| """Print a summary of specialization stats for all files in the |
| default stats folders. |
| """ |
| |
| import argparse |
| import collections |
| import json |
| import os.path |
| import opcode |
| from datetime import date |
| import itertools |
| import sys |
| |
| if os.name == "nt": |
| DEFAULT_DIR = "c:\\temp\\py_stats\\" |
| else: |
| DEFAULT_DIR = "/tmp/py_stats/" |
| |
| #Create list of all instruction names |
| specialized = iter(opcode._specialized_instructions) |
| opname = ["<0>"] |
| for name in opcode.opname[1:]: |
| if name.startswith("<"): |
| try: |
| name = next(specialized) |
| except StopIteration: |
| pass |
| opname.append(name) |
| |
| # opcode_name --> opcode |
| # Sort alphabetically. |
| opmap = {name: i for i, name in enumerate(opname)} |
| opmap = dict(sorted(opmap.items())) |
| |
| TOTAL = "specialization.hit", "specialization.miss", "execution_count" |
| |
| def format_ratio(num, den): |
| """ |
| Format a ratio as a percentage. When the denominator is 0, returns the empty |
| string. |
| """ |
| if den == 0: |
| return "" |
| else: |
| return f"{num/den:.01%}" |
| |
| def join_rows(a_rows, b_rows): |
| """ |
| Joins two tables together, side-by-side, where the first column in each is a |
| common key. |
| """ |
| if len(a_rows) == 0 and len(b_rows) == 0: |
| return [] |
| |
| if len(a_rows): |
| a_ncols = list(set(len(x) for x in a_rows)) |
| if len(a_ncols) != 1: |
| raise ValueError("Table a is ragged") |
| |
| if len(b_rows): |
| b_ncols = list(set(len(x) for x in b_rows)) |
| if len(b_ncols) != 1: |
| raise ValueError("Table b is ragged") |
| |
| if len(a_rows) and len(b_rows) and a_ncols[0] != b_ncols[0]: |
| raise ValueError("Tables have different widths") |
| |
| if len(a_rows): |
| ncols = a_ncols[0] |
| else: |
| ncols = b_ncols[0] |
| |
| default = [""] * (ncols - 1) |
| a_data = {x[0]: x[1:] for x in a_rows} |
| b_data = {x[0]: x[1:] for x in b_rows} |
| |
| if len(a_data) != len(a_rows) or len(b_data) != len(b_rows): |
| raise ValueError("Duplicate keys") |
| |
| # To preserve ordering, use A's keys as is and then add any in B that aren't |
| # in A |
| keys = list(a_data.keys()) + [k for k in b_data.keys() if k not in a_data] |
| return [(k, *a_data.get(k, default), *b_data.get(k, default)) for k in keys] |
| |
| def calculate_specialization_stats(family_stats, total): |
| rows = [] |
| for key in sorted(family_stats): |
| if key.startswith("specialization.failure_kinds"): |
| continue |
| if key in ("specialization.hit", "specialization.miss"): |
| label = key[len("specialization."):] |
| elif key == "execution_count": |
| continue |
| elif key in ("specialization.success", "specialization.failure", "specializable"): |
| continue |
| elif key.startswith("pair"): |
| continue |
| else: |
| label = key |
| rows.append((f"{label:>12}", f"{family_stats[key]:>12}", format_ratio(family_stats[key], total))) |
| return rows |
| |
| def calculate_specialization_success_failure(family_stats): |
| total_attempts = 0 |
| for key in ("specialization.success", "specialization.failure"): |
| total_attempts += family_stats.get(key, 0) |
| rows = [] |
| if total_attempts: |
| for key in ("specialization.success", "specialization.failure"): |
| label = key[len("specialization."):] |
| label = label[0].upper() + label[1:] |
| val = family_stats.get(key, 0) |
| rows.append((label, val, format_ratio(val, total_attempts))) |
| return rows |
| |
| def calculate_specialization_failure_kinds(name, family_stats, defines): |
| total_failures = family_stats.get("specialization.failure", 0) |
| failure_kinds = [ 0 ] * 40 |
| for key in family_stats: |
| if not key.startswith("specialization.failure_kind"): |
| continue |
| _, index = key[:-1].split("[") |
| index = int(index) |
