Refactor dashboard
This commit is contained in:
Peter Stockings
270
features/dashboard.py
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270
features/dashboard.py
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from utils import calculate_estimated_1rm, get_exercise_graph_model
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class Dashboard:
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def __init__(self, db_connection_method):
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self.execute = db_connection_method
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def get_people_ids(self):
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query = """
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SELECT person_id
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FROM Person
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ORDER BY person_id
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"""
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result = self.execute(query)
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# Extract and return the list of IDs
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return [row["person_id"] for row in result]
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def get_earliest_and_latest_workout_dates(self, selected_people_ids):
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# Create placeholders for the person IDs
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placeholders = ", ".join(["%s"] * len(selected_people_ids))
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sql_query = f"""
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SELECT
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MIN(w.start_date) AS earliest_date,
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MAX(w.start_date) AS latest_date
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FROM workout w
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INNER JOIN topset t ON w.workout_id = t.workout_id
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WHERE w.person_id IN ({placeholders});
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"""
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result = self.execute(sql_query, selected_people_ids)
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if not result or not result[0]:
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return None, None
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return result[0]['earliest_date'], result[0]['latest_date']
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def list_of_performed_exercise_ids(self, selected_people_ids, min_date, max_date):
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# Create placeholders for the person IDs
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placeholders = ", ".join(["%s"] * len(selected_people_ids))
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sql_query = f"""
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SELECT
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ARRAY_AGG(DISTINCT e.exercise_id) AS exercise_ids
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FROM workout w
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LEFT JOIN topset t ON w.workout_id = t.workout_id
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LEFT JOIN exercise e ON t.exercise_id = e.exercise_id
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WHERE w.start_date BETWEEN %s AND %s
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AND w.person_id IN ({placeholders})
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"""
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# Add min_date, max_date, and selected_people_ids to the parameters
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params = [min_date, max_date] + selected_people_ids
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result = self.execute(sql_query, params)
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if not result or not result[0]:
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return []
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return result[0]['exercise_ids']
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def get_exercises_with_selection(self, selected_people_ids, start_date, end_date, selected_exercise_ids):
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# Create placeholders for the person IDs
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placeholders = ", ".join(["%s"] * len(selected_people_ids))
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# SQL query to fetch all exercises performed by the selected people in the given time range
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sql_query = f"""
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SELECT DISTINCT
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e.exercise_id,
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e.name AS exercise_name
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FROM
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workout w
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JOIN
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topset t ON w.workout_id = t.workout_id
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JOIN
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exercise e ON t.exercise_id = e.exercise_id
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WHERE
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w.person_id IN ({placeholders})
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AND w.start_date BETWEEN %s AND %s
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ORDER BY
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e.name ASC;
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"""
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# Add parameters for the query
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params = selected_people_ids + [start_date, end_date]
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# Execute the query with parameters
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result = self.execute(sql_query, params)
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if not result:
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return [] # No exercises found in the given time range
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# Add the "selected" property to each exercise
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exercises = []
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for row in result:
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exercises.append({
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"id": row["exercise_id"],
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"name": row["exercise_name"],
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"selected": row["exercise_id"] in selected_exercise_ids
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})
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return exercises
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def get_people_with_selection(self, selected_people_ids):
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# SQL query to fetch all people
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sql_query = """
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SELECT DISTINCT
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p.person_id AS id,
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p.name AS name
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FROM
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person p
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ORDER BY
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p.name ASC;
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"""
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# Execute the query (no parameters required since we're fetching all people)
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result = self.execute(sql_query)
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if not result:
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return [] # No people found
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# Add the "selected" property to each person
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people = []
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for row in result:
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people.append({
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"id": row["id"],
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"name": row["name"],
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"selected": row["id"] in selected_people_ids
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})
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return people
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def generate_exercise_progress_graphs(self, person_id, exercise_id, exercise_name, exercise_sets):
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# Extract the required data
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estimated_1rm = [t["estimated_1rm"] for t in exercise_sets]
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repetitions = [t["reps"] for t in exercise_sets]
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weight = [t["weight"] for t in exercise_sets]
