine_files([base_file], filters))
new_avg = compute_avg(combine_files([new_file], filters))
if not base_avg or not new_avg:
return None
# Collect all sections from both
all_sections = list(base_avg["sections"])
for s in new_avg["sections"]:
if s not in all_sections:
all_sections.append(s)
# Build file lookup
base_files = {f["file"]: f for f in base_avg["files"]}
new_files = {f["file"]: f for f in new_avg["files"]}
# Get all file names
all_file_names = set(base_files.keys()) | set(new_files.keys())
# Build comparison data
comparison = []
comparison_files = []
for fname in sorted(all_file_names):
base_f = base_files.get(fname)
new_f = new_files.get(fname)
b = base_files.get(fname, {})
n = new_files.get(fname, {})
b_size = b.get("size", 0)
n_size = n.get("size", 0)
row = {"file": fname, "sections": {}, "total": {}}
# Symbol diffs
b_syms = {s["name"]: s for s in b.get("symbols", [])}
n_syms = {s["name"]: s for s in n.get("symbols", [])}
all_syms = set(b_syms.keys()) | set(n_syms.keys())
symbols = []
for sym in all_syms:
sb = b_syms.get(sym, {}).get("size", 0)
sn = n_syms.get(sym, {}).get("size", 0)
symbols.append({"name": sym, "base": sb, "new": sn, "diff": sn - sb})
symbols.sort(key=lambda x: abs(x["diff"]), reverse=True)
for section in all_sections:
base_val = base_f["sections"].get(section, 0) if base_f else 0
new_val = new_f["sections"].get(section, 0) if new_f else 0
row["sections"][section] = {"base": base_val, "new": new_val, "diff": new_val - base_val}
comparison_files.append({
"file": fname,
"size": {"base": b_size, "new": n_size, "diff": n_size - b_size},
"symbols": symbols,
})
base_total = base_f["total"] if base_f else 0
new_total = new_f["total"] if new_f else 0
row["total"] = {"base": base_total, "new": new_total, "diff": new_total - base_total}
comparison.append(row)
total = {
"base": base_avg.get("TOTAL", 0),
"new": new_avg.get("TOTAL", 0),
"diff": new_avg.get("TOTAL", 0) - base_avg.get("TOTAL", 0),
}
return {
"base_file": base_file,
"new_file": new_file,
"sections": all_sections,
"files": comparison
"total": total,
"files": comparison_files,
}
def format_diff(base, new, diff):
"""Format a diff value with percentage."""
if diff == 0:
return f"{new}"
if base == 0 or new == 0:
return f"{base}{new}"
pct = (diff / base) * 100
sign = "+" if diff > 0 else ""
return f"{base}{new} ({sign}{diff}, {sign}{pct:.1f}%)"
def get_sort_key(sort_order):
"""Get sort key function based on sort order.
@ -232,131 +281,148 @@ def get_sort_key(sort_order):
Returns:
Tuple of (key_func, reverse)
"""
def _size_val(entry):
if isinstance(entry.get('total'), int):
return entry.get('total', 0)
if isinstance(entry.get('total'), dict):
return entry['total'].get('new', 0)
return entry.get('size', 0)
if sort_order == 'size-':
return lambda x: x.get('total', 0) if isinstance(x.get('total'), int) else x['total']['new'], True
return _size_val, True
elif sort_order == 'size+':
return lambda x: x.get('total', 0) if isinstance(x.get('total'), int) else x['total']['new'], False
return _size_val, False
elif sort_order == 'name-':
return lambda x: x.get('file', ''), True
else: # name+
return lambda x: x.get('file', ''), False
def write_json_output(json_data, path):
"""Write JSON output with indentation."""
with open(path, "w", encoding="utf-8") as outf:
json.dump(json_data, outf, indent=2)
def render_combine_table(json_data, sort_order='name+'):
"""Render averaged sizes as markdown table lines (no title)."""
files = json_data.get("files", [])
if not files:
return ["No entries."]
