TradeExecution#

API documentation for tradeexecutor.state.trade.TradeExecution Python class in Trading Strategy framework.

class TradeExecution[source]#

Bases: object

Trade execution tracker.

  • One TradeExecution instance can only represent one swap

Each trade has a reserve currency that we use to trade the token (usually USDC).

Each trade can be

  • Buy: swap quote token -> base token

  • Sell: swap base token -> quote token

When doing a buy planned_reserve (fiat) is the input. This yields to executed_quantity of tokens that may be different from planned_quantity.

When doing a sell planned_quantity (token) is the input. This yields to executed_reserve of fiat that might be different from `planned_reserve.

Trade execution has four states

  • Planning: The execution object is prepared

  • Capital allocation and transaction creation: We move reserve from out portfolio to the trade in internal accounting

  • Transaction broadcast: trade cannot be cancelled in this point

  • Resolving the trade: We check the Ethereum transaction receipt to see how well we succeeded in the trade

There trade state is resolved based on the market variables (usually timestamps).

__init__(trade_id, position_id, trade_type, pair, opened_at, planned_quantity, planned_reserve, planned_price, reserve_currency, route=None, flags=None, planned_collateral_allocation=None, executed_collateral_allocation=None, planned_collateral_consumption=None, executed_collateral_consumption=None, reserve_currency_exchange_rate=None, planned_mid_price=None, planned_max_slippage=None, started_at=None, reserve_currency_allocated=None, broadcasted_at=None, executed_at=None, failed_at=None, executed_price=None, executed_quantity=None, executed_reserve=None, slippage_tolerance=None, fee_tier=None, lp_fees_paid=None, lp_fees_estimated=None, lp_fee_exchange_rate=None, native_token_price=None, retry_of=None, blockchain_transactions=<factory>, notes=None, repaired_at=None, repaired_trade_id=None, price_structure=None, post_execution_price_structure=None, cost_of_gas=None, portfolio_value_at_creation=None, leverage=None, planned_loan_update=None, executed_loan_update=None, closing=None, claimed_interest=None, paid_interest=None, exchange_name=None)#
Parameters:
Return type:

None

Methods

__init__(trade_id, position_id, trade_type, ...)

add_note(line)

Add a new-line separated note to the trade.

calculate_asset_deltas()

Get the expected amount fo token balance change in a wallet for this trade.

from_dict(kvs, *[, infer_missing])

from_json(s, *[, parse_float, parse_int, ...])

get_action_verb()

What is the action verb for this trade.

get_allocated_value()

get_claimed_interest()

How much US interest we have claimed in this trade.

get_cost_of_gas_usd()

Get the cost of gas for this trade in USD

get_credit_supply_reserve_change()

How many tokens this trade takes/adds to the reserves.

get_debug_dump()

Return class contents for logging.

get_decision_lag()

How long it took between strategy decision cycle starting and the strategy to make a decision.

get_equity_for_position()

Get the planned or executed quantity of the base token.

get_equity_for_reserve()

Get the planned or executed quantity of the quote token.

get_executed_value()

Estimate the USD value of this trade.

get_execution_lag()

How long it took between strategy decision cycle starting and the trade executed.

get_execution_sort_position()

When this trade should be executed.

get_expected_borrow_quantity_change()

How much this trade is impacting the borrowed quantity on a loan.

get_expected_collateral_quantity_change()

How much this trade is impacting the collateral quantity on a loan.

get_failed_transaction()

Get the transaction that failed this trade.

get_fees_paid()

Get total swap fees paid for trade.

get_human_description()

User friendly description for this trade

get_input_asset()

How we fund this trade.

get_output_asset()

What asset we receive out from this trade

get_planned_collateral_allocation()

get_planned_max_gas_price()

Get the maximum gas fee set to all transactions in this trade.

get_planned_reserve()

get_planned_value()

How much we plan to swap in this trade.

get_position_quantity()

Get the planned or executed quantity of the base token.

get_raw_planned_collateral_allocation()

Return the amount of allocated collteraal for the buy as raw token units.

get_raw_planned_quantity()

Return the amount of USD token for the buy as raw token units.

get_raw_planned_reserve()

Return the amount of USD token for the buy as raw token units.

get_repaid_interest()

How much USD interest payments this trade made.

