1
0
mirror of https://github.com/gsi-upm/senpy synced 2024-12-22 04:58:12 +00:00

WIP: working on a full refactor for v2.0

This is still not functional, because it involves a LOT of changes to
the basic structure of the project. Some of the main changes can be seen
in the CHANGELOG.md file, if you're interested, but it boils down to
simplifying the logic of plugins (no more activation/deactivation
shenanigans), more robust typing and use of schemas (pydantic) to
avoid inconsistencies and user errors.
This commit is contained in:
J. Fernando Sánchez 2024-12-13 00:01:27 +01:00
parent 9414b0e3e6
commit 54e4dcd5d4
54 changed files with 919 additions and 1487 deletions

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@ -5,17 +5,20 @@ 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).
## [Unreleased]
### Changed
* Changed the underlying model to use `pydantic` models
* Plugin interface slightly changed. Activation should be performed in the `activate` method
* data directory selection logic is slightly modified, and will choose one of the following (in this order): `data_folder` (argument), `$SENPY_DATA` or `$CWD`
* Plugins cannot be deactivated
### Fixed
* Tests now use strict mode to detect errors on optional plugins
* Tests now detect errors on optional plugins
### Added
* The code of many senpy community plugins have been included by default. However, additional files (e.g., licensed data) and/or installing additional dependencies may be necessary for some plugins. Read each plugin's documentation for more information.
* `optional` attribute in plugins. Optional plugins may fail to load or activate but the server will be started regardless, unless running in strict mode
* `--strict` flag to set strict mode. In this mode, the server will not start when optional plugins fail to load
* Option in shelf plugins to ignore pickling errors
### Removed
* `--only-install`, `--only-test` and `--only-list` flags were removed in favor of `--no-run` + `--install`/`--test`/`--dependencies`
### Changed
* data directory selection logic is slightly modified, and will choose one of the following (in this order): `data_folder` (argument), `$SENPY_DATA` or `$CWD`
## [1.0.6]
### Fixed

9
TODO.md Normal file
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@ -0,0 +1,9 @@
* Upload context to www.gsi.upm.es/ontologies/senpy
* Use context from gsi.upm.es
* Add example of morality analysis
* Simplify plugin loading
* Simplify models
* Remove json schemas and generate pydantic objects
* Remove some of the meta-programming magic
* Migrate to openapi/quart

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@ -0,0 +1,42 @@
{
"@context": "http://senpy.gsi.upm.es/api/contexts/YXBpP2FsZ289ZW1",
"@id": ":Result1",
"@type": "results",
"activities": [
{
"@id": ":MoralAnalysis1_Activity",
"@type": "amor:MoralValueAnalysis",
"prov:wasAssociatedWith": ":MoralAnalysis1",
"amor:usedMoralValueModel": "amor-mft:MoralFoundationsTheory",
"amor:analysed": "news1",
"amor:usedMLModel": ":model1",
"prov:generated": ":annotation3"
}
],
"entries": [
{
"@id": "http://micro.blog/status1",
"@type": [
"nif:RFC5147String",
"nif:Context"
],
"nif:isString": "Dear Microsoft, put your Windows Phone on your newest #open technology program. You'll be awesome. #opensource",
"morality": [
{
"@id": ":annotation3",
"@type": "amor:MoralValueAnnotation",
"nif:beginIndex": 80,
"nif:endIndex": 97,
"amor:hasMoralValueCategory": "mft:Authority",
"amor:confidence": 0.75,
"amor-mft:hasPolarityIntensity": 0.2,
"amor:annotated": "http://micro.blog/status1",
"nif:anchorOf": "You'll be awesome.",
"prov:wasGeneratedBy": ":MoralAnalysis1_Activity"
}
],
"emotions": [
]
}
]
}

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@ -1,53 +0,0 @@
#
# Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from senpy import AnalysisPlugin
import multiprocessing
def _train(process_number):
return process_number
class Async(AnalysisPlugin):
'''An example of an asynchronous module'''
author = '@balkian'
version = '0.2'
sync = False
def _do_async(self, num_processes):
pool = multiprocessing.Pool(processes=num_processes)
values = sorted(pool.map(_train, range(num_processes)))
return values
def activate(self):
self.value = self._do_async(4)
def analyse_entry(self, entry, params):
values = self._do_async(2)
entry.async_values = values
yield entry
test_cases = [
{
'input': 'any',
'expected': {
'async_values': [0, 1]
}
}
]

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@ -24,8 +24,8 @@ import basic
class BasicAnalyseEntry(plugins.SentimentPlugin):
'''Equivalent to Basic, implementing the analyse_entry method'''
author = '@balkian'
version = '0.1'
author: str = '@balkian'
version: str = '0.1'
mappings = {
'pos': 'marl:Positive',
@ -43,7 +43,7 @@ class BasicAnalyseEntry(plugins.SentimentPlugin):
entry.sentiments.append(s)
yield entry
test_cases = [{
test_cases: list[dict] = [{
'input': 'Hello :)',
'polarity': 'marl:Positive'
}, {

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@ -24,8 +24,8 @@ import basic
class BasicBox(SentimentBox):
''' A modified version of Basic that also does converts annotations manually'''
author = '@balkian'
version = '0.1'
author: str = '@balkian'
version: str = '0.1'
def predict_one(self, features, **kwargs):
output = basic.get_polarity(features[0])
@ -35,7 +35,7 @@ class BasicBox(SentimentBox):
return [0, 0, 1]
return [0, 1, 0]
test_cases = [{
test_cases: list[dict] = [{
'input': 'Hello :)',
'polarity': 'marl:Positive'
}, {

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@ -25,8 +25,8 @@ import basic
class Basic(SentimentBox):
'''Provides sentiment annotation using a lexicon'''
author = '@balkian'
version = '0.1'
author: str = '@balkian'
version: str = '0.1'
def predict_one(self, features, **kwargs):
output = basic.get_polarity(features[0])
@ -36,7 +36,7 @@ class Basic(SentimentBox):
return [0, 1, 0]
return [0, 0, 1]
test_cases = [{
test_cases: list[dict] = [{
'input': u'Hello :)',
'polarity': 'marl:Positive'
}, {

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@ -25,8 +25,8 @@ import basic
class Dictionary(plugins.SentimentPlugin):
'''Sentiment annotation using a configurable lexicon'''
author = '@balkian'
version = '0.2'
author: str = '@balkian'
version: str = '0.2'
dictionaries = [basic.emojis, basic.emoticons]
@ -42,7 +42,7 @@ class Dictionary(plugins.SentimentPlugin):
entry.sentiments.append(s)
yield entry
test_cases = [{
test_cases: list[dict] = [{
'input': 'Hello :)',
'polarity': 'marl:Positive'
}, {
@ -61,7 +61,7 @@ class EmojiOnly(Dictionary):
'''Sentiment annotation with a basic lexicon of emojis'''
dictionaries = [basic.emojis]
test_cases = [{
test_cases: list[dict] = [{
'input': 'Hello :)',
'polarity': 'marl:Neutral'
}, {
@ -80,7 +80,7 @@ class EmoticonsOnly(Dictionary):
'''Sentiment annotation with a basic lexicon of emoticons'''
dictionaries = [basic.emoticons]
test_cases = [{
test_cases: list[dict] = [{
'input': 'Hello :)',
'polarity': 'marl:Positive'
}, {
@ -102,7 +102,7 @@ class Salutes(Dictionary):
'marl:Negative': ['Good bye', ]
}]
test_cases = [{
test_cases: list[dict] = [{
'input': 'Hello :)',
'polarity': 'marl:Positive'
}, {

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@ -19,15 +19,15 @@ from senpy import AnalysisPlugin, easy
class Dummy(AnalysisPlugin):
'''This is a dummy self-contained plugin'''
author = '@balkian'
version = '0.1'
author: str = '@balkian'
version: str = '0.1'
def analyse_entry(self, entry, params):
entry['nif:isString'] = entry['nif:isString'][::-1]
entry.text = entry.text[::-1]
entry.reversed = entry.get('reversed', 0) + 1
yield entry
test_cases = [{
test_cases: list[dict] = [{
'entry': {
'nif:isString': 'Hello',
},

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@ -19,9 +19,9 @@ from senpy import AnalysisPlugin, easy
class DummyRequired(AnalysisPlugin):
'''This is a dummy self-contained plugin'''
author = '@balkian'
version = '0.1'
extra_params = {
author: str = '@balkian'
version: str = '0.1'
extra_params: dict = {
'example': {
'description': 'An example parameter',
'required': True,
@ -30,11 +30,11 @@ class DummyRequired(AnalysisPlugin):
}
def analyse_entry(self, entry, params):
entry['nif:isString'] = entry['nif:isString'][::-1]
entry.text = entry.text[::-1]
entry.reversed = entry.get('reversed', 0) + 1
yield entry
test_cases = [{
test_cases: list[dict] = [{
'entry': {
'nif:isString': 'Hello',
},

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@ -22,11 +22,11 @@ from senpy.models import EmotionSet, Emotion, Entry
class EmoRand(EmotionPlugin):
'''A sample plugin that returns a random emotion annotation'''
name = 'emotion-random'
author = '@balkian'
version = '0.1'
url = "https://github.com/gsi-upm/senpy-plugins-community"
onyx__usesEmotionModel = "emoml:big6"
name: str = 'emotion-random'
author: str = '@balkian'
version: str = '0.1'
url: str = "https://github.com/gsi-upm/senpy-plugins-community"
usesEmotionModel: str = "emoml:big6"
def analyse_entry(self, entry, activity):
category = "emoml:big6happiness"

