Magic and Muscle：使用 Magic 和 DuckDB 进行 ETL，其中包含我的举重训练数据

docker pull mageai/mageai:latest

from mage_ai.io.file import fileioimport pandas as pdif 'data_loader' not in globals():    from mage_ai.data_preparation.decorators import data_loaderif 'test' not in globals():    from mage_ai.data_preparation.decorators import test@data_loaderdef load_data_from_file(*args, **kwargs):    filepath = 'default_repo/data_strong.csv'    df = pd.read_csv(filepath, sep=';')      return df@testdef test_output(output, *args) -> none:    assert output is not none, 'the output is undefined'`

import pandas as pdif 'transformer' not in globals():    from mage_ai.data_preparation.decorators import transformerif 'test' not in globals():    from mage_ai.data_preparation.decorators import testbody_part = {'squat (barbell)': 'pernas',    'bench press (barbell)': 'peitoral',    'deadlift (barbell)': 'costas',    'triceps pushdown (cable - straight bar)': 'bracos',    'bent over row (barbell)': 'costas',    'leg press': 'pernas',    'overhead press (barbell)': 'ombros',    'romanian deadlift (barbell)': 'costas',    'lat pulldown (machine)': 'costas',    'bench press (dumbbell)': 'peitoral',    'skullcrusher (dumbbell)': 'bracos',    'lying leg curl (machine)': 'pernas',    'hammer curl (dumbbell)': 'bracos',    'overhead press (dumbbell)': 'ombros',    'lateral raise (dumbbell)': 'ombros',    'chest press (machine)': 'peitoral',    'incline bench press (barbell)': 'peitoral',    'hip thrust (barbell)': 'pernas',    'agachamento pausado ': 'pernas',    'larsen press': 'peitoral',    'triceps dip': 'bracos',    'farmers march ': 'abdomen',    'lat pulldown (cable)': 'costas',    'face pull (cable)': 'ombros',    'stiff leg deadlift (barbell)': 'pernas',    'bulgarian split squat': 'pernas',    'front squat (barbell)': 'pernas',    'incline bench press (dumbbell)': 'peitoral',    'reverse fly (dumbbell)': 'ombros',    'push press': 'ombros',    'good morning (barbell)': 'costas',    'leg extension (machine)': 'pernas',    'standing calf raise (smith machine)': 'pernas',    'skullcrusher (barbell)': 'bracos',    'strict military press (barbell)': 'ombros',    'seated leg curl (machine)': 'pernas',    'bench press - close grip (barbell)': 'peitoral',    'hip adductor (machine)': 'pernas',    'deficit deadlift (barbell)': 'pernas',    'sumo deadlift (barbell)': 'costas',    'box squat (barbell)': 'pernas',    'seated row (cable)': 'costas',    'bicep curl (dumbbell)': 'bracos',    'spotto press': 'peitoral',    'incline chest fly (dumbbell)': 'peitoral',    'incline row (dumbbell)': 'costas'}@transformerdef transform(data, *args, **kwargs):    strong_data = data[['date', 'workout name', 'exercise name', 'weight', 'reps',    'workout duration']]    strong_data['body part'] = strong_data['exercise name'].map(body_part)    return strong_data@testdef test_output(output, *args) -> none:    assert output is not none, 'the output is undefined'

CREATE OR REPLACE TABLE powerlifting (    _date DATE,    workout_name STRING,    exercise_name STRING,    weight STRING,    reps STRING,    workout_duration STRING,    body_part STRING);INSERT INTO powerlifting SELECT * FROM {{ df_1 }};