#!/usr/bin/env python3
"""Deterministically export existing scientific records as Hub-viewable JSONL."""
import json
from pathlib import Path

ROOT=Path(__file__).resolve().parent.parent
V=ROOT/'verification'
GROUPS=[
 ('verification_results.json','fixed_contraction_cases','balanced_half', '1.3'),
 ('verification_results.json','general_rho_cases','balanced_general_rho','1.3'),
 ('verification_results.json','markov_and_spd_cases','stochastic_and_spd','15.1'),
 ('broadening_verification_results.json','scalar_cases','scalar_exact_hitting','1.2'),
 ('broadening_verification_results.json','approximation_cases','scalar_additive','6.1'),
 ('revision3_scalar_verification_results.json','direct_recurrence_cases','sentinel_recurrence','3.2'),
 ('revision3_scalar_verification_results.json','partition_cases','sentinel_partition','3.3'),
 ('revision3_fluid_verification_results.json','cases','one_interruption','9.3'),
 ('revision3_observable_results.json','assignment_cases','observable_rank','7.1'),
 ('revision3_observable_results.json','quotient_cases','observable_quotient','8.1'),
]
SUITES=[
 ('original','verification_results.json','verify_nhairun.py'),
 ('scalar_matching','broadening_verification_results.json','verify_broadening.py'),
 ('sentinel','revision3_scalar_verification_results.json','verify_revision3_scalar.py'),
 ('markers','revision3_marker_results.json','verify_revision3_markers.py'),
 ('one_interruption','revision3_fluid_verification_results.json','verify_revision3_fluid.py'),
 ('observable','revision3_observable_results.json','verify_revision3_observable.py'),
]

def load(name):return json.loads((V/name).read_text(encoding='utf-8'))
def packed(value):return json.dumps(value,ensure_ascii=False,sort_keys=True,separators=(',',':'))
def has_float(value):
 if isinstance(value,float):return True
 if isinstance(value,dict):return any(has_float(v) for v in value.values())
 if isinstance(value,list):return any(has_float(v) for v in value)
 return False
def integer(case,*keys):
 for key in keys:
  if key in case and isinstance(case[key],int) and not isinstance(case[key],bool):return case[key]
 return -1

def rows():
 ledger=load('claim_ledger.json')
 claims=[dict(claim_id=c['id'],status=c['status'],statement=c['statement'],
  assumptions=c.get('assumptions',[]),limitations=c.get('limits',[]),
  supporting_code=c.get('code',[]),record_json=packed(c)) for c in ledger['claims']]
 cases=[]
 for filename,key,family,theorem in GROUPS:
  for index,c in enumerate(load(filename)[key]):
   count=integer(c,'requests','size','N')
   if count<0 and 'centers' in c:count=len(c['centers'])
   if count<0 and 'original_centers' in c:count=len(c['original_centers'])+3
   if count<0 and 'values' in c:count=(2*len(c['values'])+3 if family=='sentinel_partition' else 2*len(c['values']))
   cases.append(dict(case_id=f'{family}-{index:03d}',family=family,
    theorem_reference=theorem,source_record='verification/'+filename,
    source_collection=key,source_index=index,request_count=count,
    state_dimension=integer(c,'hidden_dimension','dimension','ambient_dimension'),
    observed_dimension=integer(c,'observed_dimension'),variation_rank=integer(c,'variation_rank'),
    rho=str(c.get('rho',c.get('contraction',''))),
    orders_checked=integer(c,'orders','orders_enumerated','unsplit_orders','distinct_matrix_orders'),
    contains_float_diagnostics=has_float(c),case_json=packed(c)))
 audits=[]
 for suite,filename,script in SUITES:
  d=load(filename)
  audits.append(dict(suite_id=suite,source_record='verification/'+filename,
   verifier='code/'+script,assertions_count=d.get('assertions_total',0),
   placements_checked=d.get('ordered_distinct_sentinel_placements',0),
   scope=d.get('scope','Finite implementation checks; all-instance claims rely on manuscript proofs.'),
   arithmetic=d.get('arithmetic','Exact integer marker identities'),
   details_json=packed({k:v for k,v in d.items() if not isinstance(v,list)})))
 return {'claims':claims,'cases':cases,'verification_suites':audits}

def main():
 data=rows();destination=ROOT/'data';destination.mkdir(exist_ok=True)
 for name,records in data.items():
  (destination/(name+'.jsonl')).write_text(''.join(packed(r)+'\n' for r in records),encoding='utf-8')
 stats={name:len(records) for name,records in data.items()}
 stats.update(assertions_total=sum(r['assertions_count'] for r in data['verification_suites']),
  separate_marker_placements=sum(r['placements_checked'] for r in data['verification_suites']))
 (ROOT/'metadata'/'dataset_summary.json').write_text(json.dumps(stats,indent=2)+'\n',encoding='utf-8')
 print(json.dumps(stats,indent=2))

if __name__=='__main__':main()