def mocked_load_data(datadir, pairs=[], timeframe='0m',
timerange=None, *args, **kwargs):
hz = 0.1
base = 0.001
NEOBTC = [
[
tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
math.sin(x * hz) / 1000 + base,
123.45
] for x in range(0, 500)]
hz = 0.2
base = 0.002
LTCBTC = [
[
tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
math.sin(x * hz) / 1000 + base,
123.45
] for x in range(0, 500)]
pairdata = {'NEO/BTC': ohlcv_to_dataframe(NEOBTC, '1h', pair="NEO/BTC",
fill_missing=True),
'LTC/BTC': ohlcv_to_dataframe(LTCBTC, '1h', pair="LTC/BTC",
fill_missing=True)}
return pairdata
def test_ohlcv_drop_incomplete(caplog):
timeframe = '1d'
ticks = [
[
1559750400000, # 2019-06-04
8.794e-05, # open
8.948e-05, # high
8.794e-05, # low
8.88e-05, # close
2255, # volume (in quote currency)
],
[
1559836800000, # 2019-06-05
8.88e-05,
8.942e-05,
8.88e-05,
8.893e-05,
9911,
],
[
1559923200000, # 2019-06-06
8.891e-05,
8.893e-05,
8.875e-05,
8.877e-05,
2251
],
[
1560009600000, # 2019-06-07
8.877e-05,
8.883e-05,
8.895e-05,
8.817e-05,
123551
]
]
caplog.set_level(logging.DEBUG)
data = ohlcv_to_dataframe(ticks,
timeframe,
pair="UNITTEST/BTC",
fill_missing=False,
drop_incomplete=False)
assert len(data) == 4
assert not log_has("Dropping last candle", caplog)
# Drop last candle
data = ohlcv_to_dataframe(ticks,
timeframe,
pair="UNITTEST/BTC",
fill_missing=False,
drop_incomplete=True)
assert len(data) == 3
assert log_has("Dropping last candle", caplog)
def test_ohlcv_fill_up_missing_data2(caplog):
timeframe = '5m'
ticks = [
[
1511686200000, # 8:50:00
8.794e-05, # open
8.948e-05, # high
8.794e-05, # low
8.88e-05, # close
2255, # volume (in quote currency)
],
[
1511686500000, # 8:55:00
8.88e-05,
8.942e-05,
8.88e-05,
8.893e-05,
9911,
],
[
1511687100000, # 9:05:00
8.891e-05,
8.893e-05,
8.875e-05,
8.877e-05,
2251
],
[
1511687400000, # 9:10:00
8.877e-05,
8.883e-05,
8.895e-05,
8.817e-05,
123551
]
]
# Generate test-data without filling missing
data = ohlcv_to_dataframe(ticks,
timeframe,
pair="UNITTEST/BTC",
fill_missing=False)
assert len(data) == 3
caplog.set_level(logging.DEBUG)
data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC")
assert len(data2) == 4
# 3rd candle has been filled
row = data2.loc[2, :]
assert row['volume'] == 0
# close should match close of previous candle
assert row['close'] == data.loc[1, 'close']
assert row['open'] == row['close']
assert row['high'] == row['close']
assert row['low'] == row['close']
# Column names should not change
assert (data.columns == data2.columns).all()
assert log_has_re(
f"Missing data fillup for UNITTEST/BTC: before: "
f"{len(data)} - after: {len(data2)}.*", caplog)
def test_ohlcv_to_dataframe(ohlcv_history_list, caplog):
columns = ['date', 'open', 'high', 'low', 'close', 'volume']
caplog.set_level(logging.DEBUG)
# Test file with BV data
dataframe = ohlcv_to_dataframe(ohlcv_history_list, '5m', pair="UNITTEST/BTC",
fill_missing=True)
assert dataframe.columns.tolist() == columns
assert log_has('Converting candle (OHLCV) data to dataframe for pair UNITTEST/BTC.', caplog)
def test_load_cached_data_for_updating(mocker, testdatadir) -> None:
data_handler = get_datahandler(testdatadir, 'json')
test_data = None
test_filename = testdatadir.joinpath('UNITTEST_BTC-1m.json')
with open(test_filename, "rt") as file:
test_data = json.load(file)
test_data_df = ohlcv_to_dataframe(test_data,
'1m',
'UNITTEST/BTC',
fill_missing=False,
drop_incomplete=False)
# now = last cached item + 1 hour
now_ts = test_data[-1][0] / 1000 + 60 * 60
mocker.patch('arrow.utcnow', return_value=arrow.get(now_ts))
# timeframe starts earlier than the cached data
# should fully update data
timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m',
timerange, data_handler)
assert data.empty
assert start_ts == test_data[0][0] - 1000