key_func, reverse = get_sort_key(sort_order)
files_sorted = sorted(files, key=key_func, reverse=reverse)
total_size = json_data.get("TOTAL") or (sum(f.get("size", 0) for f in files_sorted) or 1)
pct_strings = [
f"{(f.get('percent') if f.get('percent') is not None else (f.get('size', 0) / total_size * 100 if total_size else 0)):.1f}%"
for f in files_sorted]
pct_width = 6
size_width = max(len("size"), *(len(str(f.get("size", 0))) for f in files_sorted), len(str(total_size)))
file_width = max(len("File"), *(len(f.get("file", "")) for f in files_sorted), len("TOTAL"))
# Build section totals on the fly from file data
sections_global = defaultdict(int)
for f in files_sorted:
for name, size in (f.get("sections") or {}).items():
sections_global[name] += size
# Display sections in reverse alphabetical order for stable column layout
section_names = sorted(sections_global.keys(), reverse=True)
section_widths = {}
for name in section_names:
max_val = max((f.get("sections", {}).get(name, 0) for f in files_sorted), default=0)
section_widths[name] = max(len(name), len(str(max_val)), 1)
if not section_names:
header = f"| {'File':<{file_width}} | {'size':>{size_width}} | {'%':>{pct_width}} |"
separator = f"| :{'-' * (file_width - 1)} | {'-' * (size_width - 1)}: | {'-' * (pct_width - 1)}: |"
else:
header_parts = [f"| {'File':<{file_width}} |"]
sep_parts = [f"| :{'-' * (file_width - 1)} |"]
for name in section_names:
header_parts.append(f" {name:>{section_widths[name]}} |")
sep_parts.append(f" {'-' * (section_widths[name] - 1)}: |")
header_parts.append(f" {'size':>{size_width}} | {'%':>{pct_width}} |")
sep_parts.append(f" {'-' * (size_width - 1)}: | {'-' * (pct_width - 1)}: |")
header = "".join(header_parts)
separator = "".join(sep_parts)
lines = [header, separator]
for f, pct_str in zip(files_sorted, pct_strings):
size_val = f.get("size", 0)
parts = [f"| {f.get('file', ''):<{file_width}} |"]
if section_names:
sections_map = f.get("sections") or {}
if isinstance(sections_map, list):
sections_map = {
s.get("name"): s.get("size", 0)
for s in sections_map
if isinstance(s, dict) and s.get("name")
}
for name in section_names:
parts.append(f" {sections_map.get(name, 0):>{section_widths[name]}} |")
parts.append(f" {size_val:>{size_width}} | {pct_str:>{pct_width}} |")
lines.append("".join(parts))
total_parts = [f"| {'TOTAL':<{file_width}} |"]
if section_names:
for name in section_names:
total_parts.append(f" {sections_global.get(name, 0):>{section_widths[name]}} |")
total_parts.append(f" {total_size:>{size_width}} | {'100.0%':>{pct_width}} |")
lines.append("".join(total_parts))
return lines
def write_combine_markdown(json_data, path, sort_order='name+', title="TinyUSB Average Code Size Metrics"):
"""Write averaged size data to a markdown file."""
md_lines = [f"# {title}", ""]
md_lines.extend(render_combine_table(json_data, sort_order))
md_lines.append("")
if json_data.get("file_list"):
md_lines.extend(["<details>", "<summary>Input files</summary>", ""])
md_lines.extend([f"- {mf}" for mf in json_data["file_list"]])
md_lines.extend(["", "</details>", ""])
with open(path, "w", encoding="utf-8") as f:
f.write("\n".join(md_lines))
def write_compare_markdown(comparison, path, sort_order='size'):
"""Write comparison data to markdown file."""
sections = comparison["sections"]
md_lines = [
"# Size Difference Report",
"",
"Because TinyUSB code size varies by port and configuration, the metrics below represent the averaged totals across all example builds."
