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"""
orchestrate_cr.py β Fully automated CR application pipeline.
Reads an Excel contribution list, downloads all Accepted CRs and their target
TSs, parses tracked changes from each CR, applies them to the TS, and
finalises the document metadata β all without any per-CR manual scripting.
Usage:
python3 orchestrate_cr.py <excel_path> [person_name] [--output-dir DIR] [--author NAME]
Arguments:
excel_path Path to .xls or .xlsx contribution list (Windows paths OK)
person_name Name to match in SubmittedBy column (default: "Ly Thanh PHAN")
Options:
--output-dir Base output folder (default: ~/CR_Processing)
--author Tracked-change author name (default: "CR Application")
--retry-mode Skip steps 1-4; apply CRs listed in failed_ts.json
--ts-mode Apply all CRs for a given spec number across all versions
--ts-id Spec number to process in ts-mode (e.g. "102 267")
--excel-hash Excel hash used to filter the HF index in ts-mode
--hf-repo HuggingFace dataset repo containing the CR index
"""
import argparse
import contextlib
import datetime
import io
import json
import os
import re
import shutil
import sys
import time
from pathlib import Path
import docx as docx_lib
# ββ sys.path setup ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
SCRIPT_DIR = Path(__file__).parent
FETCH_SCRIPTS = SCRIPT_DIR.parent.parent / 'fetch-crs' / 'scripts'
sys.path.insert(0, str(SCRIPT_DIR))
sys.path.insert(0, str(FETCH_SCRIPTS))
from fetch_crs import parse_excel, download_cr, parse_cr_cover, download_ts, wsl_path
from cr_parser import parse_cr
from ts_applicator import apply_manifest
from finalize_ts import (
extract_cr_metadata,
compute_pub_date,
derive_new_version,
update_change_history_table,
update_history_table,
update_title_para,
NoChangeHistoryTable,
)
from docx_helpers import RevCounter, AUTHOR as DEFAULT_AUTHOR, DATE as DEFAULT_DATE
# ββ Display / logging helpers βββββββββββββββββββββββββββββββββββββββββββββββββ
def _section(title):
bar = '=' * 60
print(f'\n{bar}')
print(f' {title}')
print(bar)
class _TeeWriter:
"""Writes to both real stdout and a StringIO buffer simultaneously."""
def __init__(self, real, buf):
self._real = real
self._buf = buf
def write(self, s):
self._real.write(s)
self._buf.write(s)
def flush(self):
self._real.flush()
# ββ Small report / cache helpers βββββββββββββββββββββββββββββββββββββββββββββ
def _print_report(report, *, detailed=True):
"""Print per-TS result lines from a report list."""
for ts_key, n_ok, n_skip, n_crs, out_path, log_path, errors in report:
status = 'OK' if out_path and not errors else ('WARN' if out_path else 'FAIL')
print(f' [{status}] {ts_key}')
if detailed:
print(f' CRs: {n_crs} | Body changes applied: {n_ok} | Skipped: {n_skip}')
if out_path:
print(f' Output: {out_path.parent.name}/{out_path.name}')
if log_path and log_path.exists():
print(f' Log: {log_path.parent.name}/{log_path.name}')
for err in errors:
print(f' ! {err}')
def _copy_cr_cache_if_needed(cr_paths, cr_dir, output_dir):
"""Copy downloaded CRs into output_dir/CRs when a shared cache is used."""
run_cr_dir = output_dir / 'CRs'
if cr_dir.resolve() != run_cr_dir.resolve():
run_cr_dir.mkdir(parents=True, exist_ok=True)
for p in cr_paths.values():
if p.exists():
shutil.copy2(p, run_cr_dir / p.name)
# ββ Per-TS-group apply helper βββββββββββββββββββββββββββββββββββββββββββββββββ
def _apply_ts_group(spec_number, version, uids, ts_paths, cr_paths, spec_dir,
author, tc_date, log_label='Pipeline Log'):
"""Parse, apply, and finalise one TS group. Returns one report tuple."""
