cli_module.py

import logging
import sys

from enforce_typing import enforce_types

from pdr_backend.analytics.check_network import check_network_main
from pdr_backend.analytics.get_predictions_info import (
    get_predictions_info_main,
    get_predictoors_info_main,
    get_traction_info_main,
)
from pdr_backend.cli.cli_arguments import (
    do_help_long,
    do_help_short,
    get_arg_parser,
    print_args,
)
from pdr_backend.deployer.deployer import main as deployer_main
from pdr_backend.dfbuyer.dfbuyer_agent import DFBuyerAgent
from pdr_backend.lake.etl import ETL
from pdr_backend.lake.gql_data_factory import GQLDataFactory
from pdr_backend.lake.ohlcv_data_factory import OhlcvDataFactory
from pdr_backend.payout.payout import do_ocean_payout, do_rose_payout
from pdr_backend.ppss.ppss import PPSS
from pdr_backend.pred_submitter.deploy import deploy_pred_submitter_mgr_contract
from pdr_backend.predictoor.predictoor_agent import PredictoorAgent
from pdr_backend.publisher.publish_assets import publish_assets
from pdr_backend.sim.multisim_engine import MultisimEngine
from pdr_backend.aimodel.plots_dash import arima_dash
from pdr_backend.sim.sim_dash import sim_dash
from pdr_backend.sim.sim_engine import SimEngine
from pdr_backend.trader.approach1.trader_agent1 import TraderAgent1
from pdr_backend.trader.approach2.trader_agent2 import TraderAgent2
from pdr_backend.trueval.trueval_agent import TruevalAgent
from pdr_backend.util.core_accounts import fund_accounts_with_OCEAN
from pdr_backend.util.currency_types import Eth
from pdr_backend.util.topup import topup_main
from pdr_backend.util.web3_accounts import (
    create_accounts,
    fund_accounts,
    print_balances,
)

logger = logging.getLogger("cli")


@enforce_types
def _do_main():
    if len(sys.argv) <= 1 or sys.argv[1] == "help":
        do_help_short(0)
    if sys.argv[1] == "help_long":
        do_help_long(0)

    func_name = f"do_{sys.argv[1]}"
    func = globals().get(func_name)
    if func is None:
        do_help_long(1)

    parser = get_arg_parser(func_name)
    args, nested_args = parser.parse_known_args()

    do_log_args = func_name != "do_print_balances"
    if do_log_args:
        print_args(args, nested_args)

    func(args, nested_args)


# ========================================================================
# actual cli implementations. Given in same order as HELP_LONG


# do_help() is implemented in cli_arguments and imported, so nothing needed here


@enforce_types
def do_sim(args, nested_args=None):
    ppss = PPSS(
        yaml_filename=args.PPSS_FILE,
        network="development",
        nested_override_args=nested_args,
    )
    feedset = ppss.predictoor_ss.predict_train_feedsets[0]
    if len(ppss.predictoor_ss.predict_train_feedsets) > 0:
        logger.warning("Multiple predict feeds provided, using the first one")
    sim_engine = SimEngine(ppss, feedset)
    sim_engine.run()


@enforce_types
# pylint: disable=unused-argument
def do_predictoor(args, nested_args=None):
    ppss = args.PPSS
    agent = PredictoorAgent(ppss)
    agent.run()


@enforce_types
# pylint: disable=unused-argument
def do_trader(args, nested_args=None):
    ppss = args.PPSS
    approach = args.APPROACH

    if approach == 1:
        agent = TraderAgent1(ppss)
    elif approach == 2:
        agent = TraderAgent2(ppss)
    else:
        raise ValueError(f"Unknown trader approach {approach}")

    agent.run()


@enforce_types
def do_claim_OCEAN(args, nested_args=None):
    ppss = PPSS(
        yaml_filename=args.PPSS_FILE,
        network="sapphire-mainnet",
        nested_override_args=nested_args,
    )
    do_ocean_payout(ppss)


@enforce_types
def do_claim_ROSE(args, nested_args=None):
    ppss = PPSS(
        yaml_filename=args.PPSS_FILE,
        network="sapphire-mainnet",
        nested_override_args=nested_args,
    )
    do_rose_payout(ppss)


@enforce_types
def do_multisim(args, nested_args=None):
    d = PPSS.constructor_dict(
        yaml_filename=args.PPSS_FILE,
        nested_override_args=nested_args,
    )
    multisim_engine = MultisimEngine(d=d)
    multisim_engine.run()


@enforce_types
# pylint: disable=unused-argument
def do_deployer(args, nested_args=None):
    deployer_main(args)


@enforce_types
# pylint: disable=unused-argument
def do_lake(args, nested_args=None):
    ppss = args.PPSS
    ohlcv_data_factory = OhlcvDataFactory(ppss.lake_ss)
    df = ohlcv_data_factory.get_mergedohlcv_df()
    print(df)