"Because TinyUSB code size varies by port and configuration, the metrics below represent the averaged totals across all example builds.",
"",
"Note: If there is no change, only one value is shown.",
"",
]
# Build header
header = "| File |"
separator = "|:-----|"
for s in sections:
header += f" {s} |"
separator += "-----:|"
header += " Total |"
separator += "------:|"
significant, minor, unchanged = _split_by_significance(comparison["files"], sort_order)
def is_significant(file_row):
for s in sections:
sd = file_row["sections"][s]
diff = abs(sd["diff"])
base = sd["base"]
if base == 0:
if diff != 0:
return True
else:
if (diff / base) * 100 > 1.0:
return True
return False
# Sort files based on sort_order
if sort_order == 'size-':
key_func = lambda x: abs(x["total"]["diff"])
reverse = True
elif sort_order in ('size', 'size+'):
key_func = lambda x: abs(x["total"]["diff"])
reverse = False
elif sort_order == 'name-':
key_func = lambda x: x['file']
reverse = True
else: # name or name+
key_func = lambda x: x['file']
reverse = False
sorted_files = sorted(comparison["files"], key=key_func, reverse=reverse)
significant = []
minor = []
unchanged = []
for f in sorted_files:
no_change = f["total"]["diff"] == 0 and all(f["sections"][s]["diff"] == 0 for s in sections)
if no_change:
unchanged.append(f)
else:
(significant if is_significant(f) else minor).append(f)
def render_table(title, rows, collapsed=False):
def render(title, rows, collapsed=False):
if collapsed:
md_lines.append(f"<details><summary>{title}</summary>")
md_lines.append("")
else:
md_lines.append(f"## {title}")
if not rows:
md_lines.append("No entries.")
md_lines.append("")
if collapsed:
md_lines.append("</details>")
md_lines.append("")
return
md_lines.append(header)
md_lines.append(separator)
sum_base = {s: 0 for s in sections}
sum_base["total"] = 0
sum_new = {s: 0 for s in sections}
sum_new["total"] = 0
for f in rows:
row = f"| {f['file']} |"
for s in sections:
sd = f["sections"][s]
sum_base[s] += sd["base"]
sum_new[s] += sd["new"]
row += f" {format_diff(sd['base'], sd['new'], sd['diff'])} |"
td = f["total"]
sum_base["total"] += td["base"]
sum_new["total"] += td["new"]
row += f" {format_diff(td['base'], td['new'], td['diff'])} |"
md_lines.append(row)
# Add sum row
sum_row = "| **SUM** |"
for s in sections:
diff = sum_new[s] - sum_base[s]
sum_row += f" {format_diff(sum_base[s], sum_new[s], diff)} |"
total_diff = sum_new["total"] - sum_base["total"]
sum_row += f" {format_diff(sum_base['total'], sum_new['total'], total_diff)} |"
md_lines.append(sum_row)
md_lines.extend(render_compare_table(_build_rows(rows, sort_order), include_sum=True))
md_lines.append("")
if collapsed:
md_lines.append("</details>")
md_lines.append("")
render_table("Changes >1% in any section", significant)
render_table("Changes <1% in all sections", minor)
render_table("No changes", unchanged, collapsed=True)
render("Changes >1% in size", significant)
render("Changes <1% in size", minor)
render("No changes", unchanged, collapsed=True)
with open(path, "w", encoding="utf-8") as f:
f.write("\n".join(md_lines))
@ -365,14 +431,22 @@ def write_compare_markdown(comparison, path, sort_order='size'):
def print_compare_summary(comparison, sort_order='name+'):
"""Print diff report to stdout in table form."""
sections = comparison["sections"]
files = comparison["files"]
rows = _build_rows(files, sort_order)
lines = render_compare_table(rows, include_sum=True)
for line in lines:
print(line)
def _build_rows(files, sort_order):
"""Sort files and prepare printable fields."""
def sort_key(file_row):
if sort_order == 'size-':
return abs(file_row["total"]["diff"])
return abs(file_row["size"]["diff"])
if sort_order in ('size', 'size+'):
return abs(file_row["total"]["diff"])
return abs(file_row["size"]["diff"])
if sort_order == 'name-':
return file_row['file']
return file_row['file']
@ -380,63 +454,118 @@ def print_compare_summary(comparison, sort_order='name+'):
reverse = sort_order in ('size-', 'name-')
files_sorted = sorted(files, key=sort_key, reverse=reverse)
# Build formatted rows first to compute column widths precisely
rows = []
value_lengths = []
for f in files_sorted:
section_vals = {}
for s in sections:
sd = f["sections"][s]
text = format_diff(sd['base'], sd['new'], sd['diff'])
section_vals[s] = text
value_lengths.append(len(text))
td = f["total"]
total_text = format_diff(td['base'], td['new'], td['diff'])
value_lengths.append(len(total_text))
rows.append({"file": f['file'], "sections": section_vals, "total": total_text, "raw": f})
sd = f["size"]
diff_val = sd['new'] - sd['base']
if sd['base'] == 0:
pct_str = "n/a"
else:
pct_val = (diff_val / sd['base']) * 100
pct_str = f"{pct_val:+.1f}%"
rows.append({
"file": f['file'],
"base": sd['base'],
"new": sd['new'],
"diff": diff_val,
"pct": pct_str,
})
return rows
# Column widths
name_width = max(len(r["file"]) for r in rows) if rows else len("File")
name_width = max(name_width, len("File"), 3) # at least width of SUM
col_width = max(12, *(len(s) for s in sections), len("Total"), *(value_lengths or [0]))
ffmt = '{:' + f'>{name_width}' + '} |'
col_fmt = '{:' + f'>{col_width}' + '}'
def _split_by_significance(files, sort_order):
"""Split files into >1% changes, <1% changes, and no changes."""