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start_dates = [t["workout_start_date"] for t in exercise_sets]
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messages = [
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f'{t["reps"]} x {t["weight"]}kg ({t["estimated_1rm"]}kg E1RM) on {t["workout_start_date"].strftime("%d %b %y")}'
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for t in exercise_sets
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]
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epoch = "All"
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# Check for valid data before generating the graph
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if exercise_name and estimated_1rm and repetitions and weight and start_dates and messages:
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exercise_progress = get_exercise_graph_model(
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title=exercise_name,
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estimated_1rm=estimated_1rm,
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repetitions=repetitions,
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weight=weight,
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start_dates=start_dates,
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messages=messages,
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epoch=epoch,
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person_id=person_id,
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exercise_id=exercise_id,
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)
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return exercise_progress
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def get(self, selected_people_ids, start_date, end_date, selected_exercise_ids):
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# Create placeholders for selected_people_ids and selected_exercise_ids
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people_placeholders = ", ".join(["%s"] * len(selected_people_ids))
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exercise_placeholders = ", ".join(["%s"] * len(selected_exercise_ids))
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# SQL query to fetch data
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sql_query = f"""
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SELECT
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p.person_id,
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p.name AS person_name,
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e.exercise_id,
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e.name AS exercise_name,
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t.topset_id,
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t.repetitions,
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t.weight,
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w.start_date AS workout_date,
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w.workout_id
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FROM
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person p
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JOIN
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workout w ON p.person_id = w.person_id
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JOIN
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topset t ON w.workout_id = t.workout_id
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JOIN
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exercise e ON t.exercise_id = e.exercise_id
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WHERE
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p.person_id IN ({people_placeholders})
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AND w.start_date BETWEEN %s AND %s
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AND e.exercise_id IN ({exercise_placeholders})
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ORDER BY
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p.person_id ASC, e.exercise_id ASC, t.topset_id DESC;
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"""
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# Add parameters for the query
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params = selected_people_ids + [start_date, end_date] + selected_exercise_ids
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# Execute the query
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result = self.execute(sql_query, params)
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# Handle empty result
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if not result:
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return {"people": []}
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# Organize data into the desired structure
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people_map = {}
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for row in result:
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# Person level
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person_id = row["person_id"]
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if person_id not in people_map:
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people_map[person_id] = {
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"id": person_id,
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"name": row["person_name"],
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"exercises": {}
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}
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# Exercise level
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exercise_id = row["exercise_id"]
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person_exercises = people_map[person_id]["exercises"]
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if exercise_id not in person_exercises:
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person_exercises[exercise_id] = {
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"id": exercise_id,
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"name": row["exercise_name"],
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"sets": []
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}
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# Set level
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person_exercises[exercise_id]["sets"].append({
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"id": row["topset_id"],
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"reps": row["repetitions"],
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"weight": row["weight"],
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"exercise_id": row["exercise_id"],
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"exercise_name": row["exercise_name"],
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"workout_id": row["workout_id"],
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"workout_start_date": row["workout_date"],
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"estimated_1rm": calculate_estimated_1rm(row["weight"], row["repetitions"])
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})
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# Convert the map into a list of people, generate graphs, and organize exercises
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people = []
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for person_id, person_data in people_map.items():
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exercises = []
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for exercise_id, exercise_data in person_data["exercises"].items():
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# Sort sets by timestamp (descending)
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exercise_data["sets"] = sorted(
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exercise_data["sets"], key=lambda x: x["id"], reverse=True
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)
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# Generate the graph for the exercise
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graph = self.generate_exercise_progress_graphs(
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person_id=person_id,
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exercise_id=exercise_id,
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exercise_name=exercise_data["name"],
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exercise_sets=exercise_data["sets"]
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)
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# Add the graph to the exercise data
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exercises.append({
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"id": exercise_data["id"],
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"name": exercise_data["name"],
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"graph": graph,
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"sets": exercise_data["sets"]
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})
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person_data["exercises"] = exercises
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people.append(person_data)
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return {"dashboard": people}
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