from os import getenv

import aioredis
import orjson
import redis

# Elasticsearch
from elasticsearch import AsyncElasticsearch

import util

trues = ("true", "1", "t", True)

# INDEX = "msg"

log = util.get_logger("db")

# Redis (legacy)
r = redis.from_url("redis://ssdb:1289", db=0)

# AIORedis
ar = aioredis.from_url("redis://ssdb:1289", db=0)

TYPES_MAIN = [
    "msg",
    "notice",
    "action",
    "part",
    "join",
    "kick",
    "quit",
    "nick",
    "mode",
    "topic",
    "update",
]
MAIN_SRC_MAP = {
    "dis": "main",
    "irc": "restricted",
    "4ch": "main",
}

TYPES_META = ["who"]
TYPES_INT = ["conn", "highlight", "znc", "query", "self"]
KEYNAME = "queue"

ELASTICSEARCH_USERNAME = getenv("ELASTICSEARCH_USERNAME", "elastic")
ELASTICSEARCH_PASSWORD = getenv("ELASTICSEARCH_PASSWORD", "changeme")
ELASTICSEARCH_HOST = getenv("ELASTICSEARCH_HOST", "localhost")
ELASTICSEARCH_TLS = getenv("ELASTICSEARCH_TLS", "false") in trues

client = None

# These are sometimes numeric, sometimes strings.
# If they are seen to be numeric first, ES will erroneously
# index them as "long" and then subsequently fail to index messages
# with strings in the field.
keyword_fields = ["nick_id", "user_id", "net_id"]

mapping = {
    "mappings": {
        "properties": {
            "ts": {"type": "date", "format": "epoch_second"},
            "file_tim": {"type": "date", "format": "epoch_millis"},
        }
    }
}
for field in keyword_fields:
    mapping["mappings"]["properties"][field] = {"type": "text"}


async def initialise_elasticsearch():
    """
    Initialise the Elasticsearch client.
    """
    auth = (ELASTICSEARCH_USERNAME, ELASTICSEARCH_PASSWORD)
    client = AsyncElasticsearch(ELASTICSEARCH_HOST, http_auth=auth, verify_certs=False)
    for index in ("main", "restricted"):
        if await client.indices.exists(index=index):
            # update index with mapping
            await client.indices.put_mapping(
                index=index, properties=mapping["mappings"]["properties"]
            )
        else:
            await client.indices.create(index=index, mappings=mapping["mappings"])
    return client


async def store_batch(data):
    global client
    if not client:
        client = await initialise_elasticsearch()
    indexmap = {}
    for msg in data:
        if msg["type"] in TYPES_MAIN:
            # index = "main"
            index = MAIN_SRC_MAP[msg["src"]]
            # schema = mc_s.schema_main
        elif msg["type"] in TYPES_META:
            index = "meta"
            # schema = mc_s.schema_meta
        elif msg["type"] in TYPES_INT:
            index = "internal"
            # schema = mc_s.schema_int

        INDEX = index

        # if key in schema:
        #     if isinstance(value, int):
        #         if schema[key].startswith("string") or schema[key].startswith(
        #             "text"
        #         ):
        #             msg[key] = str(value)
        # body = orjson.dumps(msg)
        if "ts" not in msg:
            raise Exception("No TS in msg")
        if INDEX not in indexmap:
            indexmap[INDEX] = [msg]
        else:
            indexmap[INDEX].append(msg)

    for index, index_messages in indexmap.items():
        for message in index_messages:
            result = await client.index(index=index, body=message)
            if not result["result"] == "created":
                log.error(f"Indexing failed: {result}")
    log.debug(f"Indexed {len(data)} messages in ES")


async def queue_message(msg):
    """
    Queue a message on the Redis buffer.
    """
    message = orjson.dumps(msg)
    await ar.lpush(KEYNAME, message)


async def queue_message_bulk(data):
    """
    Queue multiple messages on the Redis buffer.
    """
    for msg in data:
        message = orjson.dumps(msg)
        await ar.lpush(KEYNAME, message)