PandasTraderRunner

tradeexecutor.strategy.pandas_trader.runner.PandasTraderRunner Python class in Trading Strategy framework.

class PandasTraderRunner

Bases: StrategyRunner

A trading executor for Pandas math based algorithm.

__init__(*args, decide_trades, max_data_age=None, **kwargs)

Parameters:

• decide_trades (TradeDecider) –

• max_data_age (Optional[timedelta]) –

Methods

__init__(*args, decide_trades[, max_data_age])
check_accounts(universe, state)	Perform extra accounting checks on live trading startup.
check_position_triggers(clock, state, ...)	Check stop loss/take profit for positions.
get_image_and_dark_image(figure, width, height)	Renders the figure as a PNG image and a dark theme PNG image.
get_large_images(large_figure)	Gets the png image of the figure and the dark theme png image.
get_small_images(small_figure)	Gets the png image of the figure and the dark theme png image.
is_progress_report_needed()	Do we log the strategy steps to logger?
on_clock(clock, executor_universe, ...)	Run one strategy tick.
on_data_signal()
pretick_check(ts, universe)	Check the data looks more or less sane.
refresh_visualisations(state, universe)	Update the visualisations in the run state.
repair_state(state)	Repair unclean state issues.
report_after_execution(clock, universe, ...)
report_after_sync_and_revaluation(clock, ...)
report_before_execution(clock, universe, ...)
report_strategy_thinking(...)	Strategy admin helpers to understand a live running strategy.
revalue_portfolio(ts, state, valuation_method)	Revalue portfolio based on the data.
setup_routing(universe)	Setups routing state for this cycle.
sync_portfolio(strategy_cycle_ts, universe, ...)	Adjust portfolio balances based on the external events.
tick(strategy_cycle_timestamp, universe, ...)	Execute the core functions of a strategy.
update_strategy_thinking_image_data(...)	Update the strategy thinking image data with small, small dark theme, large, and large dark theme images.

__init__(*args, decide_trades, max_data_age=None, **kwargs)

Parameters:

• decide_trades (TradeDecider) –

• max_data_age (Optional[timedelta]) –

on_clock(clock, executor_universe, pricing_model, state, debug_details)

Run one strategy tick.

Parameters:

• clock (datetime) –

• executor_universe (TradingStrategyUniverse) –

• pricing_model (PricingModel) –

• state (State) –

• debug_details (dict) –

Return type:

List[TradeExecution]

pretick_check(ts, universe)

Check the data looks more or less sane.

Parameters:

• ts (datetime) –

• universe (TradingStrategyUniverse) –

refresh_visualisations(state, universe)

Update the visualisations in the run state.

This will update RunState.visualisations for the current strategy.

• In-process memory charts are served by webhook

• In-process memory charts are posted to Discord, etc.

• This is called on the startup, so that we have immediately good visualisation to show over the webhook when the web server boots up

• This is called after each strategy thinking cycle is complete.

The function is overridden by the child class for actual strategy runner specific implementation.

Parameters:

• state (State) –

• universe (TradingStrategyUniverse) –

update_strategy_thinking_image_data(small_image, large_image)

Update the strategy thinking image data with small, small dark theme, large, and large dark theme images.

Parameters:

• small_image – 512 x 512 image PNG

• large_image – 1920 x 1920 image SVG

get_small_images(small_figure)

Gets the png image of the figure and the dark theme png image. Images are 512 x 512.

get_large_images(large_figure)

Gets the png image of the figure and the dark theme png image. Images are 1024 x 1024.

get_image_and_dark_image(figure, width, height)

Renders the figure as a PNG image and a dark theme PNG image.

report_strategy_thinking(strategy_cycle_timestamp, cycle, universe, state, trades, debug_details)

Strategy admin helpers to understand a live running strategy.

• Post latest variables

• Draw the single pair strategy visualisation.

To manually test the visualisation see: manual-visualisation-test.py.

Parameters:

• strategy_cycle_timestamp (datetime) – real time lock

• cycle (int) – Cycle number

• universe (TradingStrategyUniverse) – Currnet trading universe

• trades (List[TradeExecution]) – Trades executed on this cycle

• state (State) – Current execution state

• debug_details (dict) – Dict of random debug stuff