ts_key = f'TS {spec_number} v{version}'
spec_compact = spec_number.replace(' ', '')
new_v = derive_new_version(version)
stem = f'ts_{spec_compact}_v{new_v}_was_v{version}'
ts_applied = spec_dir / f'ts_{spec_compact}_v{version}_applied.docx'
ts_final = spec_dir / f'{stem}.docx'
log_path = spec_dir / f'{stem}.log'
errors = []
print(f'\n-- {ts_key} ({len(uids)} CR(s): {", ".join(uids)}) --')
if (spec_number, version) not in ts_paths:
msg = 'TS download failed β skipping'
print(f' SKIP: {msg}')
return (ts_key, 0, 0, len(uids), None, log_path, [msg])
ts_in = ts_paths[(spec_number, version)]
log_buf = io.StringIO()
tee = _TeeWriter(sys.stdout, log_buf)
with contextlib.redirect_stdout(tee):
log_header = (
f'{log_label}\n'
f'TS: {spec_number} v{version} -> v{new_v}\n'
f'CRs: {", ".join(uids)}\n'
f'Date: {datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n'
f'{"=" * 60}\n'
)
print(log_header, end='')
combined_manifest = []
participating_uids = []
for uid in uids:
if uid not in cr_paths:
errors.append(f'[{uid}] CR download had failed β skipped')
continue
print(f' Parsing {uid}... ', end='', flush=True)
try:
changes = parse_cr(cr_paths[uid])
combined_manifest.extend(changes)
participating_uids.append(uid)
print(f'{len(changes)} change(s)')
except Exception as e:
errors.append(f'[{uid}] parse ERROR: {e}')
print(f'ERROR: {e}')
if not combined_manifest:
print(' No changes parsed β skipping apply step.')
log_path.write_text(log_buf.getvalue(), encoding='utf-8')
return (ts_key, 0, 0, len(uids), None, log_path,
errors + ['No changes parsed'])
print(f' Applying {len(combined_manifest)} change(s) to {ts_in.name}...')
try:
n_ok, n_skip, log_lines, n_parsed, n_merged = apply_manifest(
ts_in, combined_manifest, ts_applied, author=author, date=tc_date
)
except Exception as e:
errors.append(f'apply_manifest ERROR: {e}')
print(f' ERROR: {e}')
log_path.write_text(log_buf.getvalue(), encoding='utf-8')
return (ts_key, 0, 0, len(uids), None, log_path, errors)
for line in log_lines:
print(f' {line}')
for line in log_lines:
if line.strip().startswith('ERROR'):
errors.append(line.strip())
print(f' Parsed: {n_parsed} body changes (merged to {n_merged} groups)'
f' β Applied: {n_ok} Skipped: {n_skip}')
print(' Finalising metadata...')
ts_final_or_applied = ts_applied # fallback if finalise raises
try:
ts_doc = docx_lib.Document(str(ts_applied))
rev = RevCounter(ts_doc)
pub_ym, pub_month_year = compute_pub_date()
old_v = version
title_text = ts_doc.paragraphs[0].text
date_match = re.search(r'\((\d{4}-\d{2})\)', title_text)
old_date_str = date_match.group(1) if date_match else ''
print(f' Version: {old_v} -> {new_v}')
print(f' Publication: {pub_month_year} ({pub_ym})')
for uid in participating_uids:
try:
meta = extract_cr_metadata(str(cr_paths[uid]))
ch_cells = update_change_history_table(
ts_doc, meta, pub_ym, old_v, new_v, rev, author, tc_date
)
print(f' [Change History] {uid}: {ch_cells}')
except NoChangeHistoryTable:
print(f' [Change History] {uid}: NOT PRESENT β this document has no Change History table (History table only)')
except Exception as e:
errors.append(f'[{uid}] Change History ERROR: {e}')
print(f' [Change History] {uid}: ERROR β {e}')
try:
h_cells = update_history_table(
ts_doc, new_v, pub_month_year, rev, author, tc_date
)
print(f' [History] {h_cells}')
except Exception as e:
errors.append(f'History table ERROR: {e}')
print(f' [History] ERROR β {e}')
if old_date_str:
try:
update_title_para(
ts_doc, old_v, new_v, old_date_str, pub_ym, rev, author, tc_date
)
print(f' [Title] V{old_v} -> V{new_v}, ({old_date_str}) -> ({pub_ym})')
except Exception as e:
errors.append(f'Title update ERROR: {e}')
print(f' [Title] ERROR β {e}')
else:
print(f' [Title] SKIP β no (YYYY-MM) pattern in: {title_text!r}')
ts_doc.save(str(ts_final))
print(f' Saved: {spec_compact}/{ts_final.name}')
print(f' Log: {spec_compact}/{log_path.name}')
ts_final_or_applied = ts_final
except Exception as e:
errors.append(f'Finalisation ERROR: {e}')
print(f' Finalisation ERROR: {e}')
log_path.write_text(log_buf.getvalue(), encoding='utf-8')
return (ts_key, n_ok, n_skip, len(uids), ts_final_or_applied, log_path, errors)
# ββ Shared Steps 2, 4, 5, 6 ββββββββββββββββββββββββββββββββββββββββββββββββββ
def _run_steps_2_to_6(cr_list, ts_groups, output_dir, cr_dir, ts_dir,
eol_user, eol_password, author, tc_date):
"""
Execute steps 2 (download CRs), 4 (download TSs), 5 & 6 (apply + finalise).