get_reserve_currency_exchange_rate()

What was the reserve stablecoin exchange trade for this trade.

get_reserve_quantity()

Get the planned or executed quantity of the quote token.

get_revert_reason()

Get the transaction failure reason.

get_short_label()

Get action + token + trade id label.

get_sign()

Return the sign of the trade.

get_status()

Resolve the trade status.

get_value()

Get estimated or realised value of this trade.

get_volume()

Get the volume this trade generated.

is_accounted_for_equity()

Does this trade contribute towards the trading position equity.

is_accounting_correction()

This trade is an accounting correction.

is_buy()

Trade is considered spot buy or long if the planned quantity is positive.

is_credit_based()

This trade uses loans

is_credit_supply()

This is a credit supply trade.

is_executed()

Did this trade ever execute.

is_failed()

This trade was succcessfully completed.

is_leverage()

This is margined trade.

is_long()

This is margined long trade.

is_pending()

This trade was succcessfully completed.

is_planned()

This trade is still in planning, unallocated.

is_rebalance()

This trade is part of the normal strategy rebalance.

is_reduce()

This trade decreases the exposure of existing position.

is_repair_needed()

This trade needs repair, but is not repaired yet.

is_repair_trade()

This trade is fixes a frozen position and counters another trade.

is_repaired()

The automatic execution failed and this was later repaired.

is_sell()

Trade is considered sell or short if planned quantity is set negative.

is_short()

This is margined short trade.

is_spot()

This is a spot marget trade.

is_started()

This trade has a txid allocated.

is_stop_loss()

This trade is made to close stop loss on a position.

is_success()

This trade was succcessfully completed.

is_take_profit()

This trade is made to close take profit on a position.

is_test()

The trade was performed by perform-test-trade command.

is_triggered()

Was this trade based on a trigger signal.

is_unfinished()

We could not confirm this trade back from the blockchain after broadcasting.

mark_broadcasted(broadcasted_at[, rebroadcast])

Mark this trade to enter a brodcast phase.

mark_failed(failed_at)

mark_success(executed_at, executed_price, ...)

Mark trade success.

pretty_print()

Get diagnostics output for the trade.

schema(*[, infer_missing, only, exclude, ...])

set_blockchain_transactions(txs)

Set the physical transactions needed to perform this trade.

to_dict([encode_json])

to_json(*[, skipkeys, ensure_ascii, ...])

Attributes

broadcasted_at

When this trade entered mempool

claimed_interest

How much interest we have claimed from collateral for this position.

closing

Closing flag set on leveraged positions.

cost_of_gas

Cost of gas in terms of native token

exchange_name

The DEX name where this trade was executed.

executed_at

Timestamp of the block where the txid was first mined.

executed_collateral_allocation

Executed amount of collateral we spend for the debt token buyback

executed_collateral_consumption

Planned amount of collateral that we use to pay back the debt

executed_loan_update

New position loan parameters that become effective if this trade executes

executed_price

What was the actual price we received

executed_quantity

How much underlying token we traded, the actual realised amount.

executed_reserve

How much reserves we spend for this traded, the actual realised amount.

failed_at

The trade did not go through.

fee_tier

LP fee % recorded before the execution starts.

flags

Execution specific flags.

leverage

Leverage factor used when opening a position

lp_fee_exchange_rate

What is the conversation rate between quote token and US dollar used in LP fee conversion.

lp_fees_estimated

LP fees estimated in the USD

lp_fees_paid

LP fees paid, in terms of the amount in token

native_token_price

USD price per blockchain native currency unit, at the time of execution

notes

Human readable notes about this trade

paid_interest

How much interest this trade paid back on the debt.

planned_collateral_allocation

Planned amount of reserve currency that goes in or out to collateral.

planned_collateral_consumption

Planned amount of collateral that we use to pay back the debt

planned_loan_update

New position loan parameters that will become effective if this trade executes

planned_max_slippage

How much slippage we could initially tolerate, 0.01 is 1% slippage.

planned_mid_price

What we thought was the mid-price when we made the decision to tale this trade

portfolio_value_at_creation

The total porfolio value when this position was opened

post_execution_price_structure

TradePricing after the trade was executed.

price_structure

Related TradePricing instance

repaired_at

Trade was manually repaired

repaired_trade_id

Which is the trade that this trade is repairing.

