automatic import of python-pylotoncycle

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+/pylotoncycle-0.6.0.tar.gz
diff --git a/python-pylotoncycle.spec b/python-pylotoncycle.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-pylotoncycle
+Version:	0.6.0
+Release:	1
+Summary:	Module to access your Peloton workout data
+License:	BSD
+URL:		https://github.com/justmedude/pylotoncycle
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/c6/db/0c32bc59cc5bf0ab5c3aa8fd7a078d1110cbfa6658ebbaeb967ba26d7918/pylotoncycle-0.6.0.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-requests
+
+%description
+# PylotonCycle
+Python Library for getting your Peloton workout data.
+
+## Table of contents
+* [General info](#general-info)
+* [Example Usage](#example-usage)
+
+## 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
+```
+import pylotoncycle
+
+username = 'your username or email address'
+password = 'your password'
+conn = pylotoncycle.PylotonCycle(username, password)
+workouts = conn.GetRecentWorkouts(5)
+```
+`workouts` is a list of workouts.
+
+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'}
+```
+
+An example of how you may fetch performance data for a ride
+```
+import pprint
+
+conn = pylotoncycle.PylotonCycle(username, password)
+workouts = conn.GetRecentWorkouts(5)
+for w in workouts:
+    workout_id = w['id']
+    resp = conn.GetWorkoutMetricsById(workout_id)
+    pprint.pprint(resp)
+
+```
+
+## Install
+This package is available via pip install.
+```
+pip install pylotoncycle
+```
+
+## 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.
+
+
+
+
+%package -n python3-pylotoncycle
+Summary:	Module to access your Peloton workout data
+Provides:	python-pylotoncycle
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-pylotoncycle
+# PylotonCycle
+Python Library for getting your Peloton workout data.
+
+## Table of contents
+* [General info](#general-info)
+* [Example Usage](#example-usage)
+
+## 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
+```
+import pylotoncycle
+
+username = 'your username or email address'
+password = 'your password'
+conn = pylotoncycle.PylotonCycle(username, password)
+workouts = conn.GetRecentWorkouts(5)
+```
+`workouts` is a list of workouts.
+
+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'}
+```
+
+An example of how you may fetch performance data for a ride
+```
+import pprint
+
+conn = pylotoncycle.PylotonCycle(username, password)
+workouts = conn.GetRecentWorkouts(5)
+for w in workouts:
+    workout_id = w['id']
+    resp = conn.GetWorkoutMetricsById(workout_id)
+    pprint.pprint(resp)
+
+```
+
+## Install
+This package is available via pip install.
+```
+pip install pylotoncycle
+```
+
+## 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.
+
+
+
+
+%package help
+Summary:	Development documents and examples for pylotoncycle
+Provides:	python3-pylotoncycle-doc
+%description help
+# PylotonCycle
+Python Library for getting your Peloton workout data.
+
+## Table of contents
+* [General info](#general-info)
+* [Example Usage](#example-usage)
+
+## 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
+```
+import pylotoncycle
+
+username = 'your username or email address'
+password = 'your password'
+conn = pylotoncycle.PylotonCycle(username, password)
+workouts = conn.GetRecentWorkouts(5)
+```
+`workouts` is a list of workouts.
+
+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'}
+```
+
+An example of how you may fetch performance data for a ride
+```
+import pprint
+
+conn = pylotoncycle.PylotonCycle(username, password)
+workouts = conn.GetRecentWorkouts(5)
+for w in workouts:
+    workout_id = w['id']
+    resp = conn.GetWorkoutMetricsById(workout_id)
+    pprint.pprint(resp)
+
+```
+
+## Install
+This package is available via pip install.
+```
+pip install pylotoncycle
+```
+
+## 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.
+
+
+
+
+%prep
+%autosetup -n pylotoncycle-0.6.0
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-pylotoncycle -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu Mar 09 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.0-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..d01bb52
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+e06f8bfc04450f9bd8d3af4a74d09f31  pylotoncycle-0.6.0.tar.gz