pymarket.transactions.transactions module

class pymarket.transactions.transactions.TransactionManager

Bases: object

An interaface to store and manage all transactions. Transactions are the minimal unit to represent the outcome of a market.

name_col

Name of the columns to use in the dataframe returned.

Type:list of str

n_trans

Number of transactions currently in the Manager

Type:int

trans

List of the actual transactions available

Type:list of tuples

add_transaction(bid, quantity, price, source, active)

Add a transaction to the transactions list

Parameters:

• bid (int) – Unique identifier of the bid
• quantity (float) – transacted quantity
• price (float) – transacted price
• source (int) – Identifier of the second party in the trasaction, -1 if there is no clear second party, such as in a double auction.
• active – True` if the bid is still active after the transaction.

Returns:

trans_id – id of the added transaction, -1 if fails

Return type:

int

Examples

>>> tm = pm.TransactionManager()
>>> tm.add_transaction(1, 0.5, 2.1, -1, False)
0
>>> tm.trans
[(1, 0.5, 2.1, -1, False)]
>>> tm.n_trans
1

get_df()

Returns the transaction dataframe

Returns:df – A pandas dataframe representing all the transactions stored. Return type:pd.DataFrame

Examples

>>> tm = pm.TransactionManager()
>>> tm.add_transaction(1, 0.5, 2.1, -1, False)
0
>>> tm.add_transaction(5, 0, 0, 3, True)
1
>>> tm.get_df()
   bid  quantity  price  source  active
0    1       0.5    2.1      -1   False
1    5       0.0    0.0       3    True

merge(other)

Merges two transaction managers with each other There are no checks on whether the new TransactionManger is consisten after the merge.

Parameters:other (TransactionManager) – A different transaction manager to merge with Returns:trans – A new transaction Manager with the transactions of the two. Return type:TransactionManager

Examples

>>> tm_1 = pm.TransactionManager()
>>> tm_1.add_transaction(1, 0.5, 2.1, -1, False)
0
>>> tm_2 = pm.TransactionManager()
>>> tm_2.add_transaction(5, 0, 0, 3, True)
0
>>> tm_3 = tm_1.merge(tm_2)
>>> tm_3.get_df()
   bid  quantity  price  source  active
0    1       0.5    2.1      -1   False
1    5       0.0    0.0       3    True

name_col = ['bid', 'quantity', 'price', 'source', 'active']