# timeframe starts in the center of the cached data
# should return the chached data w/o the last item
timerange = TimeRange('date', None, test_data[0][0] / 1000 + 1, 0)
data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m',
timerange, data_handler)
assert_frame_equal(data, test_data_df.iloc[:-1])
assert test_data[-2][0] <= start_ts < test_data[-1][0]
# timeframe starts after the chached data
# should return the chached data w/o the last item
timerange = TimeRange('date', None, test_data[-1][0] / 1000 + 100, 0)
data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m',
timerange, data_handler)
assert_frame_equal(data, test_data_df.iloc[:-1])
assert test_data[-2][0] <= start_ts < test_data[-1][0]
# no datafile exist
# should return timestamp start time
timerange = TimeRange('date', None, now_ts - 10000, 0)
data, start_ts = _load_cached_data_for_updating('NONEXIST/BTC', '1m',
timerange, data_handler)
assert data.empty
assert start_ts == (now_ts - 10000) * 1000
# no datafile exist, no timeframe is set
# should return an empty array and None
data, start_ts = _load_cached_data_for_updating('NONEXIST/BTC', '1m', None,
data_handler)
assert data.empty
assert start_ts is None
def test_datesarray_to_datetimearray(ohlcv_history_list):
dataframes = ohlcv_to_dataframe(ohlcv_history_list, "5m", pair="UNITTEST/BTC",
fill_missing=True)
dates = datesarray_to_datetimearray(dataframes['date'])
assert isinstance(dates[0], datetime.datetime)
assert dates[0].year == 2017
assert dates[0].month == 11
assert dates[0].day == 26
assert dates[0].hour == 8
assert dates[0].minute == 50
date_len = len(dates)
assert date_len == 2
def refresh_latest_ohlcv(self, pair_list: List[Tuple[str, str]]) -> List[Tuple[str, List]]:
"""
Refresh in-memory OHLCV asynchronously and set `_klines` with the result
Loops asynchronously over pair_list and downloads all pairs async (semi-parallel).
Only used in the dataprovider.refresh() method.
:param pair_list: List of 2 element tuples containing pair, interval to refresh
:return: TODO: return value is only used in the tests, get rid of it
"""
logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list))
input_coroutines = []
# Gather coroutines to run
for pair, timeframe in set(pair_list):
if (not ((pair, timeframe) in self._klines)
or self._now_is_time_to_refresh(pair, timeframe)):
input_coroutines.append(self._async_get_candle_history(pair, timeframe))
else:
logger.debug(
"Using cached candle (OHLCV) data for pair %s, timeframe %s ...",
pair, timeframe
)
results = asyncio.get_event_loop().run_until_complete(
asyncio.gather(*input_coroutines, return_exceptions=True))
# handle caching
for res in results:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
pair = res[0]
timeframe = res[1]
ticks = res[2]
# keeping last candle time as last refreshed time of the pair
if ticks:
self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
# keeping parsed dataframe in cache
self._klines[(pair, timeframe)] = ohlcv_to_dataframe(
ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
return results
def _download_pair_history(datadir: Path,
exchange: Exchange,
pair: str, *,
timeframe: str = '5m',
timerange: Optional[TimeRange] = None,
data_handler: IDataHandler = None) -> bool:
"""
Download latest candles from the exchange for the pair and timeframe passed in parameters
The data is downloaded starting from the last correct data that
exists in a cache. If timerange starts earlier than the data in the cache,
the full data will be redownloaded
Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
:param pair: pair to download
:param timeframe: Timeframe (e.g "5m")
:param timerange: range of time to download
:return: bool with success state
"""
data_handler = get_datahandler(datadir, data_handler=data_handler)
try:
logger.info(
f'Download history data for pair: "{pair}", timeframe: {timeframe} '
f'and store in {datadir}.'
