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Python utility script to load large CSV data into sqlite in chunks
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# ----------------------------------------------------- | |
# python utility script to load large CSV data into sqlite in chunks | |
# dependencies: Pandas & sqlalchemy | |
# csv file used for testing : https://www.kaggle.com/sirpunch/meetups-data-from-meetupcom#members.csv | |
# ----------------------------------------------------- | |
# {Modification Log} | |
# ----------------------------------------------------- | |
# Author: Senthilnathan | |
# Maintainer: {maintainer} | |
# Created At: 12/14/2019 | |
# Last Modified: 12/14/2019 | |
# Status: production | |
# ----------------------------------------------------- | |
import pandas as pd | |
from sqlalchemy import create_engine | |
import datetime as dt | |
# variables (Start) | |
dbname='meetup' | |
tname='members' | |
encoding='ISO-8859-1' | |
csv_database = create_engine('sqlite:///{}.db'.format(dbname)) | |
start = dt.datetime.now() | |
chunksize = 100000 | |
i = 0 | |
j = 1 | |
# variables (End) | |
try: | |
file = 'members.csv' # Change the path | |
for df in pd.read_csv(file, encoding=encoding, chunksize=chunksize, iterator=True): | |
df = df.rename(columns={c: c.replace(' ', '') for c in df.columns}) | |
df.index += j | |
i += 1 # chunk count | |
print('{} seconds: completed {} rows'.format((dt.datetime.now() - start).seconds, i * chunksize)) | |
df.to_sql(tname, csv_database, if_exists='append') | |
j = df.index[-1] + 1 | |
end = dt.datetime.now() | |
print('Finished importing ~{} rows into sqlite in {} seconds'.format(i * chunksize, (end - start).seconds)) | |
except Exception as e: | |
print('Exception during import - [{}]'.format(str(e))) |
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