124 lines
3.5 KiB
Python
124 lines
3.5 KiB
Python
"""
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Various tool function for Freqtrade and scripts
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"""
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import gzip
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import logging
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import re
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from datetime import datetime
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from pathlib import Path
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from typing.io import IO
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import numpy as np
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import rapidjson
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logger = logging.getLogger(__name__)
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def shorten_date(_date: str) -> str:
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"""
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Trim the date so it fits on small screens
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"""
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new_date = re.sub('seconds?', 'sec', _date)
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new_date = re.sub('minutes?', 'min', new_date)
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new_date = re.sub('hours?', 'h', new_date)
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new_date = re.sub('days?', 'd', new_date)
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new_date = re.sub('^an?', '1', new_date)
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return new_date
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############################################
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# Used by scripts #
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# Matplotlib doesn't support ::datetime64, #
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# so we need to convert it into ::datetime #
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############################################
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def datesarray_to_datetimearray(dates: np.ndarray) -> np.ndarray:
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"""
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Convert an pandas-array of timestamps into
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An numpy-array of datetimes
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:return: numpy-array of datetime
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"""
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return dates.dt.to_pydatetime()
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def file_dump_json(filename: Path, data, is_zip=False) -> None:
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"""
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Dump JSON data into a file
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:param filename: file to create
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:param data: JSON Data to save
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:return:
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"""
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logger.info(f'dumping json to "{filename}"')
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if is_zip:
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if filename.suffix != '.gz':
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filename = filename.with_suffix('.gz')
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with gzip.open(filename, 'w') as fp:
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rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE)
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else:
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with open(filename, 'w') as fp:
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rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE)
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logger.debug(f'done json to "{filename}"')
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def json_load(datafile: IO):
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"""
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load data with rapidjson
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Use this to have a consistent experience,
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sete number_mode to "NM_NATIVE" for greatest speed
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"""
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return rapidjson.load(datafile, number_mode=rapidjson.NM_NATIVE)
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def file_load_json(file):
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gzipfile = file.with_suffix(file.suffix + '.gz')
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# Try gzip file first, otherwise regular json file.
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if gzipfile.is_file():
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logger.debug('Loading ticker data from file %s', gzipfile)
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with gzip.open(gzipfile) as tickerdata:
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pairdata = json_load(tickerdata)
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elif file.is_file():
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logger.debug('Loading ticker data from file %s', file)
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with open(file) as tickerdata:
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pairdata = json_load(tickerdata)
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else:
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return None
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return pairdata
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def format_ms_time(date: int) -> str:
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"""
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convert MS date to readable format.
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: epoch-string in ms
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"""
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return datetime.fromtimestamp(date/1000.0).strftime('%Y-%m-%dT%H:%M:%S')
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def deep_merge_dicts(source, destination):
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"""
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Values from Source override destination, destination is returned (and modified!!)
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Sample:
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>>> a = { 'first' : { 'rows' : { 'pass' : 'dog', 'number' : '1' } } }
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>>> b = { 'first' : { 'rows' : { 'fail' : 'cat', 'number' : '5' } } }
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>>> merge(b, a) == { 'first' : { 'rows' : { 'pass' : 'dog', 'fail' : 'cat', 'number' : '5' } } }
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True
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"""
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for key, value in source.items():
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if isinstance(value, dict):
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# get node or create one
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node = destination.setdefault(key, {})
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deep_merge_dicts(value, node)
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else:
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destination[key] = value
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return destination
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def round_dict(d, n):
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"""
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Rounds float values in the dict to n digits after the decimal point.
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"""
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return {k: (round(v, n) if isinstance(v, float) else v) for k, v in d.items()}
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