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v1.3.0 ... v5_x

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963961354b README.md: Use travis-ci.com domain for badge 2020-12-08 09:10:41 +02:00
18 changed files with 77749 additions and 5834 deletions

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@ -1,6 +1,6 @@
image: archlinux
packages:
- python-poetry
- python-pipenv
- postgresql
sources:
- https://git.sr.ht/~alanorth/dspace-statistics-api
@ -15,7 +15,10 @@ tasks:
createdb -U postgres -O dspacestatistics --encoding=UNICODE dspacestatistics
cd dspace-statistics-api
psql -U postgres -d dspacestatistics < tests/dspacestatistics.sql
poetry install --no-root
pipenv install --dev
- test: |
cd dspace-statistics-api
poetry run pytest
pipenv run pytest
environment:
PIPENV_NOSPIN: 'True'
PIPENV_HIDE_EMOJIS: 'True'

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@ -1,15 +1,12 @@
dist: bionic
language: python
python:
- "3.5"
- "3.6"
- "3.7"
- "3.8"
- "3.8-dev" # 3.8 development branch
jobs:
allow_failures:
- python: "3.8-dev"
addons:
postgresql: "10"
postgresql: "9.6"
before_script:
- psql --version
- createuser -U postgres dspacestatistics

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@ -4,37 +4,13 @@ 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).
## [1.3.0] - 2020-10-06
### Changed
- Minor refactoring of indexer
### Added
- Ability to get statistics for arbitrary items and date ranges by POSTing a JSON-formatted request to /items as opposed to the current `GET /items` which returns pre-indexed all-time stats for all items
### Updated
- Run pipenv update, bringing minor updates to pytest, psycopg2-binary, etc
## [1.2.1] - 2020-03-02
### Changed
- Help text in API docs should reference UUIDs
- Sample SQL file for tests should use UUIDs
## [1.2.0] - 2020-03-02
### Changed
- Remove Python 3.5 from TravisCI because black requires Python >= 3.6
- Adapt API for DSpace 6+ UUIDs
- This requires dropping the statistics database and re-indexing
### Updated
- Run pipenv update, bringing requests 2.23.0 and pytest 5.3.5
## [1.1.1] - 2019-11-27
### Added
- Configuration for automatic sorting of imports with isort
- Configuration for automatic code formatting with black
### Updated
- Run pipenv update, bringing psycopg2 2.8.4, requests 2.22.0, pytest 5.3.1,
- Run pipenv update, bringing psycogpg 2.8.3, requests 2.22.0, pytest 5.3.1,
and gunicorn 20.0.4
### Changed

20
Pipfile Normal file
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@ -0,0 +1,20 @@
[[source]]
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[dev-packages]
ipython = "*"
"flake8" = "*"
pytest = "*"
isort = "*"
black = "*"
[requires]
python_version = "3.8"

397
Pipfile.lock generated Normal file
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@ -0,0 +1,397 @@
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View File

@ -1,10 +1,7 @@
# DSpace Statistics API [![Build Status](https://travis-ci.org/ilri/dspace-statistics-api.svg?branch=master)](https://travis-ci.org/ilri/dspace-statistics-api) [![builds.sr.ht status](https://builds.sr.ht/~alanorth/dspace-statistics-api.svg)](https://builds.sr.ht/~alanorth/dspace-statistics-api?)
DSpace stores item view and download events in a Solr "statistics" core. This information is available for use in the various DSpace user interfaces, but is not exposed externally via any APIs. The DSpace 4/5/6 [REST API](https://wiki.lyrasis.org/display/DSDOC5x/REST+API), for example, only exposes information about communities, collections, item metadata, and bitstreams.
# DSpace Statistics API [![Build Status](https://travis-ci.com/ilri/dspace-statistics-api.svg?branch=master)](https://travis-ci.com/ilri/dspace-statistics-api) [![builds.sr.ht status](https://builds.sr.ht/~alanorth/dspace-statistics-api.svg)](https://builds.sr.ht/~alanorth/dspace-statistics-api?)
DSpace stores item view and download events in a Solr "statistics" core. This information is available for use in the various DSpace user interfaces, but is not exposed externally via any APIs. The DSpace 4/5 [REST API](https://wiki.duraspace.org/display/DSDOC5x/REST+API), for example, only exposes information about communities, collections, item metadata, and bitstreams.
- If your DSpace is version 4 or 5, use [dspace-statistics-api v1.1.1](https://github.com/ilri/dspace-statistics-api/releases/tag/v1.1.1)
- If your DSpace is version 6+, use [dspace-statistics-api v1.2.0 or greater](https://github.com/ilri/dspace-statistics-api/releases/tag/v1.2.0)
This project contains an indexer and a [Falcon-based](https://falcon.readthedocs.io/) web application to make the statistics available via a simple REST API. You can read more about the Solr queries used to gather the item view and download statistics on the [DSpace wiki](https://wiki.lyrasis.org/display/DSPACE/Solr).
This project contains an indexer and a [Falcon-based](https://falcon.readthedocs.io/) web application to make the statistics available via a simple REST API. You can read more about the Solr queries used to gather the item view and download statistics on the [DSpace wiki](https://wiki.duraspace.org/display/DSPACE/Solr).
If you use the DSpace Statistics API please cite:
@ -12,9 +9,9 @@ If you use the DSpace Statistics API please cite:
## Requirements
- Python 3.6+
- Python 3.5+
- PostgreSQL version 9.5+ (due to [`UPSERT` support](https://wiki.postgresql.org/wiki/UPSERT))
- DSpace with [Solr usage statistics enabled](https://wiki.lyrasis.org/display/DSDOC5x/SOLR+Statistics) (tested with 5.x)
- DSpace with [Solr usage statistics enabled](https://wiki.duraspace.org/display/DSDOC5x/SOLR+Statistics) (tested with 5.x)
## Installation
Create a Python virtual environment and install the dependencies:
@ -81,38 +78,21 @@ The API exposes the following endpoints:
- GET `/`return a basic API documentation page.
- GET `/items`return views and downloads for all items that Solr knows about¹. Accepts `limit` and `page` query parameters for pagination of results (`limit` must be an integer between 1 and 100, and `page` must be an integer greater than or equal to 0).
- POST `/items`return views and downloads for an arbitrary list of items. Accepts `limit`, `page`, `dateFrom`, and `dateTo` parameters².
- GET `/item/id`return views and downloads for a single item (`id` must be a UUID). Returns HTTP 404 if an item id is not found.
- GET `/item/id`return views and downloads for a single item (`id` must be a positive integer). Returns HTTP 404 if an item id is not found.
The item id is the *internal* UUID for an item. You can get these from the standard DSpace REST API.
The item id is the *internal* id for an item. You can get these from the standard DSpace REST API.
¹ We are querying the Solr statistics core, which technically only knows about items that have either views or downloads. If an item is not present here you can assume it has zero views and zero downloads, but not necessarily that it does not exist in the repository.
² POST requests to `/items` should be in JSON format with the following parameters:
```
{
"limit": 100, // optional, integer between 0 and 100, default 100
"page": 0, // optional, integer greater than 0, default 0
"dateFrom": "2020-01-01T00:00:00Z", // optional, default *
"dateTo": "2020-09-09T00:00:00Z", // optional, default *
"items": [
"f44cf173-2344-4eb2-8f00-ee55df32c76f",
"2324aa41-e9de-4a2b-bc36-16241464683e",
"8542f9da-9ce1-4614-abf4-f2e3fdb4b305",
"0fe573e7-042a-4240-a4d9-753b61233908"
]
}
```
## TODO
## Todo
- Better logging
- Version API (or at least include a /version endpoint?)
- Version API
- Use JSON in PostgreSQL
- Add top items endpoint, perhaps `/top/items` or `/items/top`?
- Actually we could add `/items?limit=10&sort=views`
- Make community and collection stats available
- Support [DSpace 6 UUIDs](https://jira.duraspace.org/browse/DS-1782)
- Switch to [Python 3.6+ f-string syntax](https://realpython.com/python-f-strings/)
- Check IDs in database to see if they are deleted...
## License