header = ffmt.format('File') + ''.join(col_fmt.format(s) + ' |' for s in sections) + col_fmt.format('Total')
print(header)
print('-' * len(header))
def is_significant(file_row):
base = file_row["size"]["base"]
diff = abs(file_row["size"]["diff"])
if base == 0:
return diff != 0
return (diff / base) * 100 > 1.0
sum_base = {s: 0 for s in sections}
sum_new = {s: 0 for s in sections}
rows_sorted = sorted(
files,
key=lambda f: abs(f["size"]["diff"]) if sort_order.startswith("size") else f["file"],
reverse=sort_order in ('size-', 'name-'),
)
for row in rows:
line = ffmt.format(row['file'])
for s in sections:
sd = row["raw"]["sections"][s]
sum_base[s] += sd["base"]
sum_new[s] += sd["new"]
line += col_fmt.format(row['sections'][s]) + ' |'
significant = []
minor = []
unchanged = []
for f in rows_sorted:
if f["size"]["diff"] == 0:
unchanged.append(f)
else:
(significant if is_significant(f) else minor).append(f)
line += col_fmt.format(row['total'])
print(line)
return significant, minor, unchanged
# Sum row
sum_row = ffmt.format('SUM')
for s in sections:
diff = sum_new[s] - sum_base[s]
sum_row += col_fmt.format(format_diff(sum_base[s], sum_new[s], diff)) + ' |'
total_base = sum(sum_base.values())
total_new = sum(sum_new.values())
sum_row += col_fmt.format(format_diff(total_base, total_new, total_new - total_base))
print('-' * len(header))
print(sum_row)
def render_compare_table(rows, include_sum):
"""Return markdown table lines for given rows."""
if not rows:
return ["No entries.", ""]
sum_base = sum(r["base"] for r in rows)
sum_new = sum(r["new"] for r in rows)
total_diff = sum_new - sum_base
total_pct = "n/a" if sum_base == 0 else f"{(total_diff / sum_base) * 100:+.1f}%"
base_width = max(len("base"), *(len(str(r["base"])) for r in rows))
new_width = max(len("new"), *(len(str(r["new"])) for r in rows))
diff_width = max(len("diff"), *(len(f"{r['diff']:+}") for r in rows))
pct_width = max(len("% diff"), *(len(r["pct"]) for r in rows))
name_width = max(len("file"), *(len(r["file"]) for r in rows))
if include_sum:
base_width = max(base_width, len(str(sum_base)))
new_width = max(new_width, len(str(sum_new)))
diff_width = max(diff_width, len(f"{total_diff:+}"))
pct_width = max(pct_width, len(total_pct))
name_width = max(name_width, len("TOTAL"))
header = (
f"| {'file':<{name_width}} | "
f"{'base':>{base_width}} | "
f"{'new':>{new_width}} | "
f"{'diff':>{diff_width}} | "
f"{'% diff':>{pct_width}} |"
)
separator = (
f"| :{'-' * (name_width - 1)} | "
f"{'-' * base_width}:| "
f"{'-' * new_width}:| "
f"{'-' * diff_width}:| "
f"{'-' * pct_width}:|"
)
lines = [header, separator]
for r in rows:
diff_str = f"{r['diff']:+}"
lines.append(
f"| {r['file']:<{name_width}} | "
f"{str(r['base']):>{base_width}} | "
f"{str(r['new']):>{new_width}} | "
f"{diff_str:>{diff_width}} | "
f"{r['pct']:>{pct_width}} |"
)
if include_sum:
lines.append(
f"| {'TOTAL':<{name_width}} | "
f"{sum_base:>{base_width}} | "
f"{sum_new:>{new_width}} | "
f"{total_diff:+{diff_width}d} | "
f"{total_pct:>{pct_width}} |"
)
return lines
def cmd_combine(args):
"""Handle combine subcommand."""
