dspace-statistics-api/database.py

from config import SQLITE_DB
import sqlite3

def database_connection_rw():
    connection = sqlite3.connect(SQLITE_DB)
    # allow iterating over row results by column key
    connection.row_factory = sqlite3.Row

    return connection

def database_connection_ro():
    connection = sqlite3.connect('file:{0}?mode=ro'.format(SQLITE_DB), uri=True)
    # allow iterating over row results by column key
    connection.row_factory = sqlite3.Row

    return connection

# vim: set sw=4 ts=4 expandtab:
app.py: Get item statistics from SQLite database It is much more efficient to cache view and download statistics in a database than to query Solr on demand (not to mention that it is not possible to page easily with facets in Solr). I decided to use SQLite because it is fast, native in Python 3, and doesn't require any extra steps during provisioning (assuming permissions are ok). 2018-09-23 15:47:00 +02:00			`from config import SQLITE_DB`
			`import sqlite3`

Split database access into RW and RO The indexer need to be able to write to the database, but the API only needs to read it. 2018-09-23 23:00:05 +02:00			`def database_connection_rw():`
app.py: Get item statistics from SQLite database It is much more efficient to cache view and download statistics in a database than to query Solr on demand (not to mention that it is not possible to page easily with facets in Solr). I decided to use SQLite because it is fast, native in Python 3, and doesn't require any extra steps during provisioning (assuming permissions are ok). 2018-09-23 15:47:00 +02:00			`connection = sqlite3.connect(SQLITE_DB)`
			`# allow iterating over row results by column key`
			`connection.row_factory = sqlite3.Row`

			`return connection`

Split database access into RW and RO The indexer need to be able to write to the database, but the API only needs to read it. 2018-09-23 23:00:05 +02:00			`def database_connection_ro():`
			`connection = sqlite3.connect('file:{0}?mode=ro'.format(SQLITE_DB), uri=True)`
			`# allow iterating over row results by column key`
			`connection.row_factory = sqlite3.Row`

			`return connection`

app.py: Get item statistics from SQLite database It is much more efficient to cache view and download statistics in a database than to query Solr on demand (not to mention that it is not possible to page easily with facets in Solr). I decided to use SQLite because it is fast, native in Python 3, and doesn't require any extra steps during provisioning (assuming permissions are ok). 2018-09-23 15:47:00 +02:00			`# vim: set sw=4 ts=4 expandtab:`