View File

@ -1,8 +1,6 @@
import falcon
from .database import DatabaseManager
from .items import get_downloads, get_views
from .util import validate_items_post_parameters
class RootResource:
@ -29,10 +27,11 @@ class AllItemsResource:
cursor.execute("SELECT COUNT(id) FROM items")
pages = round(cursor.fetchone()[0] / limit)
# get statistics and use limit and offset to page through results
# get statistics, ordered by id, and use limit and offset to page through results
cursor.execute(
"SELECT id, views, downloads FROM items LIMIT %s OFFSET %s",
[limit, offset],
"SELECT id, views, downloads FROM items ORDER BY id ASC LIMIT {} OFFSET {}".format(
limit, offset
)
)
# create a list to hold dicts of item stats
@ -42,7 +41,7 @@ class AllItemsResource:
for item in cursor:
statistics.append(
{
"id": str(item["id"]),
"id": item["id"],
"views": item["views"],
"downloads": item["downloads"],
}
@ -57,93 +56,31 @@ class AllItemsResource:
resp.media = message
@falcon.before(validate_items_post_parameters)
def on_post(self, req, resp):
"""Handles POST requests"""
# Build the Solr date string, ie: [* TO *]
if req.context.dateFrom and req.context.dateTo:
solr_date_string = f"[{req.context.dateFrom} TO {req.context.dateTo}]"
elif not req.context.dateFrom and req.context.dateTo:
solr_date_string = f"[* TO {req.context.dateTo}]"
elif req.context.dateFrom and not req.context.dateTo:
solr_date_string = f"[{req.context.dateFrom} TO *]"
else:
solr_date_string = "[* TO *]"
# Helper variables to make working with pages/items/results easier and
# to make the code easier to understand
number_of_items: int = len(req.context.items)
pages: int = int(number_of_items / req.context.limit)
first_item: int = req.context.page * req.context.limit
last_item: int = first_item + req.context.limit
# Get a subset of the POSTed items based on our limit. Note that Python
# list slicing and indexing are both zero based, but the first and last
# items in a slice can be confusing. See this ASCII diagram:
#
# +---+---+---+---+---+---+
# | P | y | t | h | o | n |
# +---+---+---+---+---+---+
# Slice position: 0 1 2 3 4 5 6
# Index position: 0 1 2 3 4 5
#
# So if we have a list items with 240 items:
#
# 1st set: items[0:100] would give items at indexes 0 to 99
# 2nd set: items[100:200] would give items at indexes 100 to 199
# 3rd set: items[200:300] would give items at indexes 200 to 239
items_subset: list = req.context.items[first_item:last_item]
views: dict = get_views(solr_date_string, items_subset)
downloads: dict = get_downloads(solr_date_string, items_subset)
# create a list to hold dicts of item stats
statistics = list()
# iterate over views dict to extract views and use the item id as an
# index to the downloads dict to extract downloads.
for k, v in views.items():
statistics.append({"id": k, "views": v, "downloads": downloads[k]})
message = {
"currentPage": req.context.page,
"totalPages": pages,
"limit": req.context.limit,
"statistics": statistics,
}
resp.status = falcon.HTTP_200
resp.media = message
class ItemResource:
def on_get(self, req, resp, item_id):
"""Handles GET requests"""
import psycopg2.extras
# Adapt Pythons uuid.UUID type to PostgreSQLs uuid
# See: https://www.psycopg.org/docs/extras.html
psycopg2.extras.register_uuid()
with DatabaseManager() as db:
db.set_session(readonly=True)
with db.cursor() as cursor:
cursor = db.cursor()
cursor.execute(
"SELECT views, downloads FROM items WHERE id=%s", [str(item_id)]
"SELECT views, downloads FROM items WHERE id={}".format(item_id)
)
if cursor.rowcount == 0:
raise falcon.HTTPNotFound(
title="Item not found",
description=f'The item with id "{str(item_id)}" was not found.',
description='The item with id "{}" was not found.'.format(
item_id
),
)
else:
results = cursor.fetchone()
statistics = {
"id": str(item_id),
"id": item_id,
"views": results["views"],
"downloads": results["downloads"],
}
@ -154,6 +91,6 @@ class ItemResource:
api = application = falcon.API()
api.add_route("/", RootResource())
api.add_route("/items", AllItemsResource())
api.add_route("/item/{item_id:uuid}", ItemResource())
api.add_route("/item/{item_id:int}", ItemResource())
# vim: set sw=4 ts=4 expandtab:

View File

@ -15,7 +15,9 @@ class DatabaseManager:
"""Manage database connection."""
def __init__(self):
self._connection_uri = f"dbname={DATABASE_NAME} user={DATABASE_USER} password={DATABASE_PASS} host={DATABASE_HOST} port={DATABASE_PORT}"
self._connection_uri = "dbname={} user={} password={} host={} port={}".format(
DATABASE_NAME, DATABASE_USER, DATABASE_PASS, DATABASE_HOST, DATABASE_PORT
)
def __enter__(self):
try:

View File

@ -2,7 +2,7 @@
<html lang="en-US">
<head>
<meta charset="UTF-8">
<title>DSpace Statistics API v1.3.0</title>
<title>DSpace Statistics API</title>
</head>
<body>
<h1>DSpace Statistics API</h1>
@ -10,28 +10,11 @@
<ul>
<li>GET <code>/</code>return a basic API documentation page.</li>
<li>GET <code>/items</code>return views and downloads for all items that Solr knows about¹. Accepts <code>limit</code> and <code>page</code> query parameters for pagination of results (<code>limit</code> must be an integer between 1 and 100, and <code>page</code> must be an integer greater than or equal to 0).</li>
<li>POST <code>/items</code>return views and downloads for an arbitrary list of items. Accepts <code>limit</code>, <code>page</code>, <code>dateFrom</code>, and <code>dateTo</code> parameters².</li>
<li>GET <code>/item/id</code>return views and downloads for a single item (<code>id</code> must be a UUID). Returns HTTP 404 if an item id is not found.</li>
<li>GET <code>/item/id</code>return views and downloads for a single item (<code>id</code> must be a positive integer). Returns HTTP 404 if an item id is not found.</li>
</ul>
<p>The item id is the <em>internal</em> uuid for an item. You can get these from the standard DSpace REST API.</p>
<p>The item id is the <em>internal</em> id for an item. You can get these from the standard DSpace REST API.</p>
<hr/>
<p>¹ We are querying the Solr statistics core, which technically only knows about items that have either views or downloads. If an item is not present here you can assume it has zero views and zero downloads, but not necessarily that it does not exist in the repository.</p>
<p>² POST requests to <code>/items</code> should be in JSON format with the following parameters:
<pre><code>{
"limit": 100, // optional, integer between 0 and 100, default 100
"page": 0, // optional, integer greater than 0, default 0
"dateFrom": "2020-01-01T00:00:00Z", // optional, default *
"dateTo": "2020-09-09T00:00:00Z", // optional, default *
"items": [
"f44cf173-2344-4eb2-8f00-ee55df32c76f",
"2324aa41-e9de-4a2b-bc36-16241464683e",
"8542f9da-9ce1-4614-abf4-f2e3fdb4b305",
"0fe573e7-042a-4240-a4d9-753b61233908"
]
}</code></pre>
</p>
<p>¹ We are querying the Solr statistics core, which technically only knows about items that have either views or downloads. If an item is not present here you can assume it has zero views and zero downloads, but not necessarily that it does not exist in the repository.</code>
</body>
</html>