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@ -0,0 +1,63 @@
@prefix : <http://www.gsi.upm.es/ontologies/amor/examples#> .
@prefix amor: <http://www.gsi.upm.es/ontologies/amor/ns#> .
@prefix amor-bhv: <http://www.gsi.upm.es/ontologies/amor/models/bhv/ns#> .
@prefix amor-mft: <http://www.gsi.upm.es/ontologies/amor/models/mft/ns#> .
@prefix bhv: <http://www.gsi.upm.es/ontologies/bhv#> .
@prefix mft: <http://www.gsi.upm.es/ontologies/mft/ns#> .
@prefix mls: <http://www.w3.org/ns/mls#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix schema: <http://schema.org/> .
:news1 a owl:NamedIndividual, schema:NewsArticle ;
schema:articleBody "Director Comey says the probe into last year's US election would assess if crimes were committed."^^xsd:string ;
schema:datePublished "2017-03-20T20:30:54+00:00"^^schema:Date ;
schema:headline "Trump Russia claims: FBI's Comey confirms investigation of election 'interference'"^^xsd:string ;
schema:image <http://ichef-1.bbci.co.uk/news/560/media/images/75306000/jpg/_75306515_line976.jpg>,
<http://ichef.bbci.co.uk/news/560/cpsprodpb/8AB9/production/_95231553_comey2.jpg>,
<http://ichef.bbci.co.uk/news/560/cpsprodpb/17519/production/_95231559_committee.jpg>,
<http://ichef.bbci.co.uk/news/560/cpsprodpb/CC81/production/_95235325_f704a6dc-c017-4971-aac3-04c03eb097fb.jpg>,
<http://ichef-1.bbci.co.uk/news/560/cpsprodpb/11AA1/production/_95235327_c0b59f9e-316e-4641-aa7e-3fec6daea62b.jpg>,
<http://ichef.bbci.co.uk/news/560/cpsprodpb/0F99/production/_95239930_trumptweet.png>,
<http://ichef-1.bbci.co.uk/news/560/cpsprodpb/10DFA/production/_95241196_mediaitem95241195.jpg>,
<http://ichef.bbci.co.uk/news/560/cpsprodpb/2CA0/production/_95242411_comey.jpg>,
<http://ichef.bbci.co.uk/news/560/cpsprodpb/11318/production/_95242407_mediaitem95242406.jpg>,
<http://ichef-1.bbci.co.uk/news/560/cpsprodpb/BCED/production/_92856384_line976.jpg>,
<http://ichef-1.bbci.co.uk/news/560/cpsprodpb/12B64/production/_95244667_mediaitem95244666.jpg> ;
schema:mainEntityOfPage <http://www.bbc.com/news/world-us-canada-39324587> ;
schema:publisher :bbc ;
schema:url <http://www.bbc.com/news/world-us-canada-39324587> .
:bbc a schema:Organization ;
schema:logo <http://www.bbc.co.uk/news/special/2015/newsspec_10857/bbc_news_logo.png?cb=1> ;
schema:name "BBC News"^^xsd:string .
:robot1 a prov:SoftwareAgent .
:model1 a mls:Model .
:logisticRegression a mls:Algorithm ;
rdfs:label "Logistic Regression"@en ,
"Regresión Logística"@es .
:run1 a mls:Run ;
mls:executes :wekaLogistic ;
mls:hasInput :credit-a ;
mls:hasOutput :model1 ;
mls:realizes :logisticRegression .
:analysis3 a amor:MoralValueAnalysis ;
prov:wasAssociatedWith :robot1 ;
amor:usedMoralValueModel amor-mft:MoralFoundationsTheory ;
amor:analysed :news1 ;
amor:usedMLModel :model1 ;
prov:generated :annotation3 .
:annotation3 a amor:MoralValueAnnotation ;
amor:hasMoralValueCategory mft:Authority ;
amor:confidence "0.75"^^xsd:float ;
amor-mft:hasPolarityIntensity "0.2"^^xsd:float ;
amor:annotated :news1 .

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@ -0,0 +1,10 @@
from senpy.ns import amor, amor_bhv, amor_mft, prov
from senpy.plugins import MoralityPlugin
class DummyMoralityPlugin(MoralityPlugin):
moralValueModel: str = amor_mft["MoralFoundationTHeory"]
def annotate(self, entry, activity, **kwargs):
yield MoralAnnotation(amor_bhv['Conservation'],
confidence=1.8)

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@ -21,7 +21,7 @@ from senpy.plugins import SentimentPlugin
class NoOp(SentimentPlugin):
'''This plugin does nothing. Literally nothing.'''
version = 0
version: str = 0
def analyse_entry(self, entry, *args, **kwargs):
yield entry

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@ -24,11 +24,10 @@ import basic
class ParameterizedDictionary(plugins.SentimentPlugin):
'''This is a basic self-contained plugin'''
author: str = '@balkian'
version: str = '0.2'
author = '@balkian'
version = '0.2'
extra_params = {
extra_params: dict = {
'positive-words': {
'description': 'Comma-separated list of words that are considered positive',
'aliases': ['positive'],
@ -56,7 +55,7 @@ class ParameterizedDictionary(plugins.SentimentPlugin):
entry.sentiments.append(s)
yield entry
test_cases = [
test_cases: list[dict] = [
{
'input': 'Hello :)',
'polarity': 'marl:Positive',

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@ -20,12 +20,12 @@ from senpy import SentimentPlugin, Sentiment, Entry
class RandSent(SentimentPlugin):
'''A sample plugin that returns a random sentiment annotation'''
name = 'sentiment-random'
author = "@balkian"
version = '0.1'
url = "https://github.com/gsi-upm/senpy-plugins-community"
marl__maxPolarityValue = '1'
marl__minPolarityValue = "-1"
name: str = 'sentiment-random'
author: str = "@balkian"
version: str = '0.1'
url: str = "https://github.com/gsi-upm/senpy-plugins-community"
maxPolarityValue: float = 1
minPolarityValue: float = -1
def analyse_entry(self, entry, activity):
polarity_value = max(-1, min(1, random.gauss(0.2, 0.2)))

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@ -22,8 +22,8 @@ from mypipeline import pipeline
class PipelineSentiment(SentimentBox):
'''This is a pipeline plugin that wraps a classifier defined in another module
(mypipeline).'''
author = '@balkian'
version = 0.1
author: str = '@balkian'
version: str = 0.1
maxPolarityValue = 1
minPolarityValue = -1
@ -32,7 +32,7 @@ class PipelineSentiment(SentimentBox):
return [1, 0, 0]
return [0, 0, 1]
test_cases = [
test_cases: list[dict] = [
{
'input': 'The sentiment for senpy should be positive :)',
'polarity': 'marl:Positive'

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@ -20,10 +20,10 @@ from time import sleep
class Sleep(AnalysisPlugin):
'''Dummy plugin to test async'''
author = "@balkian"
version = "0.2"
author: str = "@balkian"
version: str = "0.2"
timeout = 0.05
extra_params = {
extra_params: dict = {
"timeout": {
"@id": "timeout_sleep",
"aliases": ["timeout", "to"],
@ -32,7 +32,8 @@ class Sleep(AnalysisPlugin):
}
}
def activate(self, *args, **kwargs):
def __init__(self, **kwargs):
super().__init__(**kwargs)
sleep(self.timeout)
def analyse_entry(self, entry, params):

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@ -13,3 +13,4 @@ scipy
scikit-learn>=0.20
responses
jmespath
deprecation==2.1.0

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@ -137,7 +137,7 @@ def main():
'--fail',
action='store_true',
default=False,
help='Do not exit if some plugins fail to activate')
help='Do not exit if some plugins can not be instantiated')
parser.add_argument(
'--enable-cors',
'--cors',
@ -165,13 +165,14 @@ def main():
install=args.install,
strict=args.strict,
data_folder=args.data_folder)
folders = list(args.plugins_folder) if args.plugins_folder else []
if not folders:
folders.append(".")
for p in folders:
sp.add_folder(p)
plugins = sp.plugins(plugin_type=None, is_activated=False)
plugins = sp.plugins(plugin_type=None)
maxname = max(len(x.name) for x in plugins)
maxversion = max(len(str(x.version)) for x in plugins)
print('Found {} plugins:'.format(len(plugins)))
@ -187,7 +188,7 @@ def main():
print('Listing dependencies')
missing = []
installed = []
for plug in sp.plugins(is_activated=False):
for plug in sp.plugins():
inst, miss, nltkres = list_dependencies(plug)
if not any([inst, miss, nltkres]):
continue
@ -209,17 +210,11 @@ def main():
sp.install_deps()
if args.test:
sp.activate_all(sync=True)
easy_test(sp.plugins(is_activated=True), debug=args.debug)
easy_test(sp.plugins(), debug=args.debug)
if args.no_run:
return
sp.activate_all(sync=True)
if sp.strict:
inactive = sp.plugins(is_activated=False)
assert not inactive
print('Senpy version {}'.format(senpy.__version__))
print('Server running on port %s:%d. Ctrl+C to quit' % (args.host,
args.port))
@ -238,8 +233,6 @@ def main():
debug=app.debug)
except KeyboardInterrupt:
print('Bye!')
sp.deactivate_all()
if __name__ == '__main__':
main()

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@ -15,7 +15,8 @@
#
from future.utils import iteritems
from .models import Error, Results, Entry, from_string
from .models import Results, Entry, from_string
from .errors import Error, InvalidParams
import logging
logger = logging.getLogger(__name__)
@ -169,7 +170,7 @@ EVAL_PARAMS = {
"aliases": ["plug", "p", "plugins", "algorithms", 'algo', 'a', 'plugin'],
"description": "Plugins to evaluate",
"required": True,
"help": "See activated plugins in /plugins",
"help": "See plugins at /plugins",
"processor": API_PARAMS['algorithm']['processor']
},
"dataset": {
@ -294,12 +295,7 @@ def parse_params(indict, *specs):
wrong_params[param] = spec[param]
if wrong_params:
logger.debug("Error parsing: %s", wrong_params)
message = Error(
status=400,
message='Missing or invalid parameters',
parameters=outdict,
errors=wrong_params)
raise message
raise InvalidParams(wrong_params)
return outdict
@ -315,10 +311,9 @@ def get_all_params(plugins, *specs):
def get_extra_params(plugins):
'''Get a list of possible parameters given a list of plugins'''
params = {}
extra_params = {}
extra_params: dict = {}
for plugin in plugins:
this_params = plugin.get('extra_params', {})
for k, v in this_params.items():
for k, v in plugin.extra_params.items():
if k not in extra_params:
extra_params[k] = {}
extra_params[k][plugin.name] = v
@ -372,7 +367,7 @@ def parse_analyses(params, plugins):
if not plugin:
continue
this_params = filter_params(params, plugin, i)
parsed = parse_params(this_params, plugin.get('extra_params', {}))
parsed = parse_params(this_params, plugin.extra_params)
analysis = plugin.activity(parsed)
analysis_list.append(analysis)
return analysis_list
@ -414,7 +409,7 @@ def parse_call(params):
params = parse_params(params, NIF_PARAMS)
if params['informat'] == 'text':
results = Results()
entry = Entry(nif__isString=params['input'], id='prefix:') # Use @base
entry = Entry(text=params['input'], id='prefix:') # Use @base
results.entries.append(entry)
elif params['informat'] == 'json-ld':
results = from_string(params['input'], cls=Results)