| failure_kinds[index] = family_stats[key] |
| failures = [(value, index) for (index, value) in enumerate(failure_kinds)] |
| failures.sort(reverse=True) |
| rows = [] |
| for value, index in failures: |
| if not value: |
| continue |
| rows.append((kind_to_text(index, defines, name), value, format_ratio(value, total_failures))) |
| return rows |
| |
| def print_specialization_stats(name, family_stats, defines): |
| if "specializable" not in family_stats: |
| return |
| total = sum(family_stats.get(kind, 0) for kind in TOTAL) |
| if total == 0: |
| return |
| with Section(name, 3, f"specialization stats for {name} family"): |
| rows = calculate_specialization_stats(family_stats, total) |
| emit_table(("Kind", "Count", "Ratio"), rows) |
| rows = calculate_specialization_success_failure(family_stats) |
| if rows: |
| print_title("Specialization attempts", 4) |
| emit_table(("", "Count:", "Ratio:"), rows) |
| rows = calculate_specialization_failure_kinds(name, family_stats, defines) |
| emit_table(("Failure kind", "Count:", "Ratio:"), rows) |
| |
| def print_comparative_specialization_stats(name, base_family_stats, head_family_stats, defines): |
| if "specializable" not in base_family_stats: |
| return |
| |
| base_total = sum(base_family_stats.get(kind, 0) for kind in TOTAL) |
| head_total = sum(head_family_stats.get(kind, 0) for kind in TOTAL) |
| if base_total + head_total == 0: |
| return |
| with Section(name, 3, f"specialization stats for {name} family"): |
| base_rows = calculate_specialization_stats(base_family_stats, base_total) |
| head_rows = calculate_specialization_stats(head_family_stats, head_total) |
| emit_table( |
| ("Kind", "Base Count", "Base Ratio", "Head Count", "Head Ratio"), |
| join_rows(base_rows, head_rows) |
| ) |
| base_rows = calculate_specialization_success_failure(base_family_stats) |
| head_rows = calculate_specialization_success_failure(head_family_stats) |
| rows = join_rows(base_rows, head_rows) |
| if rows: |
| print_title("Specialization attempts", 4) |
| emit_table(("", "Base Count:", "Base Ratio:", "Head Count:", "Head Ratio:"), rows) |
| base_rows = calculate_specialization_failure_kinds(name, base_family_stats, defines) |
| head_rows = calculate_specialization_failure_kinds(name, head_family_stats, defines) |
| emit_table( |
| ("Failure kind", "Base Count:", "Base Ratio:", "Head Count:", "Head Ratio:"), |
| join_rows(base_rows, head_rows) |
| ) |
| |
| def gather_stats(input): |
| # Note the output of this function must be JSON-serializable |
| |
| if os.path.isfile(input): |
| with open(input, "r") as fd: |
| return json.load(fd) |
| elif os.path.isdir(input): |
| stats = collections.Counter() |
| for filename in os.listdir(input): |
| with open(os.path.join(input, filename)) as fd: |
| for line in fd: |
| try: |
| key, value = line.split(":") |
| except ValueError: |
| print(f"Unparsable line: '{line.strip()}' in {filename}", file=sys.stderr) |
| continue |
| key = key.strip() |
| value = int(value) |
| stats[key] += value |
| stats['__nfiles__'] += 1 |
| return stats |
| else: |
| raise ValueError(f"{input:r} is not a file or directory path") |
| |
| def extract_opcode_stats(stats): |
| opcode_stats = [ {} for _ in range(256) ] |
| for key, value in stats.items(): |
| if not key.startswith("opcode"): |
| continue |
| n, _, rest = key[7:].partition("]") |
| opcode_stats[int(n)][rest.strip(".")] = value |
| return opcode_stats |
| |
| def parse_kinds(spec_src, prefix="SPEC_FAIL"): |
| defines = collections.defaultdict(list) |
| start = "#define " + prefix + "_" |
| for line in spec_src: |
| line = line.strip() |
| if not line.startswith(start): |
| continue |
| line = line[len(start):] |
| name, val = line.split() |
| defines[int(val.strip())].append(name.strip()) |
