def clean_order(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["state"] = State.to_enum(data["state"])
data["time_in_force"] = TimeInForce.to_enum(data["time_in_force"])
data["side"] = ExecutionType.to_enum(data["side"])
data["type"] = OrderType.to_enum(data["type"])
data["executions"] = [
Execution(**clean_execution(e)) for e in data["executions"]
]
consolidate_price_data(data, [
"price", "stop_price", "dollar_based_amount", "total_notional",
"executed_notional"
])
data = convert_floats(data, [
"cumulative_quantity", "quantity", "average_price", "fees",
"stop_price", "last_trail_price"
])
data = convert_dates(data, [
"last_transaction_at", "stop_triggered_at",
"last_trail_price_updated_at"
])
return data
def clean_portfolio(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_floats(
data,
[
"market_value",
"equity",
"extended_hours_market_value",
"extended_hours_equity",
"extended_hours_portfolio_equity",
"last_core_market_value",
"last_core_equity",
"last_core_portfolio_equity",
"excess_margin",
"excess_maintenance",
"excess_margin_with_uncleared_deposits",
"excess_maintenance_with_uncleared_deposits",
"equity_previous_close",
"portfolio_equity_previous_close",
"adjusted_equity_previous_close",
"adjusted_portfolio_equity_previous_close",
"withdrawable_amount",
"unwithdrawable_deposits",
"unwithdrawable_grants",
],
)
data = convert_dates(data, ["start_date"])
return data
def clean_execution(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_floats(data, ["price", "quantity"])
data = convert_dates(data, ["settlement_date", "timestamp"])
return data
def clean_rating(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["type"] = RatingType.to_enum(data["type"])
data = convert_dates(data, ["published_at"])
return data
def clean_historicals(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_floats(
data, ["open_price", "close_price", "high_price", "low_price"])
data = convert_dates(data, ["begins_at"])
return data
def clean_mover(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["price_movement"] = PriceMovement(
**clean_price_movement(data["price_movement"]))
data = convert_dates(data)
return data
def clean_offers(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["asks"] = [Offer(**clean_offer(o)) for o in data["asks"]]
data["bids"] = [Offer(**clean_offer(o)) for o in data["bids"]]
data = convert_dates(data)
return data
def clean_transfer(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["direction"] = TransferDirection.to_enum(data["direction"])
data["state"] = State.to_enum(data["state"])
data["rhs_state"] = State.to_enum(data["rhs_state"])
data = convert_floats(data, ["amount", "fees", "early_access_amount"])
data = convert_dates(
data, ["expected_landing_date", "expected_landing_datetime"])
return data
def clean_dividend(input_data: Dict[str, str]) -> Dict[str, Any]:
data: Dict[str, Any] = deepcopy(input_data)
data["drip_order_execution_price"] = (
Price(**clean_price(data["drip_order_execution_price"]))
if "drip_order_execution_price" in data else None)
data["state"] = DividendState.to_enum(data["state"])
data = convert_floats(
data,
["amount", "rate", "position", "withholding", "drip_order_quantity"])
data = convert_dates(data, ["record_date", "payable_date", "paid_at"])
return data
def clean_option(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["min_ticks"] = Tick(**clean_tick(data["min_ticks"]))
data["rhs_tradability"] = Tradability.to_enum(data["rhs_tradability"])
data["state"] = State.to_enum(data["state"])
data["tradability"] = Tradability.to_enum(data["tradability"])
data["type"] = OptionType.to_enum(data["type"])
data = convert_floats(
data,
[
"strike_price",
"adjusted_mark_price",
"ask_price",
"ask_size",
"bid_price",
"bid_size",
"break_even_price",
"high_price",
"last_trade_price",
"last_trade_size",
"low_price",
"mark_price",
"open_interest",
"previous_close_price",
"volume",
"chance_of_profit_long",
"chance_of_profit_short",
"delta",
"gamma",
"implied_volatility",
"rho",
"theta",
"vega",
"high_fill_rate_buy_price",
"high_fill_rate_sell_price",
"low_fill_rate_buy_price",
"low_fill_rate_sell_price",
],
)
data = convert_dates(data, ["expiration_date", "issue_date", "sellout_datetime", "previous_close_date"])
return data
def clean_quote(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_floats(
data,
[
"ask_price",
"bid_price",
"last_trade_price",
"last_extended_hours_trade_price",
"previous_close",
"adjusted_previous_close",
],
)
data = convert_dates(data, ["previous_close_date"])
return data
def clean_ratings(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data["ratings"] = [Rating(**clean_rating(r)) for r in data["ratings"]]
# Map summary keys to RatingType enum
mapping = {
"num_buy_ratings": RatingType.BUY,
"num_hold_ratings": RatingType.HOLD,
"num_sell_ratings": RatingType.SELL,
}
summary: Dict[RatingType, int] = {}
for summary_key, value in data["summary"].items():
if summary_key in mapping.keys():
summary[mapping[summary_key]] = value
else:
print(f"WARNING: Rating Summary Type: {summary_key} not found.")
data["summary"] = summary
data = convert_dates(data, ["ratings_published_at"])
return data
def clean_position(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_floats(
data,
[
"quantity",
"intraday_quantity",
"average_buy_price",
"pending_average_buy_price",
"intraday_average_buy_price",
"shares_available_for_exercise",
"shares_held_for_buys",
"shares_held_for_options_collateral",
"shares_held_for_options_events",
"shares_held_for_sells",
"shares_held_for_stock_grants",
"shares_pending_from_options_events",
],
)
data = convert_dates(data)
return data
def clean_fundamentals(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_floats(
data,
[
"open",
"high",
"low",
"volume",
"average_volume_2_weeks",
"average_volume",
"high_52_weeks",
"low_52_weeks",
"market_cap",
"shares_outstanding",
],
)
data = convert_floats(data,
["dividend_yield", "float", "pb_ratio", "pe_ratio"],
0.00)
data = convert_dates(data, ["datetime"])
return data
def clean_earnings_call(input_data: Dict[str, Any]) -> Dict[str, Any]:
return convert_dates(input_data, ["datetime"])
def clean_earnings_report(input_data: Dict[str, Any]) -> Dict[str, Any]:
return convert_dates(input_data, ["date"])
def clean_news(input_data: Dict[str, Any]) -> Dict[str, Any]:
data = deepcopy(input_data)
data = convert_dates(data, ["published_at"])
return data