reserve_currency_allocated

How much reserves was moved on this trade before execution

reserve_currency_exchange_rate

What is the reserve currency exchange rate used for this trade

retry_of

route

Taken route.

slippage_tolerance

Slippage tolerance for this trade.

started_at

When this trade was decided

strategy_cycle_at

Alias for opened_at.

trade_id

Trade id is unique among all trades in the same portfolio

position_id

Position id is unique among all trades in the same portfolio

trade_type

Spot, margin, lending, etc.

pair

Which trading pair this trade was for

opened_at

What was the strategy cycle timestamp for it was created.

planned_quantity

Positive for buy, negative for sell.

planned_reserve

How many reserve tokens (USD) we use in this trade

planned_price

What we thought the execution price for this trade would have been at the moment of strategy decision.

reserve_currency

Which reserve currency we are going to take.

blockchain_transactions

Associated blockchain transaction details.

trade_id: int#

Trade id is unique among all trades in the same portfolio

position_id: int#

Position id is unique among all trades in the same portfolio

trade_type: TradeType#

Spot, margin, lending, etc.

pair: TradingPairIdentifier#

Which trading pair this trade was for

opened_at: datetime.datetime | None#

What was the strategy cycle timestamp for it was created.

Naive UTC timestamp.

If the trade was executed by a take profit/stop loss trigger then this is the trigger timestamp (not wall clock time)

Not available if the trade was done outside the strategy execution (manual trades, accounting corrections).

See also

planned_quantity: Decimal#

Positive for buy, negative for sell.

  • Always accurately known for sells.

  • This can be zero for leveraged trades if the trade only adjusts the collateral.

planned_reserve: Decimal#

How many reserve tokens (USD) we use in this trade

For spot market

  • Always a position number (only the sign of planned_quantity changes between buy/sell)

  • For buys, Always known accurately for buys.

  • For sells, an estimation based on planned_price

Expressed in reserve_currency.

For leverage

  • Positive: we need to move our reserves to collateral to increase margin

  • Negative: position exposure is reduced, so we need less collateral and are getting collateral back

planned_price: float#

What we thought the execution price for this trade would have been at the moment of strategy decision.

This price includes any fees we pay for LPs, and should become executed_price if the execution is perfect.

For the market price see planned_mid_price.

reserve_currency: AssetIdentifier#

Which reserve currency we are going to take. Note that pair.quote might be different from reserve currency. This is because we can do three-way trades like BUSD -> BNB -> Cake when our routing model supports this.

route: str | None = None#

Taken route.

This is set by GenericRouting and allows match to trades to their taken routes after the trades have been executed.

This is e.g. used when analysing the execution success of trades.

The value of the string is one of the route names in py:class:GenericRouting. For single executer configuration, this value is left None.

flags: Optional[Set[TradeFlag]] = None#

Execution specific flags.

See TradeFlag for info. Not available on legacy data.

planned_collateral_allocation: Optional[Decimal] = None#

Planned amount of reserve currency that goes in or out to collateral.

  • Negative if collateral is released and added to the reserves

  • Positive if reserve currency is added as the collateral

This is different from planned_reserve, as any collateral adjustment is done after the trade has been executed, where as planned_reserve needs to be deposited before the trade is executed.

Must be None for spot positions.

executed_collateral_allocation: Optional[Decimal] = None#

Executed amount of collateral we spend for the debt token buyback

See planned_collateral_allocation for details.

planned_collateral_consumption: Optional[Decimal] = None#

Planned amount of collateral that we use to pay back the debt

  • Negative if collateral is spend to pay back the debt

  • Positive if reserve currency is added as the collateral

Must be None for spot positions.

executed_collateral_consumption: Optional[Decimal] = None#

Planned amount of collateral that we use to pay back the debt

#: planned_collateral_consumption for details.

reserve_currency_exchange_rate: Optional[float] = None#

What is the reserve currency exchange rate used for this trade

planned_mid_price: Optional[float] = None#

What we thought was the mid-price when we made the decision to tale this trade

This is the market price of the asset at the time of the trade decision.

planned_max_slippage: Optional[float] = None#

How much slippage we could initially tolerate, 0.01 is 1% slippage.

started_at: Optional[datetime] = None#

When this trade was decided

Wall clock time.

