Quick look into Strava Data

In [115]:

    

%matplotlib inline
import matplotlib.pyplot as plt

from stravalib import Client, unithelper


    

In [12]:

    

client = Client()
# Register for an app here https://www.strava.com/settings/api
# You'll get your client_id there and then you can update 'your_client_id' here
authorize_url = client.authorization_url(client_id='your_client_id', redirect_uri='http://localhost:8282/authorized')
authorize_url

# If you navigate to the authorize_url, it will try and redirect to the redirect_uri; the code will be a url parameter.


    

    
Out[12]:





u'https://www.strava.com/oauth/authorize?approval_prompt=auto&redirect_uri=http%3A%2F%2Flocalhost%3A8282%2Fauthorized&response_type=code&client_id=12480'

In [14]:

    

# Your client_secret is also in the https://www.strava.com/settings/api page
access_token = client.exchange_code_for_token(client_id='your_client_id', client_secret='your_client_secret', code='your_code')


    

In [17]:

    

client.access_token = access_token


    

In [90]:

    

activities = [(activity.start_date, unithelper.kilometers(activity.distance)) 
              for activity in client.get_activities() if activity.type=='Run']


    

In [91]:

    

activities


    

    
Out[91]:





[(datetime.datetime(2016, 7, 11, 14, 4, 6, tzinfo=<UTC>),
  Quantity(5.645899999999999, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 25, 13, 44, 6, tzinfo=<UTC>),
  Quantity(17.7926, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 22, 14, 7, 57, tzinfo=<UTC>),
  Quantity(10.583200000000001, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 20, 12, 38, 11, tzinfo=<UTC>),
  Quantity(8.329799999999999, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 18, 12, 4, 6, tzinfo=<UTC>),
  Quantity(21.4738, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 16, 14, 34, 23, tzinfo=<UTC>),
  Quantity(6.3905, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 8, 11, 4, 14, tzinfo=<UTC>),
  Quantity(6.388, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 6, 10, 46, 19, tzinfo=<UTC>),
  Quantity(6.3106, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 4, 11, 50, 7, tzinfo=<UTC>),
  Quantity(21.2264, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 6, 1, 10, 43, 46, tzinfo=<UTC>),
  Quantity(6.5887, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 28, 11, 39, 30, tzinfo=<UTC>),
  Quantity(22.0942, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 25, 10, 43, 29, tzinfo=<UTC>),
  Quantity(6.810899999999999, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 23, 10, 35, 12, tzinfo=<UTC>),
  Quantity(6.6732, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 21, 11, 36, 15, tzinfo=<UTC>),
  Quantity(17.0265, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 17, 10, 30, 45, tzinfo=<UTC>),
  Quantity(6.6728000000000005, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 14, 12, 9, 12, tzinfo=<UTC>),
  Quantity(12.840399999999999, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 11, 10, 33, 6, tzinfo=<UTC>),
  Quantity(6.6188, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 9, 10, 33, 43, tzinfo=<UTC>),
  Quantity(6.6643, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 7, 12, 4, 30, tzinfo=<UTC>),
  Quantity(11.2114, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False))),
 (datetime.datetime(2016, 5, 2, 10, 36, 15, tzinfo=<UTC>),
  Quantity(6.5451999999999995, NamedComposedUnit('km', ComposedUnit([LeafUnit('m', True)], [], 1000), False)))]

In [93]:

    

plt.figure(figsize=(15, 15))
ax = plt.subplot(111)
plt.plot([x[0] for x in activities], [x[1] for x in activities], 'o-', label='runs')
plt.legend(loc=4)
plt.ylabel('Kilometers')
plt.xlabel('Date')
plt.grid()
plt.show()


    

In [116]:

    

weekday_activities = [a for a in client.get_activities() 
                      if a.start_date.today().weekday() < 5 and 
                      a.type=='Run' and 
                      unithelper.kilometers(a.distance).num < 8]


    

In [102]:

    

weekday_activities


    

    
Out[102]:





[<Activity id=637450085 name=u'Easy Run after an injury hiatus' resource_state=2>,
 <Activity id=611081984 name=u'Morning Run' resource_state=2>,
 <Activity id=602555813 name=u'Morning Run' resource_state=2>,
 <Activity id=600329979 name=u'Morning Run' resource_state=2>,
 <Activity id=594915696 name=u'Morning Run' resource_state=2>,
 <Activity id=587414156 name=u'Morning Run' resource_state=2>,
 <Activity id=585283560 name=u'Morning Run' resource_state=2>,
 <Activity id=578841889 name=u'Morning Run' resource_state=2>,
 <Activity id=572442770 name=u'Morning Run' resource_state=2>,
 <Activity id=570415486 name=u'Morning Run' resource_state=2>,
 <Activity id=562936311 name=u'Morning Run' resource_state=2>]

In [117]:

    

plt.figure(figsize=(15, 15))
ax = plt.subplot(111)
plt.plot([x.start_date for x in weekday_activities],
         [unithelper.kph(x.average_speed) for x in weekday_activities], 'o-', label='runs')
plt.legend(loc=4)
plt.ylabel('Kilometers per hour')
plt.xlabel('Date')
plt.grid()
plt.show()