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@ -20,7 +20,8 @@ Blueprints for Senpy
"""
from flask import (Blueprint, request, current_app, render_template, url_for,
jsonify, redirect)
from .models import Error, Response, Help, Plugins, read_schema, dump_schema, Datasets
from .models import BASE_CONTEXT, Help, Plugins, Datasets
from .errors import Error
from . import api
from .version import __version__
from functools import wraps
@ -102,7 +103,7 @@ def index():
@api_blueprint.route('/contexts/<code>')
def context(code=''):
context = Response._context
context = BASE_CONTEXT
context['@base'] = url_for('api.decode', code=code, _external=True)
context['endpoint'] = url_for('api.api_root', _external=True)
return jsonify({"@context": context})
@ -113,22 +114,58 @@ def decode(code):
try:
return redirect(decoded_url(code))
except Exception:
return Error('invalid URL').flask()
return to_flask(Error('invalid URL'))
@ns_blueprint.route('/') # noqa: F811
def index():
context = Response._context.copy()
context = BASE_CONTEXT.copy()
context['endpoint'] = url_for('api.api_root', _external=True)
return jsonify({"@context": context})
@api_blueprint.route('/schemas/<schema>')
def schema(schema="definitions"):
try:
return dump_schema(read_schema(schema))
except Exception as ex: # Should be FileNotFoundError, but it's missing from py2
return Error(message="Schema not found: {}".format(ex), status=404).flask()
# from .models import read_schema, dump_schema
#@api_blueprint.route('/schemas/<schema>')
#def schema(schema="definitions"):
# try:
# return dump_schema(read_schema(schema))
# except Exception as ex: # Should be FileNotFoundError, but it's missing from py2
# return Error(message="Schema not found: {}".format(ex), status=404).flask()
def to_flask(resp,
in_headers=False,
headers=None,
outformat='json-ld',
**kwargs):
"""
Return the values and error to be used in flask.
So far, it returns a fixed context. We should store/generate different
contexts if the plugin adds more aliases.
"""
headers = headers or {}
if isinstance(resp, Error):
status = resp.code
resp = resp.to_response()
else:
status = 200
kwargs["with_context"] = not in_headers
content, mimetype = resp.serialize(format=outformat,
with_mime=True,
**kwargs)
if outformat == 'json-ld' and in_headers:
headers.update({
"Link":
('<%s>;'
'rel="http://www.w3.org/ns/json-ld#context";'
' type="application/ld+json"' % kwargs.get('context_uri'))
})
return FlaskResponse(
response=content,
status=status,
headers=headers,
mimetype=mimetype)
def basic_api(f):
@ -171,7 +208,7 @@ def basic_api(f):
prefix = params.get('prefix')
code = encode_url(prefix)
return response.flask(
return to_flask(response,
in_headers=params['in-headers'],
headers=headers,
prefix=prefix or url_for_code(code),
@ -195,11 +232,10 @@ def basic_api(f):
response = ex
response.parameters = raw_params
logger.exception(ex)
return response.flask(
return to_flask(response,
outformat=outformat,
expanded=params['expanded-jsonld'],
verbose=params.get('verbose', True),
)
verbose=params.get('verbose', True))
return decorated_function

View File

@ -16,7 +16,7 @@
from __future__ import print_function
import sys
from .models import Error
from .errors import Error
from .extensions import Senpy
from . import api
@ -49,11 +49,6 @@ def main_function(argv):
sp = Senpy(default_plugins=default_plugins, plugin_folder=plugin_folder)
request = api.parse_call(params)
algos = sp.get_plugins(request.parameters.get('algorithm', None))
if algos:
for algo in algos:
sp.activate_plugin(algo.name)
else:
sp.activate_all()
res = sp.analyse(request)
return res

23
senpy/errors.py Normal file
View File

@ -0,0 +1,23 @@
from .models import ErrorResponse
class Error(Exception):
def __init__(self, message='Generic senpy exception', errors=[]):
Exception.__init__(self, message)
self.message = message
self.errors = errors
def toResponse(self) -> ErrorResponse:
return ErrorResponse(self.message)
def __str__(self):
if not hasattr(self, 'errors'):
return self.message
return '{}:\n\t{}'.format(self.message, self.errors)
def __hash__(self):
return Exception.__hash__(self)
class InvalidParams(Error):
def __init__(self, wrong_params):
super().__init__(message='Wrong parameters:\n\t{}'.format(wrong_params))

View File

@ -15,14 +15,15 @@
#
"""
Main class for Senpy.
It orchestrates plugin (de)activation and analysis.
It orchestrates plugin discovery, creation and analysis.
"""
from future import standard_library
standard_library.install_aliases()
from . import config
from . import plugins, api
from .models import Error, AggregatedEvaluation
from .models import AggregatedEvaluation
from .errors import Error
from .plugins import AnalysisPlugin
from .blueprints import api_blueprint, demo_blueprint, ns_blueprint
@ -43,7 +44,7 @@ class Senpy(object):
def __init__(self,
app=None,
plugin_folder=".",
plugin_folders=[".", ],
data_folder=None,
install=False,
strict=None,
@ -62,16 +63,18 @@ class Senpy(object):
self._default = None
self.strict = strict if strict is not None else config.strict
self.strict = True # TODO: remove this after tests pass
self.install = install
self._plugins = {}
if plugin_folder:
self.add_folder(plugin_folder)
self.plugin_folders = plugin_folders
for folder in plugin_folders:
self._add_folder(folder)
if default_plugins:
self.add_folder('plugins', from_root=True)
self._add_folder('plugins', from_root=True)
else:
# Add only conversion plugins
self.add_folder(os.path.join('plugins', 'postprocessing'),
self._add_folder(os.path.join('plugins', 'postprocessing'),
from_root=True)
self.app = app
if app is not None:
@ -98,17 +101,18 @@ class Senpy(object):
app.register_blueprint(demo_blueprint, url_prefix="/")
def add_plugin(self, plugin):
self._plugins[plugin.name.lower()] = plugin
name = plugin.name.lower()
assert name
self._plugins[name] = plugin
self._conversion_candidates = {}
def delete_plugin(self, plugin):
del self._plugins[plugin.name.lower()]
def plugins(self, plugin_type=None, is_activated=True, **kwargs):
def plugins(self, plugin_type=None, **kwargs):
""" Return the plugins registered for a given application. Filtered by criteria """
return sorted(plugins.pfilter(self._plugins,
plugin_type=plugin_type,
is_activated=is_activated,
**kwargs),
key=lambda x: x.id)
@ -149,7 +153,7 @@ class Senpy(object):
candidates = self.plugins(**kwargs)
return list(plugins.pfilter(candidates, plugin_type=AnalysisPlugin))
def add_folder(self, folder, from_root=False):
def _add_folder(self, folder, from_root=False):
""" Find plugins in this folder and add them to this instance """
if from_root:
folder = os.path.join(os.path.dirname(__file__), folder)
@ -163,25 +167,21 @@ class Senpy(object):
else:
raise AttributeError("Not a folder or does not exist: %s", folder)
def _process(self, req, pending, done=None):
def _process(self, req, pending):
"""
Recursively process the entries with the first plugin in the list, and pass the results
to the rest of the plugins.
"""
done = done or []
if not pending:
return req
analysis = pending[0]
results = analysis.run(req)
results.activities.append(analysis)
done += analysis
return self._process(results, pending[1:], done)
return self._process(results, pending[1:])
def install_deps(self):
logger.info('Installing dependencies')
# If a plugin is activated, its dependencies should already be installed
# Otherwise, it would've failed to activate.
plugins.install_deps(*self._plugins.values())
def analyse(self, request, analyses=None):
@ -263,6 +263,7 @@ class Senpy(object):
i.emotions = newemotions
newentries.append(i)
resp.entries = newentries
resp.activities.extend(done)
return resp
def _conversion_candidate(self, fromModel, toModel):
@ -330,7 +331,7 @@ class Senpy(object):
@property
def default_plugin(self):
if not self._default or not self._default.is_activated:
if not self._default:
candidates = self.analysis_plugins()
if len(candidates) > 0:
self._default = candidates[0]
@ -342,84 +343,10 @@ class Senpy(object):
@default_plugin.setter
def default_plugin(self, value):
if isinstance(value, plugins.Plugin):
if not value.is_activated:
raise AttributeError('The default plugin has to be activated.')
self._default = value
else:
self._default = self._plugins[value.lower()]
def activate_all(self, sync=True):
ps = []
for plug in self._plugins.keys():
try:
self.activate_plugin(plug, sync=sync)
except Exception as ex:
if self.strict:
raise
logger.error('Could not activate {}: {}'.format(plug, ex))
return ps
def deactivate_all(self, sync=True):
ps = []
for plug in self._plugins.keys():
ps.append(self.deactivate_plugin(plug, sync=sync))
return ps
def _activate(self, plugin):
with plugin._lock:
if plugin.is_activated:
return
try:
logger.info("Activating plugin: {}".format(plugin.name))
assert plugin._activate()
logger.info(f"Plugin activated: {plugin.name}")
except Exception as ex:
if getattr(plugin, "optional", False) and not self.strict:
logger.info(f"Plugin could NOT be activated: {plugin.name}")
return False
raise
return plugin.is_activated
def activate_plugin(self, plugin_name, sync=True):
plugin_name = plugin_name.lower()
if plugin_name not in self._plugins:
raise Error(
message="Plugin not found: {}".format(plugin_name), status=404)
plugin = self._plugins[plugin_name]
logger.info("Activating plugin: {}".format(plugin.name))
if sync or not getattr(plugin, 'async', True) or getattr(
plugin, 'sync', False):
return self._activate(plugin)
else:
th = Thread(target=partial(self._activate, plugin))
th.start()
return th
def _deactivate(self, plugin):
with plugin._lock:
if not plugin.is_activated:
return
plugin._deactivate()
logger.info("Plugin deactivated: {}".format(plugin.name))
def deactivate_plugin(self, plugin_name, sync=True):
plugin_name = plugin_name.lower()
if plugin_name not in self._plugins:
raise Error(
message="Plugin not found: {}".format(plugin_name), status=404)
plugin = self._plugins[plugin_name]
if sync or not getattr(plugin, 'async', True) or not getattr(
plugin, 'sync', False):
plugin._deactivate()
else:
th = Thread(target=plugin.deactivate)
th.start()
return th
def teardown(self, exception):
pass