| return defines |
| |
| def pretty(defname): |
| return defname.replace("_", " ").lower() |
| |
| def kind_to_text(kind, defines, opname): |
| if kind <= 8: |
| return pretty(defines[kind][0]) |
| if opname == "LOAD_SUPER_ATTR": |
| opname = "SUPER" |
| elif opname.endswith("ATTR"): |
| opname = "ATTR" |
| elif opname in ("FOR_ITER", "SEND"): |
| opname = "ITER" |
| elif opname.endswith("SUBSCR"): |
| opname = "SUBSCR" |
| for name in defines[kind]: |
| if name.startswith(opname): |
| return pretty(name[len(opname)+1:]) |
| return "kind " + str(kind) |
| |
| def categorized_counts(opcode_stats): |
| basic = 0 |
| specialized = 0 |
| not_specialized = 0 |
| specialized_instructions = { |
| op for op in opcode._specialized_instructions |
| if "__" not in op} |
| for i, opcode_stat in enumerate(opcode_stats): |
| if "execution_count" not in opcode_stat: |
| continue |
| count = opcode_stat['execution_count'] |
| name = opname[i] |
| if "specializable" in opcode_stat: |
| not_specialized += count |
| elif name in specialized_instructions: |
| miss = opcode_stat.get("specialization.miss", 0) |
| not_specialized += miss |
| specialized += count - miss |
| else: |
| basic += count |
| return basic, not_specialized, specialized |
| |
| def print_title(name, level=2): |
| print("#"*level, name) |
| print() |
| |
| class Section: |
| |
| def __init__(self, title, level=2, summary=None): |
| self.title = title |
| self.level = level |
| if summary is None: |
| self.summary = title.lower() |
| else: |
| self.summary = summary |
| |
| def __enter__(self): |
| print_title(self.title, self.level) |
| print("<details>") |
| print("<summary>", self.summary, "</summary>") |
| print() |
| return self |
| |
| def __exit__(*args): |
| print() |
| print("</details>") |
| print() |
| |
| def to_str(x): |
| if isinstance(x, int): |
| return format(x, ",d") |
| else: |
| return str(x) |
| |
| def emit_table(header, rows): |
| width = len(header) |
| header_line = "|" |
| under_line = "|" |
| for item in header: |
| under = "---" |
| if item.endswith(":"): |
| item = item[:-1] |
| under += ":" |
| header_line += item + " | " |
| under_line += under + "|" |
| print(header_line) |
| print(under_line) |
| for row in rows: |
| if width is not None and len(row) != width: |
| raise ValueError("Wrong number of elements in row '" + str(row) + "'") |
| print("|", " | ".join(to_str(i) for i in row), "|") |
| print() |
| |
| def calculate_execution_counts(opcode_stats, total): |
| counts = [] |
| for i, opcode_stat in enumerate(opcode_stats): |
| if "execution_count" in opcode_stat: |
| count = opcode_stat['execution_count'] |
| miss = 0 |
| if "specializable" not in opcode_stat: |
| miss = opcode_stat.get("specialization.miss") |
| counts.append((count, opname[i], miss)) |
| counts.sort(reverse=True) |
| cumulative = 0 |
| rows = [] |
| for (count, name, miss) in counts: |
| cumulative += count |
| if miss: |
| miss = format_ratio(miss, count) |
| else: |
| miss = "" |
| rows.append((name, count, format_ratio(count, total), |
| format_ratio(cumulative, total), miss)) |
| return rows |
| |
| def emit_execution_counts(opcode_stats, total): |
| with Section("Execution counts", summary="execution counts for all instructions"): |
| rows = calculate_execution_counts(opcode_stats, total) |
| emit_table( |
| ("Name", "Count:", "Self:", "Cumulative:", "Miss ratio:"), |
| rows |
| ) |
| |
| def emit_comparative_execution_counts( |
| base_opcode_stats, base_total, head_opcode_stats, head_total |
| ): |
| with Section("Execution counts", summary="execution counts for all instructions"): |
| base_rows = calculate_execution_counts(base_opcode_stats, base_total) |
| head_rows = calculate_execution_counts(head_opcode_stats, head_total) |
