only return data['result'] from get_ticker_history

This commit is contained in:
gcarq 2017-11-05 23:47:59 +01:00
parent 472ce8566d
commit 60e651cb4c
15 changed files with 27 additions and 33 deletions

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@ -83,7 +83,7 @@ def analyze_ticker(pair: str) -> DataFrame:
"""
minimum_date = arrow.utcnow().shift(hours=-24)
data = get_ticker_history(pair, minimum_date)
dataframe = parse_ticker_dataframe(data['result'])
dataframe = parse_ticker_dataframe(data)
if dataframe.empty:
logger.warning('Empty dataframe for pair %s', pair)

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@ -96,7 +96,7 @@ def get_ticker(pair: str) -> dict:
return _API.get_ticker(pair)
def get_ticker_history(pair: str, minimum_date: arrow.Arrow):
def get_ticker_history(pair: str, minimum_date: arrow.Arrow) -> List:
return _API.get_ticker_history(pair, minimum_date)

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@ -105,7 +105,7 @@ class Bittrex(Exchange):
message=data['message'],
pair=pair,
minimum_date=minimum_date))
return data
return data['result']
def get_order(self, order_id: str) -> Dict:
data = _API.get_order(order_id)

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@ -85,27 +85,23 @@ class Exchange(ABC):
"""
@abstractmethod
def get_ticker_history(self, pair: str, minimum_date: Optional[arrow.Arrow] = None) -> dict:
def get_ticker_history(self, pair: str, minimum_date: Optional[arrow.Arrow] = None) -> List:
"""
Gets ticker history for given pair.
:param pair: Pair as str, format: BTC_ETC
:param minimum_date: Minimum date (optional)
:return: dict, format: {
'success': bool,
'message': str,
'result': [
{
'O': float, (Open)
'H': float, (High)
'L': float, (Low)
'C': float, (Close)
'V': float, (Volume)
'T': datetime, (Time)
'BV': float, (Base Volume)
},
...
]
}
:return: list, format: [
{
'O': float, (Open)
'H': float, (High)
'L': float, (Low)
'C': float, (Close)
'V': float, (Volume)
'T': datetime, (Time)
'BV': float, (Base Volume)
},
...
]
"""
def get_order(self, order_id: str) -> Dict:

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@ -11,9 +11,7 @@ from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, popula
@pytest.fixture
def result():
with open('freqtrade/tests/testdata/btc-eth.json') as data_file:
data = json.load(data_file)
return parse_ticker_dataframe(data['result'])
return parse_ticker_dataframe(json.load(data_file))
def test_dataframe_has_correct_columns(result):

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