View File

@ -21,27 +21,74 @@
# Connects to a DSpace Solr statistics core and ingests item views and downloads
# into a PostgreSQL database for use by other applications (like an API).
#
# This script is written for Python 3.6+ and requires several modules that you
# This script is written for Python 3.5+ and requires several modules that you
# can install with pip (I recommend using a Python virtual environment):
#
# $ pip install psycopg2-binary
# $ pip install SolrClient psycopg2-binary
#
# See: https://solrclient.readthedocs.io/en/latest/SolrClient.html
# See: https://wiki.duraspace.org/display/DSPACE/Solr
import re
import psycopg2.extras
import requests
from .config import SOLR_SERVER
from .database import DatabaseManager
from .util import get_statistics_shards
# Enumerate the cores in Solr to determine if statistics have been sharded into
# yearly shards by DSpace's stats-util or not (for example: statistics-2018).
def get_statistics_shards():
# Initialize an empty list for statistics core years
statistics_core_years = []
# URL for Solr status to check active cores
solr_query_params = {"action": "STATUS", "wt": "json"}
solr_url = SOLR_SERVER + "/admin/cores"
res = requests.get(solr_url, params=solr_query_params)
if res.status_code == requests.codes.ok:
data = res.json()
# Iterate over active cores from Solr's STATUS response (cores are in
# the status array of this response).
for core in data["status"]:
# Pattern to match, for example: statistics-2018
pattern = re.compile("^statistics-[0-9]{4}$")
if not pattern.match(core):
continue
# Append current core to list
statistics_core_years.append(core)
# Initialize a string to hold our shards (may end up being empty if the Solr
# core has not been processed by stats-util).
shards = str()
if len(statistics_core_years) > 0:
# Begin building a string of shards starting with the default one
shards = "{}/statistics".format(SOLR_SERVER)
for core in statistics_core_years:
# Create a comma-separated list of shards to pass to our Solr query
#
# See: https://wiki.apache.org/solr/DistributedSearch
shards += ",{}/{}".format(SOLR_SERVER, core)
# Return the string of shards, which may actually be empty. Solr doesn't
# seem to mind if the shards query parameter is empty and I haven't seen
# any negative performance impact so this should be fine.
return shards
def index_views():
# get total number of distinct facets for items with a minimum of 1 view,
# otherwise Solr returns all kinds of weird ids that are actually not in
# the database. Also, stats are expensive, but we need stats.calcdistinct
# so we can get the countDistinct summary to calculate how many pages of
# results we have.
# so we can get the countDistinct summary.
#
# see: https://lucene.apache.org/solr/guide/6_6/the-stats-component.html
solr_query_params = {
@ -87,7 +134,9 @@ def index_views():
while results_current_page <= results_num_pages:
# "pages" are zero based, but one based is more human readable
print(
f"Indexing item views (page {results_current_page + 1} of {results_num_pages + 1})"
"Indexing item views (page {} of {})".format(
results_current_page + 1, results_num_pages + 1
)
)
solr_query_params = {
@ -104,6 +153,8 @@ def index_views():
"json.nl": "map", # return facets as a dict instead of a flat list
}
solr_url = SOLR_SERVER + "/statistics/select"
res = requests.get(solr_url, params=solr_query_params)
# Solr returns facets as a dict of dicts (see json.nl parameter)
@ -168,7 +219,9 @@ def index_downloads():
while results_current_page <= results_num_pages:
# "pages" are zero based, but one based is more human readable
print(
f"Indexing item downloads (page {results_current_page + 1} of {results_num_pages + 1})"
"Indexing item downloads (page {} of {})".format(
results_current_page + 1, results_num_pages + 1
)
)
solr_query_params = {
@ -185,6 +238,8 @@ def index_downloads():
"json.nl": "map", # return facets as a dict instead of a flat list
}
solr_url = SOLR_SERVER + "/statistics/select"
res = requests.get(solr_url, params=solr_query_params)
# Solr returns facets as a dict of dicts (see json.nl parameter)
@ -209,7 +264,7 @@ with DatabaseManager() as db:
# create table to store item views and downloads
cursor.execute(
"""CREATE TABLE IF NOT EXISTS items
(id UUID PRIMARY KEY, views INT DEFAULT 0, downloads INT DEFAULT 0)"""
(id INT PRIMARY KEY, views INT DEFAULT 0, downloads INT DEFAULT 0)"""
)
# commit the table creation before closing the database connection

View File

@ -1,105 +0,0 @@
import requests
from .config import SOLR_SERVER
def get_views(solr_date_string: str, items: list):
"""
Get view statistics for a list of items from Solr.
:parameter solr_date_string (str): Solr date string, for example "[* TO *]"
:parameter items (list): a list of item IDs
:returns: A dict of item IDs and views
"""
from .util import get_statistics_shards
shards = get_statistics_shards()
# Join the UUIDs with "OR" and escape the hyphens for Solr
solr_items_string: str = " OR ".join(items).replace("-", r"\-")
solr_query_params = {
"q": f"id:({solr_items_string})",
"fq": f"type:2 AND isBot:false AND statistics_type:view AND time:{solr_date_string}",
"facet": "true",
"facet.field": "id",
"facet.mincount": 1,
"shards": shards,
"rows": 0,
"wt": "json",
"json.nl": "map", # return facets as a dict instead of a flat list
}
solr_url = SOLR_SERVER + "/statistics/select"
res = requests.get(solr_url, params=solr_query_params)
# Create an empty dict to store views
data = {}
# Solr returns facets as a dict of dicts (see the json.nl parameter)
views = res.json()["facet_counts"]["facet_fields"]
# iterate over the 'id' dict and get the item ids and views
for item_id, item_views in views["id"].items():
data[item_id] = item_views
# Check if any items have missing stats so we can set them to 0
if len(data) < len(items):
# List comprehension to get a list of item ids (keys) in the data
data_ids = [k for k, v in data.items()]
for item_id in items:
if item_id not in data_ids:
data[item_id] = 0
continue
return data
def get_downloads(solr_date_string: str, items: list):
"""
Get download statistics for a list of items from Solr.
:parameter solr_date_string (str): Solr date string, for example "[* TO *]"
:parameter items (list): a list of item IDs
:returns: A dict of item IDs and downloads
"""
from .util import get_statistics_shards
shards = get_statistics_shards()
# Join the UUIDs with "OR" and escape the hyphens for Solr
solr_items_string: str = " OR ".join(items).replace("-", r"\-")
solr_query_params = {
"q": f"owningItem:({solr_items_string})",
"fq": f"type:0 AND isBot:false AND statistics_type:view AND bundleName:ORIGINAL AND time:{solr_date_string}",
"facet": "true",
"facet.field": "owningItem",
"facet.mincount": 1,
"shards": shards,
"rows": 0,
"wt": "json",
"json.nl": "map", # return facets as a dict instead of a flat list
}
solr_url = SOLR_SERVER + "/statistics/select"
res = requests.get(solr_url, params=solr_query_params)
# Create an empty dict to store downloads
data = {}
# Solr returns facets as a dict of dicts (see the json.nl parameter)
downloads = res.json()["facet_counts"]["facet_fields"]
# Iterate over the 'owningItem' dict and get the item ids and downloads
for item_id, item_downloads in downloads["owningItem"].items():
data[item_id] = item_downloads
# Check if any items have missing stats so we can set them to 0
if len(data) < len(items):
# List comprehension to get a list of item ids (keys) in the data
data_ids = [k for k, v in data.items()]
for item_id in items:
if item_id not in data_ids:
data[item_id] = 0
continue
return data
# vim: set sw=4 ts=4 expandtab:

View File

@ -1,138 +0,0 @@
import falcon
def get_statistics_shards():
"""Enumerate the cores in Solr to determine if statistics have been sharded into
yearly shards by DSpace's stats-util or not (for example: statistics-2018).
Returns:
str:A list of Solr statistics shards separated by commas.
"""
import re
import requests
from .config import SOLR_SERVER
# Initialize an empty list for statistics core years
statistics_core_years = []
# URL for Solr status to check active cores
solr_query_params = {"action": "STATUS", "wt": "json"}
solr_url = SOLR_SERVER + "/admin/cores"
res = requests.get(solr_url, params=solr_query_params)
if res.status_code == requests.codes.ok:
data = res.json()
# Iterate over active cores from Solr's STATUS response (cores are in
# the status array of this response).
for core in data["status"]:
# Pattern to match, for example: statistics-2018
pattern = re.compile("^statistics-[0-9]{4}$")
if not pattern.match(core):
continue
# Append current core to list
statistics_core_years.append(core)
# Initialize a string to hold our shards (may end up being empty if the Solr
# core has not been processed by stats-util).
shards = str()
if len(statistics_core_years) > 0:
# Begin building a string of shards starting with the default one
shards = f"{SOLR_SERVER}/statistics"
for core in statistics_core_years:
# Create a comma-separated list of shards to pass to our Solr query
#
# See: https://wiki.apache.org/solr/DistributedSearch
shards += f",{SOLR_SERVER}/{core}"
# Return the string of shards, which may actually be empty. Solr doesn't
# seem to mind if the shards query parameter is empty and I haven't seen
# any negative performance impact so this should be fine.
return shards
def is_valid_date(date):
import datetime
try:
# Solr date format is: 2020-01-01T00:00:00Z
# See: https://docs.python.org/3/library/datetime.html#strftime-strptime-behavior
datetime.datetime.strptime(date, "%Y-%m-%dT%H:%M:%SZ")
return True
except ValueError:
raise falcon.HTTPBadRequest(
title="Invalid parameter",
description=f"Invalid date format: {date}. The value must be in format: 2020-01-01T00:00:00Z.",
)
def validate_items_post_parameters(req, resp, resource, params):
"""Check the POSTed request parameters for the `/items` endpoint.
Meant to be used as a `before` hook.
"""
import json
# Only attempt to read the POSTed request if its length is not 0 (or
# rather, in the Python sense, if length is not a False-y value).
if req.content_length:
doc = json.load(req.bounded_stream)
else:
raise falcon.HTTPBadRequest(
title="Invalid request", description="Request body is empty."
)
# Parse date parameters from request body (will raise an HTTPBadRequest
# from is_valid_date() if any parameters are invalid)
if "dateFrom" in doc and is_valid_date(doc["dateFrom"]):
req.context.dateFrom = doc["dateFrom"]
else:
req.context.dateFrom = None
if "dateTo" in doc and is_valid_date(doc["dateTo"]):
req.context.dateTo = doc["dateTo"]
else:
req.context.dateTo = None
# Parse the limit parameter from the POST request body
if "limit" in doc:
if isinstance(doc["limit"], int) and 0 < doc["limit"] < 100:
req.context.limit = doc["limit"]
else:
raise falcon.HTTPBadRequest(
title="Invalid parameter",
description='The "limit" parameter is invalid. The value must be an integer between 0 and 100.',
)
else:
req.context.limit = 100
# Parse the page parameter from the POST request body
if "page" in doc:
if isinstance(doc["page"], int) and doc["page"] >= 0:
req.context.page = doc["page"]
else:
raise falcon.HTTPBadRequest(
title="Invalid parameter",
description='The "page" parameter is invalid. The value must be at least 0.',
)
else:
req.context.page = 0
# Parse the list of items from the POST request body
if "items" in doc:
if isinstance(doc["items"], list) and len(doc["items"]) > 0:
req.context.items = doc["items"]
else:
raise falcon.HTTPBadRequest(
title="Invalid parameter",
description='The "items" parameter is invalid. The value must be a comma-separated list of item UUIDs.',
)
else:
req.context.items = list()

868
poetry.lock generated
View File

@ -1,868 +0,0 @@
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View File

@ -1,25 +0,0 @@
[tool.poetry]
name = "dspace-statistics-api"
version = "1.3.0"
description = "A simple REST API to expose Solr view and download statistics for items in a DSpace repository."
authors = ["Alan Orth <aorth@mjanja.ch>"]
license = "GPL-3.0-only"
[tool.poetry.dependencies]
python = "^3.6"
gunicorn = "^20.0.4"
falcon = "^2.0.0"
psycopg2-binary = "^2.8.6"
requests = "^2.24.0"
[tool.poetry.dev-dependencies]
ipython = { version = "^7.18.1", python = "^3.7" }
flake8 = "^3.8.4"
pytest = "^6.1.1"
isort = "^5.5.4"
black = "^20.8b1"
pytest-clarity = "^0.3.0-alpha.0"
[build-system]
requires = ["poetry>=0.12"]
build-backend = "poetry.masonry.api"

