72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
from typing import List, Optional
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from fastapi import APIRouter, Depends, HTTPException
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from app.api.deps import get_training_repository
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from app.core.database.repository import TrainingRepository
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from app.core.dto.training import ExerciseNameDTO
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from app.core.metrics import Record, summarize
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from app.schemas.exercises import (
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ExerciseProgressResponse,
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RecordResponse,
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SessionMetricsResponse,
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SessionRowResponse,
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)
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router = APIRouter()
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def record_response(record: Optional[Record]) -> Optional[RecordResponse]:
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return RecordResponse(value=record.value, date=record.date) if record else None
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@router.get("/", response_model=List[ExerciseNameDTO])
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async def list_exercise_names(
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repository: TrainingRepository = Depends(get_training_repository),
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):
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"""Distinct exercise names with the number of times each was done."""
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return await repository.list_exercise_names()
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@router.get("/progress/", response_model=ExerciseProgressResponse)
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async def exercise_progress(
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name: str,
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repository: TrainingRepository = Depends(get_training_repository),
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):
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"""The whole history of the exercise with progress metrics.
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The name is matched exactly, but case-insensitively: what was typed may differ in case.
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"""
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names_by_casefold = {
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item.name.casefold(): item.name
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for item in await repository.list_exercise_names()
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}
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exact_name = names_by_casefold.get(name.strip().casefold())
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if exact_name is None:
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raise HTTPException(status_code=404, detail="Exercise not found")
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progress = summarize(await repository.exercise_history(exact_name))
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return ExerciseProgressResponse(
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name=exact_name,
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weighted=progress.weighted,
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max_weight=progress.max_weight,
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best_primary=record_response(progress.best_primary),
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best_secondary=record_response(progress.best_secondary),
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first_primary=progress.first_primary,
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last_primary=progress.last_primary,
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primary_change=progress.primary_change,
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primary_change_percent=progress.primary_change_percent,
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rows=[
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SessionRowResponse(
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training_id=row.session.training_id,
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date=row.session.date,
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trainer=row.session.trainer,
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splitted_weight=row.session.splitted_weight,
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approaches=row.session.approaches,
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metrics=SessionMetricsResponse.model_validate(
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row.metrics, from_attributes=True
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),
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)
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for row in progress.rows
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],
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)
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