import json

import demistomock as demisto
import pytest
from IPEnrichment import ip_enrichment_script


def util_load_json(path: str):
    with open(path, encoding="utf-8") as f:
        return json.load(f)


# End-to-end: TIM + Core lookups + enrichIndicators (batch data from file)
def test_ip_enrichment_script_end_to_end_with_batch_file(mocker):
    """
    Given:
        - Two IPs.
        - TIM returns:
            * 1.1.1.1 with TIM score 3, brand2 score 3 (Medium reliability), brand1 score 2 (High reliability).
              (IOC marked as manually edited → top-level Status should be "Manual")
            * 8.8.8.8 with TIM score 1, brand3 score 1 (Low reliability)
        - Batches:
            * createNewIndicator (no-op outputs)
            * core-get-IP-analytics-prevalence (Core.AnalyticsPrevalence.Ip)
            * enrichIndicators per IP (DBotScore only → not surfaced by current mapping)
    When:
        - ip_enrichment_script runs end-to-end.
    Then:
        - IPEnrichment contains both IPs.
        - 1.1.1.1 has 3 Results items (TIM + brand1 + brand2).
        - MaxScore=3, MaxVerdict=Malicious, TIMScore=3 for 1.1.1.1.
        - Vendor Results include Reliability propagated from TIM score cache.
        - TIM row in Results does NOT contain Status/ModifiedTime (popped to top-level).
        - Core prevalence are mapped/preserved.
    """
    tim_pages = util_load_json("test_data/mock_ip_tim_results.json")["pages"]
    batch_data = util_load_json("test_data/mock_ip_batch_results.json")

    ip_list = ["1.1.1.1", "8.8.8.8"]
    mocker.patch.object(demisto, "args", return_value={"ip_list": ",".join(ip_list)})

    # is_xsiam
    mocker.patch("IPEnrichment.is_xsiam", return_value=True)
    mocker.patch("IPEnrichment.is_platform", return_value=False)
    # extractIndicators -> validates input
    mocker.patch(
        "AggregatedCommandApiModule.execute_command",
        return_value=[{"EntryContext": {"ExtractedIndicators": {"IP": ip_list}}}],
    )

    # IndicatorsSearcher -> yield TIM pages
    class _MockSearcher:
        def __init__(self, pages):
            self.pages = pages

        def __iter__(self):
            return iter(self.pages)

    mocker.patch("AggregatedCommandApiModule.IndicatorsSearcher", return_value=_MockSearcher(tim_pages))

    # Enabled brands/instances
    mocker.patch.object(
        demisto,
        "getModules",
        return_value={
            "m1": {"state": "active", "brand": "brand1"},
            "m2": {"state": "active", "brand": "brand2"},
            "core": {"state": "active", "brand": "Core"},
            "coreir": {"state": "active", "brand": "Cortex Core - IR"},
        },
    )

    # Helpers to shape BatchExecutor output into (result, hr, err) tuples
    def _wrap_each_as_command(entries, hr=""):
        return [[(e, hr, "")] for e in entries]

    def _wrap_all_in_one_command(entries, hr=""):
        return [[(e, hr, "") for e in entries]]

    # Patch BatchExecutor.execute_list_of_batches to return our fixtures aligned to commands
    def _fake_execute_list_of_batches(self, list_of_batches, brands_to_run=None, verbose=False):
        out = []

        # ----- Batch 1: createNewIndicator -----
        b1_cmds = list_of_batches[0]
        b1_entries = batch_data["batch1_createNewIndicator"]
        if len(b1_cmds) == 1:
            out.append(_wrap_all_in_one_command(b1_entries))
        else:
            assert len(b1_entries) == len(b1_cmds), "batch1 size mismatch vs fixture"
            out.append(_wrap_each_as_command(b1_entries))

        # ----- Batch 2: prevalence, enrichIndicators -----
        b2_cmds = list_of_batches[1]
        assert "get-endpoint-data" not in [c.name for c in b2_cmds]
        assert b2_cmds[0].name == "core-get-IP-analytics-prevalence"

        batch2_results = []

        prevalence_entries = batch_data["batch2_core_prevalence"]
        assert len(prevalence_entries) == 1
        batch2_results.extend(_wrap_each_as_command(prevalence_entries, hr="prevalence-hr"))

        enrich_entries = batch_data["batch2_enrichIndicators"]
        enrich_cmds_count = sum(1 for c in b2_cmds if c.name == "enrichIndicators")
        if enrich_cmds_count == 1:
            batch2_results.extend(_wrap_all_in_one_command(enrich_entries))
        else:
            assert len(enrich_entries) == enrich_cmds_count, "enrichIndicators size mismatch vs fixture"
            batch2_results.extend(_wrap_each_as_command(enrich_entries))

        out.append(batch2_results)
        return out

    mocker.patch("AggregatedCommandApiModule.BatchExecutor.execute_list_of_batches", _fake_execute_list_of_batches)

