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Author SHA1 Message Date
f65089f9ce CHANGELOG.md: Update and move to 0.4.3 release 2018-10-17 09:51:44 +03:00
1db5cf1c29 README.md: Grammar 2018-10-17 09:51:35 +03:00
e581c4b1aa README.md: Improve documentation 2018-10-17 09:50:30 +03:00
e8d356c9ca README.md: Add TODO about Python 3.6+ f-string syntax
They are faster.
2018-10-17 09:13:25 +03:00
34a9b8d629 CHANGELOG.md: Add unreleased changes for Travis CI 2018-10-14 19:02:09 +03:00
41e3d66a0e .travis.yml: Only build master branch 2018-10-14 19:00:31 +03:00
9b2a6137b4 README.md: Add Travis CI badge
For now this is only an indicator that the Python requirements can
be satisfied and installed.
2018-10-14 18:58:12 +03:00
600b986f99 .travis.yml: Use Python 3.7-dev instead of 3.7
I don't think Travis supports Python 3.7 yet because the builds for
that version keep failing.
2018-10-14 18:57:30 +03:00
49a7790794 .travis.yml: Move script to one line 2018-10-14 18:53:45 +03:00
f2deba627c .travis.yml: Run pip install as script
Basically for now there are no tests so I just want to just check
that requirements.txt is correct and that all dependencies can be
installed.
2018-10-14 18:47:14 +03:00
9323513794 README.md: Update instructions 2018-10-14 18:45:40 +03:00
daf15610f2 CHANGELOG.md: Update changes and move to 0.4.2 2018-10-05 00:19:18 +03:00
4ede966dbb indexer.py: Fix logic error in SQL insert
This was inserting correctly on the first run, but subsequent runs
were inserting into the incorrect column on conflict. This made it
seem like there were downloads for items where there were none.
2018-10-05 00:16:24 +03:00
3580473a6d README.md: Add TODO about JSON in PostgreSQL 2018-10-03 20:08:18 +03:00
071c24535f README.md: Add TODO about API versions 2018-10-03 11:12:18 +03:00
4291aecac4 README.md: Formatting 2018-09-27 12:45:15 +03:00
46bf537e88 CHANGELOG.md: Add note about cursor change 2018-09-27 11:08:42 +03:00
eaca5354d3 app.py: Iterate directly on cursor
We don't need to create an intermediate variable for the results of
the SQL query because psycopg2's cursor is iterable.

See: http://initd.org/psycopg/docs/cursor.html
2018-09-27 11:03:44 +03:00
4600288ee4 CHANGELOG.md: Add note about ujson 2018-09-27 09:53:42 +03:00
8179563378 requirements.txt: pip freeze 2018-09-27 09:53:16 +03:00
b14c3eef4d indexer.py: Use ujson instead of json
Falcon optionally makes use of the ujson library to speed up media
(de)serialization, error serialization, and query string parsing.

See: https://falcon.readthedocs.io/en/stable/user/install.html
2018-09-27 09:51:40 +03:00
71a789b13f CHANGELOG.md. Add unreleased changes 2018-09-27 09:30:48 +03:00
c68ddacaa4 README.md: Add note about systemd units for deployment 2018-09-27 09:26:47 +03:00
9c9e79769e README.md: Add TODO 2018-09-27 09:17:45 +03:00
2ad5ade556 README.md: Improve introduction 2018-09-27 09:12:52 +03:00
7412a09670 README.md: Improve introduction 2018-09-27 09:07:28 +03:00
bb744a00b8 README.md: Add requirements 2018-09-27 08:57:27 +03:00
7499b89d99 CHANGELOG.md: Move unreleased changes to v0.4.1 2018-09-27 08:15:54 +03:00
2c1e4952b1 indexer.py: Remove comment
I had left this there so I could remember how to get the number of
facets, but I don't need it anymore.
2018-09-26 23:27:48 +03:00
379f202c3f CHANGELOG.md: Add unreleased changes 2018-09-26 23:26:48 +03:00
560fa6056d README.md: Remove batch inserts from TODO 2018-09-26 23:25:35 +03:00
385a34e5d0 indexer.py: Use psycopg2's execute_values to batch inserts
Batch inserts are much faster than a series of individual inserts
because they drastically reduce the overhead caused by round-trip
communication with the server. My tests in development confirm:

  - cursor.execute(): 19 seconds
  - execute_values(): 14 seconds

I'm currently only working with 4,500 rows, but I will experiment
with larger data sets, as well as larger batches. For example, on
the PostgreSQL mailing list a user reports doing 10,000 rows with
a page size of 100.