cr_list : list of (uid, title)
ts_groups : dict {(spec_number, version): [uid, ...]} β may be pre-built
(ts-mode) or None to trigger Step 3 (cover page parse).
"""
# ββ Step 2: Download CR DOCXs βββββββββββββββββββββββββββββββββββββββββββββ
_section('Step 2 β Downloading CR DOCXs')
cr_paths = {} # uid -> Path
for uid, _ in cr_list:
docx_path, note = download_cr(uid, cr_dir, eol_user, eol_password)
if docx_path:
cr_paths[uid] = docx_path
print(f' [{uid}] OK ({note}) β {docx_path.name}')
else:
print(f' [{uid}] FAILED β {note}')
n_cr_failed = len(cr_list) - len(cr_paths)
if n_cr_failed:
print(f' {len(cr_paths)}/{len(cr_list)} downloaded ({n_cr_failed} failed)')
else:
print(f' All {len(cr_list)} CR(s) downloaded successfully')
# ββ Step 3: Parse cover pages (only when ts_groups not pre-built) βββββββββ
if ts_groups is None:
_section('Step 3 β Parsing CR cover pages')
ts_groups = {}
uid_cover_failed = []
for uid in cr_paths:
spec_number, version = parse_cr_cover(cr_paths[uid])
if spec_number and version:
key = (spec_number, version)
ts_groups.setdefault(key, []).append(uid)
print(f' [{uid}] -> TS {spec_number} v{version}')
else:
uid_cover_failed.append(uid)
print(f' [{uid}] WARNING: could not parse cover page β skipping')
if not ts_groups:
print('\nNo TSs identified. Nothing to apply.')
return [], {}, {}, {}
# ββ Step 4: Download TSs ββββββββββββββββββββββββββββββββββββββββββββββββββ
_section('Step 4 β Downloading TSs')
ts_paths = {} # (spec_number, version) -> Path
spec_dirs = {} # (spec_number, version) -> Path (per-spec subfolder)
for (spec_number, version) in ts_groups:
spec_compact = spec_number.replace(' ', '')
spec_dir = ts_dir / spec_compact
spec_dir.mkdir(parents=True, exist_ok=True)
spec_dirs[(spec_number, version)] = spec_dir
print(f' [TS {spec_number} v{version}] ', end='', flush=True)
filename, note = None, "not attempted"
for attempt in range(1, 4):
filename, note = download_ts(spec_number, version, spec_dir, eol_user, eol_password)
if filename:
break
if attempt < 3:
print(f'\n [attempt {attempt}/3 failed β retrying in 5s: {note}]', flush=True)
print(f' [TS {spec_number} v{version}] ', end='', flush=True)
time.sleep(5)
else:
print(f'\n [all 3 attempts failed]', flush=True)
if filename:
ts_paths[(spec_number, version)] = spec_dir / filename
print(f'OK ({note}) β {spec_compact}/{filename}')
else:
print(f'FAILED β {note}')
# Write failed_ts.json
failed_ts_entries = [
{
"spec_number": spec_number,
"version": version,
"spec_compact": spec_number.replace(' ', ''),
"spec_dir": str(spec_dirs[(spec_number, version)]),
"expected_filename": f"ts_{spec_number.replace(' ', '')}_v{version}.docx",
"cr_uids": ts_groups[(spec_number, version)],
"cr_dir": str(cr_dir),
}
for (spec_number, version) in ts_groups
if (spec_number, version) not in ts_paths
]
(output_dir / "failed_ts.json").write_text(
json.dumps(failed_ts_entries, indent=2)
)
# Write failed_cr.json
failed_cr_entries = []
for uid, _ in cr_list:
if uid not in cr_paths:
sn, v = next(
((sn, v) for (sn, v), uids in ts_groups.items() if uid in uids),
(None, None),
)
sc = sn.replace(' ', '') if sn else None
sd = spec_dirs.get((sn, v)) if sn else None
failed_cr_entries.append({
"uid": uid,
"cr_dir": str(cr_dir),
"expected_filename": f"{uid}.docx",
"ts_spec_number": sn,
"ts_version": v,
"ts_spec_dir": str(sd) if sd else None,
"ts_expected_filename": f"ts_{sc}_v{v}.docx" if sc and v else None,
})
(output_dir / "failed_cr.json").write_text(json.dumps(failed_cr_entries, indent=2))