| base_data = dict((x[0], x[1:]) for x in base_rows) |
| head_data = dict((x[0], x[1:]) for x in head_rows) |
| opcodes = set(base_data.keys()) | set(head_data.keys()) |
| |
| rows = [] |
| default = [0, "0.0%", "0.0%", 0] |
| for opcode in opcodes: |
| base_entry = base_data.get(opcode, default) |
| head_entry = head_data.get(opcode, default) |
| if base_entry[0] == 0: |
| change = 1 |
| else: |
| change = (head_entry[0] - base_entry[0]) / base_entry[0] |
| rows.append( |
| (opcode, base_entry[0], head_entry[0], |
| f"{100*change:0.1f}%")) |
| |
| rows.sort(key=lambda x: -abs(float(x[-1][:-1]))) |
| |
| emit_table( |
| ("Name", "Base Count:", "Head Count:", "Change:"), |
| rows |
| ) |
| |
| def get_defines(): |
| spec_path = os.path.join(os.path.dirname(__file__), "../../Python/specialize.c") |
| with open(spec_path) as spec_src: |
| defines = parse_kinds(spec_src) |
| return defines |
| |
| def emit_specialization_stats(opcode_stats): |
| defines = get_defines() |
| with Section("Specialization stats", summary="specialization stats by family"): |
| for i, opcode_stat in enumerate(opcode_stats): |
| name = opname[i] |
| print_specialization_stats(name, opcode_stat, defines) |
| |
| def emit_comparative_specialization_stats(base_opcode_stats, head_opcode_stats): |
| defines = get_defines() |
| with Section("Specialization stats", summary="specialization stats by family"): |
| for i, (base_opcode_stat, head_opcode_stat) in enumerate(zip(base_opcode_stats, head_opcode_stats)): |
| name = opname[i] |
| print_comparative_specialization_stats(name, base_opcode_stat, head_opcode_stat, defines) |
| |
| def calculate_specialization_effectiveness(opcode_stats, total): |
| basic, not_specialized, specialized = categorized_counts(opcode_stats) |
| return [ |
| ("Basic", basic, format_ratio(basic, total)), |
| ("Not specialized", not_specialized, format_ratio(not_specialized, total)), |
| ("Specialized", specialized, format_ratio(specialized, total)), |
| ] |
| |
| def emit_specialization_overview(opcode_stats, total): |
| with Section("Specialization effectiveness"): |
| rows = calculate_specialization_effectiveness(opcode_stats, total) |
| emit_table(("Instructions", "Count:", "Ratio:"), rows) |
| for title, field in (("Deferred", "specialization.deferred"), ("Misses", "specialization.miss")): |
| total = 0 |
| counts = [] |
| for i, opcode_stat in enumerate(opcode_stats): |
| # Avoid double counting misses |
| if title == "Misses" and "specializable" in opcode_stat: |
| continue |
| value = opcode_stat.get(field, 0) |
| counts.append((value, opname[i])) |
| total += value |
| counts.sort(reverse=True) |
| if total: |
| with Section(f"{title} by instruction", 3): |
| rows = [ (name, count, format_ratio(count, total)) for (count, name) in counts[:10] ] |
| emit_table(("Name", "Count:", "Ratio:"), rows) |
| |
| def emit_comparative_specialization_overview(base_opcode_stats, base_total, head_opcode_stats, head_total): |
| with Section("Specialization effectiveness"): |
| base_rows = calculate_specialization_effectiveness(base_opcode_stats, base_total) |
| head_rows = calculate_specialization_effectiveness(head_opcode_stats, head_total) |
| emit_table( |
| ("Instructions", "Base Count:", "Base Ratio:", "Head Count:", "Head Ratio:"), |
| join_rows(base_rows, head_rows) |
| ) |
| |
| def get_stats_defines(): |
| stats_path = os.path.join(os.path.dirname(__file__), "../../Include/pystats.h") |
| with open(stats_path) as stats_src: |
| defines = parse_kinds(stats_src, prefix="EVAL_CALL") |
| return defines |
| |
| def calculate_call_stats(stats): |
| defines = get_stats_defines() |
| total = 0 |
| for key, value in stats.items(): |
| if "Calls to" in key: |
| total += value |
| rows = [] |
