forked from platypush/platypush
parent
e3c04d9316
commit
f9bd5b3abc
6 changed files with 218 additions and 191 deletions
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@ -10,7 +10,6 @@ Backends
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platypush/backend/button.flic.rst
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platypush/backend/button.flic.rst
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platypush/backend/camera.pi.rst
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platypush/backend/camera.pi.rst
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platypush/backend/chat.telegram.rst
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platypush/backend/chat.telegram.rst
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platypush/backend/google.fit.rst
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platypush/backend/google.pubsub.rst
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platypush/backend/google.pubsub.rst
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platypush/backend/gps.rst
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platypush/backend/gps.rst
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platypush/backend/http.rst
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platypush/backend/http.rst
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@ -1,6 +0,0 @@
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``google.fit``
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================================
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.. automodule:: platypush.backend.google.fit
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:members:
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@ -1,129 +0,0 @@
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import datetime
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import time
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from platypush.backend import Backend
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from platypush.context import get_plugin
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from platypush.message.event.google.fit import GoogleFitEvent
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from platypush.utils import camel_case_to_snake_case
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class GoogleFitBackend(Backend):
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"""
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This backend will listen for new Google Fit events (e.g. new weight/height
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measurements, new fitness activities etc.) on the specified data streams and
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fire an event upon new data.
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Requires:
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* The **google.fit** plugin
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(:class:`platypush.plugins.google.fit.GoogleFitPlugin`) enabled.
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"""
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_default_poll_seconds = 60
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_default_user_id = 'me'
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_last_timestamp_varname = '_GOOGLE_FIT_LAST_TIMESTAMP_'
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def __init__(
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self,
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data_sources,
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user_id=_default_user_id,
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poll_seconds=_default_poll_seconds,
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*args,
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**kwargs
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):
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"""
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:param data_sources: Google Fit data source IDs to monitor. You can
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get a list of the available data sources through the
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:meth:`platypush.plugins.google.fit.GoogleFitPlugin.get_data_sources`
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action
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:type data_sources: list[str]
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:param user_id: Google user ID to track (default: 'me')
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:type user_id: str
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:param poll_seconds: How often the backend will query the data sources
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for new data points (default: 60 seconds)
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:type poll_seconds: float
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"""
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super().__init__(*args, **kwargs)
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self.data_sources = data_sources
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self.user_id = user_id
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self.poll_seconds = poll_seconds
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def run(self):
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super().run()
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self.logger.info(
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'Started Google Fit backend on data sources {}'.format(self.data_sources)
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)
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while not self.should_stop():
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try:
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for data_source in self.data_sources:
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varname = self._last_timestamp_varname + data_source
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last_timestamp = float(
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get_plugin('variable').get(varname).output.get(varname) or 0
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)
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new_last_timestamp = last_timestamp
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self.logger.info(
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'Processing new entries from data source {}, last timestamp: {}'.format(
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data_source,
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str(datetime.datetime.fromtimestamp(last_timestamp)),
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)
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)
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data_points = (
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get_plugin('google.fit')
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.get_data(user_id=self.user_id, data_source_id=data_source)
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.output
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)
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new_data_points = 0
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for dp in data_points:
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dp_time = dp.pop('startTime', 0)
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if 'dataSourceId' in dp:
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del dp['dataSourceId']
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if dp_time > last_timestamp:
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self.bus.post(
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GoogleFitEvent(
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user_id=self.user_id,
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data_source_id=data_source,
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data_type=dp.pop('dataTypeName'),
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start_time=dp_time,
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end_time=dp.pop('endTime'),
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modified_time=dp.pop('modifiedTime'),
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values=dp.pop('values'),
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**{
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camel_case_to_snake_case(k): v
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for k, v in dp.items()
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}
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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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last_timestamp = new_last_timestamp
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self.logger.info(
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'Got {} new entries from data source {}, last timestamp: {}'.format(
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new_data_points,
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data_source,
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str(datetime.datetime.fromtimestamp(last_timestamp)),
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)
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)
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get_plugin('variable').set(**{varname: last_timestamp})
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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.exception(e)
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continue
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time.sleep(self.poll_seconds)
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# vim:sw=4:ts=4:et:
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@ -1,8 +0,0 @@
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manifest:
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events:
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platypush.message.event.google.fit.GoogleFitEvent: when a newdata point is received
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on one of the registered streams.
