import itertools
import json
import os

import requests

CE_ENDPOINT = os.environ["CE_ENDPOINT"]
LOG_DIAG_TASK = os.environ["LOG_DIAG_TASK_NAME"]
METRIC_DIAG_TASK = os.environ["METRIC_DIAG_TASK_NAME"]


def map_task(task, tp):
    result = {
        "timestamp": task["created_at"],
        "type": tp,
        "duplicate": False,
        "advice": [],
    }

    ids = set()
    for a in task["data"]["advice"]:
        _id = a.get("id")
        if _id in ids:
            continue
        advice = {
            "id": _id,
            "name": a.get("name"),
            "category": a.get("category"),
            "component": a.get("component"),
            "content": a.get("content"),
            "qualified": a.get("qualified"),
            "instance": a.get("instance"),
            "level": a.get("level"),
            "type": a.get("type"),
        }
        result["advice"].append(advice)

    return result


def group_task(tasks):
    m = {}
    for task in tasks:
        k = f'{task["type"]}-{task["timestamp"]//60}'
        if k not in m:
            m[k] = []
        m[k].append(task)
    return [
        {
            "timestamp": g[0]["timestamp"] // 60 * 60,
            "type": g[0]["type"],
            "advice": list(itertools.chain(*[t["advice"] for t in g])),
        }
        for g in m.values()
    ]


def lambda_handler(event, context):
    tasks = []

    resp = requests.post(
        f'https://{CE_ENDPOINT}/tasks/{LOG_DIAG_TASK}?status=success&begin={event["kwargs"]["start_ts"]}&end={event["kwargs"]["stop_ts"]}',
        json.dumps(
            {
                "args": {
                    "cluster": event["kwargs"]["cluster"],
                },
                "data": {
                    "abnormal": True,
                },
            }
        ),
    )

    tasks += [map_task(t, "log") for t in resp.json()]

    resp = requests.post(
        f'https://{CE_ENDPOINT}/tasks/{METRIC_DIAG_TASK}?status=success&begin={event["kwargs"]["start_ts"]}&end={event["kwargs"]["stop_ts"]}',
        json.dumps(
            {
                "args": {
                    "cluster": event["kwargs"]["cluster"],
                },
                "data": {
                    "abnormal": True,
                },
            }
        ),
    )
    tasks += [map_task(t, "metric") for t in resp.json()]

    tasks = group_task(tasks)
    tasks = sorted(tasks, key=lambda x: -x["timestamp"])

    # mark duplicated results
    _ids = set()
    for t in tasks:
        _id = t["advice"]["id"]
        if _id in _ids:
            t["duplicate"] = True
            continue
        _ids.add(_id)

    if len(tasks) == 0:
        return {"abnormal": False, "content": []}

    return {"abnormal": True, "content": tasks}