if failed_cr_entries:
print(f' {len(failed_cr_entries)} failed CR download(s) written to failed_cr.json')
# ββ Steps 5 & 6: Apply CRs + Finalise each TS ββββββββββββββββββββββββββββ
_section('Steps 5 & 6 β Applying CRs and Finalising Metadata')
report = [] # (ts_key, n_ok, n_skip, n_crs, out_path, log_path, errors)
for (spec_number, version), uids in ts_groups.items():
spec_compact = spec_number.replace(' ', '')
spec_dir = spec_dirs.get((spec_number, version), ts_dir / spec_compact)
spec_dir.mkdir(parents=True, exist_ok=True)
report.append(_apply_ts_group(
spec_number, version, uids, ts_paths, cr_paths, spec_dir, author, tc_date
))
return report, cr_paths, ts_paths, spec_dirs
# ββ Main ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def main():
ap = argparse.ArgumentParser(
description='Fully automated CR application pipeline.',
formatter_class=argparse.RawDescriptionHelpFormatter,
)
ap.add_argument(
'excel_path',
nargs='?',
default=None,
help='Path to .xls or .xlsx contribution list (not required in --retry-mode or --ts-mode)',
)
ap.add_argument(
'person_name',
nargs='?',
default='Ly Thanh PHAN',
help='Name to match in SubmittedBy column (default: "Ly Thanh PHAN")',
)
ap.add_argument(
'--output-dir',
default=str(Path.home() / 'CR_Processing'),
help='Base output directory (default: ~/CR_Processing)',
)
ap.add_argument(
'--author',
default=DEFAULT_AUTHOR,
help=f'Tracked change author name (default: "{DEFAULT_AUTHOR}")',
)
ap.add_argument(
'--retry-mode',
action='store_true',
help='Skip steps 1-4; apply CRs to TSs listed in failed_ts.json that now have their DOCX on disk',
)
ap.add_argument(
'--ts-mode',
action='store_true',
help='Apply all CRs for a given spec number across all versions (uses HF index)',
)
ap.add_argument(
'--ts-id',
default='',
help='Spec number to process in ts-mode, e.g. "102 267"',
)
ap.add_argument(
'--excel-hash',
default='',
help='Excel hash used to filter the HF index in ts-mode',
)
ap.add_argument(
'--hf-repo',
default='OrganizedProgrammers/CR_Index',
help='HuggingFace dataset repo containing the CR index',
)
ap.add_argument(
'--cr-cache-dir',
default='',
help='Shared directory for caching downloaded CR DOCXs across runs '
'(default: <output-dir>/CRs)',
)
args = ap.parse_args()
if args.ts_mode and not args.ts_id:
ap.error('--ts-id is required when using --ts-mode')
if not args.ts_mode and not args.retry_mode and not args.excel_path:
ap.error('excel_path is required when not in --retry-mode or --ts-mode')
eol_user = os.environ.get("EOL_USER", "")
eol_password = os.environ.get("EOL_PASSWORD", "")
if not eol_user or not eol_password:
sys.exit("ERROR: EOL_USER and EOL_PASSWORD must be set")
output_dir = Path(wsl_path(args.output_dir)).expanduser()
cr_cache = args.cr_cache_dir.strip()
cr_dir = Path(wsl_path(cr_cache)).expanduser() if cr_cache else output_dir / 'CRs'
ts_dir = output_dir / 'TS'
cr_dir.mkdir(parents=True, exist_ok=True)
ts_dir.mkdir(parents=True, exist_ok=True)
author = args.author
tc_date = DEFAULT_DATE
# ββ Retry mode β skip steps 1-4, reconstruct state from failed_ts.json βββ
if args.retry_mode:
failed_ts_path = output_dir / 'failed_ts.json'
failed_cr_path = output_dir / 'failed_cr.json'
failed_ts_entries = json.loads(failed_ts_path.read_text()) if failed_ts_path.exists() else []
failed_cr_entries = json.loads(failed_cr_path.read_text()) if failed_cr_path.exists() else []
if not failed_ts_entries and not failed_cr_entries:
print('No failed TSs or CRs β nothing to retry.')
