"""Actionable reports from privacy-minimized evidence, without raw sidecars."""
import hashlib
import html
import json
from pathlib import Path
from samsara.core.privacy import minimize_inventory
from samsara.core.storage import write_private
from samsara.analyzers.assessment import assess
from samsara.analyzers.summary import summarize

MANUAL_STEPS = ['Confirm application and business owners and obtain administrator retirement approval.',
                'Validate historical usage across a representative business cycle, including infrequent and offline jobs.',
                'Review DNS, load balancers, monitoring, backups, firewall logs and service-account consumers.',
                'Verify custom tasks and share consumers; resolve incomplete checks and confirm rollback/retention requirements.']


def private_assessment(data, assessment):
    # Never trust a marker or cached finding to authorize raw data disclosure.
    source=data.get('server',{}).get('collection_source')
    clean=minimize_inventory(data, trusted_source=source)
    policy=assessment.get('scoring',{}).get('policy') if isinstance(assessment,dict) else None
    if policy is not None:
        import copy
        policy=copy.deepcopy(policy)
        policy['name']='Deployment scoring policy'
    return clean, assess(clean, policy=policy)


def export_json(path, data, assessment):
    data, assessment=private_assessment(data, assessment)
    write_private(path,json.dumps({'inventory_result':data,'assessment':assessment},indent=2))


def inventory_artifact(path, data):
    """Explicit minimized inventory export; never writes a raw sidecar."""
    data=minimize_inventory(data)
    payload=(json.dumps(data,indent=2,ensure_ascii=True)+'\n').encode('utf-8')
    destination=Path(path).with_suffix('.inventory.json')
    write_private(destination,payload)
    return destination, hashlib.sha256(payload).hexdigest()


def table(headers, rows):
    escape = lambda value: html.escape(str(value))
    if not rows:
        return '<p class="muted">None identified in collected evidence. Review missing evidence before drawing conclusions.</p>'
    return '<div class="table"><table><thead><tr>' + ''.join('<th>'+escape(h)+'</th>' for h in headers) + '</tr></thead><tbody>' + ''.join('<tr>'+''.join('<td>'+escape(v)+'</td>' for v in row)+'</tr>' for row in rows) + '</tbody></table></div>'


