load_partial_data#

API documentation for tradeexecutor.strategy.trading_strategy_universe.load_partial_data Python function.

load_partial_data(client, execution_context, time_bucket, pairs, universe_options, liquidity=False, liquidity_time_bucket=None, liquidity_query_type=OHLCVCandleType.tvl_v1, preloaded_tvl_df=None, stop_loss_time_bucket=None, required_history_period=None, lending_reserves=None, lending_candle_types=(<LendingCandleType.supply_apr: 'supply_apr'>, <LendingCandleType.variable_borrow_apr: 'variable_borrow_apr'>), start_at=None, end_at=None, name=None, candle_progress_bar_desc=None, lending_candle_progress_bar_desc=None, pair_extra_metadata=False, vaults=None, vault_bundled_price_data=False)[source]#

Load pair data for given trading pairs.

A loading function designed to load data for 2-20 pairs. Instead of loading all pair data over Parquet datasets, load only specific pair data from their corresponding JSONL endpoints.

This function works in low memory environments unlike tradeexecutor.strategy.trading_strategy_universe.load_all_data().

Example of loading spot-only data:

… code-block:: python

def create_trading_universe(

ts: datetime.datetime, client: Client, execution_context: ExecutionContext, universe_options: UniverseOptions,

) -> TradingStrategyUniverse:

dataset = load_partial_data(

client=client, time_bucket=Parameters.candle_time_bucket, pairs=pairs_df, execution_context=execution_context, universe_options=universe_options, liquidity=True, liquidity_time_bucket=TimeBucket.d1, liquidity_query_type=OHLCVCandleType.tvl_v2,

)

strategy_universe = TradingStrategyUniverse.create_from_dataset(

dataset, reserve_asset=”0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913”, # USDC on Base forward_fill=True, # We got very gappy data from low liquid DEX coins

)

return universe

Example of loading spot pair and Aave credit pool data:
Parameters:

  • client (BaseClient) – Trading Strategy client instance

  • time_bucket (TimeBucket) – The candle time frame.

  • pairs (Union[Collection[Union[Tuple[ChainId, str | None, str, str, float], Tuple[ChainId, str | None, str, str]]], DataFrame]) –

    List of trading pair tickers.

    Can be

    • Human-readable descriptions, see tradingstrategy.pair.HumanReadableTradingPairDescription.

    • Direct pandas.DataFrame of pairs.

  • lending_resserves –

    Lending reserves for which you want to download the data.

    Either list of lending pool descriptions or preloaded lending universe.

  • lending_candle_types (Collection[LendingCandleType]) – What lending data columns to load

  • liquidity – Set true to load liquidity data as well

  • liquidity_time_bucket (tradingstrategy.timebucket.TimeBucket | None) –

    Granularity of loaded TVL data.

    If not given use time_bucket.

  • liquidity_query_type (OHLCVCandleType) –

    Whether to use new-style or old-style data for TVL.

    See OHLCVCandleType for details.

  • preloaded_tvl_df (pandas.core.frame.DataFrame | None) –

    Liquidity data was earlier loaded with fetch_tvl(min_tvl) when constructing the trading universe.

    We do not reload this same data, but use the preloaded DataFrame directly.

  • lending_reserves (Optional[Union[LendingReserveUniverse, Collection[Union[Tuple[ChainId, LendingProtocolType, str], Tuple[ChainId, LendingProtocolType, str, str]]]]]) – Set true to load lending reserve data as well

  • stop_loss_time_bucket (Optional[TimeBucket]) – If set load stop loss trigger data using this candle granularity.

  • execution_context (ExecutionContext) – Defines if we are live or backtesting

  • universe_options (UniverseOptions) – Override values given the strategy file. Used in testing the framework.

  • required_history_period (datetime.timedelta | None) –

    How much historical data we need to load.

    Depends on the strategy. Defaults to load all data.

  • start_at (datetime.datetime | None) –

    Load data for a specific backtesting data range.

    TODO: Going to be deprecatd. Please use universe_options.start_at instead.

  • end_at (datetime.datetime | None) –

    Load data for a specific backtesting data range.

    TODO: Going to be deprecatd. Please use universe_options.end_at instead.

  • name (str | None) – The loading operation name used in progress bars

  • candle_progress_bar_desc (str | None) – Override the default progress bar message

  • lending_candle_progress_bar_desc (str | None) – Override the default progress bar message

  • pair_extra_metadata –

    Load TokenSniffer data, buy/sell tax and other extra metadata.

    Slow and API endpoint severely limited. Use only if you are dealing with a limited number of pairs.

  • vaults (list[tuple[tradingstrategy.chain.ChainId, str]] | None) –

    List of (chain, vault address) tuples to load vault data for.

    Vault metadata loeaded from tradingstrategy data bundle.

    Currently does not load any historical data.

  • vault_bundled_price_data –

    For vaults, also load bundled static price data.

    Use minimal backtest dataset from Trading Strategy package bundle.

    Not applicable for live trading.

Lending_candle_types:

What lending data columns to load

Returns:

Datataset containing the requested data

Return type:

Dataset