# create_benchmark_table.py import argparse import json import re import sys from pathlib import Path from pprint import pprint from collections import defaultdict from typing import Dict, Any, Optional import pandas as pd import html # Import the html module for escaping # Regular expression to parse "test_name (size)" format DIR_PATTERN = re.compile(r"^(.*?) \((.*?)\)$") # Standard location for criterion estimates relative to the benchmark dir ESTIMATES_PATH_NEW = Path("new") / "estimates.json" # Fallback location (older versions or baseline comparisons) ESTIMATES_PATH_BASE = Path("base") / "estimates.json" # Standard location for the HTML report relative to the benchmark's specific directory REPORT_HTML_RELATIVE_PATH = Path("report") / "index.html" def load_criterion_reports(criterion_root_dir: Path) -> Dict[str, Dict[str, Dict[str, Any]]]: """ Loads Criterion benchmark results from a specified directory and finds HTML paths. Args: criterion_root_dir: The Path object pointing to the main 'target/criterion' directory. Returns: A nested dictionary structured as: { test_name: { size: {'json': json_content, 'html_path': relative_html_path}, ... }, ... } Returns an empty dict if the root directory is not found or empty. """ results: Dict[str, Dict[str, Dict[str, Any]]] = defaultdict(dict) if not criterion_root_dir.is_dir(): print( f"Error: Criterion root directory not found or is not a directory: {criterion_root_dir}", file=sys.stderr, ) return {} print(f"Scanning for benchmark reports in: {criterion_root_dir}") for item in criterion_root_dir.iterdir(): # We are only interested in directories matching the pattern if not item.is_dir(): continue match = DIR_PATTERN.match(item.name) if not match: # print(f"Skipping directory (name doesn't match pattern): {item.name}") continue test_name = match.group(1).strip() size = match.group(2).strip() benchmark_dir_name = item.name # Store the original directory name benchmark_dir_path = item # The Path object to the benchmark dir json_path: Optional[Path] = None # Look for the estimates JSON file (prefer 'new', fallback to 'base') if (benchmark_dir_path / ESTIMATES_PATH_NEW).is_file(): json_path = benchmark_dir_path / ESTIMATES_PATH_NEW elif (benchmark_dir_path / ESTIMATES_PATH_BASE).is_file(): json_path = benchmark_dir_path / ESTIMATES_PATH_BASE # The HTML report is at a fixed location relative to the benchmark directory html_path = benchmark_dir_path / REPORT_HTML_RELATIVE_PATH if json_path is None or not json_path.is_file(): print( f"Warning: Could not find estimates JSON in {benchmark_dir_path}. Skipping benchmark size '{test_name} ({size})'.", file=sys.stderr, ) continue # Skip if no JSON data if not html_path.is_file(): print( f"Warning: Could not find HTML report at expected location {html_path}. Skipping benchmark size '{test_name} ({size})'.", file=sys.stderr, ) continue # Skip if no HTML report # Try loading the JSON data try: with json_path.open("r", encoding="utf-8") as f: json_data = json.load(f) # Store both the JSON data and the relative path to the HTML report results[test_name][size] = { 'json': json_data, # The path from the criterion root to the specific benchmark's report/index.html 'html_path_relative_to_criterion_root': str(Path(benchmark_dir_name) / REPORT_HTML_RELATIVE_PATH).replace('\\', '/') # Ensure forward slashes } # print(f" Loaded: {test_name} ({size}) from {json_path}, html: {html_path}") except json.JSONDecodeError: print(f"Error: Failed to decode JSON from {json_path}", file=sys.stderr) except IOError as e: print(f"Error: Failed to read file {json_path}: {e}", file=sys.stderr) except Exception as e: print( f"Error: An unexpected error occurred loading {json_path}: {e}", file=sys.stderr, ) # Convert defaultdict back to regular dict for cleaner output (optional) return dict(results) def format_nanoseconds(ns: float) -> str: """Formats nanoseconds into a human-readable string with units.""" if pd.isna(ns): return "-" if ns < 1_000: return f"{ns:.2f} ns" elif ns < 1_000_000: return f"{ns / 1_000:.2f} µs" elif ns < 1_000_000_000: return f"{ns / 1_000_000:.2f} ms" else: return f"{ns / 1_000_000_000:.2f} s" def generate_html_table_with_links(results: Dict[str, Dict[str, Dict[str, Any]]], html_base_path: str) -> str: """ Generates an HTML table from benchmark results, with cells linking to reports. Args: results: The nested dictionary loaded by load_criterion_reports, including 'json' data and 'html_path_relative_to_criterion_root'. html_base_path: The base URL path where the 'target/criterion' directory is hosted on the static site, relative to the output HTML file. e.g., '../target/criterion/' Returns: A string containing the full HTML table. """ if not results: return "

No benchmark results found or loaded.

