dspace-statistics-api/dspace_statistics_api/config.py

import os

# Check if Solr connection information was provided in the environment
SOLR_SERVER = os.environ.get('SOLR_SERVER', 'http://localhost:8080/solr')

DATABASE_NAME = os.environ.get('DATABASE_NAME', 'dspacestatistics')
DATABASE_USER = os.environ.get('DATABASE_USER', 'dspacestatistics')
DATABASE_PASS = os.environ.get('DATABASE_PASS', 'dspacestatistics')
DATABASE_HOST = os.environ.get('DATABASE_HOST', 'localhost')
DATABASE_PORT = os.environ.get('DATABASE_PORT', '5432')

# vim: set sw=4 ts=4 expandtab:
Refactor configuration into separate module There is a good example of this in the Project Weekend GitHub profile. See: https://github.com/projectweekend/Falcon-PostgreSQL-API-Seed 2018-09-18 15:59:28 +02:00			`import os`

			`# Check if Solr connection information was provided in the environment`
			`SOLR_SERVER = os.environ.get('SOLR_SERVER', 'http://localhost:8080/solr')`
Add vim modeline to all Python files Uses four spaces for tab and shift widths, and turns on expansion of tabs to spaces. 2018-09-23 10:33:26 +02:00
Use PostgreSQL instead of SQLite I was very surprised how easy and fast and robust SQLite was, but in the end I realized that its UPSERT support only came in version 3.24 and both Ubuntu 16.04 and 18.04 have older versions than that! I did manage to install libsqlite3-0 from Ubuntu 18.04 cosmic on my xenial host, but that feels dirty. PostgreSQL has support for UPSERT since 9.5, not to mention the same nice LIMIT and OFFSET clauses. 2018-09-24 23:49:47 +02:00			`DATABASE_NAME = os.environ.get('DATABASE_NAME', 'dspacestatistics')`
			`DATABASE_USER = os.environ.get('DATABASE_USER', 'dspacestatistics')`
			`DATABASE_PASS = os.environ.get('DATABASE_PASS', 'dspacestatistics')`
			`DATABASE_HOST = os.environ.get('DATABASE_HOST', 'localhost')`
Allow configuration of PostgreSQL port Defaults to port 5432, but can be overridden with DATABASE_PORT. 2018-11-03 21:40:45 +01:00			`DATABASE_PORT = os.environ.get('DATABASE_PORT', '5432')`
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
Add vim modeline to all Python files Uses four spaces for tab and shift widths, and turns on expansion of tabs to spaces. 2018-09-23 10:33:26 +02:00			`# vim: set sw=4 ts=4 expandtab:`