    # Act
    res = ip_enrichment_script(
        ip_list=ip_list,
        external_enrichment=True,
        verbose=True,
        enrichment_brands=["brand1", "brand2", "Core", "Cortex Core - IR"],
        additional_fields=False,
    )
    outputs = res.outputs
    assert outputs is not None

    # IPEnrichment indicators
    enrichment_list = outputs.get("IPEnrichment(val.Value && val.Value == obj.Value)", [])
    enrichment_map = {item["Value"]: item for item in enrichment_list}
    assert set(enrichment_map.keys()) == set(ip_list)

    # 1.1.1.1 should have TIM + brand1 + brand2
    ip1 = enrichment_map["1.1.1.1"]
    brands_present = {r.get("Brand") for r in ip1["Results"]}
    assert brands_present == {"TIM", "brand1", "brand2"}
    assert len(ip1["Results"]) == 3

    # Vendor results with reliability
    b1 = next(r for r in ip1["Results"] if r["Brand"] == "brand1")
    assert b1["Score"] == 2
    assert b1["PositiveDetections"] == 5
    assert b1.get("Reliability") == "High"

    b2 = next(r for r in ip1["Results"] if r["Brand"] == "brand2")
    assert b2["Score"] == 3
    assert b2["PositiveDetections"] == 37
    assert b2.get("Reliability") == "Medium"

    # TIM line present but without Status/ModifiedTime (popped to top-level)
    tim_row = next(r for r in ip1["Results"] if r["Brand"] == "TIM")
    assert "Status" not in tim_row
    assert "ModifiedTime" not in tim_row

    # Max fields and TIMScore
    assert ip1["MaxScore"] == 3
    assert ip1["MaxVerdict"] == "Malicious"
    assert ip1["TIMScore"] == 3

    # Optional: we set the IOC "manuallyEditedFields" → top-level Status should be Manual
    assert ip1.get("Status") == "Manual"

    # Core prevalence mapped
    prevalence_ctx = outputs.get("Core.AnalyticsPrevalence.Ip", [])
    assert isinstance(prevalence_ctx, list)
    assert len(prevalence_ctx) == 2
    assert {d["Ip"] for d in prevalence_ctx} == {"1.1.1.1", "8.8.8.8"}


def test_ip_enrichment_script_with_internal_ip(mocker):
    """
    Given:
        - One internal IP.
    When:
        - ip_enrichment_script runs.
    Then:
        - get-endpoint-data command is executed.
        - EndpointData is mapped and preserved.
    """
    batch_data = util_load_json("test_data/mock_ip_batch_results.json")
    ip_list = ["192.168.1.1"]
    mocker.patch.object(demisto, "args", return_value={"ip_list": ",".join(ip_list)})
    mocker.patch("IPEnrichment.is_xsiam", return_value=True)
    mocker.patch("IPEnrichment.is_platform", return_value=False)
    mocker.patch(
        "AggregatedCommandApiModule.execute_command",
        return_value=[{"EntryContext": {"ExtractedIndicators": {"IP": ip_list}}}],
    )
    mocker.patch("AggregatedCommandApiModule.IndicatorsSearcher", return_value=iter([]))
    mocker.patch.object(
        demisto,
        "getModules",
        return_value={
            "core": {"state": "active", "brand": "Core"},
            "coreir": {"state": "active", "brand": "Cortex Core - IR"},
        },
    )

    def _wrap_each_as_command(entries, hr=""):
        return [[(e, hr, "")] for e in entries]

    def _wrap_all_in_one_command(entries, hr=""):
        return [[(e, hr, "") for e in entries]]