@enforce_types
# pylint: disable=unused-argument
def do_analytics(args, nested_args=None):
    """
    @description
        This runs all dependencies to build analytics
        All raw, clean, and aggregate data will be generated
        1. All subgraph data will be fetched
        2. All analytic data will be built
        3. Lake contains all required data
        4. Dashboards read from lake

        Please use nested_args to control lake_ss
        ie: st_timestr, fin_timestr, parquet_dir
    """
    ppss = args.PPSS

    gql_data_factory = GQLDataFactory(ppss)
    etl = ETL(ppss, gql_data_factory)
    etl.do_etl()


@enforce_types
# pylint: disable=unused-argument
def do_get_predictoors_info(args, nested_args=None):
    """
    @description
        The following args are post-lake filters:
        ST = Start time string (e.g. "2021-01-01")
        END = End time string (e.g. "2022-01-01")
        PDRS = List of predictoor addresses to filter on (e.g. ["0x1", "0x2"])
    """
    ppss = args.PPSS
    pdrs = args.PDRS or []
    get_predictoors_info_main(ppss, args.ST, args.END, pdrs)


@enforce_types
# pylint: disable=unused-argument
def do_get_predictions_info(args, nested_args=None):
    """
    @description
        The following args are post-lake filters:
        ST = Start time string (e.g. "2021-01-01")
        END = End time string (e.g. "2022-01-01")
        PDRS = List of feed addresses to filter on (e.g. ["0x1", "0x2"])
    """
    ppss = args.PPSS
    feeds = args.FEEDS or []
    get_predictions_info_main(ppss, args.ST, args.END, feeds)


@enforce_types
# pylint: disable=unused-argument
def do_get_traction_info(args, nested_args=None):
    """
    @description
        PQDIR = overrides lake parquet dir

        The following args are post-lake filters:
        ST = Start time string (e.g. "2021-01-01")
        END = End time string (e.g. "2022-01-01")
    """
    ppss = args.PPSS
    ppss.lake_ss.d["parquet_dir"] = args.PQDIR
    get_traction_info_main(ppss, args.ST, args.END)


@enforce_types
# pylint: disable=unused-argument
def do_check_network(args, nested_args=None):
    ppss = args.PPSS
    check_network_main(ppss, args.LOOKBACK_HOURS)


@enforce_types
# pylint: disable=unused-argument
def do_trueval(args, nested_args=None, testing=False):
    ppss = args.PPSS
    predictoor_batcher_addr = ppss.web3_pp.get_address("PredictoorHelper")
    agent = TruevalAgent(ppss, predictoor_batcher_addr)

    agent.run(testing)


@enforce_types
# pylint: disable=unused-argument
def do_dfbuyer(args, nested_args=None):
    ppss = args.PPSS
    agent = DFBuyerAgent(ppss)
    agent.run()


@enforce_types
# pylint: disable=unused-argument
def do_publisher(args, nested_args=None):
    ppss = args.PPSS

    if ppss.web3_pp.network == "development":
        fund_accounts_with_OCEAN(ppss.web3_pp)
    publish_assets(ppss.web3_pp, ppss.publisher_ss)


@enforce_types
# pylint: disable=unused-argument
def do_topup(args, nested_args=None):
    ppss = args.PPSS
    topup_main(ppss)


@enforce_types
# pylint: disable=unused-argument
def do_create_accounts(args, nested_args=None):
    create_accounts(args.NUM)


@enforce_types
# pylint: disable=unused-argument
def do_print_balances(args, nested_args=None):
    ppss = args.PPSS
    account = args.ACCOUNT
    print_balances(account, ppss.web3_pp)


@enforce_types
# pylint: disable=unused-argument
def do_fund_accounts(args, nested_args=None):
    ppss = args.PPSS
    to_accounts = args.ACCOUNTS
    fund_accounts(Eth(args.TOKEN_AMOUNT), to_accounts, ppss.web3_pp, args.NATIVE_TOKEN)


@enforce_types
# pylint: disable=unused-argument
def do_deploy_pred_submitter_mgr(args, nested_args=None):
    ppss = args.PPSS
    contract_address = deploy_pred_submitter_mgr_contract(ppss.web3_pp)
    logger.info(
        "Prediction Submitter Manager Contract deployed at %s", contract_address
    )


@enforce_types
# pylint: disable=unused-argument
def do_sim_plots(args, nested_args=None):
    sim_dash(args)


@enforce_types
# pylint: disable=unused-argument
def do_arima_plots(args, nested_args=None):
    ppss = PPSS(
        yaml_filename=args.PPSS_FILE,
        network="development",
        nested_override_args=nested_args,
    )
    arima_dash(ppss)