Storing last processed timestamp per fit metric instead of a single timestamp for all the metrics to prevent new data points from being masked from newer ones from other metrics
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1 changed files with 19 additions and 20 deletions
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@ -27,7 +27,7 @@ class GoogleFitBackend(Backend):
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_default_poll_seconds = 60
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_default_poll_seconds = 60
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_default_user_id = 'me'
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_default_user_id = 'me'
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_last_timestamp_varname = '_GOOGLE_FIT_LAST_TIMESTAMP'
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_last_timestamp_varname = '_GOOGLE_FIT_LAST_TIMESTAMP_'
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def __init__(self, data_sources, user_id=_default_user_id,
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def __init__(self, data_sources, user_id=_default_user_id,
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poll_seconds=_default_poll_seconds, *args, **kwargs):
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poll_seconds=_default_poll_seconds, *args, **kwargs):
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@ -51,26 +51,26 @@ class GoogleFitBackend(Backend):
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self.user_id = user_id
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self.user_id = user_id
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self.poll_seconds = poll_seconds
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self.poll_seconds = poll_seconds
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def run(self):
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def run(self):
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super().run()
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super().run()
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self.logger.info('Started Google Fit backend on data sources {}'.format(
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self.logger.info('Started Google Fit backend on data sources {}'.format(
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self.data_sources))
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self.data_sources))
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last_timestamp = float(get_plugin('variable').
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get(self._last_timestamp_varname).output.
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get(self._last_timestamp_varname) or 0)
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while not self.should_stop():
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while not self.should_stop():
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new_last_timestamp = last_timestamp
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self.logger.info('Scanning fit data source, last seen timestamp: {}'.
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format(str(datetime.datetime.fromtimestamp(last_timestamp))))
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try:
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try:
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for data_source in self.data_sources:
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for data_source in self.data_sources:
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data_source_last_timestamp = 0
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varname = self._last_timestamp_varname + data_source
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last_timestamp = float(get_plugin('variable').
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get(varname).output.get(varname) or 0)
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new_last_timestamp = last_timestamp
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self.logger.info('Processing new entries from data source {}, last timestamp: {}'.
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format(data_source,
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str(datetime.datetime.fromtimestamp(last_timestamp))))
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data_points = get_plugin('google.fit').get_data(
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data_points = get_plugin('google.fit').get_data(
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user_id=self.user_id, data_source_id=data_source).output
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user_id=self.user_id, data_source_id=data_source).output
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new_data_points = 0
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for dp in data_points:
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for dp in data_points:
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dp_time = dp.pop('startTime', 0)
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dp_time = dp.pop('startTime', 0)
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@ -89,22 +89,21 @@ class GoogleFitBackend(Backend):
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for k, v in dp.items()}
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for k, v in dp.items()}
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))
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))
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new_data_points += 1
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new_last_timestamp = max(dp_time, new_last_timestamp)
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new_last_timestamp = max(dp_time, new_last_timestamp)
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data_source_last_timestamp = max(dp_time, data_source_last_timestamp)
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self.logger.info('Got {} entries from data source {}, last timestamp: {}'.
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format(len(data_points), data_source,
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str(datetime.datetime.fromtimestamp(data_source_last_timestamp))))
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last_timestamp = new_last_timestamp
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last_timestamp = new_last_timestamp
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self.logger.info('Got {} new entries from data source {}, last timestamp: {}'.
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format(new_data_points, data_source,
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str(datetime.datetime.fromtimestamp(last_timestamp))))
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get_plugin('variable').set(**{
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get_plugin('variable').set(**{varname: last_timestamp})
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self._last_timestamp_varname: last_timestamp})
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except Exception as e:
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except Exception as e:
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self.logger.warning('Exception while processing Fit data')
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self.logger.warning('Exception while processing Fit data')
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self.logger.exception(e)
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self.logger.exception(e)
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continue
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continue
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time.sleep(self.poll_seconds)
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time.sleep(self.poll_seconds)
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