View File

@ -1,231 +1,27 @@
appdirs==1.4.4 \
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attrs==20.2.0 \
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backcall==0.2.0; python_version >= "3.7" and python_version < "4.0" \
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black==20.8b1 \
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certifi==2020.6.20 \
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chardet==3.0.4 \
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click==7.1.2 \
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colorama==0.4.3; python_version >= "3.7" and python_version < "4.0" and sys_platform == "win32" or sys_platform == "win32" \
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dataclasses==0.6; python_version < "3.7" \
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decorator==4.4.2; python_version >= "3.7" and python_version < "4.0" \
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falcon==2.0.0 \
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--hash=sha256:54f2cb4b687035b2a03206dbfc538055cc48b59a953187b0458aa1b574d47b53 \
--hash=sha256:eea593cf466b9c126ce667f6d30503624ef24459f118c75594a69353b6c3d5fc
flake8==3.8.4 \
--hash=sha256:749dbbd6bfd0cf1318af27bf97a14e28e5ff548ef8e5b1566ccfb25a11e7c839 \
--hash=sha256:aadae8761ec651813c24be05c6f7b4680857ef6afaae4651a4eccaef97ce6c3b
gunicorn==20.0.4 \
--hash=sha256:cd4a810dd51bf497552cf3f863b575dabd73d6ad6a91075b65936b151cbf4f9c \
--hash=sha256:1904bb2b8a43658807108d59c3f3d56c2b6121a701161de0ddf9ad140073c626
idna==2.10 \
--hash=sha256:b97d804b1e9b523befed77c48dacec60e6dcb0b5391d57af6a65a312a90648c0 \
--hash=sha256:b307872f855b18632ce0c21c5e45be78c0ea7ae4c15c828c20788b26921eb3f6
importlib-metadata==2.0.0; python_version < "3.8" \
--hash=sha256:cefa1a2f919b866c5beb7c9f7b0ebb4061f30a8a9bf16d609b000e2dfaceb9c3 \
--hash=sha256:77a540690e24b0305878c37ffd421785a6f7e53c8b5720d211b211de8d0e95da
iniconfig==1.0.1 \
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--hash=sha256:e5f92f89355a67de0595932a6c6c02ab4afddc6fcdc0bfc5becd0d60884d3f69
ipython==7.18.1; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:2e22c1f74477b5106a6fb301c342ab8c64bb75d702e350f05a649e8cb40a0fb8 \
--hash=sha256:a331e78086001931de9424940699691ad49dfb457cea31f5471eae7b78222d5e
ipython-genutils==0.2.0; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8 \
--hash=sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8
isort==5.5.4 \
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--hash=sha256:ba040c24d20aa302f78f4747df549573ae1eaf8e1084269199154da9c483f07f
jedi==0.17.2; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:98cc583fa0f2f8304968199b01b6b4b94f469a1f4a74c1560506ca2a211378b5 \
--hash=sha256:86ed7d9b750603e4ba582ea8edc678657fb4007894a12bcf6f4bb97892f31d20
mccabe==0.6.1 \
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--hash=sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f
mypy-extensions==0.4.3 \
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--hash=sha256:2d82818f5bb3e369420cb3c4060a7970edba416647068eb4c5343488a6c604a8
packaging==20.4 \
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--hash=sha256:4357f74f47b9c12db93624a82154e9b120fa8293699949152b22065d556079f8
parso==0.7.1; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:97218d9159b2520ff45eb78028ba8b50d2bc61dcc062a9682666f2dc4bd331ea \
--hash=sha256:caba44724b994a8a5e086460bb212abc5a8bc46951bf4a9a1210745953622eb9
pathspec==0.8.0 \
--hash=sha256:7d91249d21749788d07a2d0f94147accd8f845507400749ea19c1ec9054a12b0 \
--hash=sha256:da45173eb3a6f2a5a487efba21f050af2b41948be6ab52b6a1e3ff22bb8b7061
pexpect==4.8.0; python_version >= "3.7" and python_version < "4.0" and sys_platform != "win32" \
--hash=sha256:0b48a55dcb3c05f3329815901ea4fc1537514d6ba867a152b581d69ae3710937 \
--hash=sha256:fc65a43959d153d0114afe13997d439c22823a27cefceb5ff35c2178c6784c0c
pickleshare==0.7.5; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:9649af414d74d4df115d5d718f82acb59c9d418196b7b4290ed47a12ce62df56 \
--hash=sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca
pluggy==0.13.1 \
--hash=sha256:966c145cd83c96502c3c3868f50408687b38434af77734af1e9ca461a4081d2d \
--hash=sha256:15b2acde666561e1298d71b523007ed7364de07029219b604cf808bfa1c765b0
prompt-toolkit==3.0.7; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:83074ee28ad4ba6af190593d4d4c607ff525272a504eb159199b6dd9f950c950 \
--hash=sha256:822f4605f28f7d2ba6b0b09a31e25e140871e96364d1d377667b547bb3bf4489
psycopg2-binary==2.8.6 \
--hash=sha256:11b9c0ebce097180129e422379b824ae21c8f2a6596b159c7659e2e5a00e1aa0 \
--hash=sha256:d14b140a4439d816e3b1229a4a525df917d6ea22a0771a2a78332273fd9528a4 \
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--hash=sha256:6a32f3a4cb2f6e1a0b15215f448e8ce2da192fd4ff35084d80d5e39da683e79b \
--hash=sha256:0e4dc3d5996760104746e6cfcdb519d9d2cd27c738296525d5867ea695774e67 \
--hash=sha256:cec7e622ebc545dbb4564e483dd20e4e404da17ae07e06f3e780b2dacd5cee66 \
--hash=sha256:ba381aec3a5dc29634f20692349d73f2d21f17653bda1decf0b52b11d694541f \
--hash=sha256:a0c50db33c32594305b0ef9abc0cb7db13de7621d2cadf8392a1d9b3c437ef77 \
--hash=sha256:2dac98e85565d5688e8ab7bdea5446674a83a3945a8f416ad0110018d1501b94 \
--hash=sha256:bd1be66dde2b82f80afb9459fc618216753f67109b859a361cf7def5c7968729 \
--hash=sha256:8cd0fb36c7412996859cb4606a35969dd01f4ea34d9812a141cd920c3b18be77 \
--hash=sha256:42ec1035841b389e8cc3692277a0bd81cdfe0b65d575a2c8862cec7a80e62e52 \
--hash=sha256:7312e931b90fe14f925729cde58022f5d034241918a5c4f9797cac62f6b3a9dd
ptyprocess==0.6.0; python_version >= "3.7" and python_version < "4.0" and sys_platform != "win32" \
--hash=sha256:d7cc528d76e76342423ca640335bd3633420dc1366f258cb31d05e865ef5ca1f \
--hash=sha256:923f299cc5ad920c68f2bc0bc98b75b9f838b93b599941a6b63ddbc2476394c0
py==1.9.0 \
--hash=sha256:366389d1db726cd2fcfc79732e75410e5fe4d31db13692115529d34069a043c2 \
--hash=sha256:9ca6883ce56b4e8da7e79ac18787889fa5206c79dcc67fb065376cd2fe03f342
pycodestyle==2.6.0 \
--hash=sha256:2295e7b2f6b5bd100585ebcb1f616591b652db8a741695b3d8f5d28bdc934367 \
--hash=sha256:c58a7d2815e0e8d7972bf1803331fb0152f867bd89adf8a01dfd55085434192e
pyflakes==2.2.0 \
--hash=sha256:0d94e0e05a19e57a99444b6ddcf9a6eb2e5c68d3ca1e98e90707af8152c90a92 \
--hash=sha256:35b2d75ee967ea93b55750aa9edbbf72813e06a66ba54438df2cfac9e3c27fc8