View File

@ -1,303 +0,0 @@
#
# Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
'''
Meta-programming for the models.
'''
import os
import json
import jsonschema
import inspect
import copy
from abc import ABCMeta
from collections import namedtuple
from collections.abc import MutableMapping
class BaseMeta(ABCMeta):
'''
Metaclass for models. It extracts the default values for the fields in
the model.
For instance, instances of the following class wouldn't need to mark
their version or description on initialization:
.. code-block:: python
class MyPlugin(Plugin):
version=0.3
description='A dull plugin'
Note that these operations could be included in the __init__ of the
class, but it would be very inefficient.
'''
_subtypes = {}
def __new__(mcs, name, bases, attrs, **kwargs):
register_afterwards = False
defaults = {}
aliases = {}
attrs = mcs.expand_with_schema(name, attrs)
if 'schema' in attrs:
register_afterwards = True
for base in bases:
if hasattr(base, '_defaults'):
defaults.update(getattr(base, '_defaults'))
if hasattr(base, '_aliases'):
aliases.update(getattr(base, '_aliases'))
info, rest = mcs.split_attrs(attrs)
for i in list(info.keys()):
if isinstance(info[i], _Alias):
aliases[i] = info[i].indict
if info[i].default is not None:
defaults[i] = info[i].default
else:
defaults[i] = info[i]
rest['_defaults'] = defaults
rest['_aliases'] = aliases
cls = super(BaseMeta, mcs).__new__(mcs, name, tuple(bases), rest)
if register_afterwards:
mcs.register(cls, defaults['@type'])
return cls
@classmethod
def register(mcs, rsubclass, rtype=None):
mcs._subtypes[rtype or rsubclass.__name__] = rsubclass
@staticmethod
def expand_with_schema(name, attrs):
if 'schema' in attrs: # Schema specified by name
schema_file = '{}.json'.format(attrs['schema'])
elif 'schema_file' in attrs:
schema_file = attrs['schema_file']
del attrs['schema_file']
else:
return attrs
if '/' not in 'schema_file':
thisdir = os.path.dirname(os.path.realpath(__file__))
schema_file = os.path.join(thisdir,
'schemas',
schema_file)
schema_path = 'file://' + schema_file
with open(schema_file) as f:
schema = json.load(f)
resolver = jsonschema.RefResolver(schema_path, schema)
if '@type' not in attrs:
attrs['@type'] = name
attrs['_schema_file'] = schema_file
attrs['schema'] = schema
attrs['_validator'] = jsonschema.Draft4Validator(schema, resolver=resolver)
schema_defaults = BaseMeta.get_defaults(attrs['schema'])
attrs.update(schema_defaults)
return attrs
@staticmethod
def is_func(v):
return inspect.isroutine(v) or inspect.ismethod(v) or \
inspect.ismodule(v) or isinstance(v, property)
@staticmethod
def is_internal(k):
return k[0] == '_' or k == 'schema' or k == 'data'
@staticmethod
def get_key(key):
if key[0] != '_':
key = key.replace("__", ":", 1)
return key
@staticmethod
def split_attrs(attrs):
'''
Extract the attributes of the class.
This allows adding default values in the class definition.
e.g.:
'''
isattr = {}
rest = {}
for key, value in attrs.items():
if not (BaseMeta.is_internal(key)) and (not BaseMeta.is_func(value)):
isattr[key] = value
else:
rest[key] = value
return isattr, rest
@staticmethod
def get_defaults(schema):
temp = {}
for obj in [
schema,
] + schema.get('allOf', []):
for k, v in obj.get('properties', {}).items():
if 'default' in v and k not in temp:
temp[k] = v['default']
return temp
def make_property(key, default=None):
def fget(self):
if default:
return self.get(key, copy.copy(default))
return self[key]
def fdel(self):
del self[key]
def fset(self, value):
self[key] = value
return fget, fset, fdel
class CustomDict(MutableMapping, object):
'''
A dictionary whose elements can also be accessed as attributes. Since some
characters are not valid in the dot-notation, the attribute names also
converted. e.g.:
> d = CustomDict()
> d.key = d['ns:name'] = 1
> d.key == d['key']
True
> d.ns__name == d['ns:name']
'''
_defaults = {}
_aliases = {'id': '@id'}
def __init__(self, *args, **kwargs):
super(CustomDict, self).__init__()
for k, v in self._defaults.items():
self[k] = copy.copy(v)
for arg in args:
self.update(arg)
for k, v in kwargs.items():
self[k] = v
return self
def serializable(self, **kwargs):
def ser_or_down(item):
if hasattr(item, 'serializable'):
return item.serializable(**kwargs)
elif isinstance(item, dict):
temp = dict()
for kp in item:
vp = item[kp]
temp[kp] = ser_or_down(vp)
return temp
elif isinstance(item, list) or isinstance(item, set):
return list(ser_or_down(i) for i in item)
else:
return item
return ser_or_down(self.as_dict(**kwargs))
def __getitem__(self, key):
return self.__dict__[key]
def __setitem__(self, key, value):
'''Do not insert data directly, there might be a property in that key. '''
key = self._key_to_attr(key)
return setattr(self, key, value)
def __delitem__(self, key):
key = self._key_to_attr(key)
del self.__dict__[key]
def as_dict(self, verbose=True, aliases=False):
attrs = self.__dict__.keys()
if not verbose and hasattr(self, '_terse_keys'):
attrs = self._terse_keys + ['@type', '@id']
res = {k: getattr(self, k) for k in attrs
if not self._internal_key(k) and hasattr(self, k)}
if not aliases:
return res
for k, ok in self._aliases.items():
if ok in res:
res[k] = getattr(res, ok)
del res[ok]
return res
def __iter__(self):
return (k for k in self.__dict__ if not self._internal_key(k))
def __len__(self):
return len(self.__dict__)
def update(self, other):
for k, v in other.items():
self[k] = v
def _attr_to_key(self, key):
key = key.replace("__", ":", 1)
key = self._aliases.get(key, key)
return key
def _key_to_attr(self, key):
if self._internal_key(key):
return key
if key in self._aliases:
key = self._aliases[key]
else:
key = key.replace(":", "__", 1)
return key
def __getattr__(self, key):
nkey = self._attr_to_key(key)
if nkey in self.__dict__:
return self.__dict__[nkey]
elif nkey == key:
raise AttributeError("Key not found: {}".format(key))
return getattr(self, nkey)
def __setattr__(self, key, value):
super(CustomDict, self).__setattr__(self._attr_to_key(key), value)
def __delattr__(self, key):
super(CustomDict, self).__delattr__(self._attr_to_key(key))
@staticmethod
def _internal_key(key):
return key[0] == '_'
def __str__(self):
return json.dumps(self.serializable(), sort_keys=True, indent=4)
def __repr__(self):
return json.dumps(self.serializable(), sort_keys=True, indent=4)
_Alias = namedtuple('Alias', ['indict', 'default'])
def alias(key, default=None):
return _Alias(key, default)

