def _resolve_pairs_list(self, config: Dict[str, Any]) -> None:
"""
Helper for download script.
Takes first found:
* -p (pairs argument)
* --pairs-file
* whitelist from config
"""
if "pairs" in config:
return
if "pairs_file" in self.args and self.args.pairs_file:
pairs_file = Path(self.args.pairs_file)
logger.info(f'Reading pairs file "{pairs_file}".')
# Download pairs from the pairs file if no config is specified
# or if pairs file is specified explicitely
if not pairs_file.exists():
raise OperationalException(f'No pairs file found with path "{pairs_file}".')
with pairs_file.open('r') as f:
config['pairs'] = json_load(f)
config['pairs'].sort()
return
if "config" in self.args and self.args.config:
logger.info("Using pairlist from configuration.")
config['pairs'] = config.get('exchange', {}).get('pair_whitelist')
else:
# Fall back to /dl_path/pairs.json
pairs_file = Path(config['datadir']) / config['exchange']['name'].lower() / "pairs.json"
if pairs_file.exists():
with pairs_file.open('r') as f:
config['pairs'] = json_load(f)
if 'pairs' in config:
config['pairs'].sort()
def get_latest_optimize_filename(directory: Union[Path, str],
variant: str) -> str:
"""
Get latest backtest export based on '.last_result.json'.
:param directory: Directory to search for last result
:param variant: 'backtest' or 'hyperopt' - the method to return
:return: string containing the filename of the latest backtest result
:raises: ValueError in the following cases:
* Directory does not exist
* `directory/.last_result.json` does not exist
* `directory/.last_result.json` has the wrong content
"""
if isinstance(directory, str):
directory = Path(directory)
if not directory.is_dir():
raise ValueError(f"Directory '{directory}' does not exist.")
filename = directory / LAST_BT_RESULT_FN
if not filename.is_file():
raise ValueError(
f"Directory '{directory}' does not seem to contain backtest statistics yet."
)
with filename.open() as file:
data = json_load(file)
if f'latest_{variant}' not in data:
raise ValueError(f"Invalid '{LAST_BT_RESULT_FN}' format.")
return data[f'latest_{variant}']
def load_backtest_data(filename) -> pd.DataFrame:
"""
Load backtest data file.
:param filename: pathlib.Path object, or string pointing to the file.
:return: a dataframe with the analysis results
"""
if isinstance(filename, str):
filename = Path(filename)
if not filename.is_file():
raise ValueError(f"File {filename} does not exist.")
with filename.open() as file:
data = json_load(file)
df = pd.DataFrame(data, columns=BT_DATA_COLUMNS)
df['open_time'] = pd.to_datetime(df['open_time'],
unit='s',
utc=True,
infer_datetime_format=True)
df['close_time'] = pd.to_datetime(df['close_time'],
unit='s',
utc=True,
infer_datetime_format=True)
df['profitabs'] = df['close_rate'] - df['open_rate']
df = df.sort_values("open_time").reset_index(drop=True)
return df
def load_backtest_metadata(filename: Union[Path, str]) -> Dict[str, Any]:
"""
Read metadata dictionary from backtest results file without reading and deserializing entire
file.
:param filename: path to backtest results file.
:return: metadata dict or None if metadata is not present.
"""
filename = get_backtest_metadata_filename(filename)
try:
with filename.open() as fp:
return json_load(fp)
except FileNotFoundError:
return {}
except Exception as e:
raise OperationalException(
'Unexpected error while loading backtest metadata.') from e
def load_backtest_stats(filename: Union[Path, str]) -> Dict[str, Any]:
"""
Load backtest statistics file.
:param filename: pathlib.Path object, or string pointing to the file.
:return: a dictionary containing the resulting file.
"""
if isinstance(filename, str):
filename = Path(filename)
if filename.is_dir():
filename = filename / get_latest_backtest_filename(filename)
if not filename.is_file():
raise ValueError(f"File {filename} does not exist.")
logger.info(f"Loading backtest result from {filename}")
with filename.open() as file:
data = json_load(file)
return data
def load_params_from_file(self) -> Dict:
filename_str = getattr(self, '__file__', '')
if not filename_str:
return {}
filename = Path(filename_str).with_suffix('.json')
if filename.is_file():
logger.info(f"Loading parameters from file {filename}")
try:
params = json_load(filename.open('r'))
if params.get('strategy_name') != self.__class__.__name__:
raise OperationalException(
'Invalid parameter file provided.')
return params
except ValueError:
logger.warning("Invalid parameter file format.")
return {}
logger.info("Found no parameter file.")
return {}
def load_cached_data_for_updating(
filename: Path, ticker_interval: str,
timerange: Optional[TimeRange]) -> Tuple[List[Any], Optional[int]]:
"""
Load cached data and choose what part of the data should be updated
"""
since_ms = None
# user sets timerange, so find the start time
if timerange:
if timerange.starttype == 'date':
since_ms = timerange.startts * 1000
elif timerange.stoptype == 'line':
num_minutes = timerange.stopts * timeframe_to_minutes(
ticker_interval)
since_ms = arrow.utcnow().shift(
minutes=num_minutes).timestamp * 1000
# read the cached file
if filename.is_file():
with open(filename, "rt") as file:
data = misc.json_load(file)
# remove the last item, could be incomplete candle
if data:
data.pop()
else:
data = []
if data:
if since_ms and since_ms < data[0][0]:
# Earlier data than existing data requested, redownload all
data = []
else:
# a part of the data was already downloaded, so download unexist data only
since_ms = data[-1][0] + 1
return (data, since_ms)