pygments==2.7.1; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:307543fe65c0947b126e83dd5a61bd8acbd84abec11f43caebaf5534cbc17998 \
--hash=sha256:926c3f319eda178d1bd90851e4317e6d8cdb5e292a3386aac9bd75eca29cf9c7
pyparsing==2.4.7 \
--hash=sha256:ef9d7589ef3c200abe66653d3f1ab1033c3c419ae9b9bdb1240a85b024efc88b \
--hash=sha256:c203ec8783bf771a155b207279b9bccb8dea02d8f0c9e5f8ead507bc3246ecc1
pytest==6.1.1 \
--hash=sha256:7a8190790c17d79a11f847fba0b004ee9a8122582ebff4729a082c109e81a4c9 \
--hash=sha256:8f593023c1a0f916110285b6efd7f99db07d59546e3d8c36fc60e2ab05d3be92
pytest-clarity==0.3.0a0 \
--hash=sha256:5cc99e3d9b7969dfe17e5f6072d45a917c59d363b679686d3c958a1ded2e4dcf
regex==2020.9.27 \
--hash=sha256:d23a18037313714fb3bb5a94434d3151ee4300bae631894b1ac08111abeaa4a3 \
--hash=sha256:84e9407db1b2eb368b7ecc283121b5e592c9aaedbe8c78b1a2f1102eb2e21d19 \
--hash=sha256:5f18875ac23d9aa2f060838e8b79093e8bb2313dbaaa9f54c6d8e52a5df097be \
--hash=sha256:ae91972f8ac958039920ef6e8769277c084971a142ce2b660691793ae44aae6b \
--hash=sha256:9a02d0ae31d35e1ec12a4ea4d4cca990800f66a917d0fb997b20fbc13f5321fc \
--hash=sha256:ebbe29186a3d9b0c591e71b7393f1ae08c83cb2d8e517d2a822b8f7ec99dfd8b \
--hash=sha256:4707f3695b34335afdfb09be3802c87fa0bc27030471dbc082f815f23688bc63 \
--hash=sha256:9bc13e0d20b97ffb07821aa3e113f9998e84994fe4d159ffa3d3a9d1b805043b \
--hash=sha256:f1b3afc574a3db3b25c89161059d857bd4909a1269b0b3cb3c904677c8c4a3f7 \
--hash=sha256:5533a959a1748a5c042a6da71fe9267a908e21eded7a4f373efd23a2cbdb0ecc \
--hash=sha256:1fe0a41437bbd06063aa184c34804efa886bcc128222e9916310c92cd54c3b4c \
--hash=sha256:c570f6fa14b9c4c8a4924aaad354652366577b4f98213cf76305067144f7b100 \
--hash=sha256:eda4771e0ace7f67f58bc5b560e27fb20f32a148cbc993b0c3835970935c2707 \
--hash=sha256:60b0e9e6dc45683e569ec37c55ac20c582973841927a85f2d8a7d20ee80216ab \
--hash=sha256:088afc8c63e7bd187a3c70a94b9e50ab3f17e1d3f52a32750b5b77dbe99ef5ef \
--hash=sha256:eaf548d117b6737df379fdd53bdde4f08870e66d7ea653e230477f071f861121 \
--hash=sha256:41bb65f54bba392643557e617316d0d899ed5b4946dccee1cb6696152b29844b \
--hash=sha256:8d69cef61fa50c8133382e61fd97439de1ae623fe943578e477e76a9d9471637 \
--hash=sha256:f2388013e68e750eaa16ccbea62d4130180c26abb1d8e5d584b9baf69672b30f \
--hash=sha256:4318d56bccfe7d43e5addb272406ade7a2274da4b70eb15922a071c58ab0108c \
--hash=sha256:a6f32aea4260dfe0e55dc9733ea162ea38f0ea86aa7d0f77b15beac5bf7b369d
requests==2.24.0 \
--hash=sha256:fe75cc94a9443b9246fc7049224f75604b113c36acb93f87b80ed42c44cbb898 \
--hash=sha256:b3559a131db72c33ee969480840fff4bb6dd111de7dd27c8ee1f820f4f00231b
six==1.15.0 \
--hash=sha256:8b74bedcbbbaca38ff6d7491d76f2b06b3592611af620f8426e82dddb04a5ced \
--hash=sha256:30639c035cdb23534cd4aa2dd52c3bf48f06e5f4a941509c8bafd8ce11080259
termcolor==1.1.0 \
--hash=sha256:1d6d69ce66211143803fbc56652b41d73b4a400a2891d7bf7a1cdf4c02de613b
toml==0.10.1 \
--hash=sha256:bda89d5935c2eac546d648028b9901107a595863cb36bae0c73ac804a9b4ce88 \
--hash=sha256:926b612be1e5ce0634a2ca03470f95169cf16f939018233a670519cb4ac58b0f
traitlets==5.0.4; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:9664ec0c526e48e7b47b7d14cd6b252efa03e0129011de0a9c1d70315d4309c3 \
--hash=sha256:86c9351f94f95de9db8a04ad8e892da299a088a64fd283f9f6f18770ae5eae1b
typed-ast==1.4.1 \
--hash=sha256:73d785a950fc82dd2a25897d525d003f6378d1cb23ab305578394694202a58c3 \
--hash=sha256:aaee9905aee35ba5905cfb3c62f3e83b3bec7b39413f0a7f19be4e547ea01ebb \
--hash=sha256:0c2c07682d61a629b68433afb159376e24e5b2fd4641d35424e462169c0a7919 \
--hash=sha256:4083861b0aa07990b619bd7ddc365eb7fa4b817e99cf5f8d9cf21a42780f6e01 \
--hash=sha256:269151951236b0f9a6f04015a9004084a5ab0d5f19b57de779f908621e7d8b75 \
--hash=sha256:24995c843eb0ad11a4527b026b4dde3da70e1f2d8806c99b7b4a7cf491612652 \
--hash=sha256:fe460b922ec15dd205595c9b5b99e2f056fd98ae8f9f56b888e7a17dc2b757e7 \
--hash=sha256:4e3e5da80ccbebfff202a67bf900d081906c358ccc3d5e3c8aea42fdfdfd51c1 \
--hash=sha256:249862707802d40f7f29f6e1aad8d84b5aa9e44552d2cc17384b209f091276aa \
--hash=sha256:8ce678dbaf790dbdb3eba24056d5364fb45944f33553dd5869b7580cdbb83614 \
--hash=sha256:c9e348e02e4d2b4a8b2eedb48210430658df6951fa484e59de33ff773fbd4b41 \
--hash=sha256:bcd3b13b56ea479b3650b82cabd6b5343a625b0ced5429e4ccad28a8973f301b \
--hash=sha256:d5d33e9e7af3b34a40dc05f498939f0ebf187f07c385fd58d591c533ad8562fe \
--hash=sha256:0666aa36131496aed8f7be0410ff974562ab7eeac11ef351def9ea6fa28f6355 \
--hash=sha256:d205b1b46085271b4e15f670058ce182bd1199e56b317bf2ec004b6a44f911f6 \
--hash=sha256:6daac9731f172c2a22ade6ed0c00197ee7cc1221aa84cfdf9c31defeb059a907 \
--hash=sha256:498b0f36cc7054c1fead3d7fc59d2150f4d5c6c56ba7fb150c013fbc683a8d2d \
--hash=sha256:715ff2f2df46121071622063fc7543d9b1fd19ebfc4f5c8895af64a77a8c852c \
--hash=sha256:fc0fea399acb12edbf8a628ba8d2312f583bdbdb3335635db062fa98cf71fca4 \
--hash=sha256:d43943ef777f9a1c42bf4e552ba23ac77a6351de620aa9acf64ad54933ad4d34 \
--hash=sha256:8c8aaad94455178e3187ab22c8b01a3837f8ee50e09cf31f1ba129eb293ec30b
typing-extensions==3.7.4.3 \
--hash=sha256:dafc7639cde7f1b6e1acc0f457842a83e722ccca8eef5270af2d74792619a89f \
--hash=sha256:7cb407020f00f7bfc3cb3e7881628838e69d8f3fcab2f64742a5e76b2f841918 \
--hash=sha256:99d4073b617d30288f569d3f13d2bd7548c3a7e4c8de87db09a9d29bb3a4a60c
urllib3==1.25.10 \
--hash=sha256:e7983572181f5e1522d9c98453462384ee92a0be7fac5f1413a1e35c56cc0461 \
--hash=sha256:91056c15fa70756691db97756772bb1eb9678fa585d9184f24534b100dc60f4a
wcwidth==0.2.5; python_version >= "3.7" and python_version < "4.0" \
--hash=sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784 \
--hash=sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83
zipp==3.3.0; python_version < "3.8" \
--hash=sha256:eed8ec0b8d1416b2ca33516a37a08892442f3954dee131e92cfd92d8fe3e7066 \
--hash=sha256:64ad89efee774d1897a58607895d80789c59778ea02185dd846ac38394a8642b
-i https://pypi.org/simple
attrs==19.3.0
backcall==0.1.0
decorator==4.4.1
entrypoints==0.3
flake8==3.7.9
ipython-genutils==0.2.0
ipython==7.9.0
jedi==0.15.1
mccabe==0.6.1
more-itertools==7.2.0
packaging==19.2
parso==0.5.1
pexpect==4.7.0 ; sys_platform != 'win32'
pickleshare==0.7.5
pluggy==0.13.1
prompt-toolkit==2.0.10
ptyprocess==0.6.0
py==1.8.0
pycodestyle==2.5.0
pyflakes==2.1.1
pygments==2.5.1
pyparsing==2.4.5
pytest==5.3.1
six==1.13.0
traitlets==4.3.3
wcwidth==0.1.7

