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"""

Fraud network (ring) generation for Task 3 using networkx.



Generates complex fraud ring topologies:

- Simple cliques (3-5 ads fully connected)

- Chain structures (A-B via payment, B-C via creative — transitive reasoning required)

- Hub-and-spoke (one master account linked to satellites)



Individual ads in a ring may look borderline; the signal is in the connections.

Each edge in the graph carries the signal type that connects the two ads.

"""

from __future__ import annotations

import random
from dataclasses import dataclass, field
from typing import Dict, List, Set, Tuple

import networkx as nx


@dataclass
class FraudRing:
    ring_id: str
    member_ad_ids: List[str]
    shared_signals: Dict[str, str]  # signal_type -> shared_value
    topology: str = "clique"  # clique, chain, hub_spoke

    @property
    def size(self) -> int:
        return len(self.member_ad_ids)


_RING_TOPOLOGIES = ["clique", "chain", "hub_spoke"]

_SIGNAL_POOL_KEYS = ["payment_method", "domain_registrar", "creative_template", "targeting_overlap"]

_REGISTRAR_CHOICES = ["Njalla (privacy)", "Epik", "NameSilo", "Tucows (privacy proxy)"]
_TARGETING_CHOICES = [
    "Men 25-45, crypto+investing, US+UK+AU",
    "Adults 18-35, tech+gaming, worldwide",
    "Women 25-55, health+beauty, US+CA",
    "Adults 30-60, finance+real-estate, US+UK",
    "Adults 20-40, e-commerce+dropshipping, US+EU",
]


def _make_signal_pool(rng: random.Random, ring_index: int) -> Dict[str, str]:
    """Generate a pool of shared signal values for one ring."""
    return {
        "payment_method": f"pmt_ring_{rng.randint(10000, 99999)}",
        "domain_registrar": rng.choice(_REGISTRAR_CHOICES),
        "creative_template": f"tmpl_{rng.randint(1000, 9999)}",
        "targeting_overlap": rng.choice(_TARGETING_CHOICES),
    }


def generate_fraud_networks(

    rng: random.Random,

    n_rings: int,

    available_fraud_ad_ids: List[str],

) -> Tuple[List[FraudRing], Dict[str, List[str]]]:
    """

    Generate fraud ring structures with complex topologies.



    Returns:

        rings: list of FraudRing objects

        ad_to_rings: mapping from ad_id to list of ring_ids it belongs to

    """
    G = nx.Graph()
    rings: List[FraudRing] = []
    ad_to_rings: Dict[str, List[str]] = {}

    remaining = list(available_fraud_ad_ids)
    rng.shuffle(remaining)

    for i in range(n_rings):
        if len(remaining) < 3:
            break
        ring_size = rng.randint(3, min(5, len(remaining)))

        members = remaining[:ring_size]
        remaining = remaining[ring_size:]

        topology = rng.choice(_RING_TOPOLOGIES)
        signal_pool = _make_signal_pool(rng, i)

        signal_keys = list(_SIGNAL_POOL_KEYS)
        rng.shuffle(signal_keys)
        n_shared = rng.randint(2, len(signal_keys))
        shared_signals = {k: signal_pool[k] for k in signal_keys[:n_shared]}

        _add_edges_for_topology(G, members, shared_signals, topology, rng)

        ring_id = f"ring_{i}"
        ring = FraudRing(
            ring_id=ring_id,
            member_ad_ids=members,
            shared_signals=shared_signals,
            topology=topology,
        )
        rings.append(ring)

        for ad_id in members:
            ad_to_rings.setdefault(ad_id, []).append(ring_id)
            G.add_node(ad_id, ring_id=ring_id)

    # Optionally create bridge nodes between rings for extra complexity
    if len(rings) >= 2 and remaining:
        _add_bridge_ads(G, rings, remaining, ad_to_rings, rng)

    return rings, ad_to_rings


def _add_edges_for_topology(

    G: nx.Graph,

    members: List[str],

    shared_signals: Dict[str, str],

    topology: str,

    rng: random.Random,

) -> None:
    """Add edges to the graph based on the ring topology."""
    signal_types = list(shared_signals.keys())

    if topology == "clique":
        for i, a in enumerate(members):
            for b in members[i + 1:]:
                signal = rng.choice(signal_types)
                G.add_edge(a, b, signal_type=signal, signal_value=shared_signals[signal])

    elif topology == "chain":
        for idx in range(len(members) - 1):
            signal = signal_types[idx % len(signal_types)]
            G.add_edge(
                members[idx], members[idx + 1],
                signal_type=signal, signal_value=shared_signals[signal],
            )

    elif topology == "hub_spoke":
        hub = members[0]
        for spoke in members[1:]:
            signal = rng.choice(signal_types)
            G.add_edge(hub, spoke, signal_type=signal, signal_value=shared_signals[signal])


def _add_bridge_ads(

    G: nx.Graph,

    rings: List[FraudRing],

    remaining: List[str],

    ad_to_rings: Dict[str, List[str]],

    rng: random.Random,

) -> None:
    """Optionally link two rings via a shared bridge ad from the remaining pool."""
    if len(remaining) < 1 or len(rings) < 2:
        return

    bridge_ad = remaining.pop(0)
    r1, r2 = rings[0], rings[1]

    bridge_to_r1 = rng.choice(r1.member_ad_ids)
    bridge_to_r2 = rng.choice(r2.member_ad_ids)

    r1.member_ad_ids.append(bridge_ad)
    ad_to_rings.setdefault(bridge_ad, []).extend([r1.ring_id, r2.ring_id])

    sig_key = rng.choice(list(r1.shared_signals.keys()))
    G.add_edge(bridge_ad, bridge_to_r1, signal_type=sig_key, signal_value=r1.shared_signals[sig_key])

    sig_key2 = rng.choice(list(r2.shared_signals.keys()))
    G.add_edge(bridge_ad, bridge_to_r2, signal_type=sig_key2, signal_value=r2.shared_signals[sig_key2])


def get_ring_shared_signal_text(ring: FraudRing) -> str:
    """Describe the shared signals in a ring (for grader/debug use)."""
    lines = [f"Fraud Ring {ring.ring_id} ({ring.size} members, topology={ring.topology}):"]
    lines.append(f"  Members: {', '.join(ring.member_ad_ids)}")
    lines.append("  Shared signals:")
    for signal_type, value in ring.shared_signals.items():
        lines.append(f"    - {signal_type}: {value}")
    return "\n".join(lines)


def build_ground_truth_graph(rings: List[FraudRing]) -> nx.Graph:
    """Reconstruct the full ground truth network graph from rings.



    Used by graders to compute the expected set of edges.

    """
    G = nx.Graph()
    for ring in rings:
        for i, a in enumerate(ring.member_ad_ids):
            G.add_node(a, ring_id=ring.ring_id)
            for b in ring.member_ad_ids[i + 1:]:
                G.add_edge(a, b, ring_id=ring.ring_id)
    return G