map_files = expand_files(args.files)
all_json_data = combine_maps(map_files, args.filters)
input_files = expand_files(args.files)
all_json_data = combine_files(input_files, args.filters)
json_average = compute_avg(all_json_data)
if json_average is None:
@ -444,17 +573,18 @@ def cmd_combine(args):
sys.exit(1)
if not args.quiet:
linkermap.print_summary(json_average, False, args.sort)
for line in render_combine_table(json_average, sort_order=args.sort):
print(line)
if args.json_out:
linkermap.write_json(json_average, args.out + '.json')
write_json_output(json_average, args.out + '.json')
if args.markdown_out:
linkermap.write_markdown(json_average, args.out + '.md', sort_opt=args.sort,
title="TinyUSB Average Code Size Metrics")
write_combine_markdown(json_average, args.out + '.md', sort_order=args.sort,
title="TinyUSB Average Code Size Metrics")
def cmd_compare(args):
"""Handle compare subcommand."""
comparison = compare_maps(args.base, args.new, args.filters)
comparison = compare_files(args.base, args.new, args.filters)
if comparison is None:
print("Failed to compare files", file=sys.stderr)
@ -472,10 +602,11 @@ def main(argv=None):
subparsers = parser.add_subparsers(dest='command', required=True, help='Available commands')
# Combine subcommand
combine_parser = subparsers.add_parser('combine', help='Combine and average multiple map files')
combine_parser.add_argument('files', nargs='+', help='Path to map file(s) or glob pattern(s)')
combine_parser = subparsers.add_parser('combine', help='Combine and average multiple bloaty outputs')
combine_parser.add_argument('files', nargs='+',
help='Path to bloaty CSV output or JSON file(s) or glob pattern(s)')
combine_parser.add_argument('-f', '--filter', dest='filters', action='append', default=[],
help='Only include object files whose path contains this substring (can be repeated)')
help='Only include compile units whose path contains this substring (can be repeated)')
combine_parser.add_argument('-o', '--out', dest='out', default='metrics',
help='Output path basename for JSON and Markdown files (default: metrics)')
combine_parser.add_argument('-j', '--json', dest='json_out', action='store_true',
@ -484,16 +615,16 @@ def main(argv=None):
help='Write Markdown output file')
combine_parser.add_argument('-q', '--quiet', dest='quiet', action='store_true',
help='Suppress summary output')
combine_parser.add_argument('-S', '--sort', dest='sort', default='name+',
combine_parser.add_argument('-S', '--sort', dest='sort', default='size-',
choices=['size', 'size-', 'size+', 'name', 'name-', 'name+'],
help='Sort order: size/size- (descending), size+ (ascending), name/name+ (ascending), name- (descending). Default: name+')
help='Sort order: size/size- (descending), size+ (ascending), name/name+ (ascending), name- (descending). Default: size-')
# Compare subcommand
compare_parser = subparsers.add_parser('compare', help='Compare two map files')
compare_parser.add_argument('base', help='Base map/json file')
compare_parser.add_argument('new', help='New map/json file')
compare_parser = subparsers.add_parser('compare', help='Compare two bloaty outputs (CSV) or JSON inputs')
compare_parser.add_argument('base', help='Base CSV/JSON file')
compare_parser.add_argument('new', help='New CSV/JSON file')
compare_parser.add_argument('-f', '--filter', dest='filters', action='append', default=[],
help='Only include object files whose path contains this substring (can be repeated)')
help='Only include compile units whose path contains this substring (can be repeated)')
compare_parser.add_argument('-o', '--out', dest='out', default='metrics_compare',
help='Output path basename for Markdown file (default: metrics_compare)')
compare_parser.add_argument('-S', '--sort', dest='sort', default='name+',