See: http://initd.org/psycopg/docs/extras.html#psycopg2.extras.execute_values
See: https://github.com/psycopg/psycopg2/issues/491#issuecomment-276551038
2018-09-26 23:10:29 +03:00
d0ea62d2bd database.py: Use one line for psycopg2 imports 2018-09-26 22:23:24 +03:00
366ae25b8e README.md: Add link to psycopg2 issue about batch inserts 2018-09-26 22:23:08 +03:00
0f3054ae03 README.md: Add TODO about batch DB inserts 2018-09-26 16:31:13 +03:00
7 changed files with 90 additions and 26 deletions

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@ -2,8 +2,10 @@ language: python
python:
- "3.5"
- "3.6"
- "3.7"
install:
- pip install -r requirements.txt
- "3.7-dev"
script: pip install -r requirements.txt
branches:
only:
- master
# vim: ts=2 sw=2 et

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@ -4,6 +4,26 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
### [0.4.3] - 2018-10-17
## Changed
- Use pip install as script for Travis CI
## Improved
- Documentation for deployment and testing
## [0.4.2] - 2018-10-04
### Changed
- README.md introduction and requirements
- Use ujson instead of json
- Iterate directly on SQL cursor in `/items` route
### Fixed
- Logic error in SQL for item views
## [0.4.1] - 2018-09-26
### Changed
- Use execute_values() to batch insert records to PostgreSQL
## [0.4.0] - 2018-09-25
### Fixed
- Invalid OnCalendar syntax in dspace-statistics-indexer.timer

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@ -1,16 +1,42 @@
# DSpace Statistics API
A quick and dirty REST API to expose Solr view and download statistics for items in a DSpace repository.
# DSpace Statistics API [![Build Status](https://travis-ci.org/alanorth/dspace-statistics-api.svg?branch=master)](https://travis-ci.org/alanorth/dspace-statistics-api)
A simple REST API to expose Solr view and download statistics for items in a DSpace repository. This project contains a standalone indexing component and a WSGI application.
Written and tested in Python 3.5, 3.6, and 3.7. Requires PostgreSQL version 9.5 or greater for [`UPSERT` support](https://wiki.postgresql.org/wiki/UPSERT).
## Requirements
## Installation
Create a virtual environment and run it:
- Python 3.5+
- PostgreSQL version 9.5+ (due to [`UPSERT` support](https://wiki.postgresql.org/wiki/UPSERT))
- DSpace 4+ with [Solr usage statistics enabled](https://wiki.duraspace.org/display/DSDOC5x/SOLR+Statistics)
## Installation and Testing
Create a Python virtual environment and install the dependencies:
$ python -m venv venv
$ . venv/bin/activate
$ pip install -r requirements.txt
Set up the environment variables for Solr and PostgreSQL:
$ export SOLR_SERVER=http://localhost:8080/solr
$ export DATABASE_NAME=dspacestatistics
$ export DATABASE_USER=dspacestatistics
$ export DATABASE_PASS=dspacestatistics
$ export DATABASE_HOST=localhost
Index the Solr statistics core to populate the PostgreSQL database:
$ ./indexer.py
Run the REST API:
$ gunicorn app:api
Test to see if there are any statistics:
$ curl 'http://localhost:8000/items?limit=1'
## Deployment
There are example systemd service and timer units in the `contrib` directory.
## Using the API
The API exposes the following endpoints:
@ -22,9 +48,13 @@ The API exposes the following endpoints:
## Todo
- Add API documentation
- Close up DB connection when gunicorn shuts down gracefully
- Close DB connection when gunicorn shuts down gracefully
- Better logging
- Tests
- Check if database exists (try/except)
- Version API
- Use JSON in PostgreSQL
- Switch to [Python 3.6+ f-string syntax](https://realpython.com/python-f-strings/)
## License
This work is licensed under the [GPLv3](https://www.gnu.org/licenses/gpl-3.0.en.html).