)
# data, since_ms = _load_cached_data_for_updating_old(datadir, pair, timeframe, timerange)
data, since_ms = _load_cached_data_for_updating(pair, timeframe, timerange,
data_handler=data_handler)
logger.debug("Current Start: %s",
f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
logger.debug("Current End: %s",
f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
# Default since_ms to 30 days if nothing is given
new_data = exchange.get_historic_ohlcv(pair=pair,
timeframe=timeframe,
since_ms=since_ms if since_ms else
int(arrow.utcnow().shift(
days=-30).float_timestamp) * 1000
)
# TODO: Maybe move parsing to exchange class (?)
new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
fill_missing=False, drop_incomplete=True)
if data.empty:
data = new_dataframe
else:
data = data.append(new_dataframe)
logger.debug("New Start: %s",
f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
logger.debug("New End: %s",
f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
data_handler.ohlcv_store(pair, timeframe, data=data)
return True
except Exception as e:
logger.error(
f'Failed to download history data for pair: "{pair}", timeframe: {timeframe}. '
f'Error: {e}'
)
return False
def _download_pair_history(pair: str, *,
datadir: Path,
exchange: Exchange,
timeframe: str = '5m',
process: str = '',
new_pairs_days: int = 30,
data_handler: IDataHandler = None,
timerange: Optional[TimeRange] = None,
candle_type: CandleType,
erase: bool = False,
) -> bool:
"""
Download latest candles from the exchange for the pair and timeframe passed in parameters
The data is downloaded starting from the last correct data that
exists in a cache. If timerange starts earlier than the data in the cache,
the full data will be redownloaded
Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
:param pair: pair to download
:param timeframe: Timeframe (e.g "5m")
:param timerange: range of time to download
:param candle_type: Any of the enum CandleType (must match trading mode!)
:param erase: Erase existing data
:return: bool with success state
"""
data_handler = get_datahandler(datadir, data_handler=data_handler)
try:
if erase:
if data_handler.ohlcv_purge(pair, timeframe, candle_type=candle_type):
logger.info(f'Deleting existing data for pair {pair}, {timeframe}, {candle_type}.')
logger.info(
f'Download history data for pair: "{pair}" ({process}), timeframe: {timeframe}, '
f'candle type: {candle_type} and store in {datadir}.'
)
data, since_ms = _load_cached_data_for_updating(pair, timeframe, timerange,
data_handler=data_handler,
candle_type=candle_type)
logger.debug("Current Start: %s",
f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
logger.debug("Current End: %s",
f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
# Default since_ms to 30 days if nothing is given
new_data = exchange.get_historic_ohlcv(pair=pair,
timeframe=timeframe,
since_ms=since_ms if since_ms else
arrow.utcnow().shift(
days=-new_pairs_days).int_timestamp * 1000,
is_new_pair=data.empty,
candle_type=candle_type,
)
# TODO: Maybe move parsing to exchange class (?)
new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
fill_missing=False, drop_incomplete=True)
if data.empty:
data = new_dataframe
else:
# Run cleaning again to ensure there were no duplicate candles
# Especially between existing and new data.
data = clean_ohlcv_dataframe(concat([data, new_dataframe], axis=0), timeframe, pair,
fill_missing=False, drop_incomplete=False)
logger.debug("New Start: %s",
f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
logger.debug("New End: %s",
f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
data_handler.ohlcv_store(pair, timeframe, data=data, candle_type=candle_type)
return True
except Exception:
logger.exception(
f'Failed to download history data for pair: "{pair}", timeframe: {timeframe}.'
)
return False