View File

@ -15,141 +15,49 @@
#
'''
Senpy Models.
This implementation should mirror the JSON schema definition.
For compatibility with Py3 and for easier debugging, this new version drops
introspection and adds all arguments to the models.
'''
from __future__ import print_function
from future import standard_library
standard_library.install_aliases()
from future.utils import with_metaclass
from past.builtins import basestring
from jinja2 import Environment, BaseLoader
from typing import *
import time
import copy
import json
import os
import jsonref
from flask import Response as FlaskResponse
from pyld import jsonld
import logging
import jmespath
import json
from textwrap import dedent
from pydantic import BaseModel as PydanticModel
from pydantic import computed_field, field_validator, ConfigDict, Field
from pydantic_core import from_json
logging.getLogger('rdflib').setLevel(logging.WARN)
logger = logging.getLogger(__name__)
from rdflib import Graph
from .meta import BaseMeta, CustomDict, alias
DEFINITIONS_FILE = 'definitions.json'
CONTEXT_PATH = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'schemas',
'context.jsonld')
def get_schema_path(schema_file, absolute=False):
if absolute:
return os.path.realpath(schema_file)
else:
return os.path.join(
os.path.dirname(os.path.realpath(__file__)), 'schemas',
schema_file)
with open(CONTEXT_PATH) as f:
BASE_CONTEXT = dict(json.loads(f.read()))
def read_schema(schema_file, absolute=False):
schema_path = get_schema_path(schema_file, absolute)
schema_uri = 'file://{}'.format(schema_path)
with open(schema_path) as f:
return jsonref.load(f, base_uri=schema_uri)
def dump_schema(schema):
return jsonref.dumps(schema)
def load_context(context):
logging.debug('Loading context: {}'.format(context))
if not context:
return context
elif isinstance(context, list):
contexts = []
for c in context:
contexts.append(load_context(c))
return contexts
elif isinstance(context, dict):
return dict(context)
elif isinstance(context, basestring):
try:
with open(context) as f:
return dict(json.loads(f.read()))
except IOError:
return context
else:
raise AttributeError('Please, provide a valid context')
base_context = load_context(CONTEXT_PATH)
def register(rsubclass, rtype=None):
BaseMeta.register(rsubclass, rtype)
class BaseModel(with_metaclass(BaseMeta, CustomDict)):
class BaseModel(PydanticModel):
'''
Entities of the base model are a special kind of dictionary that emulates
a JSON-LD object. The structure of the dictionary is checked via JSON-schema.
For convenience, the values can also be accessed as attributes
(a la Javascript). e.g.:
a JSON-LD object.
The basic attributes should be set in the class, but additional values can
also be provided/set via attributes (à la Javascript). e.g.:
>>> myobject.key == myobject['key']
True
>>> myobject.ns__name == myobject['ns:name']
>>> myobject['ns:name'] = 'Peter'
True
Additionally, subclasses of this class can specify default values for their
instances. These defaults are inherited by subclasses. e.g.:
>>> class NewModel(BaseModel):
... mydefault = 5
>>> n1 = NewModel()
>>> n1['mydefault'] == 5
True
>>> n1.mydefault = 3
>>> n1['mydefault'] = 3
True
>>> n2 = NewModel()
>>> n2 == 5
True
>>> class SubModel(NewModel):
pass
>>> subn = SubModel()
>>> subn.mydefault == 5
True
Lastly, every subclass that also specifies a schema will get registered, so it
is possible to deserialize JSON and get the right type.
i.e. to recover an instance of the original class from a plain JSON.
'''
# schema_file = DEFINITIONS_FILE
_context = base_context["@context"]
def __init__(self, *args, **kwargs):
auto_id = kwargs.pop('_auto_id', False)
super(BaseModel, self).__init__(*args, **kwargs)
if auto_id:
self.id
model_config = ConfigDict(extra='ignore', ignored_types=(object, ))
context: Optional[Union[str, Dict]] = Field(default=None, serialization_alias="@context")
wasGeneratedBy: Optional[str] = Field(default=None, serialization_alias="prov:wasGeneratedBy")
@property
def id(self):
@ -161,35 +69,6 @@ class BaseModel(with_metaclass(BaseMeta, CustomDict)):
def id(self, value):
self['@id'] = value
def flask(self,
in_headers=False,
headers=None,
outformat='json-ld',
**kwargs):
"""
Return the values and error to be used in flask.
So far, it returns a fixed context. We should store/generate different
contexts if the plugin adds more aliases.
"""
headers = headers or {}
kwargs["with_context"] = not in_headers
content, mimetype = self.serialize(format=outformat,
with_mime=True,
**kwargs)
if outformat == 'json-ld' and in_headers:
headers.update({
"Link":
('<%s>;'
'rel="http://www.w3.org/ns/json-ld#context";'
' type="application/ld+json"' % kwargs.get('context_uri'))
})
return FlaskResponse(
response=content,
status=self.get('status', 200),
headers=headers,
mimetype=mimetype)
def serialize(self, format='json-ld', with_mime=False,
template=None, prefix=None, fields=None, **kwargs):
js = self.jsonld(prefix=prefix, **kwargs)
@ -240,7 +119,7 @@ class BaseModel(with_metaclass(BaseMeta, CustomDict)):
result,
options={
'expandContext': [
self._context,
self.context,
{
'prefix': prefix,
'endpoint': prefix
@ -271,261 +150,177 @@ class BaseModel(with_metaclass(BaseMeta, CustomDict)):
self['prov:wasGeneratedBy'] = another.id
def subtypes():
return BaseMeta._subtypes
def from_dict(indict, cls=None, warn=True):
if not cls:
target = indict.get('@type', None)
cls = BaseModel
try:
cls = subtypes()[target]
except KeyError:
pass
if cls == BaseModel and warn:
logger.warning('Created an instance of an unknown model')
outdict = dict()
for k, v in indict.items():
if k == '@context':
pass
elif isinstance(v, dict):
v = from_dict(indict[k])
elif isinstance(v, list):
v = v[:]
for ix, v2 in enumerate(v):
if isinstance(v2, dict):
v[ix] = from_dict(v2)
outdict[k] = copy.copy(v)
return cls(**outdict)
def from_string(string, **kwargs):
return from_dict(json.loads(string), **kwargs)
def from_json(injson, **kwargs):
indict = json.loads(injson)
return from_dict(indict, **kwargs)
class Entry(BaseModel):
schema = 'entry'
text: str = Field(serialization_alias="nif:isString")
text = alias('nif:isString')
sentiments = alias('marl:hasOpinion', [])
emotions = alias('onyx:hasEmotionSet', [])
class Sentiment(BaseModel):
schema = 'sentiment'
polarity = alias('marl:hasPolarity')
polarityValue = alias('marl:polarityValue')
class Error(BaseModel, Exception):
schema = 'error'
def __init__(self, message='Generic senpy exception', *args, **kwargs):
Exception.__init__(self, message)
super(Error, self).__init__(*args, **kwargs)
self.message = message
def __str__(self):
if not hasattr(self, 'errors'):
return self.message
return '{}:\n\t{}'.format(self.message, self.errors)
def __hash__(self):
return Exception.__hash__(self)
class AggregatedEvaluation(BaseModel):
schema = 'aggregatedEvaluation'
evaluations = alias('senpy:evaluations', [])
class Dataset(BaseModel):
schema = 'dataset'
class Datasets(BaseModel):
schema = 'datasets'
datasets = []
class Emotion(BaseModel):
schema = 'emotion'
class EmotionConversion(BaseModel):
schema = 'emotionConversion'
class EmotionConversionPlugin(BaseModel):
schema = 'emotionConversionPlugin'
class EmotionAnalysis(BaseModel):
schema = 'emotionAnalysis'
class EmotionModel(BaseModel):
schema = 'emotionModel'
onyx__hasEmotionCategory = []
class EmotionPlugin(BaseModel):
schema = 'emotionPlugin'
class EmotionSet(BaseModel):
schema = 'emotionSet'
onyx__hasEmotion = []
class Evaluation(BaseModel):
schema = 'evaluation'
metrics = alias('senpy:metrics', [])
class Entity(BaseModel):
schema = 'entity'
class Help(BaseModel):
schema = 'help'
class Metric(BaseModel):
schema = 'metric'
class Parameter(BaseModel):
schema = 'parameter'
class Plugins(BaseModel):
schema = 'plugins'
plugins = []
class Response(BaseModel):
schema = 'response'
class Activity(BaseModel):
plugin: str
params: Dict[str, Any]
analyzed: List[str] = []
class Results(BaseModel):
schema = 'results'
_terse_keys = ['entries', ]
activities = []
entries = []
def activity(self, id):
for i in self.activities:
if i.id == id:
return i
return None
class SentimentPlugin(BaseModel):
schema = 'sentimentPlugin'
class Suggestion(BaseModel):
schema = 'suggestion'
class Topic(BaseModel):
schema = 'topic'
activities: List[Activity] = []
entries: List[Entry] = []
parameters: Dict[str, str] = {}
class Analysis(BaseModel):
'''
A prov:Activity that results of executing a Plugin on an entry with a set of
parameters.
'''
schema = 'analysis'
parameters = alias('prov:used', [])
algorithm = alias('prov:wasAssociatedWith', [])
@property
def params(self):
outdict = {}
outdict['algorithm'] = self.algorithm
for param in self.parameters:
outdict[param['name']] = param['value']
return outdict
@params.setter
def params(self, value):
for k, v in value.items():
for param in self.parameters:
if param.name == k:
param.value = v
break
else:
self.parameters.append(Parameter(name=k, value=v)) # noqa: F821
def param(self, key, default=None):
for param in self.parameters:
if param['name'] == key:
return param['value']
return default
@property
def plugin(self):
return self._plugin
@plugin.setter
def plugin(self, value):
self._plugin = value
self['prov:wasAssociatedWith'] = value.id
plugin: 'Plugin'
params: dict[str, object] = {}
def run(self, request):
return self.plugin.process(request, self)
class Plugin(BaseModel):
schema = 'plugin'
extra_params = {}
class MoralityAnalysis(Analysis):
usedMoralValueModel: str
usedMLModel: Optional[str] = None
def activity(self, parameters=None):
class Annotation(BaseModel):
annotated: Optional[str] = None
wasGeneratedBy: Optional[str] = None
def add_provenance(self, entry, activity):
self.annotated = entry.id
self.wasGeneratedBy = activity.id
self[prov['wasGeneratedBy']] = activity.id
activity.analysed.append(entry.id)
class MoralAnnotation(Annotation):
def __init__(self, category, confidence=None, intensity=None,
entry=None, activity=None):
super().__init__()
if confidence is not None:
self[amor['confidence']] = confidence
if intensity is not None:
self[amor_mft['hasPolarityIntensity']] = intensity
if entry and activity:
self.add_provenance(entry, activity)
elif entry or activity:
raise Exception()
@classmethod
def from_label(cls, label):
return cls(label.category, label.confidence, label.intensity)
class Plugin(BaseModel):
name: str = Field(default='', validate_default=True)
version: Optional[str] = 'dev'
author: Optional[str] = None
extra_params: Dict[str, Any] = {}
description: str = Field(default="", json_schema_extra=dict(hidden=True))
@field_validator("description", mode="before")
@classmethod
def dedentdoc(cls, doc: str) -> str:
doc = doc or cls.get('__doc__', None)
return dedent(doc)
@field_validator("name", mode="before")
@classmethod
def clsname(cls, name: str) -> str:
name = name or cls.__name__.capitalize()
return name
@computed_field
@property
def id(self) -> str:
return 'endpoint:plugins/{}_{}'.format(self.name, self.version)
def activity(self, params, *, cls=Analysis):
'''Generate an Analysis (prov:Activity) from this plugin and the given parameters'''
a = Analysis()
a.plugin = self
if parameters:
a.params = parameters
a = cls(plugin=self, params=params)
return a
# More classes could be added programmatically
class Plugins(BaseModel):
plugins: List[Plugin] = []
def _class_from_schema(name, schema=None, schema_file=None, base_classes=None):
base_classes = base_classes or []
base_classes.append(BaseModel)
attrs = {}
if schema:
attrs['schema'] = schema
elif schema_file:
attrs['schema_file'] = schema_file
else:
attrs['schema'] = name
name = "".join((name[0].upper(), name[1:]))
return BaseMeta(name, base_classes, attrs)
class Emotion:
hasEmotionIntensity: str = Field(serialization_alias="onyx:hasEmotionIntensity")
hasEmotionCategory: str = Field(serialization_alias="onyx:hasEmotionCategory")
class Sentiment:
pass
class SentimentPlugin(Plugin):
pass
class Suggestion:
pass
class Topic:
pass
def _add_class_from_schema(*args, **kwargs):
generatedClass = _class_from_schema(*args, **kwargs)
globals()[generatedClass.__name__] = generatedClass
del generatedClass
class Context:
pass
class Dataset:
pass
class Datasets:
pass
class Definitions:
pass
class Dimensions:
pass
class EmotionAnalysis:
pass
class EmotionConversion:
pass
class EmotionConversionPlugin(Plugin):
pass
class Emotion:
pass
class EmotionModel:
pass
class EmotionPlugin(Plugin):
pass
class EmotionSet:
pass
class Entity:
pass
class ErrorResponse(BaseModel):
code: Optional[int] = 500
message: str
class Metric:
pass
class Evaluation:
pass
class AggregatedEvaluation:
pass
class Help:
pass
class Parameter:
pass
def from_dict(c, cls):
return cls.model_validate(d)
def from_string(s, cls):
return from_dict(from_json(s, allow_partial=True))