For backtested trades, this is always set to opened_at.

reserve_currency_allocated: Optional[Decimal] = None#

How much reserves was moved on this trade before execution

broadcasted_at: Optional[datetime] = None#

When this trade entered mempool

executed_at: Optional[datetime] = None#

Timestamp of the block where the txid was first mined.

For failed trades, this is not set until repaired, but instead we set failed_at.

failed_at: Optional[datetime] = None#

The trade did not go through. The timestamp when we figured this out.

executed_price: Optional[float] = None#

What was the actual price we received

This may be None for even if closed_at is set. This is because invalid trades (execution failed) may be marked close.

Set in tradeexecutor.state.State.mark_trade_success().

executed_quantity: Optional[Decimal] = None#

How much underlying token we traded, the actual realised amount. Positive for buy, negative for sell.

executed_reserve: Optional[Decimal] = None#

How much reserves we spend for this traded, the actual realised amount.

Always positive.

  • In the case of spot buy, this is how much reserve currency we spent to buy tokens

  • In the case of sell, this is how much reserve currency we will receive after the sell is closed

slippage_tolerance: Optional[float] = None#

Slippage tolerance for this trade.

Examples

  • 0: no slippage toleranc eallowed at all

  • 0.01: 1% slippage tolerance

  • 1: no slippage tolerance. MEV bots can steal all your money

We estimate executed_quantity = planned_quantity * slippage_tolerance. If any trade outcome exceeds the slippage tolerance the trade fails.

If you are usinga vault-based trading, slippage tolerance must be always set to calculate the asset delta.

See also calculate_asset_deltas().

fee_tier: Optional[float] = None#

LP fee % recorded before the execution starts.

Recorded as multiplier

Not available in the case this is ignored in backtesting or not supported by routers/trading pairs.

Used to calculate lp_fees_estimated.

Sourced from Uniswap v2 router or Uniswap v3 pool information.

lp_fees_paid: Optional[float] = None#

LP fees paid, in terms of the amount in token

The value is read back from the realised trade. LP fee is usually % of the trade. For Uniswap style exchanges fees are always taken from amount in token and directly passed to the LPs as the part of the swap, these is no separate fee information.

lp_fees_estimated: Optional[float] = None#

LP fees estimated in the USD

This is set before the execution and is mostly useful for backtesting.

lp_fee_exchange_rate: Optional[float] = None#

What is the conversation rate between quote token and US dollar used in LP fee conversion.

We set this exchange rate before the trade is started. Both lp_fees_estimated and lp_fees_paid need to use the same exchange rate, even though it would not be timestamp accurte.

native_token_price: Optional[float] = None#

USD price per blockchain native currency unit, at the time of execution

Used for converting tx fees and gas units to dollars

blockchain_transactions: List[BlockchainTransaction]#

Associated blockchain transaction details. Each trade contains 1 … n blockchain transactions. Typically this is approve() + swap() for Uniswap v2 or just swap() if we have the prior approval and approve does not need to be done for the hot wallet anymore.

notes: Optional[str] = None#

Human readable notes about this trade

Used to mark test trades from command line. Special case; not worth to display unless the field is filled in.

See add_note().

repaired_at: Optional[datetime] = None#

Trade was manually repaired

E.g. failed broadcast issue was fixed. Marked when the repair command is called.

repaired_trade_id: Optional[datetime] = None#

Which is the trade that this trade is repairing.

This trade makes a opposing trade to the trade referred here, making accounting match again and unfreezing the position.

For the repair trade

  • Strategy cycle is set to the original broken trade

  • Trade at repaired_trade_id may or may not have repaired_at set

  • This is used to mark position closed in accounting correction, although the trade itself does not carry any value

price_structure: Optional[TradePricing] = None#

Related TradePricing instance

TradePricing instance can refer to more than one swap

post_execution_price_structure: Optional[TradePricing] = None#

TradePricing after the trade was executed.

Collected by StrategyRunner after all trades have been executed.

Mostly interesting on failed trades, so we can diagnose why they might have failed due to slippage tolerance.