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install:
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pip: []
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package: platypush.backend.google.fit
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type: backend
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@ -1,8 +1,14 @@
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from platypush.plugins import action
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from datetime import datetime
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from typing import Generator, Iterable, Optional
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from platypush.context import Variable
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from platypush.message.event.google.fit import GoogleFitEvent
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from platypush.plugins import RunnablePlugin, action
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from platypush.plugins.google import GooglePlugin
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from platypush.plugins.google import GooglePlugin
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from platypush.utils import camel_case_to_snake_case
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class GoogleFitPlugin(GooglePlugin):
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class GoogleFitPlugin(GooglePlugin, RunnablePlugin):
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r"""
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r"""
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Google Fit plugin.
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Google Fit plugin.
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@ -63,6 +69,38 @@ class GoogleFitPlugin(GooglePlugin):
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script. Otherwise, if you're running the script on a desktop, a
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script. Otherwise, if you're running the script on a desktop, a
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browser window will be opened automatically.
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browser window will be opened automatically.
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When not configured with any ``data_sources``, the plugin won't start the
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event monitor and won't trigger any
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:class:`platypush.message.event.google.fit.GoogleFitEvent`. You can still
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fetch data points programmatically through the :meth:`.get_data` though.
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If you want to monitor data sources and fire events, then you need to
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explicitly define which health metrics you want to monitor through this
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integration.
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After starting the plugin, you can get a list of the available data sources
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by running the :meth:`.get_data_sources` action. The ``dataStreamId``
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fields are usually the ones you want to configure in your data sources.
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Unless you are interested in monitoring data points from specific devices,
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you may want to look for ``dataStreamId`` fields that match the
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``derived:*:merge*`` pattern. Some popular examples include:e.g.
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- ``derived:com.google.step_count.delta:merge_step_deltas``, to monitor
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the number of steps taken in a given time interval.
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- ``derived:com.google.active_minutes:com.google.android.gms:merge_active_minutes``,
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to monitor the number of active minutes in a given time interval.
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- ``derived:com.google.speed:com.google.android.gms:merge_speed``, to
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monitor the speed in a given time interval.
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- ``derived:com.google.calories.expended:com.google.android.gms:merge_calories_expended``,
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to monitor the number of calories burned in a given time interval.
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- ``derived:com.google.heart_rate.bpm:com.google.android.gms:merge_heart_rate_bpm``,
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to monitor the heart rate measured in a given time interval.
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"""
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"""
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scopes = [
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scopes = [
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@ -74,31 +112,78 @@ class GoogleFitPlugin(GooglePlugin):
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'https://www.googleapis.com/auth/fitness.location.read',
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'https://www.googleapis.com/auth/fitness.location.read',
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]
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]
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def __init__(self, user_id='me', *args, **kwargs):
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_default_user_id = 'me'
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_last_timestamp_varname = '_GOOGLE_FIT_LAST_TIMESTAMP_'
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def __init__(
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self,
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data_sources: Iterable[str] = (),
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user_id: str = _default_user_id,
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poll_interval: float = 120.0,
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**kwargs,
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):
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"""
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"""
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:param data_sources: Google Fit data source IDs to monitor - e.g.
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weight, heartbeat, steps etc. You can get a list of the available
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data sources on your account through the :meth:`.get_data_sources`
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action. If none is specified then no sources will be monitored.
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:param user_id: Default Google user_id (default: 'me', default
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:param user_id: Default Google user_id (default: 'me', default
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configured account user)
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configured account user)
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:type user_id: str or int
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:param poll_interval: How often the plugin should poll for new events
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(default: 120 seconds).
