resolve_pairs_based_on_ticker

API documentation for tradingstrategy.pair.resolve_pairs_based_on_ticker Python function.

resolve_pairs_based_on_ticker(df, chain_id=None, exchange_slug=None, pairs=None, sorting_criteria_by=('fee', 'buy_volume_all_time'), sorting_criteria_ascending=(True, False))

Resolve symbolic trading pairs to their internal integer primary key ids.

Uses pair database described DEXPair Pandas dataframe to resolve pairs to their integer ids on a single exchange.

Warning

For popular trading pairs, there will be multiple scam pairs with the same ticker name. In this case, one with the highest all-time buy volume is chosen.

Note

Pair ids are not stable and may change long term. Always resolve pair ids before a run.

Example:

Alternative Example:

Parameters:

• df (DataFrame) – DataFrame containing DEXPairs

• chain_id (Optional[ChainId]) –

  Blockchain the exchange is on.

  Set None if given part of HumanReadableTradingPairDescription.

• exchange_slug (Optional[str]) –

  Symbolic exchange name

  Set None if given part of HumanReadableTradingPairDescription.

• pairs (Union[set[tuple[tradingstrategy.chain.ChainId, str, str, str] | tuple[tradingstrategy.chain.ChainId, str, str, str, int]], Collection[Union[Tuple[ChainId, str | None, str, str, float], Tuple[ChainId, str | None, str, str]]]]) –

  List of trading pairs as (base token, quote token) tuples. Note that giving trading pair tokens in wrong order causes pairs not to be found. If any ticker does not match it is not included in the result set.

  See tradingstrategy.pair.HumanReadableTradingPairDescription.

• sorting_criteria_by (Tuple) – Resulting DataFrame sorting

• sorting_criteria_ascending (Tuple) – Resulting DataFrame sorting

Returns:

DataFrame with filtered pairs.

Warning: If you give a pair that is not found there is no error. Check that you get right amount of pairs out.

Return type:

DataFrame