def index(request):
primary_bike_id = ''
bikes = request.user.gear_set.all()
for bike in bikes:
if bike.primary:
primary_bike_id = bike.strava_id
gear_id = request.POST.get('gear_id', primary_bike_id)
before = request.POST.get('before')
after = request.POST.get('after')
if before and after:
before = datetime.datetime.strptime(before, '%Y-%m-%d') + timedelta(hours=23, minutes=59, seconds=59)
after = datetime.datetime.strptime(after, '%Y-%m-%d') + timedelta(hours=23, minutes=59, seconds=59)
else:
before = datetime.datetime.today().replace(hour=23, minute=59, second=59, microsecond=0)
after = before - timedelta(days=7)
stra = strava()
filters = [
{'field': 'athlete.id', 'query': request.user.strava_id},
{'field': 'start_date', 'query': {'$lt': before, '$gte': after}},
{'field': 'gear_id', 'query': gear_id},
]
activities = stra.aggregate_activities_mongo(filters, {
'_id': None,
'distance': {'$sum': '$distance'},
'elapsed_time': {'$sum': '$moving_time'},
'elevation': {'$sum': '$total_elevation_gain'},
'average_speed': {'$avg': '$average_speed'},
'kilojoules': {'$sum': '$kilojoules'},
})
template_fields = {
'bikes': bikes,
'gear_id':gear_id,
'before':before.strftime('%Y-%m-%d'),
'after':after.strftime('%Y-%m-%d'),
'distance': unithelper.miles(unit('m')(0)),
'time': unithelper.hours(unit('s')(0)),
'elevation': unithelper.meters(unit('m')(0)),
'avg_speed': unithelper.mph(unit('m')(0)/unit('s')(1)),
'kjs': 0,
}
activity = None
for agg in activities:
if not activity:
activity = agg
if activity:
merge_dict = template_fields.copy()
merge_dict.update({
'distance': unithelper.miles(unit('m')(activity['distance'])),
'time': unithelper.hours(unit('s')(activity['elapsed_time'])),
'elevation': unithelper.meters(unit('m')(activity['elevation'])),
'avg_speed': unithelper.mph(unit('m')(activity['average_speed'])/unit('s')(1)),
'kjs': activity['kilojoules'],
})
template_fields = merge_dict
return render_to_response('strava/templates/strava_index.html', template_fields, context_instance=RequestContext(request))
def update_ride_from_activity(strava_activity, ride):
"""
Refactoring to just set ride properties from the Strava Activity object.
:param strava_activity: The Strava Activyt
:type strava_activity: stravalib.model.Activity
:param ride: The ride model object.
:type ride: Ride
"""
# Should apply to both new and preexisting rides ...
# If there are multiple instagram photos, then request syncing of non-primary photos too.
if strava_activity.photo_count > 1 and ride.photos_fetched is None:
log.debug("Scheduling non-primary photos sync for {!r}".format(ride))
ride.photos_fetched = False
ride.private = bool(strava_activity.private)
ride.name = strava_activity.name
ride.start_date = strava_activity.start_date_local
# We need to round so that "1.0" miles in strava is "1.0" miles when we convert back from meters.
ride.distance = round(float(unithelper.miles(strava_activity.distance)), 3)
ride.average_speed = float(unithelper.mph(strava_activity.average_speed))
ride.maximum_speed = float(unithelper.mph(strava_activity.max_speed))
ride.elapsed_time = timedelta_to_seconds(strava_activity.elapsed_time)
ride.moving_time = timedelta_to_seconds(strava_activity.moving_time)
location_parts = []
if strava_activity.location_city:
location_parts.append(strava_activity.location_city)
if strava_activity.location_state:
location_parts.append(strava_activity.location_state)
location_str = ', '.join(location_parts)
ride.location = location_str
ride.commute = strava_activity.commute
ride.trainer = strava_activity.trainer
ride.manual = strava_activity.manual
ride.elevation_gain = float(unithelper.feet(strava_activity.total_elevation_gain))
ride.timezone = str(strava_activity.timezone)
# # Short-circuit things that might result in more obscure db errors later.
if ride.elapsed_time is None:
raise DataEntryError("Activities cannot have null elapsed time.")
if ride.moving_time is None:
raise DataEntryError("Activities cannot have null moving time.")
if ride.distance is None:
raise DataEntryError("Activities cannot have null distance.")
log.debug("Writing ride for {athlete!r}: \"{ride!r}\" on {date}".format(athlete=ride.athlete.name,
ride=ride.name,
date=ride.start_date.strftime('%m/%d/%y')))
def test_speed_units(self):
a = model.Activity()
a.max_speed = 1000 # m/s
a.average_speed = 1000 # m/s
self.assertEquals(3600.0, float(uh.kph(a.max_speed)))
self.assertEquals(3600.0, float(uh.kph(a.average_speed)))
a.max_speed = uh.mph(1.0)
# print repr(a.max_speed)
self.assertAlmostEqual(1.61, float(uh.kph(a.max_speed)), places=2)
def to_mph(mps):
return float(unithelper.mph(act.average_speed))
if "latlng" in stream_filter:
sdf["lat"] = [a[0] for a in sdf.latlng]
sdf["lng"] = [a[1] for a in sdf.latlng]
del sdf["latlng"]
detail_fname = join(output_detail_dir, "{0}.json".format(act.id))
sdf.to_json(detail_fname)
# with open(join(output_detail_dir, "{0}.p".format(act.id)), "wb") as f:
# pickle.dump(sdf, f, 2)
print "{0} on {1:%d %b %Y} [kudos {2}]".format(act.name, act.start_date, act.kudos_count)
print "\tHR: {0}".format(act.average_heartrate)
print "\tDistance: {0}".format(unithelper.miles(act.distance))
print "\tSpeed: {0}".format(unithelper.mph(act.average_speed))
item = dict((k, func(getattr(act, k, None))) for k, func in save_fields.iteritems())
data.append(item)
start_dates.append(act.start_date)
df = pd.DataFrame(data=data, index=start_dates)
summary_fname = join(output_dir, "summary.json")
df.to_json(summary_fname)
# with open(join(output_dir, "summary.p"), "wb") as f:
# pickle.dump(df, f, 2)
df.to_csv(join(output_dir, "summary.csv"))