| for key, value in stats.items(): |
| if "Calls to" in key: |
| rows.append((key, value, format_ratio(value, total))) |
| elif key.startswith("Calls "): |
| name, index = key[:-1].split("[") |
| index = int(index) |
| label = name + " (" + pretty(defines[index][0]) + ")" |
| rows.append((label, value, format_ratio(value, total))) |
| for key, value in stats.items(): |
| if key.startswith("Frame"): |
| rows.append((key, value, format_ratio(value, total))) |
| return rows |
| |
| def emit_call_stats(stats): |
| with Section("Call stats", summary="Inlined calls and frame stats"): |
| rows = calculate_call_stats(stats) |
| emit_table(("", "Count:", "Ratio:"), rows) |
| |
| def emit_comparative_call_stats(base_stats, head_stats): |
| with Section("Call stats", summary="Inlined calls and frame stats"): |
| base_rows = calculate_call_stats(base_stats) |
| head_rows = calculate_call_stats(head_stats) |
| rows = join_rows(base_rows, head_rows) |
| rows.sort(key=lambda x: -float(x[-1][:-1])) |
| emit_table( |
| ("", "Base Count:", "Base Ratio:", "Head Count:", "Head Ratio:"), |
| rows |
| ) |
| |
| def calculate_object_stats(stats): |
| total_materializations = stats.get("Object new values") |
| total_allocations = stats.get("Object allocations") + stats.get("Object allocations from freelist") |
| total_increfs = stats.get("Object interpreter increfs") + stats.get("Object increfs") |
| total_decrefs = stats.get("Object interpreter decrefs") + stats.get("Object decrefs") |
| rows = [] |
| for key, value in stats.items(): |
| if key.startswith("Object"): |
| if "materialize" in key: |
| ratio = format_ratio(value, total_materializations) |
| elif "allocations" in key: |
| ratio = format_ratio(value, total_allocations) |
| elif "increfs" in key: |
| ratio = format_ratio(value, total_increfs) |
| elif "decrefs" in key: |
| ratio = format_ratio(value, total_decrefs) |
| else: |
| ratio = "" |
| label = key[6:].strip() |
| label = label[0].upper() + label[1:] |
| rows.append((label, value, ratio)) |
| return rows |
| |
| def emit_object_stats(stats): |
| with Section("Object stats", summary="allocations, frees and dict materializatons"): |
| rows = calculate_object_stats(stats) |
| emit_table(("", "Count:", "Ratio:"), rows) |
| |
| def emit_comparative_object_stats(base_stats, head_stats): |
| with Section("Object stats", summary="allocations, frees and dict materializatons"): |
| base_rows = calculate_object_stats(base_stats) |
| head_rows = calculate_object_stats(head_stats) |
| emit_table(("", "Base Count:", "Base Ratio:", "Head Count:", "Head Ratio:"), join_rows(base_rows, head_rows)) |
| |
| def get_total(opcode_stats): |
| total = 0 |
| for opcode_stat in opcode_stats: |
| if "execution_count" in opcode_stat: |
| total += opcode_stat['execution_count'] |
| return total |
| |
| def emit_pair_counts(opcode_stats, total): |
| pair_counts = [] |
| for i, opcode_stat in enumerate(opcode_stats): |
| if i == 0: |
| continue |
| for key, value in opcode_stat.items(): |
| if key.startswith("pair_count"): |
| x, _, _ = key[11:].partition("]") |
| if value: |
| pair_counts.append((value, (i, int(x)))) |
| with Section("Pair counts", summary="Pair counts for top 100 pairs"): |
| pair_counts.sort(reverse=True) |
| cumulative = 0 |
| rows = [] |
| for (count, pair) in itertools.islice(pair_counts, 100): |
| i, j = pair |
| cumulative += count |
| rows.append((opname[i] + " " + opname[j], count, format_ratio(count, total), |
| format_ratio(cumulative, total))) |
| emit_table(("Pair", "Count:", "Self:", "Cumulative:"), |
| rows |
| ) |
| with Section("Predecessor/Successor Pairs", summary="Top 5 predecessors and successors of each opcode"): |
| predecessors = collections.defaultdict(collections.Counter) |