    def _fake_execute_list_of_batches(self, list_of_batches, brands_to_run=None, verbose=False):
        out = []
        b1_cmds = list_of_batches[0]
        b1_entries = batch_data["batch1_createNewIndicator"]
        if len(b1_cmds) == 1:
            out.append(_wrap_all_in_one_command(b1_entries))
        else:
            assert len(b1_entries) == len(b1_cmds), "batch1 size mismatch vs fixture"
            out.append(_wrap_each_as_command(b1_entries))

        b2_cmds = list_of_batches[1]
        assert b2_cmds[0].name == "get-endpoint-data"
        batch2_results = []
        endpoint_entries = batch_data["batch2_core_endpoint_data"]
        assert len(endpoint_entries) == 1
        batch2_results.extend(_wrap_each_as_command(endpoint_entries, hr="endpoint-hr"))
        prevalence_entries = batch_data["batch2_core_prevalence"]
        assert len(prevalence_entries) == 1
        batch2_results.extend(_wrap_each_as_command(prevalence_entries, hr="prevalence-hr"))
        enrich_entries = batch_data["batch2_enrichIndicators"]
        enrich_cmds_count = sum(1 for c in b2_cmds if c.name == "enrichIndicators")
        if enrich_cmds_count == 1:
            batch2_results.extend(_wrap_all_in_one_command(enrich_entries))
        else:
            assert len(enrich_entries) == enrich_cmds_count, "enrichIndicators size mismatch vs fixture"
            batch2_results.extend(_wrap_each_as_command(enrich_entries))

        out.append(batch2_results)
        return out

    mocker.patch("AggregatedCommandApiModule.BatchExecutor.execute_list_of_batches", _fake_execute_list_of_batches)

    res = ip_enrichment_script(
        ip_list=ip_list,
        external_enrichment=True,
        verbose=True,
        enrichment_brands=["Core", "Cortex Core - IR"],
        additional_fields=False,
    )
    outputs = res.outputs
    assert outputs is not None
    endpoint_ctx = outputs.get(
        "EndpointData"
        "(val.Brand && val.Brand == obj.Brand && val.ID && val.ID == obj.ID && val.Hostname && val.Hostname == obj.Hostname)",
        [],
    )
    assert isinstance(endpoint_ctx, list)
    assert len(endpoint_ctx) == 2
    assert {e["Brand"] for e in endpoint_ctx} == {"Core"}
    assert {e["Hostname"] for e in endpoint_ctx} == {"host-1", "host-2"}


def test_ip_enrichment_uses_builtin_command_on_platform(mocker):
    """
    Given:
        - Running on the unified Cortex platform (is_xsiam and is_platform both True).
    When:
        - ip_enrichment_script builds its command batches.
    Then:
        - The prevalence command is the built-in "getIPAnalyticsPrevalence".
        - Its command_type is CommandType.BUILTIN (not the legacy INTERNAL core command).
    """
    from AggregatedCommandApiModule import CommandType

    ip_list = ["1.1.1.1"]
    captured_batches: dict = {}

    class _StopAfterCapture(Exception):
        pass

    def _capture_batches(self, list_of_batches, brands_to_run=None, verbose=False):
        captured_batches["batches"] = list_of_batches
        raise _StopAfterCapture

    mocker.patch.object(demisto, "args", return_value={"ip_list": ",".join(ip_list)})
    mocker.patch("IPEnrichment.is_xsiam", return_value=True)
    mocker.patch("IPEnrichment.is_platform", return_value=True)
    mocker.patch(
        "AggregatedCommandApiModule.execute_command",
        return_value=[{"EntryContext": {"ExtractedIndicators": {"IP": ip_list}}}],
    )
    mocker.patch("AggregatedCommandApiModule.IndicatorsSearcher", return_value=iter([]))
    mocker.patch.object(
        demisto,
        "getModules",
        return_value={"coreir": {"state": "active", "brand": "Cortex Core - IR"}},
    )
    mocker.patch("AggregatedCommandApiModule.BatchExecutor.execute_list_of_batches", _capture_batches)

    with pytest.raises(_StopAfterCapture):
        ip_enrichment_script(
            ip_list=ip_list,
            external_enrichment=True,
            verbose=True,
            enrichment_brands=["Cortex Core - IR"],
            additional_fields=False,
        )

    b2_cmds = captured_batches["batches"][1]
    prevalence_cmds = [c for c in b2_cmds if c.name == "getIPAnalyticsPrevalence"]
    assert len(prevalence_cmds) == 1
    assert prevalence_cmds[0].command_type == CommandType.BUILTIN