" # Get all unique sizes (columns) and test names (rows) # Using ordered dictionaries to maintain insertion order from loading, then sorting keys # Or simply sort the keys after extraction: all_sizes = sorted(list(set(size for test_data in results.values() for size in test_data.keys()))) all_test_names = sorted(list(results.keys())) html_string = """

Criterion Benchmark Results

Each cell links to the detailed Criterion report for that specific benchmark size.

Note: Values shown are the midpoint of the mean confidence interval, formatted for readability.

""" # Add size headers for size in all_sizes: html_string += f"\n" html_string += """ """ # Add data rows for test_name in all_test_names: html_string += f"\n" html_string += f" \n" # Iterate through all possible sizes to ensure columns align for size in all_sizes: cell_data = results.get(test_name, {}).get(size) mean_value = pd.NA # Default value full_report_url = "#" # Default link to self or dummy if cell_data and 'json' in cell_data and 'html_path_relative_to_criterion_root' in cell_data: try: # Extract mean from JSON mean_data = cell_data['json'].get("mean") if mean_data and "confidence_interval" in mean_data: ci = mean_data["confidence_interval"] if "lower_bound" in ci and "upper_bound" in ci: lower, upper = ci["lower_bound"], ci["upper_bound"] if isinstance(lower, (int, float)) and isinstance(upper, (int, float)): mean_value = (lower + upper) / 2.0 else: print(f"Warning: Non-numeric bounds for {test_name} ({size}).", file=sys.stderr) else: print(f"Warning: Missing confidence_interval bounds for {test_name} ({size}).", file=sys.stderr) else: print(f"Warning: Missing 'mean' data for {test_name} ({size}).", file=sys.stderr) # Construct the full relative URL relative_report_path = cell_data['html_path_relative_to_criterion_root'] full_report_url = f"{html_base_path}{relative_report_path}" # Ensure forward slashes and resolve potential double slashes if html_base_path ends in / full_report_url = str(Path(full_report_url)).replace('\\', '/') except Exception as e: print(f"Error processing cell data for {test_name} ({size}): {e}", file=sys.stderr) # Keep mean_value as NA and URL as '#' # Format the mean value for display formatted_mean = format_nanoseconds(mean_value) # Create the link cell # Only make it a link if a valid report path was found if full_report_url and full_report_url != "#": html_string += f' \n' else: # Display value without a link if no report path html_string += f' \n' html_string += f"\n" html_string += """
Benchmark Name{html.escape(size)}
{html.escape(test_name)}{html.escape(formatted_mean)}{html.escape(formatted_mean)}
""" return html_string if __name__ == "__main__": DEFAULT_CRITERION_PATH = "target/criterion" # Default relative path from benchmark_results.html to the criterion root on the hosted site # Assumes benchmark_results.html is in .../doc//benchmarks/ # And target/criterion is copied to .../doc//target/criterion/ # So the path from benchmarks/ to target/criterion/ is ../target/criterion/ DEFAULT_HTML_BASE_PATH = "../target/criterion/" parser = argparse.ArgumentParser( description="Load Criterion benchmark results from JSON files and generate an HTML table with links to reports." ) parser.add_argument( "--criterion-dir", type=str, default=DEFAULT_CRITERION_PATH, help=f"Path to the main 'target/criterion' directory (default: {DEFAULT_CRITERION_PATH}) on the runner.", ) parser.add_argument( "--html-base-path", type=str, default=DEFAULT_HTML_BASE_PATH, help=f"Relative URL path from the output HTML file to the hosted 'target/criterion' directory (default: {DEFAULT_HTML_BASE_PATH}).", ) parser.add_argument( "--output-file", type=str, default="benchmark_results.html", help="Name of the output HTML file (default: benchmark_results.html)." ) args = parser.parse_args() criterion_path = Path(args.criterion_dir) all_results = load_criterion_reports(criterion_path) if not all_results: print("\nNo benchmark results found or loaded.") # Still create an empty file or a file with an error message try: with open(args.output_file, "w", encoding="utf-8") as f: f.write("

Criterion Benchmark Results

No benchmark results found or loaded.

") print(f"Created empty/error HTML file: {args.output_file}") except IOError as e: print(f"Error creating empty/error HTML file {args.output_file}: {e}", file=sys.stderr) sys.exit(1) # Indicate failure if no data was loaded successfully print("\nSuccessfully loaded benchmark results.") # pprint(all_results) # Uncomment for debugging print(f"Generating HTML table with links using base path: {args.html_base_path}") html_output = generate_html_table_with_links(all_results, args.html_base_path) try: with open(args.output_file, "w", encoding="utf-8") as f: f.write(html_output) print(f"\nSuccessfully wrote HTML table to {args.output_file}") sys.exit(0) # Exit successfully except IOError as e: print(f"Error writing HTML output to {args.output_file}: {e}", file=sys.stderr) sys.exit(1) except Exception as e: print(f"An unexpected error occurred while writing HTML: {e}", file=sys.stderr) sys.exit(1)