For backtesting, this data is filled in, but is not meaningful.

cost_of_gas: Optional[Decimal] = None#

Cost of gas in terms of native token

E.g. on Ethereum, this is the amount of ETH spent on gas

portfolio_value_at_creation: Optional[float] = None#

The total porfolio value when this position was opened

Used for risk metrics and other statistics.

leverage: Optional[float] = None#

Leverage factor used when opening a position

planned_loan_update: Optional[Loan] = None#

New position loan parameters that will become effective if this trade executes

If the trade execution fails then the loan parameters do not change

executed_loan_update: Optional[Loan] = None#

New position loan parameters that become effective if this trade executes

Because of slippage, etc. this can differ from planned_loan_update

closing: Optional[bool] = None#

Closing flag set on leveraged positions.

After this trade is executed, any position collateral should return to the cash reserves.

TODO: Remove. Moved to flags.

claimed_interest: Optional[Decimal] = None#

How much interest we have claimed from collateral for this position.

  • For interest bearing positions, how much of accrued interest was moved to reserves in this trade.

  • Concerns only collateral, not borrow

  • Borrow interest is closed in the final trade (trade size == position quantity == principal + interest)

This is the realised interest. Any accured interest must be realised by claiming it in some trade. Usually this is the trade that closes the position. See mark_trade_success for the logic.

Expressed in reserve tokens.

See also paid_interest

TODO This must be converted to planned_paid_interest / executed_paid_interest, because the actual amount may change after execution.

paid_interest: Optional[Decimal] = None#

How much interest this trade paid back on the debt.

Expressed in base token quantity.

This is used to mark the token debt in the last trade that closes a leveraged position.

See also claimed_interest

TODO This must be converted to planned_paid_interest / executed_paid_interest because the actual amount may change after execution.

exchange_name: Optional[str] = None#

The DEX name where this trade was executed.

A human-readable debugging hint. pair will contain the exchange address itself.

Optional, to be more used in the future versions.

property strategy_cycle_at: datetime#

Alias for opened_at.

  • Get the timestamp of the strategy cycle this trade is related to

  • If this trade is outside the strategy cycle, then it is wall clock time

get_action_verb()[source]#

What is the action verb for this trade.

Used to build human readable output.

See also

Return type:

str

get_short_label()[source]#

Get action + token + trade id label.

See also

Return type:

str

pretty_print()[source]#

Get diagnostics output for the trade.

Use Python pprint module.

Return type:

str

get_debug_dump()[source]#

Return class contents for logging.

Returns:

Indented JSON-like content

Return type:

str

get_human_description()[source]#

User friendly description for this trade

Return type:

str

get_reserve_currency_exchange_rate()[source]#

What was the reserve stablecoin exchange trade for this trade.

Returns:

1.0 if not set

Return type:

float

get_sign()[source]#

Return the sign of the trade.

  • 1 for buy

  • ``-1` for sell

Return type:

int

is_sell()[source]#

Trade is considered sell or short if planned quantity is set negative.

For some of the repaired trades the quantity is set to zero, just to create accounting reference when correcting the total balances. These trades are considered sell trades.

Return type:

bool

is_buy()[source]#

Trade is considered spot buy or long if the planned quantity is positive.

Return type:

bool

is_success()[source]#

This trade was succcessfully completed.

Return type:

bool

is_test()[source]#

The trade was performed by perform-test-trade command.

The trade and the position should not be counted in the statistics.

Return type:

bool

is_failed()[source]#

This trade was succcessfully completed.

Return type:

bool

is_pending()[source]#

This trade was succcessfully completed.

Return type:

bool

is_planned()[source]#

This trade is still in planning, unallocated.

Return type:

bool

is_started()[source]#

This trade has a txid allocated.

Return type:

bool

is_rebalance()[source]#

This trade is part of the normal strategy rebalance.

Return type:

bool

is_stop_loss()[source]#

This trade is made to close stop loss on a position.

Return type:

bool

is_take_profit()[source]#

This trade is made to close take profit on a position.

Return type:

bool

is_triggered()[source]#

Was this trade based on a trigger signal.

Return type:

bool

is_accounted_for_equity()[source]#

Does this trade contribute towards the trading position equity.

Failed trades are reverted. Only their fees account.

Return type:

bool

is_unfinished()[source]#

We could not confirm this trade back from the blockchain after broadcasting.

Return type:

bool

is_repaired()[source]#

The automatic execution failed and this was later repaired.

A manual repair command was issued and it manaeged to correctly repair this trade and underlying transactions.