return
_section('Retry mode β Steps 5 & 6 only')
print(f'Retrying {len(failed_ts_entries)} TS(s) from failed_ts.json')
ts_groups = {}
spec_dirs = {}
ts_paths = {}
cr_paths = {}
for entry in failed_ts_entries:
spec_number = entry['spec_number']
version = entry['version']
key = (spec_number, version)
ts_groups[key] = entry['cr_uids']
spec_dir = Path(entry['spec_dir'])
spec_dirs[key] = spec_dir
expected = spec_dir / entry['expected_filename']
if expected.exists():
ts_paths[key] = expected
print(f' [TS {spec_number} v{version}] DOCX found β will apply')
else:
print(f' [TS {spec_number} v{version}] DOCX missing β skipping')
cr_entry_dir = Path(entry['cr_dir'])
for uid in entry['cr_uids']:
extracted = cr_entry_dir / f'{uid}_extracted.docx'
plain = cr_entry_dir / f'{uid}.docx'
if extracted.exists():
cr_paths[uid] = extracted
elif plain.exists():
cr_paths[uid] = plain
# ββ Recover CRs from failed_cr.json ββββββββββββββββββββββββββββββββββ
still_failed_cr = []
for entry in failed_cr_entries:
uid = entry['uid']
cr_entry_dir = Path(entry['cr_dir'])
extracted = cr_entry_dir / f'{uid}_extracted.docx'
plain = cr_entry_dir / entry['expected_filename']
if extracted.exists():
cr_paths[uid] = extracted
elif plain.exists():
cr_paths[uid] = plain
else:
still_failed_cr.append(entry)
continue
sn, v = entry['ts_spec_number'], entry['ts_version']
if sn and v:
key = (sn, v)
ts_groups.setdefault(key, [])
if uid not in ts_groups[key]:
ts_groups[key].append(uid)
if key not in spec_dirs and entry['ts_spec_dir']:
spec_dirs[key] = Path(entry['ts_spec_dir'])
if key not in ts_paths and entry['ts_spec_dir'] and entry['ts_expected_filename']:
ts_file = Path(entry['ts_spec_dir']) / entry['ts_expected_filename']
if ts_file.exists():
ts_paths[key] = ts_file
print(f' [{uid}] CR recovered β will apply to TS {sn} v{v}')
else:
print(f' [{uid}] CR recovered but TS group unknown β skipping apply')
failed_cr_path.write_text(json.dumps(still_failed_cr, indent=2))
# ββ Steps 5 & 6 (retry mode) βββββββββββββββββββββββββββββββββββββββββ
report = []
for (spec_number, version), uids in ts_groups.items():
spec_compact = spec_number.replace(' ', '')
spec_dir = spec_dirs.get((spec_number, version), ts_dir / spec_compact)
spec_dir.mkdir(parents=True, exist_ok=True)
report.append(_apply_ts_group(
spec_number, version, uids, ts_paths, cr_paths, spec_dir, author, tc_date,
log_label='Pipeline Log (retry)'
))
# Update failed_ts.json β remove entries that are now resolved
still_failed = [
e for e in failed_ts_entries
if not (Path(e['spec_dir']) / e['expected_filename']).exists()
]
failed_ts_path.write_text(json.dumps(still_failed, indent=2))
_section('Retry Summary')
n_success = sum(1 for r in report if r[4] is not None and not r[6])
n_partial = sum(1 for r in report if r[4] is not None and r[6])
n_failed = sum(1 for r in report if r[4] is None)
n_cr_still = len(still_failed_cr)
print(f'TSs processed: {n_success} fully OK, {n_partial} with warnings, {n_failed} skipped/failed')
if n_cr_still:
print(f'CRs still missing: {n_cr_still} (see failed_cr.json)')
_print_report(report, detailed=False)
return
# ββ TS mode β load HF index, skip Steps 1 & 3 ββββββββββββββββββββββββββββ
if args.ts_mode:
hf_token = os.environ.get("HF_TOKEN", "")
if not hf_token:
sys.exit("ERROR: HF_TOKEN must be set in ts-mode")
from hf_cr_index import load_hf_index
_section(f'TS mode β spec {args.ts_id!r}')
print(f'Loading HF index from {args.hf_repo}...')
