def convert(cls, row, header):
"""
Converts the given `row` into a `Transaction`
Args:
row (list): The row as a list of values
header (list): Description of each row entry
Notes:
The list lengths of row and header have to equal.
Returns:
CryptoTransaction: The row converted into a CryptoTransaction
"""
assert len(row) == len(
header), 'Each column must have an entry in the header!'
assert isinstance(row, list), 'The row should be a list'
assert isinstance(header, list), 'The header should be list'
row_ = TradeHistoryParser.Row(row=row, header=header)
return Deposit(
timestamp=datetime.datetime.utcfromtimestamp(
row_[cls._COLUMN_APPLY_TIME] / 1E3),
address=row_[cls._COLUMN_ADDRESS],
txid=row_[cls._COLUMN_TXID],
coin=row_[cls._COLUMN_COIN],
amount=row_[cls._COLUMN_AMOUNT_TRANSFER],
fee=Fee(amount=0, currency=""),
status=row_[cls._COLUMN_STATUS],
exchange="Binance",
)
def convert(cls, row, header):
"""
Converts the given `row` into a `Transaction`
Args:
row (list): The row as a list of values
header (list): Description of each row entry
Notes:
The list lengths of row and header have to equal.
Returns:
CryptoTransaction: The row converted into a CryptoTransaction
"""
assert len(row) == len(header), 'Each column must have an entry in the header!'
assert isinstance(row, list), 'The row should be a list'
assert isinstance(header, list), 'The header should be list'
row_ = TradeHistoryParser.Row(row=row, header=header)
base, quota = row_[cls._COLUMN_BASE_ASSET], row_[cls._COLUMN_QUOTE_ASSET]
return CryptoTransaction(
datetime=datetime.datetime.utcfromtimestamp(row_[BinanceCrawlerParser._COLUMN_TIME] / 1000),
trading_pair=(Position(amount=row_[BinanceCrawlerParser._COLUMN_TOTAL_QUOTA], currency=quota),
Position(amount=row_[BinanceCrawlerParser._COLUMN_QUANTITY], currency=base)),
trading_type=row_[BinanceCrawlerParser._COLUMN_SIDE],
price=row_[BinanceCrawlerParser._COLUMN_PRICE],
fee=Fee(row_[BinanceCrawlerParser._COLUMN_FEE], row_[BinanceCrawlerParser._COLUMN_FEE_COIN]),
exchange="Binance"
)
def parse(self, csv_file):
csv_content = self._read_file(csv_file)
# the first line is a disclaimer and the second line is the title with the account email address
del csv_content[0:2]
# the third line is the header
header = csv_content[0]
del csv_content[0]
# check if each entry in the header is in our list
for c in header:
if c not in self._COLUMNS:
# otherwise, rise an exception that the parser is out of date
raise ParserOutdatedError(
'The column {} is unknown. The parser has to be updated!'.
format(c))
transactions = []
# parse all other rows
for row in csv_content:
row_ = TradeHistoryParser.Row(row=row, header=header)
if row_[self._COLUMN_TYPE] in ['buy', 'sell']:
# only process buy and sells
transactions.append(
CryptoTransaction(
datetime=row_[self._COLUMN_DATE],
trading_pair=(
Position(amount=row_[self._COLUMN_FIAT_AMOUNT],
currency=row_[self._COLUMN_FIAT]),
Position(amount=row_[self._COLUMN_CRYPTO_AMOUNT],
currency=row_[self._COLUMN_CRYPTO])),
trading_type=row_[self._COLUMN_TYPE],
# calculate the price based on the amount of fiat used to buy a certain amount of cryptocoins
price=row_[self._COLUMN_FIAT_AMOUNT] /
row_[self._COLUMN_CRYPTO_AMOUNT],
# we actually cannot calculate the fee using the data provided by bitpanda
fee=Fee(0, row_[self._COLUMN_FIAT]),
exchange="Bitpanda"))
return transactions
def parse(self, csv_file):
csv_content = self._read_file(csv_file)
# the first line is the header of the csv columns
header = csv_content[0]
del csv_content[0]
# check if each entry in the header is in our list
for c in header:
if c not in self._COLUMNS:
# otherwise, rise an exception that the parser is out of date
raise ParserOutdatedError(
'The column {} is unknown. The parser has to be updated!'.
format(c))
transactions = []
# parse all other rows
for row in csv_content:
row_ = TradeHistoryParser.Row(row=row, header=header)
base, quota = _market_to_trading_pair(row_[self._COLUMN_MARKET])
# old binance files had different way to store datetimes which will not be converted
# by the xlsx module by default. Thus, we have to check this manually.
if not isinstance(row_.get(self._COLUMN_DATE), datetime.datetime):
row_[self._COLUMN_DATE] = datetime.datetime.strptime(
row_[self._COLUMN_DATE], "%d.%m.%y %H:%M")
# convert the row to a transaction
transactions.append(
CryptoTransaction(
datetime=row_[self._COLUMN_DATE],
trading_pair=(Position(amount=row_[self._COLUMN_TOTAL],
currency=quota),
Position(
amount=row_[self._COLUMN_COIN_AMOUNT],
currency=base)),
trading_type=row_[self._COLUMN_TYPE],
price=row_[self._COLUMN_PRICE],
fee=Fee(row_[self._COLUMN_FEE],
row_[self._COLUMN_FEE_COIN]),
exchange="Binance"))
return transactions
def parse(self, file):
content = self._read_file(file)
# the first line is the header of the csv columns
header = content[0]
del content[0]
# check if each entry in the header is in our list
for c in header:
if c not in self._COLUMNS:
# otherwise, rise an exception that the parser is out of date
raise ParserOutdatedError(
'The column {} is unknown. The parser has to be updated!'.
format(c))
deposits = []
# parse all other rows
for row in content:
row_ = TradeHistoryParser.Row(row=row, header=header)
d = Deposit(
timestamp=row_[self._COLUMN_DATE],
address=row_[self._COLUMN_ADDRESS],
txid=row_[self._COLUMN_TXID],
coin=row_[self._COLUMN_COIN],
amount=row_[self._COLUMN_AMOUNT],
fee=Fee(amount=row_[self._COLUMN_TRANSACTIONFEE], currency=""),
status=row_[self._COLUMN_STATUS],
exchange="Binance",
)
deposits.append(d)
return deposits