See also is_repair_trade().

Return type:

bool

is_executed()[source]#

Did this trade ever execute.

Return type:

bool

is_repair_needed()[source]#

This trade needs repair, but is not repaired yet.

Return type:

bool

is_repair_trade()[source]#

This trade is fixes a frozen position and counters another trade.

Return type:

bool

is_accounting_correction()[source]#

This trade is an accounting correction.

This is a virtual trade made to have the

Return type:

bool

is_leverage()[source]#

This is margined trade.

Return type:

bool

is_credit_based()[source]#

This trade uses loans

Return type:

bool

is_credit_supply()[source]#

This is a credit supply trade.

Return type:

bool

is_spot()[source]#

This is a spot marget trade.

Return type:

bool

is_short()[source]#

This is margined short trade.

Return type:

bool

is_long()[source]#

This is margined long trade.

Return type:

bool

is_reduce()[source]#

This trade decreases the exposure of existing position.

After the trade is executed we have more cash in hand.

Return type:

bool

get_input_asset()[source]#

How we fund this trade.

Return type:

AssetIdentifier

get_output_asset()[source]#

What asset we receive out from this trade

Return type:

AssetIdentifier

get_status()[source]#

Resolve the trade status.

Based on the different state variables set on this item, figure out what is the best status for this trade.

Return type:

TradeStatus

get_executed_value()[source]#

Estimate the USD value of this trade.

Based on the

  • Exact quantity and exact crypto price we got executed at

  • USD exchange rate known at the time of the execution

Returns:

0.0 if the trade is not executed, or repaired without proper quantity

Return type:

float

get_planned_value()[source]#

How much we plan to swap in this trade.

Return type:

float

get_raw_planned_reserve()[source]#

Return the amount of USD token for the buy as raw token units.

Return type:

int

get_raw_planned_collateral_allocation()[source]#

Return the amount of allocated collteraal for the buy as raw token units.

Return type:

int

get_raw_planned_quantity()[source]#

Return the amount of USD token for the buy as raw token units.

Return type:

int

get_position_quantity()[source]#

Get the planned or executed quantity of the base token.

  • Positive for buy, negative for sell.

  • Return executed quantity if the trade has been done

  • Otherwise return planned quantity

Return type:

Decimal

get_reserve_quantity()[source]#

Get the planned or executed quantity of the quote token.

Negative for buy, positive for sell.

Return type:

Decimal

get_equity_for_position()[source]#

Get the planned or executed quantity of the base token.

Positive for buy, negative for sell.

Return type:

Decimal

get_equity_for_reserve()[source]#

Get the planned or executed quantity of the quote token.

Negative for buy, positive for sell.

Return type:

Decimal

get_value()[source]#

Get estimated or realised value of this trade.

Value is always a positive number.

Return type:

float

get_claimed_interest()[source]#

How much US interest we have claimed in this trade.

  • Interest can be only claimed on collateral

  • Borrow interest is paid back in the final trade

Return type:

float

get_repaid_interest()[source]#

How much USD interest payments this trade made.

  • Interest can be only claimed on collateral

  • Borrow interest is paid back in the final trade

Return type:

float

get_expected_borrow_quantity_change()[source]#

How much this trade is impacting the borrowed quantity on a loan.

Returns:

Planned value only

Return type:

Decimal

get_expected_collateral_quantity_change()[source]#

How much this trade is impacting the collateral quantity on a loan.

Returns:

Planned value only

Return type:

Decimal

get_fees_paid()[source]#

Get total swap fees paid for trade. Returns 0 instead of None

Returns:

total amount of lp fees (swap fees) paid in US dollars

Return type:

float

get_execution_sort_position()[source]#

When this trade should be executed.

  • Closing trades should go first

  • Selling trades should go first

We need to execute sells first because we need to have cash in hand to execute buys.

Returns:

Sortable int

Return type:

int

get_decision_lag()[source]#

How long it took between strategy decision cycle starting and the strategy to make a decision.

Return type:

timedelta

get_execution_lag()[source]#

How long it took between strategy decision cycle starting and the trade executed.

Return type:

Optional[timedelta]

get_failed_transaction()[source]#

Get the transaction that failed this trade.

Extract the EVM revert reason from the underlying transactions.

