Merge pull request #91 from NodeJSmith/feature/organization_and_more_best_practices

Feature/organization and more best practices

Author: NodeJSmith

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.12.1"
+current_version = "0.13.0"
 
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)(?:-(?P<rc_l>rc)(?P<rc>0|[1-9]\\d*))?"
 

.codespellrc

@@ -1,3 +1,3 @@
 [codespell]
-skip = ./build,./.venv/,./venv/,./.tox,.git,*.pdf,*.svg,versioneer.py,package-lock.json,_vendor,*.css,.codespellrc,poetry.lock
+skip = ./build,./.venv/,./venv/,./.tox,.git,*.pdf,*.svg,versioneer.py,package-lock.json,_vendor,*.css,.codespellrc,poetry.lock,uv.lock
 ignore-words-list = OT,Checkin,Tread,AllTime,allTime,tread

.readthedocs.yaml

@@ -14,5 +14,5 @@ build:
       # See https://github.com/readthedocs/readthedocs.org/pull/11152/
       - PATH="/home/docs/.local/bin:$PATH" && VIRTUAL_ENV=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --active --link-mode=copy
 
-mkdocs:
-  configuration: mkdocs.yml
+sphinx:
+  configuration: source/conf.py

cliff.toml

@@ -1,14 +1,14 @@
 from otf_api import Otf
-from otf_api.models.enums import ChallengeCategory, EquipmentType
+from otf_api.models.workouts import ChallengeCategory, EquipmentType
 
 
-def main():
+def main():  # noqa: D103, ANN201
     otf = Otf()
 
     # You can get challenges by equipment or by challenge category
 
     for et in EquipmentType:
-        benchmarks = otf.get_benchmarks_by_equipment(et)
+        benchmarks = otf.workouts.get_benchmarks_by_equipment(et)
         if not benchmarks:
             continue
         print(f"Equipment: {et.name}, Challenges: {len(benchmarks):,}")
@@ -63,7 +63,7 @@ def main():
             """
 
     for ct in ChallengeCategory:
-        benchmarks = otf.get_benchmarks_by_challenge_category(ct)
+        benchmarks = otf.workouts.get_benchmarks_by_challenge_category(ct)
         if not benchmarks:
             continue
         print(f"Challenge Name: {ct.name}, Challenges: {len(benchmarks):,}")

docs/index.md

@@ -1,10 +1,12 @@
 from datetime import time
 
+import pendulum
+
 from otf_api import Otf
-from otf_api.filters import ClassFilter, ClassType, DoW
+from otf_api.models.bookings import ClassFilter, ClassType, DoW
 
 
-def main():
+def main():  # noqa: D103, ANN201
     otf = Otf()
 
     # you can use the ClassFilter model to setup filters to only return the classes
@@ -25,7 +27,7 @@ def main():
 
     # the call to `get_classes` will return classes that match either of these filters
 
-    classes = otf.get_classes(filters=[cf, cf2])
+    classes = otf.bookings.get_classes(filters=[cf, cf2])
     print(classes[0].model_dump_json(indent=4))
 
     """
@@ -70,7 +72,7 @@ def main():
     # You can also get the classes that you have booked
     # You can pass a start_date, end_date, status, and limit as arguments
 
-    bookings = otf.get_bookings()
+    bookings = otf.bookings.get_bookings()
 
     print("Latest Upcoming Class:")
     print(bookings[-1].model_dump_json(indent=4))
@@ -129,7 +131,7 @@ def main():
     # If it is a past class that you attended, it will also include workout data - it is best
     # to use the `get_workout_from_boooking` method to get an actual Workout object, as this
     # combines data from multiple endpoints to give you the same data that is shown in the app
-    bookings_new = otf.get_bookings_new()
+    bookings_new = otf.bookings.get_bookings_new()
     print("Furthest Upcoming Class (New):")
     print(bookings_new[0].model_dump_json(indent=4))
     """
@@ -179,8 +181,9 @@ def main():
     """
 
     # you can get the workout data from a booking by calling `get_workout_from_booking`
+    bookings_new = otf.bookings.get_bookings_new(pendulum.today().subtract(months=1))
     booking = next(x for x in bookings_new if x.workout is not None)
-    workout = otf.get_workout_from_booking(booking)
+    workout = otf.workouts.get_workout_from_booking(booking)
     print(workout.model_dump_json(indent=4, exclude_none=True))
     """
     {

docs/usage.md

@@ -1,14 +1,14 @@
 from otf_api import Otf
 
 
-def main():
+def main():  # noqa: D103, ANN201
     otf = Otf()
 
