Tx Range¶

class blocksci.TxRange¶

all¶: Returns a list of all of the objects in the range

base_size¶

For each item: The size of the non-segwit data in bytes

Type:	`numpy.ndarray[uint32]`

block¶

For each item: The block that this transaction was in

Type:	`blocksci.BlockRange`

block_height¶

For each item: The height of the block that this transaction was in

Type:	`numpy.ndarray[int32]`

block_time¶

For each item: The time that the block containing this transaction arrived

Type:	`numpy.ndarray[NumpyDatetime]`

change_output¶

For each item: If the change address in this transaction can be determined via the fresh address criteria, return it. Otherwise return None.

Type:	`blocksci.OutputOptionalRange`

fee¶

For each item: The fee paid by this transaction

Type:	`numpy.ndarray[int64]`

fee_per_byte(size_measure: str='virtual') → numpy.ndarray[int64]¶

For each item: The ratio of fee paid to size of this transaction. By default this uses veritual size, but passing total, base, weight, or virtual let’s you choose what measure of size you want

Return type:	`numpy.ndarray[int64]`

hash¶

For each item: The 256-bit hash of this transaction

Type:	`numpy.ndarray[S64]`

includes_output_of_type(address_type: blocksci.address_type) → numpy.ndarray[NumpyBool]¶

For each item: Check whether the given transaction includes an output of the given address type

Return type:	`numpy.ndarray[NumpyBool]`

including_output_of_type(address_type: blocksci.address_type) → blocksci.TxIterator¶

Returns a range containing only transactions including an output of the given address type

Return type:	`blocksci.TxIterator`

index¶

For each item: The internal index of this transaction

Type:	`numpy.ndarray[uint32]`

input_count¶

For each item: The number of inputs this transaction has

Type:	`numpy.ndarray[uint16]`

input_value¶

For each item: The sum of the value of all of the inputs

Type:	`numpy.ndarray[int64]`

inputs¶

For each item: A list of the inputs of the transaction

Type:	`blocksci.InputIterator`

ins¶

For each item: A list of the inputs of the transaction

Type:	`blocksci.InputIterator`

is_coinbase¶

For each item: Return’s true if this transaction is a Coinbase transaction

Type:	`numpy.ndarray[NumpyBool]`

locktime¶

For each item: The locktime of this transasction

Type:	`numpy.ndarray[uint32]`

observed_in_mempool¶

For each item: Returns whether this transaction was seen in the mempool by the recorder

Type:	`numpy.ndarray[NumpyBool]`

op_return¶

For each item: If this transaction included a null data address, return its output. Otherwise return None

Type:	`blocksci.OutputOptionalRange`

output_count¶

For each item: The number of outputs this transaction has

Type:	`numpy.ndarray[uint16]`

output_value¶

For each item: The sum of the value of all of the outputs

Type:	`numpy.ndarray[int64]`

outputs¶

For each item: A list of the outputs of the transaction

Type:	`blocksci.OutputIterator`

outs¶

For each item: A list of the outputs of the transaction

Type:	`blocksci.OutputIterator`

size_bytes¶

For each item: The size of this transaction in bytes

Type:	`numpy.ndarray[uint32]`

time_seen¶

For each item: If recorded by the mempool recorder, the time that this transaction was first seen by your node

Type:	`blocksci.DateOptionalRange`

total_size¶

For each item: The size all transaction data in bytes

Type:	`numpy.ndarray[uint32]`

virtual_size¶

For each item: The weight of the transaction divided by 4

Type:	`numpy.ndarray[uint32]`

weight¶

For each item: Three times the base size plus the total size

Type:	`numpy.ndarray[uint32]`