pylotoncycle 0.9.5

Module to access your Peloton workout data

PylotonCycle

Python Library for getting your Peloton workout data.

Table of contents

• General info
• Example Usage
• Testing

General info

As someone who wants to see my progress over time, I've been wanting a way to pull and play with my ride data. However, I'm also cautious about linking myself to too many external parties. As I've been playing with other libraries out there, I wanted something that was a bit more intuitive and would play nicer with the rest of my python code. So, PylotonCycle is born.

Example Usage

An example of how you may fetch performance data for a ride and easily manage credentials.

import pylotoncycle
import json
import os
import pprint
# Copy the sample.auth.json to auth.json and fill in your username and password
AUTH_FILE = "auth.json"
def save_dict(d, path=AUTH_FILE):
    with open(path, "w", encoding="utf-8") as f:
        json.dump(d, f, ensure_ascii=False, indent=4)

def load_dict(path=AUTH_FILE):
    if not os.path.exists(path):
        return {}
    with open(path, "r", encoding="utf-8") as f:
        return json.load(f)

auth = load_dict()
conn = pylotoncycle.PylotonCycle(username=auth.get('username'), password=auth.get('password'),
                    access_token=auth.get('access_token'),refresh_token=auth.get('refresh_token'))

workouts = conn.GetRecentWorkouts(5)
for w in workouts:
    workout_id = w['id']
    resp = conn.GetWorkoutMetricsById(workout_id)
    parsed_metrics = conn.ParseMetricsData(resp)
    pprint.pprint(parsed_metrics)

save_dict(conn.GetAuthInfo())

workouts is a list of workouts. ParseMetricsData converts supported performance graph payloads into a dictionary keyed by workout offset seconds. Cycling and other metrics-based payloads use the metrics, seconds_since_pedaling_start, and segment_list fields. Outdoor GPS payloads use location_data and segment_list.