View File

@ -1,66 +1,9 @@
certifi==2020.6.20 \
--hash=sha256:8fc0819f1f30ba15bdb34cceffb9ef04d99f420f68eb75d901e9560b8749fc41 \
--hash=sha256:5930595817496dd21bb8dc35dad090f1c2cd0adfaf21204bf6732ca5d8ee34d3
chardet==3.0.4 \
--hash=sha256:fc323ffcaeaed0e0a02bf4d117757b98aed530d9ed4531e3e15460124c106691 \
--hash=sha256:84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae
falcon==2.0.0 \
--hash=sha256:733033ec80c896e30a43ab3e776856096836787197a44eb21022320a61311983 \
--hash=sha256:f93351459f110b4c1ee28556aef9a791832df6f910bea7b3f616109d534df06b \
--hash=sha256:e9efa0791b5d9f9dd9689015ea6bce0a27fcd5ecbcd30e6d940bffa4f7f03389 \
--hash=sha256:59d1e8c993b9a37ea06df9d72cf907a46cc8063b30717cdac2f34d1658b6f936 \
--hash=sha256:a5ebb22a04c9cc65081938ee7651b4e3b4d2a28522ea8ec04c7bdd2b3e9e8cd8 \
--hash=sha256:95bf6ce986c1119aef12c9b348f4dee9c6dcc58391bdd0bc2b0bf353c2b15986 \
--hash=sha256:aa184895d1ad4573fbfaaf803563d02f019ebdf4790e41cc568a330607eae439 \
--hash=sha256:74cf1d18207381c665b9e6292d65100ce146d958707793174b03869dc6e614f4 \
--hash=sha256:24adcd2b29a8ffa9d552dc79638cd21736a3fb04eda7d102c6cebafdaadb88ad \
--hash=sha256:18157af2a4fc3feedf2b5dcc6196f448639acf01c68bc33d4d5a04c3ef87f494 \
--hash=sha256:e3782b7b92fefd46a6ad1fd8fe63fe6c6f1b7740a95ca56957f48d1aee34b357 \
--hash=sha256:9712975adcf8c6e12876239085ad757b8fdeba223d46d23daef82b47658f83a9 \
--hash=sha256:54f2cb4b687035b2a03206dbfc538055cc48b59a953187b0458aa1b574d47b53 \
--hash=sha256:eea593cf466b9c126ce667f6d30503624ef24459f118c75594a69353b6c3d5fc
gunicorn==20.0.4 \
--hash=sha256:cd4a810dd51bf497552cf3f863b575dabd73d6ad6a91075b65936b151cbf4f9c \
--hash=sha256:1904bb2b8a43658807108d59c3f3d56c2b6121a701161de0ddf9ad140073c626
idna==2.10 \
--hash=sha256:b97d804b1e9b523befed77c48dacec60e6dcb0b5391d57af6a65a312a90648c0 \
--hash=sha256:b307872f855b18632ce0c21c5e45be78c0ea7ae4c15c828c20788b26921eb3f6
psycopg2-binary==2.8.6 \
--hash=sha256:11b9c0ebce097180129e422379b824ae21c8f2a6596b159c7659e2e5a00e1aa0 \
--hash=sha256:d14b140a4439d816e3b1229a4a525df917d6ea22a0771a2a78332273fd9528a4 \
--hash=sha256:1fabed9ea2acc4efe4671b92c669a213db744d2af8a9fc5d69a8e9bc14b7a9db \
--hash=sha256:f5ab93a2cb2d8338b1674be43b442a7f544a0971da062a5da774ed40587f18f5 \
--hash=sha256:b4afc542c0ac0db720cf516dd20c0846f71c248d2b3d21013aa0d4ef9c71ca25 \
--hash=sha256:e74a55f6bad0e7d3968399deb50f61f4db1926acf4a6d83beaaa7df986f48b1c \
--hash=sha256:0deac2af1a587ae12836aa07970f5cb91964f05a7c6cdb69d8425ff4c15d4e2c \
--hash=sha256:ad20d2eb875aaa1ea6d0f2916949f5c08a19c74d05b16ce6ebf6d24f2c9f75d1 \
--hash=sha256:950bc22bb56ee6ff142a2cb9ee980b571dd0912b0334aa3fe0fe3788d860bea2 \
--hash=sha256:b8a3715b3c4e604bcc94c90a825cd7f5635417453b253499664f784fc4da0152 \
--hash=sha256:d1b4ab59e02d9008efe10ceabd0b31e79519da6fb67f7d8e8977118832d0f449 \
--hash=sha256:ac0c682111fbf404525dfc0f18a8b5f11be52657d4f96e9fcb75daf4f3984859 \
--hash=sha256:7d92a09b788cbb1aec325af5fcba9fed7203897bbd9269d5691bb1e3bce29550 \
--hash=sha256:aaa4213c862f0ef00022751161df35804127b78adf4a2755b9f991a507e425fd \
--hash=sha256:c2507d796fca339c8fb03216364cca68d87e037c1f774977c8fc377627d01c71 \
--hash=sha256:ee69dad2c7155756ad114c02db06002f4cded41132cc51378e57aad79cc8e4f4 \
--hash=sha256:e82aba2188b9ba309fd8e271702bd0d0fc9148ae3150532bbb474f4590039ffb \
--hash=sha256:d5227b229005a696cc67676e24c214740efd90b148de5733419ac9aaba3773da \
--hash=sha256:a0eb43a07386c3f1f1ebb4dc7aafb13f67188eab896e7397aa1ee95a9c884eb2 \
--hash=sha256:e1f57aa70d3f7cc6947fd88636a481638263ba04a742b4a37dd25c373e41491a \
--hash=sha256:833709a5c66ca52f1d21d41865a637223b368c0ee76ea54ca5bad6f2526c7679 \
--hash=sha256:ba28584e6bca48c59eecbf7efb1576ca214b47f05194646b081717fa628dfddf \
--hash=sha256:6a32f3a4cb2f6e1a0b15215f448e8ce2da192fd4ff35084d80d5e39da683e79b \
--hash=sha256:0e4dc3d5996760104746e6cfcdb519d9d2cd27c738296525d5867ea695774e67 \
--hash=sha256:cec7e622ebc545dbb4564e483dd20e4e404da17ae07e06f3e780b2dacd5cee66 \
--hash=sha256:ba381aec3a5dc29634f20692349d73f2d21f17653bda1decf0b52b11d694541f \
--hash=sha256:a0c50db33c32594305b0ef9abc0cb7db13de7621d2cadf8392a1d9b3c437ef77 \
--hash=sha256:2dac98e85565d5688e8ab7bdea5446674a83a3945a8f416ad0110018d1501b94 \
--hash=sha256:bd1be66dde2b82f80afb9459fc618216753f67109b859a361cf7def5c7968729 \
--hash=sha256:8cd0fb36c7412996859cb4606a35969dd01f4ea34d9812a141cd920c3b18be77 \
--hash=sha256:42ec1035841b389e8cc3692277a0bd81cdfe0b65d575a2c8862cec7a80e62e52 \
--hash=sha256:7312e931b90fe14f925729cde58022f5d034241918a5c4f9797cac62f6b3a9dd
requests==2.24.0 \
--hash=sha256:fe75cc94a9443b9246fc7049224f75604b113c36acb93f87b80ed42c44cbb898 \
--hash=sha256:b3559a131db72c33ee969480840fff4bb6dd111de7dd27c8ee1f820f4f00231b
urllib3==1.25.10 \
--hash=sha256:e7983572181f5e1522d9c98453462384ee92a0be7fac5f1413a1e35c56cc0461 \
--hash=sha256:91056c15fa70756691db97756772bb1eb9678fa585d9184f24534b100dc60f4a
-i https://pypi.org/simple
certifi==2019.9.11
chardet==3.0.4
falcon==2.0.0
gunicorn==20.0.4
idna==2.8
psycopg2-binary==2.8.4
requests==2.22.0
urllib3==1.25.7