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"""
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"""
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super().__init__(scopes=self.scopes, *args, **kwargs)
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super().__init__(
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scopes=self.scopes,
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poll_interval=poll_interval,
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disable_monitor=not data_sources,
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**kwargs,
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)
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self.user_id = user_id
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self.user_id = user_id
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self.data_sources = data_sources
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def _last_timestamp_var(self, data_source: str) -> Variable:
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return Variable(self._last_timestamp_varname + data_source)
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def _get_last_timestamp(self, data_source: str) -> float:
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return float(self._last_timestamp_var(data_source).get() or 0)
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def _set_last_timestamp(self, data_source: str, timestamp: float):
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self._last_timestamp_var(data_source).set(timestamp)
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@action
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@action
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def get_data_sources(self, user_id=None):
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def get_data_sources(self, user_id: Optional[str] = None):
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"""
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"""
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Get the available data sources for the specified user_id
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Get the available data sources for the specified user.
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:param user_id: Target user ID (default: configured user).
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"""
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"""
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from googleapiclient.errors import HttpError
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service = self.get_service(service='fitness', version='v1')
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service = self.get_service(service='fitness', version='v1')
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try:
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sources = (
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sources = (
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service.users().dataSources().list(userId=user_id or self.user_id).execute()
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service.users() # pylint: disable=no-member
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.dataSources()
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.list(userId=user_id or self.user_id)
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.execute()
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)
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)
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except HttpError as e:
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err = f'Error while getting data sources: {e.status_code}: {e.reason}'
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self.logger.warning(err)
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raise AssertionError(err) from e
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return sources['dataSource']
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return sources['dataSource']
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@action
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@action
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def get_data(self, data_source_id, user_id=None, limit=None):
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def get_data(
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self,
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data_source_id: str,
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user_id: Optional[str] = None,
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limit: Optional[int] = 100,
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):
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"""
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"""
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Get raw data for the specified data_source_id
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Get raw data for the specified data_source_id
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:param user_id: Target user ID (default: configured user).
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:param user_id: Target user ID (default: configured user).
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:param limit: Maximum number of items to return.
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:param limit: Maximum number of items to return.
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"""
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"""
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return list(
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self._get_data(data_source_id=data_source_id, user_id=user_id, limit=limit)
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)
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def _get_timestamp(self, dp: dict, prefix: str) -> Optional[float]:
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basename = name = prefix + 'Time'
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t = dp.pop(name, None)
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if t is not None:
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return float(t)
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name = basename + 'Millis'
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t = dp.pop(name, None)
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if t is not None:
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return float(t) / 1e3
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name = basename + 'Nanos'
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t = dp.pop(name, None)
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if t is not None:
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return float(t) / 1e9
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def _get_data(
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self, data_source_id, user_id: Optional[str] = None, limit: Optional[int] = 100
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) -> Generator[dict, None, None]:
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from googleapiclient.errors import HttpError
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service = self.get_service(service='fitness', version='v1')
