from string import Template
from typing import Any
from datetime import datetime, timedelta, UTC
from utils import (
    SUBGRAPH_API_KEY,
    measure_execution_time,
    DATA_DIR,
    TMP_DIR,
    NETWORK_SUBGRAPH_URL,
    transform_to_datetime,
)
import requests
import pandas as pd
import numpy as np
from mech_request_utils import (
    collect_all_mech_delivers,
    collect_all_mech_requests,
    clean_mech_delivers,
    fix_duplicate_requestIds,
    merge_requests_delivers,
    get_ipfs_data,
    merge_json_files,
)

SUBGRAPH_HEADERS = {
    "Accept": "application/json, multipart/mixed",
    "Content-Type": "application/json",
}

QUERY_BATCH_SIZE = 1000
DATETIME_60_DAYS_AGO = datetime.now(UTC) - timedelta(days=60)
DATETIME_10_DAYS_AGO = datetime.now(UTC) - timedelta(days=10)
DATETIME_10_HOURS_AGO = datetime.now(UTC) - timedelta(hours=10)
BLOCK_NUMBER = Template(
    """
    { 
        blocks(
            first: 1,
            orderBy: timestamp,
            orderDirection: asc,
            where: {
                timestamp_gte: "${timestamp_from}",
                timestamp_lte: "${timestamp_to}"
            }
        ){
            id,
            number,
        }
    }
    """
)

LATEST_BLOCK_QUERY = """
    { 
        blocks(
            first: 1,
            orderBy: timestamp,
            orderDirection: desc,
        ){
            id,
            number,
        }
    }
    """


def fetch_last_block_number() -> dict:
    # print(f"Sending query for the subgraph = {query}")
    network_subgraph_url = NETWORK_SUBGRAPH_URL.substitute(
        subgraph_api_key=SUBGRAPH_API_KEY
    )
    query = LATEST_BLOCK_QUERY
    response = requests.post(
        network_subgraph_url,
        headers=SUBGRAPH_HEADERS,
        json={"query": query},
        timeout=300,
    )

    result_json = response.json()
    print(f"Response of the query={result_json}")
    blocks = result_json.get("data", {}).get("blocks", "")
    if len(blocks) == 0:
        raise ValueError(f"The query {query} did not return any results")
    return blocks[0]


def fetch_block_number(timestamp_from: int, timestamp_to: int) -> dict:
    """Get a block number by its timestamp margins."""

    query = BLOCK_NUMBER.substitute(
        timestamp_from=timestamp_from, timestamp_to=timestamp_to
    )
    # print(f"Sending query for the subgraph = {query}")
    network_subgraph_url = NETWORK_SUBGRAPH_URL.substitute(
        subgraph_api_key=SUBGRAPH_API_KEY
    )
    response = requests.post(
        network_subgraph_url,
        headers=SUBGRAPH_HEADERS,
        json={"query": query},
        timeout=300,
    )
    # print(f"block query: {query}")
    result_json = response.json()
    print(f"Response of the query={result_json}")
    blocks = result_json.get("data", {}).get("blocks", "")
    if len(blocks) == 0:
        raise ValueError(f"The query {query} did not return any results")
    return blocks[0]


def update_json_files():
    merge_json_files("mech_requests.json", "new_mech_requests.json")
    merge_json_files("mech_delivers.json", "new_mech_delivers.json")
    merge_json_files("merged_requests.json", "new_merged_requests.json")
    merge_json_files("tools_info.json", "new_tools_info.json")


def update_fpmmTrades_parquet(trades_filename: str) -> pd.DataFrame:
    # Read old trades parquet file
    try:
        old_trades_df = pd.read_parquet(TMP_DIR / "fpmmTrades.parquet")
    except Exception as e:
        print(f"Error reading old trades parquet file {e}")
        return None

    try:
        new_trades_df = pd.read_parquet(DATA_DIR / trades_filename)
    except Exception as e:
        print(f"Error reading new trades parquet file {e}")
        return None

