def initialize_cache(currency_pair: str, tick_rate: str) -> None:
with Cache.configure(currency_pair, DATA_CACHE_GROUP):
cache = Cache.get()
source_mod_time = get_latest_source_modification(currency_pair)
if cache.cache_exists(
) and cache.get_data_mod_time() < source_mod_time:
print('Cache invalid. Clearing cache.')
cache.clear_all_keys()
def preprocess_signals(data: pd.DataFrame, args: Namespace) -> pd.DataFrame:
with Cache.configure(args.currency_pair, args.tick_rate):
signal_strategy = SignalStrategyFactory.get(
'ma', **signal_strat_argument_parser(args))
stopping_strat_argument_parser(args)
stop_strategy = StoppingStrategyFactory.get(
args.stopping_strat, **stopping_strat_argument_parser(args))
preprocessor = Preprocessor(signal_strategy, stop_strategy)
if args.no_cache:
return preprocessor.find_signals(data)
else:
return preprocessor.get_signals(data)
def simulate(data: pd.Series, signals: pd.DataFrame,
args: Namespace) -> (pd.DataFrame, dict):
with Cache.configure(args.currency_pair, args.tick_rate):
resolver = SignalResolver(data[args.quote], args.reverse)
if args.no_cache:
resolved_signals = resolver.resolve_signals(
signals, args.start, args.stop)
else:
resolved_signals = resolver.get_resolve_signals(
signals, args.start, args.stop)
analyzer = SignalAnalyzer(resolved_signals)
stats = analyzer.get_stats(args.start, args.stop)
return resolved_signals, stats
def load_data(currency_pair: str, tick_rate: str,
no_cache: bool) -> pd.DataFrame:
source_reader = HistDataReader()
loader = DataLoader(source_reader, tick_rate)
if no_cache:
print('Cache disabled.')
data, resampled_data = loader.load_from_sources(currency_pair)
else:
with Cache.configure(currency_pair, DATA_CACHE_GROUP):
data, resampled_data = loader.load(currency_pair)
if resampled_data is not None:
print_data_summary(resampled_data)
return data, resampled_data
else:
raise RuntimeError('Unable to load data')
