Not Delayed version of ETL

This is example matches the one in Delayed. But this one has no Dask.

!rm -rf transformed_data_eager

import os
import time
import random
import pandas as pd

os.mkdir("transformed_data_eager")  

def read_a_file(filename):
    time.sleep(random.random())
    df = pd.read_csv(f"data/{filename}", parse_dates=["timestamp"], index_col="timestamp")
    return df

def do_a_transformation(df):
    time.sleep(random.random())
    df["temperature_F"] = df["temperature"] * 9/5 + 32 
    return df
  
def write_it_back_out(df, filename):
    time.sleep(random.random())
    path = f"transformed_data_eager/{filename}"
    df.to_csv(path)
    return path

filenames = os.listdir("data")

outputs = []
for filename in filenames:
    df = read_a_file(filename)
    df = do_a_transformation(df)
    path = write_it_back_out(df, filename)
    outputs.append(path)

outputs

['transformed_data_eager/4.part',
 'transformed_data_eager/2.part',
 'transformed_data_eager/5.part',
 'transformed_data_eager/1.part',
 'transformed_data_eager/7.part',
 'transformed_data_eager/8.part',
 'transformed_data_eager/3.part',
 'transformed_data_eager/0.part',
 'transformed_data_eager/6.part']