"""Versioned, deterministic model view; the archived context stays complete."""
import copy
import json
import re


IDENTIFIERS = {'source_ref', 'capture_ref', 'archive_ref', 'member_name', 'path',
               'sha256', 'git_blob', 'assessment_ref', 'case_ref', 'case_sha256',
               'snapshot_id'}


def compact_context(context):
    """Shorten storage identifiers, never source IDs or actual database row values.

    Equal identifiers receive equal aliases; different identifiers remain distinct.
    This is a presentation encoding, not semantic summarization or source selection.
    """
    aliases = {}

    def identifier(value):
        if (not isinstance(value, str) or len(value) < 64
                or not re.search(r"[0-9a-fA-F]{40,}", value)):
            return value
        if value not in aliases:
            aliases[value] = f"P{len(aliases)+1:04d}"
        label = value.rsplit('/', 1)[-1].rsplit('\\', 1)[-1]
        # Hash-only labels add no semantic information to the model.
        if len(label) >= 64 or label == value:
            return aliases[value]
        return aliases[value] + ':' + label

    def visit(value):
        if isinstance(value, list):
            return [visit(item) for item in value]
        if not isinstance(value, dict):
            return value
        result = {}
        for key, item in sorted(value.items()):
            if key == 'row':
                # Database column names may themselves be path, sha256, etc.
                result[key] = copy.deepcopy(item)
            elif key in IDENTIFIERS:
                result[key] = identifier(item)
            else:
                result[key] = visit(item)
        return result

    projected = visit(context)
    # Repeated provenance objects are encoded once, without dropping scope,
    # timestamps, authors or identifier relationships.
    counts = {}
    def count(value):
        if isinstance(value,list):
            for item in value: count(item)
        elif isinstance(value,dict):
            for key,item in value.items():
                if key == 'row': continue
                if key in {'origin','provenance'} and isinstance(item,dict):
                    encoded = model_json(item)
                    if len(encoded)>120: counts[encoded] = counts.get(encoded,0)+1
                count(item)
    count(projected)
    shared = {}
    ids = {}
    def deduplicate(value):
        if isinstance(value,list): return [deduplicate(item) for item in value]
        if not isinstance(value,dict): return value
        result = {}
        for key,item in value.items():
            if key == 'row':
                result[key] = item
                continue
            encoded = model_json(item) if key in {'origin','provenance'} and isinstance(item,dict) else None
            if encoded is not None and counts.get(encoded,0)>1:
                if encoded not in ids:
                    sid = f"M{len(ids)+1:04d}"
                    ids[encoded] = sid
                    shared[sid] = copy.deepcopy(item)
                result[key] = {'metadata_ref':ids[encoded]}
            else:
                result[key] = deduplicate(item)
        return result
    projected = deduplicate(projected)
    if shared: projected['shared_metadata'] = shared
    return projected


def model_json(value):
    return json.dumps(value, sort_keys=True, ensure_ascii=False, allow_nan=False,
                      separators=(',', ':'))