    # lowercase and strip creator_address
    new_trades_df["trader_address"] = (
        new_trades_df["trader_address"].str.lower().str.strip()
    )
    # ensure creationTimestamp compatibility
    try:
        new_trades_df["creationTimestamp"] = new_trades_df["creationTimestamp"].apply(
            lambda x: transform_to_datetime(x)
        )

    except Exception as e:
        print(f"Transformation not needed")
    try:
        old_trades_df["creationTimestamp"] = old_trades_df["creationTimestamp"].apply(
            lambda x: transform_to_datetime(x)
        )
    except Exception as e:
        print(f"Transformation not needed")

    # merge two dataframes
    merge_df = pd.concat([old_trades_df, new_trades_df], ignore_index=True)
    # avoid numpy objects
    merge_df["fpmm.arbitrationOccurred"] = merge_df["fpmm.arbitrationOccurred"].astype(
        bool
    )
    merge_df["fpmm.isPendingArbitration"] = merge_df[
        "fpmm.isPendingArbitration"
    ].astype(bool)

    # Check for duplicates
    print(f"Initial length before removing duplicates in fpmmTrades= {len(merge_df)}")

    # Remove duplicates
    # fpmm.outcomes is a numpy array
    merge_df.drop_duplicates("id", keep="last", inplace=True)
    print(f"Final length after removing duplicates in fpmmTrades= {len(merge_df)}")

    # save the parquet file
    merge_df.to_parquet(TMP_DIR / "fpmmTrades.parquet", index=False)

    return


def update_all_trades_parquet(new_trades_df: pd.DataFrame) -> pd.DataFrame:
    # Read old all_trades parquet file
    try:
        old_trades_df = pd.read_parquet(DATA_DIR / "all_trades_profitability.parquet")
    except Exception as e:
        print(f"Error reading old trades parquet file {e}")
        return None
    # merge two dataframes
    merge_df = pd.concat([old_trades_df, new_trades_df], ignore_index=True)

    # Check for duplicates
    print(f"Initial length before removing duplicates in all_trades= {len(merge_df)}")

    # Remove duplicates
    merge_df.drop_duplicates("trade_id", inplace=True)
    print(f"Final length after removing duplicates in all_trades = {len(merge_df)}")
    return merge_df


def update_tools_parquet(new_tools_filename: pd.DataFrame):
    try:
        old_tools_df = pd.read_parquet(TMP_DIR / "tools.parquet")
    except Exception as e:
        print(f"Error reading old tools parquet file {e}")
        return None
    try:
        new_tools_df = pd.read_parquet(DATA_DIR / new_tools_filename)

    except Exception as e:
        print(f"Error reading new trades parquet file {e}")
        return None

    # merge two dataframes
    merge_df = pd.concat([old_tools_df, new_tools_df], ignore_index=True)

    # Check for duplicates
    print(f"Initial length before removing duplicates in tools= {len(merge_df)}")

    # Remove duplicates
    merge_df.drop_duplicates(
        subset=["request_id", "request_time"], keep="last", inplace=True
    )
    print(f"Final length after removing duplicates in tools= {len(merge_df)}")

    # save the parquet file
    merge_df.to_parquet(TMP_DIR / "tools.parquet", index=False)


def get_mech_info_2024() -> dict[str, Any]:
    """Query the subgraph to get the 2024 information from mech."""

    date = "2024-01-01"
    datetime_jan_2024 = datetime.strptime(date, "%Y-%m-%d")
    timestamp_jan_2024 = int(datetime_jan_2024.timestamp())
    margin = timedelta(seconds=5)
    timestamp_jan_2024_plus_margin = int((datetime_jan_2024 + margin).timestamp())

    jan_block_number = fetch_block_number(
        timestamp_jan_2024, timestamp_jan_2024_plus_margin
    )
    # expecting only one block
    jan_block_number = jan_block_number.get("number", "")
    if jan_block_number.isdigit():
        jan_block_number = int(jan_block_number)

    if jan_block_number == "":
        raise ValueError(
            "Could not find a valid block number for the first of January 2024"
        )
    MECH_TO_INFO = {
        # this block number is when the creator had its first tx ever, and after this mech's creation
        "0xff82123dfb52ab75c417195c5fdb87630145ae81": (
            "old_mech_abi.json",
            jan_block_number,
        ),
        # this block number is when this mech was created
        "0x77af31de935740567cf4ff1986d04b2c964a786a": (
            "new_mech_abi.json",
            jan_block_number,
        ),
    }
    return MECH_TO_INFO


