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Python client for Strava API with a focus on fluent data handling

Project description


Python client for Strava API with a focus on fluent data handling


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Before use

You need STRAVA_ACCESS_TOKEN with activity level permissions to make use of this package. Head to the strava-oauth library for help.

When the token is fetched it is handy to store it as a environment variable

export STRAVA_ACCESS_TOKEN=<strava_access_token>


from stravaio import StravaIO

# If the token is stored as an environment varible it is not neccessary
# to pass it as an input parameters
client = StravaIO(access_token=STRAVA_ACCESS_TOKEN)


# Get logged in athlete (e.g. the owner of the token)
# Returns a stravaio.Athlete object that wraps the
# [Strava DetailedAthlete](
# with few added data-handling methods
athlete = client.get_logged_in_athlete()

# Dump athlete into a JSON friendly dict (e.g. all datetimes are converted into iso8601)
athlete_dict = athlete.to_dict()

# Store athlete infor as a JSON locally (~/.stravadata/athlete_<id>.json)


# Returns a stravaio.Activity object that wraps the 
# [Strava DetailedActivity](
activity = client.get_activity_by_id(2033203247)

# Dump activity into a JSON friendly dict
activity_dict = activity.to_dict()

# Store activity locally (~/.stravadata/activities_<athlete_id>/activity_<id>.json)

# Get list of athletes activities since a given date (after) given in a human friendly format.
# Kudos to [Maya: Datetimes for Humans(TM)](
# Returns a list of [Strava SummaryActivity]( objects
list_activities = client.get_logged_in_athlete_activities(after='last week')

# Obvious use - store all activities locally
for a in list_activities:
    activity = client.get_activity_by_id(


# Returns a stravaio.Streams object that wraps the 
# [Strava StreamSet](
streams = client.get_activity_streams(2033203247)

# Dump streams into a JSON friendly dict
streams_dict = streams.to_dict()

# Store streams locally (~/.stravadata/streams_<athlete_id>/streams_<id>.json) as a .parquet file, that can be loaded later using the
# pandas.read_parquet()

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