7
senpy/ns.py Normal file
View File

@ -0,0 +1,7 @@
from rdflib import Namespace
amor = Namespace('http://www.gsi.upm.es/ontologies/amor/ns#')
amor_bhv = Namespace('http://www.gsi.upm.es/ontologies/amor-bhv/ns#')
amor_mft = Namespace('http://www.gsi.upm.es/ontologies/amor-mft/ns#')
prov = Namespace('http://www.w3.org/ns/prov#')
emoml = Namespace('http://www.gsi.upm.es/ontologies/onyx/vocabularies/emotionml/ns#')

View File

@ -16,10 +16,7 @@
# limitations under the License.
#
from future import standard_library
standard_library.install_aliases()
from future.utils import with_metaclass
from typing import *
from functools import partial
import os.path
@ -29,6 +26,8 @@ import pickle
import logging
import pprint
import deprecation
import inspect
import sys
import subprocess
@ -38,59 +37,21 @@ import threading
import multiprocessing
import pkg_resources
from nltk import download
from textwrap import dedent
from sklearn.base import TransformerMixin, BaseEstimator
from itertools import product
from .. import models, utils
from ..errors import Error
from .. import api
from .. import gsitk_compat
from .. import testing
from .. import config
from .. import ns
logger = logging.getLogger(__name__)
class PluginMeta(models.BaseMeta):
_classes = {}
def __new__(mcs, name, bases, attrs, **kwargs):
plugin_type = set()
for base in bases:
if hasattr(base, '_plugin_type'):
plugin_type |= base._plugin_type
plugin_type.add(name)
alias = attrs.get('name', name).lower()
attrs['_plugin_type'] = plugin_type
logger.debug('Adding new plugin class: %s %s %s %s', name, bases, attrs, plugin_type)
attrs['name'] = alias
if 'description' not in attrs:
doc = attrs.get('__doc__', None)
if doc:
attrs['description'] = dedent(doc)
else:
logger.warning(
('Plugin {} does not have a description. '
'Please, add a short summary to help other developers'
).format(name))
cls = super(PluginMeta, mcs).__new__(mcs, name, bases, attrs)
if alias in mcs._classes:
if config.testing:
raise Exception(
('The type of plugin {} already exists. '
'Please, choose a different name').format(name))
else:
logger.warning('Overloading plugin class: {}'.format(alias))
mcs._classes[alias] = cls
return cls
@classmethod
def for_type(cls, ptype):
return cls._classes[ptype]
class Plugin(with_metaclass(PluginMeta, models.Plugin)):
class Plugin(models.Plugin):
'''
Base class for all plugins in senpy.
A plugin must provide at least these attributes:
@ -103,23 +64,16 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
'''
_terse_keys = ['name', '@id', '@type', 'author', 'description',
'extra_params', 'is_activated', 'url', 'version']
data_folder: str = "."
test_cases: List[Dict] = []
def __init__(self, info=None, data_folder=None, **kwargs):
def __init__(self, *, data_folder=None, **data):
"""
Provides a canonical name for plugins and serves as base for other
kinds of plugins.
"""
logger.debug("Initialising %s", info)
super(Plugin, self).__init__(**kwargs)
if info:
self.update(info)
self.validate()
self.id = 'endpoint:plugins/{}_{}'.format(self['name'],
self['version'])
self.is_activated = False
self._lock = threading.Lock()
super().__init__(**data)
self._directory = os.path.abspath(
os.path.dirname(inspect.getfile(self.__class__)))
@ -128,7 +82,6 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
if not data_folder:
data_folder = os.getcwd()
data_folder = os.path.abspath(data_folder)
subdir = os.path.join(data_folder, self.name)
@ -149,35 +102,9 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
def log(self):
return self._log
def validate(self):
missing = []
for x in ['name', 'description', 'version']:
if x not in self:
missing.append(x)
if missing:
raise models.Error(
'Missing configuration parameters: {}'.format(missing))
def get_folder(self):
return os.path.dirname(inspect.getfile(self.__class__))
def _activate(self):
if self.is_activated:
return
self.activate()
self.is_activated = True
return self.is_activated
def _deactivate(self):
self.is_activated = False
self.deactivate()
def activate(self):
pass
def deactivate(self):
pass
def process(self, request, activity, **kwargs):
"""
An implemented plugin should override this method.
@ -195,7 +122,7 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
if inspect.isgenerator(results):
for result in results:
yield result
else:
elif results:
yield results
def process_entry(self, entry, activity):
@ -210,8 +137,6 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
)
def test(self, test_cases=None):
if not self.is_activated:
self._activate()
if not test_cases:
if not hasattr(self, 'test_cases'):
raise AttributeError(
@ -235,7 +160,7 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
def test_case(self, case, mock=testing.MOCK_REQUESTS):
if 'entry' not in case and 'input' in case:
entry = models.Entry(_auto_id=False)
entry.nif__isString = case['input']
entry.text = case['input']
case['entry'] = entry
entry = models.Entry(case['entry'])
given_parameters = case.get('params', case.get('parameters', {}))
@ -265,7 +190,7 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
expected = [expected]
utils.check_template(res.entries, expected)
res.validate()
except models.Error:
except Error:
if should_fail:
return
raise
@ -302,38 +227,16 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
SenpyPlugin = Plugin
class FailedPlugin(Plugin):
"""A plugin that has failed to initialize."""
version = 0
def __init__(self, info, function):
super().__init__(info)
a = info.get('name', info.get('module', self.name))
self['name'] == a
self._function = function
self.is_activated = False
def retry(self):
return self._function()
def test(self):
'''
A module that failed to load cannot be tested. But non-optional
plugins should not fail to load in strict mode.
'''
assert self.optional and not config.strict
class Analyser(Plugin):
'''
A subclass of Plugin that analyses text and provides an annotation.
'''
# Deprecated
@deprecation.deprecated(details="Use process instead")
def analyse(self, request, activity):
return super(Analyser, self).process(request, activity)
# Deprecated
@deprecation.deprecated(details="Use process_entries instead")
def analyse_entries(self, entries, activity):
for i in super(Analyser, self).process_entries(entries, activity):
yield i
@ -402,14 +305,12 @@ class Evaluable(Plugin):
return evaluate([self], *args, **kwargs)
class SentimentPlugin(Analyser, Evaluable, models.SentimentPlugin):
class SentimentPlugin(Analyser, Evaluable):
'''
Sentiment plugins provide sentiment annotation (using Marl)
'''
minPolarityValue = 0
maxPolarityValue = 1
_terse_keys = Analyser._terse_keys + ['minPolarityValue', 'maxPolarityValue']
minPolarityValue: float = 0
maxPolarityValue: float = 1
def test_case(self, case):
if 'polarity' in case:
@ -441,7 +342,7 @@ class SentimentPlugin(Analyser, Evaluable, models.SentimentPlugin):
for feat in X:
if isinstance(feat, list):
feat = ' '.join(feat)
entries.append(models.Entry(nif__isString=feat))
entries.append(models.Entry(text=feat))
labels = []
for e in self.process_entries(entries, activity):
sent = e.sentiments[0].polarity
@ -458,10 +359,27 @@ class EmotionPlugin(Analyser, models.EmotionPlugin):
'''
Emotion plugins provide emotion annotation (using Onyx)
'''
minEmotionValue = 0
maxEmotionValue = 1
minEmotionValue: float = 0
maxEmotionValue: float = 1
_terse_keys = Analyser._terse_keys + ['minEmotionValue', 'maxEmotionValue']
class AnnotationPlugin(AnalysisPlugin):
def process_entry(self, entry, activity, **kwargs):
for annotation in self.annotate(entry):
annotation.add_provenance(entry, activity)
yield entry
def annotate(self, entry, **kwargs):
raise NotImplemented("this should be implemented in subclasses")
class MoralityPlugin(AnnotationPlugin):
moralValueModel: str = ns.amor_mft['MoralFoundationTHeory']
def activity(self, parameters=None):
return models.MoralityAnalysis(plugin=self,
usedMLModel=None,
usedMoralValueModel=self.model)
class EmotionConversion(Conversion):
@ -545,7 +463,7 @@ class TextBox(Box):
'''A black box plugin that takes only text as input'''
def to_features(self, entry, activity):
return [entry['nif:isString']]
return [entry.text]
class SentimentBox(TextBox, SentimentPlugin):
@ -553,13 +471,13 @@ class SentimentBox(TextBox, SentimentPlugin):
A box plugin where the output is only a polarity label or a tuple (polarity, polarityValue)
'''
classes = ['marl:Positive', 'marl:Neutral', 'marl:Negative']
binary = True
classes: List[str] = ['marl:Positive', 'marl:Neutral', 'marl:Negative']
binary: bool = True
def to_entry(self, features, entry, activity, **kwargs):
if len(features) != len(self.classes):
raise models.Error('The number of features ({}) does not match the classes '
raise Error('The number of features ({}) does not match the classes '
'(plugin.classes ({})'.format(len(features), len(self.classes)))
minValue = activity.param('marl:minPolarityValue', 0)
@ -590,8 +508,8 @@ class EmotionBox(TextBox, EmotionPlugin):
A box plugin where the output is only an a tuple of emotion labels
'''
EMOTIONS = []
with_intensity = True
EMOTIONS: List[str] = []
with_intensity: bool = True
def to_entry(self, features, entry, activity, **kwargs):
s = models.EmotionSet()
@ -697,7 +615,7 @@ def pfilter(plugins, plugin_type=Analyser, **kwargs):
logger.debug('Class: {}'.format(pclass))
candidates = filter(lambda x: isinstance(x, pclass), plugins)
except KeyError:
raise models.Error('{} is not a valid type'.format(plugin_type))
raise Error('{} is not a valid type'.format(plugin_type))
else:
candidates = plugins
@ -775,7 +693,7 @@ def install_deps(*plugins):
exitcode = process.wait()
installed = True
if exitcode != 0:
raise models.Error(
raise Error(
"Dependencies not properly installed: {}".format(pip_args))
installed_nltk = download(list(nltk_resources))
return installed or installed_nltk
@ -855,7 +773,7 @@ def from_module(module, **kwargs):
def one_from_module(module, root, info, **kwargs):
if '@type' in info:
cls = PluginMeta.from_type(info['@type'])
return cls(info=info, **kwargs)
return cls(**info, **kwargs)
instance = next(
from_module(module=module, root=root, info=info, **kwargs), None)
if not instance:
@ -888,7 +806,7 @@ def _from_module_name(module, root, info=None, **kwargs):
def _from_loaded_module(module, info=None, **kwargs):
for cls in _classes_in_module(module):
yield cls(info=info, **kwargs)
yield cls(**(info or {}), **kwargs)
for instance in _instances_in_module(module):
yield instance
@ -899,7 +817,7 @@ cached_evs = {}
def evaluate(plugins, datasets, **kwargs):
for plug in plugins:
if not hasattr(plug, 'as_pipe'):
raise models.Error('Plugin {} cannot be evaluated'.format(plug.name))
raise Error('Plugin {} cannot be evaluated'.format(plug.name))
if not isinstance(datasets, dict):
datasets = gsitk_compat.prepare(datasets, download=True)
@ -961,12 +879,11 @@ def evaluations_to_JSONLD(results, flatten=False):
class ScikitWrapper(BaseEstimator, TransformerMixin):
def __init__(self, plugin=None):
def __init__(self, plugin=None, **data):
super().__init__(**data)
self.plugin = plugin
def fit(self, X=None, y=None):
if self.plugin is not None and not self.plugin.is_activated:
self.plugin.activate()
return self
def transform(self, X):