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service = self.get_service(service='fitness', version='v1')
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kwargs = {
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kwargs = {
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if limit:
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if limit:
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kwargs['limit'] = limit
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kwargs['limit'] = limit
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data_points = []
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try:
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for data_point in (
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for data_point in (
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service.users()
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service.users() # pylint: disable=no-member
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.dataSources()
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.dataSources()
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.dataPointChanges()
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.dataPointChanges()
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.list(**kwargs)
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.list(**kwargs)
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.execute()
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.execute()
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.get('insertedDataPoint', [])
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.get('insertedDataPoint', [])
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):
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):
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data_point['startTime'] = float(data_point.pop('startTimeNanos')) / 1e9
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data_point['startTime'] = self._get_timestamp(data_point, 'start')
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data_point['endTime'] = float(data_point.pop('endTimeNanos')) / 1e9
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data_point['endTime'] = self._get_timestamp(data_point, 'end')
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data_point['modifiedTime'] = (
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data_point['modifiedTime'] = self._get_timestamp(data_point, 'modified')
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float(data_point.pop('modifiedTimeMillis')) / 1e6
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)
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values = []
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values = []
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for value in data_point.pop('value'):
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for value in data_point.pop('value', data_point.pop('values', [])):
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if isinstance(value, (int, float, str)):
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values.append(value)
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continue
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if value.get('intVal') is not None:
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if value.get('intVal') is not None:
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value = value['intVal']
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value = value['intVal']
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elif value.get('fpVal') is not None:
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elif value.get('fpVal') is not None:
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@ -152,9 +263,68 @@ class GoogleFitPlugin(GooglePlugin):
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values.append(value)
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values.append(value)
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data_point['values'] = values
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data_point['values'] = values
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data_points.append(data_point)
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yield data_point
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except HttpError as e:
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err = f'Error while getting data points: {e.status_code}: {e.reason}'
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self.logger.warning(err)
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raise AssertionError(err) from e
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return data_points
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def _process_data_source(self, data_source: str):
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last_timestamp = new_last_timestamp = self._get_last_timestamp(data_source)
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self.logger.debug(
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||||||
|
'Processing new entries from data source %s, last timestamp: %s',
|
||||||
|
data_source,
|
||||||
|
datetime.fromtimestamp(last_timestamp).isoformat(),
|
||||||
|
)
|
||||||
|
|
||||||
|
new_data_points = 0
|
||||||
|
for dp in self._get_data(
|
||||||
|
user_id=self.user_id,
|
||||||
|
data_source_id=data_source,
|
||||||
|
limit=100,
|
||||||
|
):
|
||||||
|
dp_time = dp.pop('startTime', 0)
|
||||||
|
dp.pop('dataStreamId', None)
|
||||||
|
|
||||||
|
if dp_time > last_timestamp:
|
||||||
|
self._bus.post(
|
||||||
|
GoogleFitEvent(
|
||||||
|
user_id=self.user_id,
|
||||||
|
data_source_id=data_source,
|
||||||
|
data_type=dp.pop('dataTypeName'),
|
||||||
|
start_time=dp_time,
|
||||||
|
end_time=dp.pop('endTime'),
|
||||||
|
modified_time=dp.pop('modifiedTime'),
|
||||||
|
values=dp.pop('values'),
|
||||||
|
**{camel_case_to_snake_case(k): v for k, v in dp.items()},
|
||||||
|
)
|
||||||
|
)
|
||||||
|
|
||||||
|
new_data_points += 1
|
||||||
|
|
||||||
|
new_last_timestamp = max(dp_time, new_last_timestamp)
|
||||||
|
|
||||||
|
last_timestamp = new_last_timestamp
|
||||||
|
if new_data_points > 0:
|
||||||
|
self._set_last_timestamp(data_source, last_timestamp)
|
||||||
|
self.logger.info(
|
||||||
|
'Got %d new entries from data source %s, last timestamp: %s',
|
||||||
|
new_data_points,
|
||||||
|
data_source,
|
||||||
|
datetime.fromtimestamp(last_timestamp).isoformat(),
|
||||||
|
)
|
||||||
|
|
||||||
|
def main(self):
|
||||||
|
while not self.should_stop():
|
||||||
|
try:
|
||||||
|
for data_source in self.data_sources:
|
||||||
|
self._process_data_source(data_source)
|
||||||
|
except Exception as e:
|
||||||
|
self.logger.warning('Exception while processing Fit data')
|
||||||
|
self.logger.exception(e)
|
||||||
|
finally:
|
||||||
|
self.wait_stop(self.poll_interval)
|
||||||
|
|
||||||
|
|
||||||
# vim:sw=4:ts=4:et:
|
# vim:sw=4:ts=4:et:
|
||||||
|
|
|
@ -1,5 +1,6 @@
|
||||||
manifest:
|
manifest:
|
||||||
events: {}
|
events:
|
||||||
|
- platypush.message.event.google.fit.GoogleFitEvent
|
||||||
install:
|
install:
|
||||||
apk:
|
apk:
|
||||||
- py3-google-api-python-client
|
- py3-google-api-python-client
|
||||||
|
|
Loading…
Reference in a new issue