     # if you need to figure out what studios are in an area, you can call `search_studios_by_geo`
     # which takes latitude, longitude, distance, page_index, and page_size as arguments
     # but you'll generally just need the first 3
     # same as with classes, you can leave it blank and get the studios within 50 miles of your home studio
-    studios_by_geo = otf.search_studios_by_geo()
+    studios_by_geo = otf.studios.search_studios_by_geo()
     print(studios_by_geo[0].model_dump_json(indent=4))
 
     """
@@ -36,7 +36,7 @@ def main():
     # if you need to get detailed information about a studio, you can call `get_studio_detail`
     # which takes a studio_uuid as an argument, but you can leave it blank to get details about your home studio
     # the return type is also StudioDetail, so the same format as the above
-    studio_detail = otf.get_studio_detail()
+    studio_detail = otf.studios.get_studio_detail()
     print(studio_detail.model_dump_json(indent=4))
 
     """
@@ -62,7 +62,7 @@ def main():
     """
 
     # you can get studio services, although I'm not sure if anyone would ever need this
-    services = otf.get_studio_services(studio_detail.studio_uuid)
+    services = otf.studios.get_studio_services(studio_detail.studio_uuid)
     for svc in services:
         print(svc.model_dump_json(indent=4))
 
@@ -85,21 +85,21 @@ def main():
 
     # you can get you favorite studios and add/remove studios from your favorites
     # this returns a list of StudioDetail, so the same format as the above
-    faves = otf.get_favorite_studios()
+    faves = otf.studios.get_favorite_studios()
     if faves:
         print(faves[0].model_dump_json(indent=4))
 
     # you can add a studio to your favorites by calling `add_favorite_studio` with a studio_uuid
-    otf.add_favorite_studio(otf.home_studio_uuid)
+    otf.studios.add_favorite_studio(otf.home_studio_uuid)
 
     # you can remove a studio from your favorites by calling `remove_favorite_studio` with a studio_uuid
-    otf.remove_favorite_studio(otf.home_studio_uuid)
+    otf.studios.remove_favorite_studio(otf.home_studio_uuid)
 
     # if you attempt to get a studio that doesn't exist, you'll a mostly empty studio detail object
     # with the studio uuid set to the provided value
     # this allows you to avoid dealing with None values + you can still group or sort by studio_uuid
 
-    invalid_studio = otf.get_studio_detail("2d07e9fc-cd14-4d5b-840e-09eb2b614c6c")
+    invalid_studio = otf.studios.get_studio_detail("2d07e9fc-cd14-4d5b-840e-09eb2b614c6c")
     assert invalid_studio.studio_uuid == "2d07e9fc-cd14-4d5b-840e-09eb2b614c6c"
     print(invalid_studio.model_dump_json(indent=4))
 

examples/challenge_tracker_examples.py

@@ -2,13 +2,14 @@
 
 from otf_api import Otf
 from otf_api.exceptions import AlreadyRatedError, ClassNotRatableError
-from otf_api.models.enums import StatsTime
+from otf_api.models.workouts import StatsTime
 
 
-def main():
+def main():  # noqa: D103, ANN201
     otf = Otf()
 
-    resp = otf.get_member_lifetime_stats_in_studio()
+    resp = otf.workouts.get_member_lifetime_stats_in_studio()
+    print("Lifetime in-studio stats:")
     print(resp.model_dump_json(indent=4))
 
     """
@@ -29,7 +30,8 @@ def main():
     }
     """
 
-    resp = otf.get_member_lifetime_stats_in_studio(StatsTime.ThisMonth)
+    resp = otf.workouts.get_member_lifetime_stats_in_studio(StatsTime.ThisMonth)
+    print("This month in-studio stats:")
     print(resp.model_dump_json(indent=4))
 
     """
@@ -53,7 +55,7 @@ def main():
     # you can get a list of workouts by calling `get_workouts`, which optionally takes a start and end date
     # the workout includes all of the details, including the performance summary, class, coach, studio, and rating data
     # from the new endpoint - the data matches what is shown in the OTF app after a workout
-    data_list = otf.get_workouts()
+    data_list = otf.workouts.get_workouts()
     print(data_list[0].model_dump_json(indent=4, exclude_none=True))
     """
     {
@@ -356,7 +358,7 @@ def main():
     with suppress(AlreadyRatedError, ClassNotRatableError):
         unrated_class = next((w for w in data_list if w.ratable and not w.class_rating), None)
         if unrated_class:
-            rated_workout = otf.rate_class_from_workout(unrated_class, 3, 3)
+            rated_workout = otf.workouts.rate_class_from_workout(unrated_class, 3, 3)
             print(rated_workout.model_dump_json(indent=4))
         else:
             print("No unrated classes found")