6
app.py
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@ -22,16 +22,16 @@ class AllItemsResource:
# get statistics, ordered by id, and use limit and offset to page through results
cursor.execute('SELECT id, views, downloads FROM items ORDER BY id ASC LIMIT {} OFFSET {}'.format(limit, offset))
results = cursor.fetchmany(limit)
cursor.close()
# create a list to hold dicts of item stats
statistics = list()
# iterate over results and build statistics object
for item in results:
for item in cursor:
statistics.append({ 'id': item['id'], 'views': item['views'], 'downloads': item['downloads'] })
cursor.close()
message = {
'currentPage': page,
'totalPages': pages,

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@ -2,8 +2,7 @@ from config import DATABASE_NAME
from config import DATABASE_USER
from config import DATABASE_PASS
from config import DATABASE_HOST
import psycopg2
import psycopg2.extras
import psycopg2, psycopg2.extras
def database_connection():
connection = psycopg2.connect("dbname={} user={} password={} host='{}'".format(DATABASE_NAME, DATABASE_USER, DATABASE_PASS, DATABASE_HOST), cursor_factory=psycopg2.extras.DictCursor)

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@ -31,7 +31,8 @@
# See: https://wiki.duraspace.org/display/DSPACE/Solr
from database import database_connection
import json
import ujson
import psycopg2.extras
from solr import solr_connection
def index_views():
@ -55,7 +56,7 @@ def index_views():
}, rows=0)
# get total number of distinct facets (countDistinct)
results_totalNumFacets = json.loads(res.get_json())['stats']['stats_fields']['id']['countDistinct']
results_totalNumFacets = ujson.loads(res.get_json())['stats']['stats_fields']['id']['countDistinct']
# divide results into "pages" (cast to int to effectively round down)
results_per_page = 100
@ -64,6 +65,9 @@ def index_views():
cursor = db.cursor()
# create an empty list to store values for batch insertion
data = []
while results_current_page <= results_num_pages:
print('Indexing item views (page {} of {})'.format(results_current_page, results_num_pages))
@ -77,19 +81,20 @@ def index_views():
'facet.offset':results_current_page * results_per_page
}, rows=0)
# check number of facets returned in the last query
#results_currentNumFacets = len(res.get_facets()['id'])
# SolrClient's get_facets() returns a dict of dicts
views = res.get_facets()
# in this case iterate over the 'id' dict and get the item ids and views
for item_id, item_views in views['id'].items():
cursor.execute('''INSERT INTO items(id, views) VALUES(%s, %s)
ON CONFLICT(id) DO UPDATE SET downloads=excluded.views''',
(item_id, item_views))
data.append((item_id, item_views))
# do a batch insert of values from the current "page" of results
sql = 'INSERT INTO items(id, views) VALUES %s ON CONFLICT(id) DO UPDATE SET views=excluded.views'
psycopg2.extras.execute_values(cursor, sql, data, template='(%s, %s)')
db.commit()
# clear all items from the list so we can populate it with the next batch
data.clear()
results_current_page += 1
cursor.close()
@ -110,7 +115,7 @@ def index_downloads():
}, rows=0)
# get total number of distinct facets (countDistinct)
results_totalNumFacets = json.loads(res.get_json())['stats']['stats_fields']['owningItem']['countDistinct']
results_totalNumFacets = ujson.loads(res.get_json())['stats']['stats_fields']['owningItem']['countDistinct']
# divide results into "pages" (cast to int to effectively round down)
results_per_page = 100
@ -119,6 +124,9 @@ def index_downloads():
cursor = db.cursor()
# create an empty list to store values for batch insertion
data = []
while results_current_page <= results_num_pages:
print('Indexing item downloads (page {} of {})'.format(results_current_page, results_num_pages))
@ -136,12 +144,16 @@ def index_downloads():
downloads = res.get_facets()
# in this case iterate over the 'owningItem' dict and get the item ids and downloads
for item_id, item_downloads in downloads['owningItem'].items():
cursor.execute('''INSERT INTO items(id, downloads) VALUES(%s, %s)
ON CONFLICT(id) DO UPDATE SET downloads=excluded.downloads''',
(item_id, item_downloads))
data.append((item_id, item_downloads))
# do a batch insert of values from the current "page" of results
sql = 'INSERT INTO items(id, downloads) VALUES %s ON CONFLICT(id) DO UPDATE SET downloads=excluded.downloads'
psycopg2.extras.execute_values(cursor, sql, data, template='(%s, %s)')
db.commit()
# clear all items from the list so we can populate it with the next batch
data.clear()
results_current_page += 1
cursor.close()

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@ -9,4 +9,5 @@ python-mimeparse==1.6.0
requests==2.19.1
six==1.11.0
SolrClient==0.2.1
ujson==1.35
urllib3==1.23