An example of a list element

{'achievement_templates': [{'description': 'Awarded for working out with a '
                                           'friend.',
                            'id': '<some id hash>',
                            'image_url': 'https://s3.amazonaws.com/peloton-achievement-images-prod/702495cd985d4791bfd3d25f36e0df72',
                            'name': 'Dynamic Duo',
                            'slug': 'two_to_tango'},
                           {'description': 'Awarded for achieving Silver in '
                                           'the May Cycling Challenge.',
                            'id': '<some id hash>',
                            'image_url': 'https://s3.amazonaws.com/challenges-and-tiers-image-prod/6b772477ccd04f189fba16f2f877faad',
                            'name': 'May Cycling Challenge',
                            'slug': 'may_cycling_challenge_silver'}],
 'created': 1589642476,
 'created_at': 1589642476,
 'device_time_created_at': 1589617276,
 'device_type': 'home_bike_v1',
 'device_type_display_name': 'Bike',
 'end_time': 1589644336,
 'fitbit_id': None,
 'fitness_discipline': 'cycling',
 'ftp_info': {'ftp': 111,
              'ftp_source': 'ftp_workout_source',
              'ftp_workout_id': '<some id hash>'},
 'has_leaderboard_metrics': True,
 'has_pedaling_metrics': True,
 'id': '<some id hash>',
 'instructor_name': 'Matt Wilpers',
 'is_total_work_personal_record': False,
 'leaderboard_rank': 5015,
 'metrics_type': 'cycling',
 'name': 'Cycling Workout',
 'overall_summary': {'avg_cadence': 85.48,
                     'avg_heart_rate': 0.0,
                     'avg_power': 179.24,
                     'avg_resistance': 47.61,
                     'avg_speed': 20.39,
                     'cadence': 0.0,
                     'calories': 496.71,
                     'distance': 10.19,
                     'heart_rate': 0.0,
                     'id': '<some id hash>',
                     'instant': 1589644336,
                     'max_cadence': 122.0,
                     'max_heart_rate': 0.0,
                     'max_power': 255.8,
                     'max_resistance': 60.95,
                     'max_speed': 23.48,
                     'power': 0.0,
                     'resistance': 0.0,
                     'seconds_since_pedaling_start': 0,
                     'speed': 0.0,
                     'total_work': 322417.21,
                     'workout_id': '<some id hash>'},
 'peloton_id': '<some id hash>',
 'platform': 'home_bike',
 'ride': {'captions': ['en-US'],
          'class_type_ids': ['<some id hash>'],
          'content_format': 'video',
          'content_provider': 'peloton',
          'description': 'Max out the effectiveness of your training with this '
                         'ride. Instructors will expertly guide you through '
                         'specific output ranges 1 through 7 to help you build '
                         'endurance, strength and speed.',
          'difficulty_estimate': 6.3779,
          'difficulty_level': None,
          'difficulty_rating_avg': 6.3779,
          'difficulty_rating_count': 17157,
          'duration': 1800,
          'equipment_ids': [],
          'equipment_tags': [],
          'excluded_platforms': [],
          'extra_images': [],
          'fitness_discipline': 'cycling',
          'fitness_discipline_display_name': 'Cycling',
          'has_closed_captions': True,
          'has_free_mode': False,
          'has_pedaling_metrics': True,
          'home_peloton_id': '<some id hash>',
          'id': '<some id hash>',
          'image_url': 'https://s3.amazonaws.com/peloton-ride-images/58aa8ebc7d51d09d6513e1a2fab53c4c62c076c6/img_1580922399_a5f1fd0e3a2e48d38ecdd6a3d874820f.png',
          'instructor_id': '<some id hash>',
          'is_archived': True,
          'is_closed_caption_shown': True,
          'is_explicit': False,
          'is_live_in_studio_only': False,
          'language': 'english',
          'length': 1940,
          'live_stream_id': '<some id hash>-live',
          'live_stream_url': None,
          'location': 'nyc',
          'metrics': ['heart_rate', 'cadence', 'calories'],
          'origin_locale': 'en-US',
          'original_air_time': 1580919480,
          'overall_estimate': 0.9956,
          'overall_rating_avg': 0.9956,
          'overall_rating_count': 20737,
          'pedaling_duration': 1800,
          'pedaling_end_offset': 1860,
          'pedaling_start_offset': 60,
          'rating': 0,
          'ride_type_id': '<some id hash>',
          'ride_type_ids': ['<some id hash>'],
          'sample_vod_stream_url': None,
          'scheduled_start_time': 1580920200,
          'series_id': '<some id hash>',
          'sold_out': False,
          'studio_peloton_id': '<some id hash>',
          'title': '30 min Power Zone Endurance Ride',
          'total_in_progress_workouts': 0,
          'total_ratings': 0,
          'total_workouts': 32489,
          'vod_stream_id': '<some id hash>-vod',
          'vod_stream_url': None},
 'start_time': 1589642537,
 'status': 'COMPLETE',
 'strava_id': None,
 'timezone': 'America/Los_Angeles',
 'title': None,
 'total_leaderboard_users': 31240,
 'total_work': 322417.21,
 'user_id': '<some id hash>',
 'workout_type': 'class'}

Install

This package is available via pip install.

pip install pylotoncycle

Testing

Run the local unit tests with:

python3 -m unittest discover -s examples/tests -p 'test_*.py'

Run the formatter check used by CI with:

python3 -m black --check .

To smoke test against the real Peloton API, set credentials in your environment and run the CSV export example:

export PELOTON_USERNAME='your_username_or_email'
export PELOTON_PASSWORD='your_password'

python3 examples/workouts_to_csv.py \
  --path /tmp/pyloton-smoke \
  --timezone America/Los_Angeles

The command should create /tmp/pyloton-smoke/workouts.csv and print the number of CSV rows downloaded.

To test a TestPyPI snapshot, install the specific dev version from TestPyPI before running the smoke test:

python3 -m venv /tmp/pylotoncycle-smoke
/tmp/pylotoncycle-smoke/bin/python -m pip install --upgrade pip
/tmp/pylotoncycle-smoke/bin/python -m pip install \
  --index-url https://test.pypi.org/simple/ \
  --extra-index-url https://pypi.org/simple/ \
  pylotoncycle==0.9.5.dev1

Replace 0.9.5.dev1 with the version printed by the TestPyPI snapshot workflow.

TODO

• Lots more to cover. I want to find the right format for pulling in the ride performance data.
• Pull in GPS data for outdoor runs

Note to folks who want to contribute

I'm very happy to take pull requests and fix bugs that come up. But, this is definitely a side project for me.