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@ -1,7 +1,6 @@
from falcon import testing
import json
import pytest
from unittest.mock import patch
from dspace_statistics_api.app import api
@ -12,371 +11,57 @@ def client():
def test_get_docs(client):
"""Test requesting the documentation at the root."""
'''Test requesting the documentation at the root.'''
response = client.simulate_get("/")
response = client.simulate_get('/')
assert isinstance(response.content, bytes)
assert response.status_code == 200
def test_get_item(client):
"""Test requesting a single item."""
'''Test requesting a single item.'''
response = client.simulate_get("/item/c3910974-c3a5-4053-9dce-104aa7bb1621")
response = client.simulate_get('/item/17')
response_doc = json.loads(response.text)
assert isinstance(response_doc["downloads"], int)
assert isinstance(response_doc["id"], str)
assert isinstance(response_doc["views"], int)
assert isinstance(response_doc['downloads'], int)
assert isinstance(response_doc['id'], int)
assert isinstance(response_doc['views'], int)
assert response.status_code == 200
def test_get_missing_item(client):
"""Test requesting a single non-existing item."""
'''Test requesting a single non-existing item.'''
response = client.simulate_get("/item/c3910974-c3a5-4053-9dce-104aa7bb1620")
response = client.simulate_get('/item/1')
assert response.status_code == 404
def test_get_items(client):
"""Test requesting 100 items."""
'''Test requesting 100 items.'''
response = client.simulate_get("/items", query_string="limit=100")
response = client.simulate_get('/items', query_string='limit=100')
response_doc = json.loads(response.text)
assert isinstance(response_doc["currentPage"], int)
assert isinstance(response_doc["totalPages"], int)
assert isinstance(response_doc["statistics"], list)
assert isinstance(response_doc['currentPage'], int)
assert isinstance(response_doc['totalPages'], int)
assert isinstance(response_doc['statistics'], list)
assert response.status_code == 200
def test_get_items_invalid_limit(client):
"""Test requesting 100 items with an invalid limit parameter."""
'''Test requesting 100 items with an invalid limit parameter.'''
response = client.simulate_get("/items", query_string="limit=101")
response = client.simulate_get('/items', query_string='limit=101')
assert response.status_code == 400
def test_get_items_invalid_page(client):
"""Test requesting 100 items with an invalid page parameter."""
'''Test requesting 100 items with an invalid page parameter.'''
response = client.simulate_get("/items", query_string="page=-1")
assert response.status_code == 400
@pytest.mark.xfail
def test_post_items_valid_dateFrom(client):
"""Test POSTing a request with a valid dateFrom parameter in the request body."""
request_body = {
"dateFrom": "2020-01-01T00:00:00Z",
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 100
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 2
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
assert isinstance(response.json["statistics"][1]["views"], int)
assert isinstance(response.json["statistics"][1]["downloads"], int)
def test_post_items_valid_dateFrom_mocked(client):
"""Mock test POSTing a request with a valid dateFrom parameter in the request body."""
request_body = {
"dateFrom": "2020-01-01T00:00:00Z",
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
get_views_return_value = {
"c3910974-c3a5-4053-9dce-104aa7bb1620": 21,
"887cc5f8-b5e7-4a2f-9053-49c91ab81313": 0,
}
get_downloads_return_value = {
"c3910974-c3a5-4053-9dce-104aa7bb1620": 575,
"887cc5f8-b5e7-4a2f-9053-49c91ab81313": 899,
}
with patch(
"dspace_statistics_api.app.get_views", return_value=get_views_return_value
):
with patch(
"dspace_statistics_api.app.get_downloads",
return_value=get_downloads_return_value,
):
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 100
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 2
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
assert isinstance(response.json["statistics"][1]["views"], int)
assert isinstance(response.json["statistics"][1]["downloads"], int)
def test_post_items_invalid_dateFrom(client):
"""Test POSTing a request with an invalid dateFrom parameter in the request body."""
request_body = {
"dateFrom": "2020-01-01T00:00:00",
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 400
@pytest.mark.xfail
def test_post_items_valid_dateTo(client):
"""Test POSTing a request with a valid dateTo parameter in the request body."""
request_body = {
"dateTo": "2020-01-01T00:00:00Z",
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 100
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 2
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
assert isinstance(response.json["statistics"][1]["views"], int)
assert isinstance(response.json["statistics"][1]["downloads"], int)
def test_post_items_valid_dateTo_mocked(client):
"""Mock test POSTing a request with a valid dateTo parameter in the request body."""
request_body = {
"dateTo": "2020-01-01T00:00:00Z",
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
get_views_return_value = {
"c3910974-c3a5-4053-9dce-104aa7bb1620": 21,
"887cc5f8-b5e7-4a2f-9053-49c91ab81313": 0,
}
get_downloads_return_value = {
"c3910974-c3a5-4053-9dce-104aa7bb1620": 575,
"887cc5f8-b5e7-4a2f-9053-49c91ab81313": 899,
}
with patch(
"dspace_statistics_api.app.get_views", return_value=get_views_return_value
):
with patch(
"dspace_statistics_api.app.get_downloads",
return_value=get_downloads_return_value,
):
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 100
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 2
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
assert isinstance(response.json["statistics"][1]["views"], int)
assert isinstance(response.json["statistics"][1]["downloads"], int)
def test_post_items_invalid_dateTo(client):
"""Test POSTing a request with an invalid dateTo parameter in the request body."""
request_body = {
"dateFrom": "2020-01-01T00:00:00",
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 400
@pytest.mark.xfail
def test_post_items_valid_limit(client):
"""Test POSTing a request with a valid limit parameter in the request body."""
request_body = {
"limit": 1,
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 1
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 1
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
def test_post_items_valid_limit_mocked(client):
"""Mock test POSTing a request with a valid limit parameter in the request body."""
request_body = {
"limit": 1,
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
get_views_return_value = {"c3910974-c3a5-4053-9dce-104aa7bb1620": 21}
get_downloads_return_value = {"c3910974-c3a5-4053-9dce-104aa7bb1620": 575}
with patch(
"dspace_statistics_api.app.get_views", return_value=get_views_return_value
):
with patch(
"dspace_statistics_api.app.get_downloads",
return_value=get_downloads_return_value,
):
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 1
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 1
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
def test_post_items_invalid_limit(client):
"""Test POSTing a request with an invalid limit parameter in the request body."""
request_body = {
"limit": -1,
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 400
@pytest.mark.xfail
def test_post_items_valid_page(client):
"""Test POSTing a request with a valid page parameter in the request body."""
request_body = {
"page": 0,
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 100
assert response.json["currentPage"] == 0
assert response.json["totalPages"] == 0
assert len(response.json["statistics"]) == 2
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
assert isinstance(response.json["statistics"][1]["views"], int)
assert isinstance(response.json["statistics"][1]["downloads"], int)
def test_post_items_valid_page_mocked(client):
"""Mock test POSTing a request with a valid page parameter in the request body."""
request_body = {
"page": 0,
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
get_views_return_value = {
"c3910974-c3a5-4053-9dce-104aa7bb1620": 21,
"887cc5f8-b5e7-4a2f-9053-49c91ab81313": 0,
}
get_downloads_return_value = {
"c3910974-c3a5-4053-9dce-104aa7bb1620": 575,
"887cc5f8-b5e7-4a2f-9053-49c91ab81313": 899,
}
with patch(
"dspace_statistics_api.app.get_views", return_value=get_views_return_value
):
with patch(
"dspace_statistics_api.app.get_downloads",
return_value=get_downloads_return_value,
):
response = client.simulate_post("/items", json=request_body)
assert response.status_code == 200
assert response.json["limit"] == 100
assert response.json["currentPage"] == 0
assert isinstance(response.json["totalPages"], int)
assert len(response.json["statistics"]) == 2
assert isinstance(response.json["statistics"][0]["views"], int)
assert isinstance(response.json["statistics"][0]["downloads"], int)
assert isinstance(response.json["statistics"][1]["views"], int)
assert isinstance(response.json["statistics"][1]["downloads"], int)
def test_post_items_invalid_page(client):
"""Test POSTing a request with an invalid page parameter in the request body."""
request_body = {
"page": -1,
"items": [
"c3910974-c3a5-4053-9dce-104aa7bb1620",
"887cc5f8-b5e7-4a2f-9053-49c91ab81313",
],
}
response = client.simulate_post("/items", json=request_body)
response = client.simulate_get('/items', query_string='page=-1')
assert response.status_code == 400