  • Each trade can consist of multiple transactions

  • Iterate transactions from the last to first and return the first failure reason

Return type:

Optional[BlockchainTransaction]

get_revert_reason()[source]#

Get the transaction failure reason.

Extract the EVM revert reason from the underlying transactions.

  • Each trade can consist of multiple transactions

  • Iterate transactions from the last to first and return the first failure reason

See also

Returns:

Cleaned revert reason message

Return type:

Optional[str]

get_volume()[source]#

Get the volume this trade generated.

If the trade is not yet executed, or failed to execute, assume zero volume.

Return type:

float

mark_broadcasted(broadcasted_at, rebroadcast=False)[source]#

Mark this trade to enter a brodcast phase.

  • Move the trade to the broadcasting phase

  • Aftr this, the execution model will attempt to perform blockchain txs and read the results back

Parameters:
  • broadcasted_at (datetime) – Wall-clock time

  • rebroadcast – Is this a second attempt to try to get the tx to the chain

mark_success(executed_at, executed_price, executed_quantity, executed_reserve, lp_fees, native_token_price, force=False, cost_of_gas=None, executed_collateral_consumption=None, executed_collateral_allocation=None)[source]#

Mark trade success.

  • Called by execution engine when we get a confirmation from the blockchain our blockchain txs where good

  • Called by repair to force trades to good state

Parameters:
  • force

    Do not check if we are in the correct previous state (broadcasted).

    Used in the accounting corrections.

  • cost_of_gas (Optional[float]) – How much we paid for gas for this trade in terms of native token e.g. Eth in Ethereum.

  • executed_at (datetime) –

  • executed_price (float) –

  • executed_quantity (Decimal) –

  • executed_reserve (Decimal) –

  • lp_fees (float) –

  • native_token_price (float) –

  • executed_collateral_consumption (Optional[Decimal]) –

  • executed_collateral_allocation (Optional[Decimal]) –

set_blockchain_transactions(txs)[source]#

Set the physical transactions needed to perform this trade.

Parameters:

txs (List[BlockchainTransaction]) –

get_planned_max_gas_price()[source]#

Get the maximum gas fee set to all transactions in this trade.

Return type:

int

calculate_asset_deltas()[source]#

Get the expected amount fo token balance change in a wallet for this trade.

Needed for vault based trading to work, as they run slippage tolerance checks on expectd inputs and outputs.

Each trade has minimum of two asset deltas

  • The token you spent to buu/sell (input)

  • The token you receive (output)

The output will always have slippage_tolerance applied. Input is passed as is.

Returns:

List of asset deltas [input, output]

Return type:

List[AssetDelta]

get_cost_of_gas_usd()[source]#

Get the cost of gas for this trade in USD

__init__(trade_id, position_id, trade_type, pair, opened_at, planned_quantity, planned_reserve, planned_price, reserve_currency, route=None, flags=None, planned_collateral_allocation=None, executed_collateral_allocation=None, planned_collateral_consumption=None, executed_collateral_consumption=None, reserve_currency_exchange_rate=None, planned_mid_price=None, planned_max_slippage=None, started_at=None, reserve_currency_allocated=None, broadcasted_at=None, executed_at=None, failed_at=None, executed_price=None, executed_quantity=None, executed_reserve=None, slippage_tolerance=None, fee_tier=None, lp_fees_paid=None, lp_fees_estimated=None, lp_fee_exchange_rate=None, native_token_price=None, retry_of=None, blockchain_transactions=<factory>, notes=None, repaired_at=None, repaired_trade_id=None, price_structure=None, post_execution_price_structure=None, cost_of_gas=None, portfolio_value_at_creation=None, leverage=None, planned_loan_update=None, executed_loan_update=None, closing=None, claimed_interest=None, paid_interest=None, exchange_name=None)#
Parameters:
Return type:

None

get_credit_supply_reserve_change()[source]#

How many tokens this trade takes/adds to the reserves.

  • Positive for consuming reserves and moving them to lending pool

  • Negative for removing lending collateral and returning them to the reservers

Only negative value warrants for action, because capital allocation for the credit supply is done when the transaction is prepared.

Returns:

None if not a credit supply trade

Return type:

decimal.Decimal | None

add_note(line)[source]#

Add a new-line separated note to the trade.

Do not remove any old notes.

Parameters:

line (str) –