View File

@ -70,11 +70,11 @@ pattern.text._read = _read
class ANEW(EmotionPlugin):
description = "This plugin consists on an emotion classifier using ANEW lexicon dictionary. It averages the VAD (valence-arousal-dominance) value of each word in the text that is also in the ANEW dictionary. To obtain a categorical value (e.g., happy) use the emotion conversion API (e.g., `emotion-model=emoml:big6`)."
author = "@icorcuera"
version = "0.5.2"
author: str = "@icorcuera"
version: str = "0.5.2"
name = "emotion-anew"
extra_params = {
extra_params: dict = {
"language": {
"description": "language of the input",
"aliases": ["language", "l"],
@ -89,7 +89,8 @@ class ANEW(EmotionPlugin):
onyx__usesEmotionModel = MODEL
nltk_resources = ['stopwords']
def activate(self, *args, **kwargs):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self._stopwords = stopwords.words('english')
dictionary={}
dictionary['es'] = {}
@ -204,7 +205,7 @@ class ANEW(EmotionPlugin):
yield entry
test_cases = [
test_cases: list[dict] = [
{
'name': 'anger with VAD=(2.12, 6.95, 5.05)',
'input': 'I hate you',

View File

@ -31,14 +31,15 @@ class DepecheMood(EmotionBox):
DepecheMood is an emotion lexicon automatically generated from news articles where users expressed their associated emotions. It contains two languages (English and Italian), as well as three types of word representations (token, lemma and lemma#PoS). For English, the lexicon contains 165k tokens, while the Italian version contains 116k. Unsupervised techniques can be applied to generate simple but effective baselines. To learn more, please visit https://github.com/marcoguerini/DepecheMood and http://www.depechemood.eu/
'''
author = 'Oscar Araque'
name = 'emotion-depechemood'
version = '0.1'
author: str = 'Oscar Araque'
name: str = 'emotion-depechemood'
version: str = '0.1'
requirements = ['pandas']
optional = True
usesEmotionModel: str = 'wna:WNAModel'
nltk_resources = ["stopwords"]
onyx__usesEmotionModel = 'wna:WNAModel'
EMOTIONS = ['wna:negative-fear',
'wna:amusement',
@ -50,16 +51,12 @@ class DepecheMood(EmotionBox):
'wna:sadness']
DM_EMOTIONS = ['AFRAID', 'AMUSED', 'ANGRY', 'ANNOYED', 'DONT_CARE', 'HAPPY', 'INSPIRED', 'SAD',]
LEXICON_URL = "https://github.com/marcoguerini/DepecheMood/raw/master/DepecheMood%2B%2B/DepecheMood_english_token_full.tsv"
def __init__(self, *args, **kwargs):
super(DepecheMood, self).__init__(*args, **kwargs)
self.LEXICON_URL = "https://github.com/marcoguerini/DepecheMood/raw/master/DepecheMood%2B%2B/DepecheMood_english_token_full.tsv"
def __init__(self, **data):
super().__init__(**data)
self._denoise = ignore(set(string.punctuation)|set('«»'))
self._stop_words = []
self._lex_vocab = None
self._lex = None
def activate(self):
self._lex = self.download_lex()
self._lex_vocab = set(list(self._lex.keys()))
self._stop_words = stopwords.words('english') + ['']
@ -127,7 +124,7 @@ class DepecheMood(EmotionBox):
estimation = self.estimate_all_emotions(tokens)
return estimation
test_cases = [
test_cases: list[dict] = [
{
'entry': {
'nif:isString': 'My cat is very happy',

View File

@ -1,5 +1,6 @@
# -*- coding: utf-8 -*-
from __future__ import division
from typing import *
import re
import nltk
import os
@ -19,10 +20,11 @@ class WNAffect(EmotionPlugin, ShelfMixin):
of each emotion. This plugin classifies among 6 emotions: anger,fear,disgust,joy,sadness
or neutral. The only available language is English (en)
'''
name = 'emotion-wnaffect'
author = ["@icorcuera", "@balkian"]
version = '0.2'
extra_params = {
name: str = 'emotion-wnaffect'
author: List[str] = ["@icorcuera", "@balkian"]
version: str = '0.2'
extra_params: Dict[str, Dict] = {
'language': {
"@id": 'lang_wnaffect',
'description': 'language of the input',
@ -31,6 +33,7 @@ class WNAffect(EmotionPlugin, ShelfMixin):
'options': ['en',]
}
}
optional = True
requirements = [
"nltk>=3.0.5",
@ -42,42 +45,8 @@ class WNAffect(EmotionPlugin, ShelfMixin):
onyx__usesEmotionModel = "emoml:big6"
nltk_resources = ['stopwords', 'averaged_perceptron_tagger_eng', 'wordnet']
def _load_synsets(self, synsets_path):
"""Returns a dictionary POS tag -> synset offset -> emotion (str -> int -> str)."""
tree = ET.parse(synsets_path)
root = tree.getroot()
pos_map = {"noun": "NN", "adj": "JJ", "verb": "VB", "adv": "RB"}
synsets = {}
for pos in ["noun", "adj", "verb", "adv"]:
tag = pos_map[pos]
synsets[tag] = {}
for elem in root.findall(
".//{0}-syn-list//{0}-syn".format(pos, pos)):
offset = int(elem.get("id")[2:])
if not offset: continue
if elem.get("categ"):
synsets[tag][offset] = Emo.emotions[elem.get(
"categ")] if elem.get(
"categ") in Emo.emotions else None
elif elem.get("noun-id"):
synsets[tag][offset] = synsets[pos_map["noun"]][int(
elem.get("noun-id")[2:])]
return synsets
def _load_emotions(self, hierarchy_path):
"""Loads the hierarchy of emotions from the WordNet-Affect xml."""
tree = ET.parse(hierarchy_path)
root = tree.getroot()
for elem in root.findall("categ"):
name = elem.get("name")
if name == "root":
Emo.emotions["root"] = Emo("root")
else:
Emo.emotions[name] = Emo(name, elem.get("isa"))
def activate(self, *args, **kwargs):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self._stopwords = stopwords.words('english')
self._wnlemma = wordnet.WordNetLemmatizer()
@ -119,10 +88,42 @@ class WNAffect(EmotionPlugin, ShelfMixin):
self._wn16_path = self.wn16_path
self._wn16 = WordNetCorpusReader(self.find_file(self._wn16_path), nltk.data.find(self.find_file(self._wn16_path)))
self.save()
def _load_synsets(self, synsets_path):
"""Returns a dictionary POS tag -> synset offset -> emotion (str -> int -> str)."""
tree = ET.parse(synsets_path)
root = tree.getroot()
pos_map = {"noun": "NN", "adj": "JJ", "verb": "VB", "adv": "RB"}
def deactivate(self, *args, **kwargs):
self.save(ignore_errors=True)
synsets = {}
for pos in ["noun", "adj", "verb", "adv"]:
tag = pos_map[pos]
synsets[tag] = {}
for elem in root.findall(
".//{0}-syn-list//{0}-syn".format(pos, pos)):
offset = int(elem.get("id")[2:])
if not offset: continue
if elem.get("categ"):
synsets[tag][offset] = Emo.emotions[elem.get(
"categ")] if elem.get(
"categ") in Emo.emotions else None
elif elem.get("noun-id"):
synsets[tag][offset] = synsets[pos_map["noun"]][int(
elem.get("noun-id")[2:])]
return synsets
def _load_emotions(self, hierarchy_path):
"""Loads the hierarchy of emotions from the WordNet-Affect xml."""
tree = ET.parse(hierarchy_path)
root = tree.getroot()
for elem in root.findall("categ"):
name = elem.get("name")
if name == "root":
Emo.emotions["root"] = Emo("root")
else:
Emo.emotions[name] = Emo(name, elem.get("isa"))
def _my_preprocessor(self, text):
@ -268,7 +269,6 @@ class WNAffect(EmotionPlugin, ShelfMixin):
'language': 'en',
'algorithm': 'emotion-wnaffect'}
self.activate()
texts = {'I hate you': 'anger',
'i am sad': 'sadness',
'i am happy with my marks': 'joy',

View File

@ -29,12 +29,12 @@ class Split(Transformation):
(or paragraphs) is required.
'''
author = ["@militarpancho", '@balkian']
version = '0.3'
author: str = ["@militarpancho", '@balkian']
version: str = '0.3'
url = "https://github.com/gsi-upm/senpy"
nltk_resources = ['punkt']
extra_params = {
extra_params: dict = {
'delimiter': {
'description': 'Split text into paragraphs or sentences.',
'aliases': ['type', 't'],
@ -47,7 +47,7 @@ class Split(Transformation):
def analyse_entry(self, entry, activity):
yield entry
chunker_type = activity.params["delimiter"]
original_text = entry['nif:isString']
original_text = entry.text
if chunker_type == "sentence":
tokenizer = PunktSentenceTokenizer()
if chunker_type == "paragraph":
@ -59,12 +59,12 @@ class Split(Transformation):
for i, chunk in enumerate(chars):
start, end = chunk
e = Entry()
e['nif:isString'] = original_text[start:end]
e.text = original_text[start:end]
if entry.id:
e.id = entry.id + "#char={},{}".format(start, end)
yield e
test_cases = [
test_cases: list[dict] = [
{
'entry': {
'nif:isString': 'Hello. World.'