def export_html(path, data, assessment):
    escape = lambda value: html.escape(str(value))
    data, assessment = private_assessment(data, assessment)
    source = 'SYNTHETIC DEMO — no real collection performed.' if data['synthetic'] else 'IMPORTED INVENTORY — source assertions not independently verified.'
    for platform in ('Linux','Windows'):
        if not data['synthetic'] and data['server'].get('collection_source') == f'Local {platform} read-only collection':
            source = f'LOCAL {platform.upper()} INVENTORY — read-only snapshot of the execution host.'
    summary = summarize(data,assessment)
    scoring = assessment['scoring']
    content = '<h1>Samsara assessment</h1><p class="source">'+escape(source)+'</p>'
    content += '<h2>Summary</h2>'
    content += '<p><strong>'+escape(data['server']['hostname'])+'</strong> · '+escape(data['collected_at'])+'</p>'
    content += f"<div class='card'><strong>Retirement risk estimate: {escape(assessment['level']).title()} · {assessment['score']}/100</strong><p>{escape(scoring['explanation'])}</p></div>"
    content += f"<p>Evidence coverage: <strong>{summary['coverage_percent']}%</strong> · Evidence confidence: <strong>{escape(summary['confidence'])}</strong> · {summary['incomplete']} checks need review.</p>"
    content += '<p>Coverage and uncertainty are separate from risk. A zero or low score is not retirement clearance. Historical usage validation and administrator approval are always required.</p>'
    content += f"<p>OS type: {escape(summary['os_type'])}<br>Version: {escape(summary['version'])}</p>"
    actionable = [row for row in assessment['findings'] if row['points']>0]
    content += '<h2>Actionable workload findings</h2>'
    content += table(['Workload','Classification','Workload score','Evidence','Why this affects scoring'],[(row['category'],row['classification'],row['points'],row['evidence'],row['scoring_reason']) for row in actionable])
    content += '<h2>How the score was calculated</h2><p>'+escape(scoring['formula'])+'</p>'
    content += table(['Workload','Selected rule','Score','Determines final score','Evidence observations'],[(row['title'],row['selected_rule'],row['score'],'Yes (co-leading)' if row['determines_final_score'] else 'No; below the maximum',row['evidence_count']) for row in scoring['breakdown']])
    content += '<details><summary>Policy weights, thresholds and audit identity</summary><p>Policy SHA-256: '+escape(scoring['policy_id'])+'</p><pre>'+escape(json.dumps(scoring['policy'],indent=2))+'</pre></details>'
    content += '<h2>Important software</h2><p>Inventory name hints only; installed software does not establish active use.</p>'
    content += table(['Software','Version','Evidence'],[(r['name'],r['version'],r['evidence']) for r in summary['software'][:12]])
    content += '<h2>Scheduled jobs and scripts</h2><p>Nonroutine enabled schedules; configuration does not confirm execution. All tasks remain in the inventory.</p>'
    content += table(['Job','Schedule','State'],[(r['name'],r['schedule'],r['status']) for r in summary['jobs'][:12]])
    context = [r for r in assessment['findings'] if r['points']==0 and r['id'] not in ('coverage','observation-limits')]
    content += '<h2>Unscored context and review items</h2><p>Routine services, administrative shares, client traffic and unknown observations do not receive workload points.</p>'
    content += table(['Category','Classification','Context'],[(r['category'],r['classification'],r['evidence']) for r in context])
    directions = {}
    for row in assessment['network_observations']:
        directions[row['direction']] = directions.get(row['direction'],0)+1
    content += '<h2>Network interpretation</h2><p>Direction inferred from listener/PID or ephemeral-port patterns is a heuristic, not a captured initiating handshake. Confirmed workload findings describe attributed observed transport activity, not verified business ownership.</p>'
    content += table(['Direction / activity','Observations'],list(sorted(directions.items())))
    content += '<h2>Collection checks / missing evidence</h2><p>Failed and partial checks reduce confidence; they never add workload risk points.</p>'
    checks = []
    for name in sorted(set(data['checks']) | set(assessment['scoring']['policy']['coverage_weights'])):
        row = data['checks'].get(name,{'status':'not_collected','message':'No status supplied.'})
        errors = '; '.join(f"{e['code']}: {e['message']}" for e in row.get('errors',[]))
        checks.append((name,row['status'],row.get('started_at','Not supplied'),row.get('completed_at','Not supplied'),row['message'],errors,'; '.join(row.get('permission_limitations',[])),'; '.join(row.get('limitations',[]))))
    content += table(['Check','Status','started_at (UTC)','completed_at (UTC)','Result','Errors','permission_limitations','Scope limitations'],checks)
    content += '<h2>Recommended manual verification</h2><ul>'+''.join('<li>'+escape(step)+'</li>' for step in MANUAL_STEPS)+'</ul>'
    content += '<h2>Privacy and omitted evidence</h2><p>Accounts, task commands, certificate identities, child paths/filenames and public peer IPs are omitted; infrastructure names and share/mount roots are kept per the privacy policy `retain` switches and pass an identifier-pattern filter. No raw inventory sidecar is generated. JSON export contains the same minimized evidence. Numeric IP addresses remain confidential infrastructure metadata. This report does not establish PHI-free operation or HIPAA compliance.</p>'
    content += table(['Inventory section','Rows'],[(name,len(rows)) for name,rows in data['inventory'].items()])
    css = 'body{font:15px system-ui;max-width:1180px;margin:32px auto;padding:20px;color:#233044;line-height:1.55}h1,h2{color:#173c60}.muted{color:#667}.source,.card,details{background:#eef3f8;padding:16px;border-radius:7px}.table{overflow-x:auto}table{border-collapse:collapse;width:100%;margin:12px 0}th,td{border:1px solid #d9e0e8;text-align:left;vertical-align:top;padding:9px;white-space:pre-wrap;overflow-wrap:anywhere}th{background:#eef3f8}pre{white-space:pre-wrap;overflow-wrap:anywhere}a{color:#1263a3}'
    write_private(path,'<!doctype html><html lang="en"><head><meta charset="utf-8"><title>Samsara</title><style>'+css+'</style></head><body>'+content+'</body></html>')