def get_value_from_dict_or_string(data, is_time_frame=False):
if isinstance(data, dict):
if is_time_frame:
return TimeFrames(data["value"])
else:
return data["value"]
else:
if is_time_frame:
if data is None:
return get_default_time_frame()
else:
return TimeFrames(data)
else:
return data
def parse_time_frames(time_frames_string_list):
result_list = []
for time_frame_string in time_frames_string_list:
try:
result_list.append(TimeFrames(time_frame_string))
except ValueError:
get_logger(TimeFrameManager.__name__).error("No time frame available for: '{0}'. Available time "
"frames are: {1}. '{0}' time frame requirement "
"ignored.".
format(time_frame_string,
[t.value for t in TimeFrames]))
return result_list
def find_min_time_frame(time_frames, min_time_frame=None):
tf_list = time_frames
if time_frames and isinstance(next(iter(time_frames)), TimeFrames):
tf_list = [t.value for t in time_frames]
min_index = 0
if min_time_frame:
min_index = TimeFrameManager.TimeFramesRank.index(min_time_frame)
# TimeFramesRank is the ordered list of timeframes
for index, tf in enumerate(TimeFrameManager.TimeFramesRank):
tf_val = tf.value
if index >= min_index and tf_val in tf_list:
try:
return TimeFrames(tf_val)
except ValueError:
pass
return min_time_frame
def __init__(self):
super().__init__()
self.time_frame = TimeFrames(self.get_specific_config()[STRATEGIES_REQUIRED_TIME_FRAME][0])
def init_config_time_frame_for_tests(config):
result = []
for time_frame in config[CONFIG_TIME_FRAME]:
result.append(TimeFrames(time_frame))
config[CONFIG_TIME_FRAME] = result
def _convert_time_frame(str_time_frame):
return TimeFrames(str_time_frame)