In my server I\'m trying to read from a bunch of sqlite3 databases (sent from web clients) and process their data. The db files are in an S3 bucket and I have their url and
SQLite requires database files to be stored on disk (it uses various locks and paging techniques). An in-memory file will not suffice.
I'd create a temporary directory to hold the database file, write it to that directory, then connect to it. The directory gives SQLite the space to write commit logs as well.
To handle all this, a context manager might be helpful:
import os.path
import shutil
import sqlite3
import sys
import tempfile
from contextlib import contextmanager
@contextmanager
def sqlite_database(inmemory_data):
path = tempfile.mkdtemp()
with open(os.path.join(path, 'sqlite.db'), 'wb') as dbfile:
dbfile.write(inmemory_data)
conn = None
try:
conn = sqlite3.connect(os.path.join(path, 'sqlite.db'))
yield conn
finally:
if conn is not None:
conn.close()
try:
shutil.rmtree(path)
except IOError:
sys.stderr.write('Failed to clean up temp dir {}'.format(path))
and use that as:
with sqlite_database(yourdata) as connection:
# query the database
This writes in-memory data to disk, opens a connection, lets you use that connection, and afterwards cleans up after you.