| successors = collections.defaultdict(collections.Counter) |
| total_predecessors = collections.Counter() |
| total_successors = collections.Counter() |
| for count, (first, second) in pair_counts: |
| if count: |
| predecessors[second][first] = count |
| successors[first][second] = count |
| total_predecessors[second] += count |
| total_successors[first] += count |
| for name, i in opmap.items(): |
| total1 = total_predecessors[i] |
| total2 = total_successors[i] |
| if total1 == 0 and total2 == 0: |
| continue |
| pred_rows = succ_rows = () |
| if total1: |
| pred_rows = [(opname[pred], count, f"{count/total1:.1%}") |
| for (pred, count) in predecessors[i].most_common(5)] |
| if total2: |
| succ_rows = [(opname[succ], count, f"{count/total2:.1%}") |
| for (succ, count) in successors[i].most_common(5)] |
| with Section(name, 3, f"Successors and predecessors for {name}"): |
| emit_table(("Predecessors", "Count:", "Percentage:"), |
| pred_rows |
| ) |
| emit_table(("Successors", "Count:", "Percentage:"), |
| succ_rows |
| ) |
| |
| def output_single_stats(stats): |
| opcode_stats = extract_opcode_stats(stats) |
| total = get_total(opcode_stats) |
| emit_execution_counts(opcode_stats, total) |
| emit_pair_counts(opcode_stats, total) |
| emit_specialization_stats(opcode_stats) |
| emit_specialization_overview(opcode_stats, total) |
| emit_call_stats(stats) |
| emit_object_stats(stats) |
| with Section("Meta stats", summary="Meta statistics"): |
| emit_table(("", "Count:"), [('Number of data files', stats['__nfiles__'])]) |
| |
| |
| def output_comparative_stats(base_stats, head_stats): |
| base_opcode_stats = extract_opcode_stats(base_stats) |
| base_total = get_total(base_opcode_stats) |
| |
| head_opcode_stats = extract_opcode_stats(head_stats) |
| head_total = get_total(head_opcode_stats) |
| |
| emit_comparative_execution_counts( |
| base_opcode_stats, base_total, head_opcode_stats, head_total |
| ) |
| emit_comparative_specialization_stats( |
| base_opcode_stats, head_opcode_stats |
| ) |
| emit_comparative_specialization_overview( |
| base_opcode_stats, base_total, head_opcode_stats, head_total |
| ) |
| emit_comparative_call_stats(base_stats, head_stats) |
| emit_comparative_object_stats(base_stats, head_stats) |
| |
| def output_stats(inputs, json_output=None): |
| if len(inputs) == 1: |
| stats = gather_stats(inputs[0]) |
| if json_output is not None: |
| json.dump(stats, json_output) |
| output_single_stats(stats) |
| elif len(inputs) == 2: |
| if json_output is not None: |
| raise ValueError( |
| "Can not output to JSON when there are multiple inputs" |
| ) |
| |
| base_stats = gather_stats(inputs[0]) |
| head_stats = gather_stats(inputs[1]) |
| output_comparative_stats(base_stats, head_stats) |
| |
| print("---") |
| print("Stats gathered on:", date.today()) |
| |
| def main(): |
| parser = argparse.ArgumentParser(description="Summarize pystats results") |
| |
| parser.add_argument( |
| "inputs", |
| nargs="*", |
| type=str, |
| default=[DEFAULT_DIR], |
| help=f""" |
| Input source(s). |
| For each entry, if a .json file, the output provided by --json-output from a previous run; |
| if a directory, a directory containing raw pystats .txt files. |
| If one source is provided, its stats are printed. |
| If two sources are provided, comparative stats are printed. |
| Default is {DEFAULT_DIR}. |
| """ |
| ) |
| |
| parser.add_argument( |
| "--json-output", |
| nargs="?", |
| type=argparse.FileType("w"), |
| help="Output complete raw results to the given JSON file." |
| ) |
| |
| args = parser.parse_args() |
| |
| if len(args.inputs) > 2: |
| raise ValueError("0-2 arguments may be provided.") |
| |
| output_stats(args.inputs, json_output=args.json_output) |
| |
| if __name__ == "__main__": |
| main() |