def get_last_block_number() -> int:
    last_block_number = fetch_last_block_number()
    # expecting only one block
    last_block_number = last_block_number.get("number", "")
    if last_block_number.isdigit():
        last_block_number = int(last_block_number)

    if last_block_number == "":
        raise ValueError("Could not find a valid block number for last month data")
    return last_block_number


def get_last_60_days_block_number() -> int:
    timestamp_60_days_ago = int((DATETIME_60_DAYS_AGO).timestamp())
    margin = timedelta(seconds=5)
    timestamp_60_days_ago_plus_margin = int((DATETIME_60_DAYS_AGO + margin).timestamp())

    last_month_block_number = fetch_block_number(
        timestamp_60_days_ago, timestamp_60_days_ago_plus_margin
    )
    # expecting only one block
    last_month_block_number = last_month_block_number.get("number", "")
    if last_month_block_number.isdigit():
        last_month_block_number = int(last_month_block_number)

    if last_month_block_number == "":
        raise ValueError("Could not find a valid block number for last month data")
    return last_month_block_number


def get_mech_info_last_60_days() -> dict[str, Any]:
    """Query the subgraph to get the last 60 days of information from mech."""
    last_month_block_number = get_last_60_days_block_number()

    MECH_TO_INFO = {
        # this block number is when the creator had its first tx ever, and after this mech's creation
        "0xff82123dfb52ab75c417195c5fdb87630145ae81": (
            "old_mech_abi.json",
            last_month_block_number,
        ),
        # this block number is when this mech was created
        "0x77af31de935740567cf4ff1986d04b2c964a786a": (
            "new_mech_abi.json",
            last_month_block_number,
        ),
    }
    print(f"last 60 days block number {last_month_block_number}")
    return MECH_TO_INFO


@measure_execution_time
def get_mech_events_since_last_run(logger):
    """Function to download only the new events since the last execution."""

    # Read the latest date from stored data
    try:
        all_trades = pd.read_parquet(DATA_DIR / "all_trades_profitability.parquet")
        latest_timestamp = max(all_trades.creation_timestamp)
        # cutoff_date = "2024-12-22"
        # latest_timestamp = pd.Timestamp(
        #     datetime.strptime(cutoff_date, "%Y-%m-%d")
        # ).tz_localize("UTC")
        print(f"Updating data since {latest_timestamp}")
    except Exception:
        print("Error while reading the profitability parquet file")
        return None

    # Get the block number of lastest date
    five_seconds = np.timedelta64(5, "s")
    last_run_block_number = fetch_block_number(
        int(latest_timestamp.timestamp()),
        int((latest_timestamp + five_seconds).timestamp()),
    )
    # expecting only one block
    last_run_block_number = last_run_block_number.get("number", "")
    if last_run_block_number.isdigit():
        last_run_block_number = int(last_run_block_number)

    if last_run_block_number == "":
        raise ValueError("Could not find a valid block number for last collected data")
    last_block_number = get_last_block_number()

    # mech requests
    requests_dict, duplicatedReqId, nr_errors = collect_all_mech_requests(
        from_block=last_run_block_number,
        to_block=last_block_number,
        filename="new_mech_requests.json",
    )
    print(f"NUMBER OF MECH REQUEST ERRORS={nr_errors}")
    # mech delivers
    delivers_dict, duplicatedIds, nr_errors = collect_all_mech_delivers(
        from_block=last_run_block_number,
        to_block=last_block_number,
        filename="new_mech_delivers.json",
    )
    print(f"NUMBER OF MECH DELIVER ERRORS={nr_errors}")
    if delivers_dict is None:
        return None
    # clean delivers
    clean_mech_delivers("new_mech_requests.json", "new_mech_delivers.json")

    # solve duplicated requestIds
    block_map = fix_duplicate_requestIds(
        "new_mech_requests.json", "new_mech_delivers.json"
    )
    # merge the two files into one source
    not_found = merge_requests_delivers(
        "new_mech_requests.json", "new_mech_delivers.json", "new_merged_requests.json"
    )

    # Add ipfs contents
    get_ipfs_data("new_merged_requests.json", "new_tools_info.json", logger)
    return latest_timestamp


if __name__ == "__main__":
    get_mech_events_since_last_run()
    # result = get_mech_info_last_60_days()
    # print(result)