Merge branch 'develop' into test_coverage
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@@ -12,7 +12,20 @@ from freqtrade.analyze import populate_indicators, parse_ticker_dataframe
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logger = logging.getLogger(__name__)
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def load_tickerdata_file(datadir, pair, ticker_interval):
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def trim_tickerlist(tickerlist, timerange):
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(stype, start, stop) = timerange
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if stype == (None, 'line'):
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return tickerlist[stop:]
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elif stype == ('line', None):
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return tickerlist[0:start]
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elif stype == ('index', 'index'):
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return tickerlist[start:stop]
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else:
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return tickerlist
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def load_tickerdata_file(datadir, pair, ticker_interval,
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timerange=None):
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"""
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Load a pair from file,
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:return dict OR empty if unsuccesful
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@@ -30,11 +43,15 @@ def load_tickerdata_file(datadir, pair, ticker_interval):
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# Read the file, load the json
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with open(file) as tickerdata:
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pairdata = json.load(tickerdata)
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if timerange:
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pairdata = trim_tickerlist(pairdata, timerange)
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return pairdata
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def load_data(datadir: str, ticker_interval: int = 5, pairs: Optional[List[str]] = None,
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refresh_pairs: Optional[bool] = False) -> Dict[str, List]:
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def load_data(datadir: str, ticker_interval: int = 5,
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pairs: Optional[List[str]] = None,
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refresh_pairs: Optional[bool] = False,
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timerange=None) -> Dict[str, List]:
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"""
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Loads ticker history data for the given parameters
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:param ticker_interval: ticker interval in minutes
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@@ -51,16 +68,21 @@ def load_data(datadir: str, ticker_interval: int = 5, pairs: Optional[List[str]]
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download_pairs(datadir, _pairs)
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for pair in _pairs:
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval)
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
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if not pairdata:
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# download the tickerdata from exchange
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download_backtesting_testdata(datadir, pair=pair, interval=ticker_interval)
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# and retry reading the pair
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval)
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pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
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result[pair] = pairdata
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return result
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def tickerdata_to_dataframe(data):
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preprocessed = preprocess(data)
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return preprocessed
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def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]:
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"""Creates a dataframe and populates indicators for given ticker data"""
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return {pair: populate_indicators(parse_ticker_dataframe(pair_data))
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