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1_batch_transform_pipeline.ipynb

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code/evaluate.py

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import pandas as pd
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from ast import literal_eval
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from sklearn.ensemble import RandomForestClassifier
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from sklearn.metrics import (
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accuracy_score,
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precision_score,

code/inference.py

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import datetime
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import pandas as pd
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from io import StringIO
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## define the logger
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logging.basicConfig(format='[%(asctime)s] p%(process)s {%(filename)s:%(lineno)d} %(levelname)s - %(message)s', level=logging.INFO)
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logger = logging.getLogger(__name__)

code/presto_preprocess_for_batch_inference.py

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import pandas as pd
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from query import BATCH_INFERENCE_QUERY
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from presto_utils import fetch_data_from_presto
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## define the logger
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logging.basicConfig(format='[%(asctime)s] p%(process)s {%(filename)s:%(lineno)d} %(levelname)s - %(message)s', level=logging.INFO)
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logger = logging.getLogger(__name__)

code/presto_preprocess_for_training.py

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import pandas as pd
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from query import TRAINING_DATA_QUERY
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from presto_utils import fetch_data_from_presto
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## define the logger
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logging.basicConfig(format='[%(asctime)s] p%(process)s {%(filename)s:%(lineno)d} %(levelname)s - %(message)s', level=logging.INFO)
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logger = logging.getLogger(__name__)

code/presto_utils.py

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## define the logger
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logging.basicConfig(format='[%(asctime)s] p%(process)s {%(filename)s:%(lineno)d} %(levelname)s - %(message)s', level=logging.INFO)
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logger = logging.getLogger(__name__)
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## function to connect to the presto server
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def _connect_presto_server(args, username, password, catalog, schema):
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"""

code/requirements.txt

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## Install the presto python client to connect to the database and extract query
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presto-python-client==0.8.4
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presto-python-client==0.8.4

code/training.py

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import logging
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import argparse
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import subprocess
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import numpy as np
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import numpy as np
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import pandas as pd
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from typing import List
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from io import StringIO

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