try:
all_records = load_hf_index(hf_token, args.hf_repo)
except Exception as e:
sys.exit(f'ERROR loading HF index: {e}')
records = [
r for r in all_records
if r.get("excel_hash") == args.excel_hash
and r.get("spec_number") == args.ts_id
]
if not records:
sys.exit(
f'ERROR: no indexed CRs found for spec {args.ts_id!r} '
f'with excel_hash={args.excel_hash!r}'
)
# Build ts_groups from index (bypasses Step 3)
ts_groups = {}
for r in records:
key = (r["spec_number"], r["version"])
ts_groups.setdefault(key, []).append(r["uid"])
# Build cr_list for Step 2 download
cr_list = [(r["uid"], r["title"]) for r in records]
print(f'Found {len(records)} CR(s) across {len(ts_groups)} version(s):')
for (spec, ver), uids in ts_groups.items():
print(f' TS {spec} v{ver}: {", ".join(uids)}')
report, cr_paths, ts_paths, spec_dirs = _run_steps_2_to_6(
cr_list, ts_groups, output_dir, cr_dir, ts_dir,
eol_user, eol_password, author, tc_date,
)
# Copy the CRs actually applied into the run output dir so the ZIP
# contains exactly the CRs used for this TS (only needed when using
# a shared CR cache that lives outside output_dir).
_copy_cr_cache_if_needed(cr_paths, cr_dir, output_dir)
_section('Final Report (TS mode)')
n_success = sum(1 for r in report if r[4] is not None and not r[6])
n_partial = sum(1 for r in report if r[4] is not None and r[6])
n_failed = sum(1 for r in report if r[4] is None)
print(f'Spec: {args.ts_id}')
print(f'CRs found: {len(cr_list)}')
print(f'TSs updated: {n_success} fully OK, {n_partial} with warnings, {n_failed} failed')
print()
_print_report(report)
print()
print(f'Output directory: {output_dir}/')
return
# ββ Normal mode βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
excel_path = wsl_path(args.excel_path)
# ββ Step 1: Parse Excel βββββββββββββββββββββββββββββββββββββββββββββββββββ
_section('Step 1 β Parsing Excel')
print(f'Excel: {excel_path}')
print(f'Person: {args.person_name!r}')
try:
cr_list = parse_excel(excel_path, args.person_name)
except Exception as e:
sys.exit(f'ERROR parsing Excel: {e}')
print(f'Found {len(cr_list)} Accepted CR(s)')
if not cr_list:
print('Nothing to process.')
return
# Steps 2, 3 (cover page parse), 4, 5, 6
report, cr_paths, ts_paths, spec_dirs = _run_steps_2_to_6(
cr_list, None, output_dir, cr_dir, ts_dir,
eol_user, eol_password, author, tc_date,
)
# Copy the CRs actually applied into the run output dir so the ZIP
# contains exactly the CRs used for this run (only needed when using
# a shared CR cache that lives outside output_dir).
_copy_cr_cache_if_needed(cr_paths, cr_dir, output_dir)
# ββ Final Report ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_section('Final Report')
n_success = sum(1 for r in report if r[4] is not None and not r[6])
n_partial = sum(1 for r in report if r[4] is not None and r[6])
n_failed = sum(1 for r in report if r[4] is None)
print(f'Person: {args.person_name}')
print(f'Excel: {excel_path}')
print(f'CRs found: {len(cr_list)}')
print(f'TSs updated: {n_success} fully OK, {n_partial} with warnings, {n_failed} failed')
print()
_print_report(report)
print()
print(f'Output directory: {output_dir}/')
if __name__ == '__main__':
main()
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