View File

@ -14,8 +14,11 @@
# limitations under the License.
#
from typing import *
from senpy.plugins import EmotionConversionPlugin
from senpy.models import EmotionSet, Emotion, Error
from senpy.models import EmotionSet, Emotion, EmotionConversion
from senpy.errors import Error
import logging
logger = logging.getLogger(__name__)
@ -27,16 +30,16 @@ class CentroidConversion(EmotionConversionPlugin):
categorical one, and vice versa. The centroids used in the conversion
are configurable and appear in the semantic description of the plugin.
'''
def __init__(self, info, *args, **kwargs):
if 'centroids' not in info:
raise Error('Centroid conversion plugins should provide '
'the centroids in their senpy file')
if 'onyx:doesConversion' not in info:
if 'centroids_direction' not in info:
raise Error('Please, provide centroids direction')
cf, ct = info['centroids_direction']
info['onyx:doesConversion'] = [{
centroids: Dict
centroids_direction: tuple[str, str]
aliases: Dict[str, str] ={}
def __super__(self, centroids, centroids_direction, doesConversion=None, aliases={}, *args, **kwargs):
super().__init__(*args, **kwargs)
cf, ct = centroids_direction
if doesConversion is None:
doesConversion = [{
'onyx:conversionFrom': cf,
'onyx:conversionTo': ct
}, {
@ -44,17 +47,16 @@ class CentroidConversion(EmotionConversionPlugin):
'onyx:conversionTo': cf
}]
if 'aliases' in info:
aliases = info['aliases']
if aliases:
ncentroids = {}
for k1, v1 in info['centroids'].items():
for k1, v1 in centroids.items():
nv1 = {}
for k2, v2 in v1.items():
nv1[aliases.get(k2, k2)] = v2
ncentroids[aliases.get(k1, k1)] = nv1
info['centroids'] = ncentroids
super(CentroidConversion, self).__init__(info, *args, **kwargs)
centroids = centroids
self.centroids = centroids
self.dimensions = set()
for c in self.centroids.values():
@ -152,7 +154,7 @@ class CentroidConversion(EmotionConversionPlugin):
"centroids_direction": ["emoml:big6", "emoml:fsre-dimensions"]
}
c = CentroidConversion(info)
c = CentroidConversion.parse_obj(info)
es1 = EmotionSet()
e1 = Emotion()

View File

@ -1,52 +0,0 @@
---
name: Ekman2FSRE
module: senpy.plugins.postprocessing.emotion.centroids
description: Plugin to convert emotion sets from Ekman to VAD
version: 0.2
# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
neutralValue: 5.0
centroids:
anger:
A: 6.95
D: 5.1
V: 2.7
S: 5.0
disgust:
A: 5.3
D: 8.05
V: 2.7
S: 5.0
fear:
A: 6.5
D: 3.6
V: 3.2
S: 5.0
happiness:
A: 7.22
D: 6.28
V: 8.6
S: 5.0
sadness:
A: 5.21
D: 2.82
V: 2.21
S: 5.0
surprise:
A: 5.0
D: 5.0
V: 5.0
S: 10.0
centroids_direction:
- emoml:big6
- emoml:fsre-dimensions
aliases: # These are aliases for any key in the centroid, to avoid repeating a long name several times
A: emoml:fsre-dimensions_arousal
V: emoml:fsre-dimensions_valence
D: emoml:fsre-dimensions_potency
S: emoml:fsre-dimensions_unpredictability
anger: emoml:big6anger
disgust: emoml:big6disgust
fear: emoml:big6fear
happiness: emoml:big6happiness
sadness: emoml:big6sadness
surprise: emoml:big6surprise

View File

@ -0,0 +1,61 @@
from typing import *
from senpy.ns import emoml
from senpy.plugins.postprocessing.emotion.centroids import CentroidConversion
class Ekman2FSRE(CentroidConversion):
''' Plugin to convert emotion sets from Ekman to VAD '''
version: str = '0.2'
# No need to specify doesConversion because centroids.py adds it automatically from centroids_direction
neutralValue: float = 5.0
centroids: Dict = {
'anger': {
'A': 6.95,
'D': 5.1,
'V': 2.7,
'S': 5.0,
},
'disgust': {
'A': 5.3,
'D': 8.05,
'V': 2.7,
'S': 5.0,
},
'fear': {
'A': 6.5,
'D': 3.6,
'V': 3.2,
'S': 5.0,
},
'happiness':{
'A': 7.22,
'D': 6.28,
'V': 8.6,
'S': 5.0,
},
'sadness': {
'A': 5.21,
'D': 2.82,
'V': 2.21,
'S': 5.0 ,
},
'surprise': {
'A': 5.0,
'D': 5.0,
'V': 5.0,
'S': 10.0,
}
}
centroids_direction: tuple[str, str] = ('emoml:big6', 'emoml:fsre-dimensions')
aliases: Dict[str, str] = { # These are aliases for any key in the centroid, to avoid repeating a long name several times
'A': emoml['emoml:fsre-dimensions_arousal'],
'V': emoml['emoml:fsre-dimensions_valence'],
'D': emoml['emoml:fsre-dimensions_potency'],
'S': emoml['emoml:fsre-dimensions_unpredictability'],
'anger': emoml['emoml:big6anger'],
'disgust': emoml['emoml:big6disgust'],
'fear': emoml['emoml:big6fear'],
'happiness': emoml['emoml:big6happiness'],
'sadness': emoml['emoml:big6sadness'],
'surprise': emoml['emoml:big6surprise'],
}

View File

@ -1,40 +0,0 @@
---
name: Ekman2PAD
module: senpy.plugins.postprocessing.emotion.centroids
description: Plugin to convert emotion sets from Ekman to VAD
version: 0.2
# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
neutralValue: 5.0
centroids:
anger:
A: 6.95
D: 5.1
P: 2.7
disgust:
A: 5.3
D: 8.05
P: 2.7
fear:
A: 6.5
D: 3.6
P: 3.2
happiness:
A: 7.22
D: 6.28
P: 8.6
sadness:
A: 5.21
D: 2.82
P: 2.21
centroids_direction:
- emoml:big6
- emoml:pad-dimensions
aliases: # These are aliases for any key in the centroid, to avoid repeating a long name several times
P: emoml:pad-dimensions_pleasure
A: emoml:pad-dimensions_arousal
D: emoml:pad-dimensions_dominance
anger: emoml:big6anger
disgust: emoml:big6disgust
fear: emoml:big6fear
happiness: emoml:big6happiness
sadness: emoml:big6sadness

View File

@ -0,0 +1,54 @@
from typing import *
from senpy.ns import emoml
from senpy.plugins.postprocessing.emotion.centroids import CentroidConversion
class Ekman2PAD(CentroidConversion):
'''Plugin to convert emotion sets from Ekman to VAD'''
version: str = '0.2'
# No need to specify doesConversion because centroids.py adds it automatically from centroids_direction
neutralValue: float = 5.0
centroids: Dict = {
'anger': {
'A': 6.95,
'D': 5.1,
'V': 2.7,
},
'disgust': {
'A': 5.3,
'D': 8.05,
'V': 2.7,
},
'fear': {
'A': 6.5,
'D': 3.6,
'V': 3.2,
},
'happiness':{
'A': 7.22,
'D': 6.28,
'V': 8.6,
},
'sadness': {
'A': 5.21,
'D': 2.82,
'V': 2.21,
},
'surprise': {
'A': 5.0,
'D': 5.0,
'V': 5.0,
}
}
centroids_direction: tuple[str, str] = (emoml['big6'], emoml['pad-dimensions'])
aliases: Dict[str, str] = { # These are aliases for any key in the centroid, to avoid repeating a long name several times
'A': emoml['pad-dimensions_arousal'],
'V': emoml['pad-dimensions_potency'],
'D': emoml['pad-dimensions_dominance'],
'anger': emoml['emoml:big6anger'],
'disgust': emoml['emoml:big6disgust'],
'fear': emoml['emoml:big6fear'],
'happiness': emoml['emoml:big6happiness'],
'sadness': emoml['emoml:big6sadness'],
'surprise': emoml['emoml:big6surprise'],
}

View File

@ -19,15 +19,15 @@ from senpy import PostProcessing, easy_test
class MaxEmotion(PostProcessing):
'''Plugin to extract the emotion with highest value from an EmotionSet'''
author = '@dsuarezsouto'
version = '0.1'
author: str = '@dsuarezsouto'
version: str = '0.1'
def process_entry(self, entry, activity):
if len(entry.emotions) < 1:
yield entry
return
set_emotions = entry.emotions[0]['onyx:hasEmotion']
set_emotions = entry.emotions[0].hasEmotion
# If there is only one emotion, do not modify it
if len(set_emotions) < 2:
@ -38,17 +38,16 @@ class MaxEmotion(PostProcessing):
# Extract max emotion from the set emotions (emotion with highest intensity)
for tmp_emotion in set_emotions:
if tmp_emotion['onyx:hasEmotionIntensity'] > max_emotion[
'onyx:hasEmotionIntensity']:
if tmp_emotion.hasEmotionIntensity > max_emotion.hasEmotionIntensity:
max_emotion = tmp_emotion
if max_emotion['onyx:hasEmotionIntensity'] == 0:
max_emotion['onyx:hasEmotionCategory'] = "neutral"
max_emotion['onyx:hasEmotionIntensity'] = 1.0
if max_emotion.hasEmotionIntensity == 0:
max_emotion.hasEmotionCategory = "neutral"
max_emotion.hasEmotionIntensity = 1.0
entry.emotions[0]['onyx:hasEmotion'] = [max_emotion]
entry.emotions[0].hasEmotion = [max_emotion]
entry.emotions[0]['prov:wasGeneratedBy'] = activity.id
entry.emotions[0].wasGeneratedBy = activity.id
yield entry
def check(self, request, plugins):
@ -57,7 +56,7 @@ class MaxEmotion(PostProcessing):
# Test Cases:
# 1 Normal Situation.
# 2 Case to return a Neutral Emotion.
test_cases = [
test_cases: list[dict] = [
{
"name": "If there are several emotions within an emotion set, reduce it to one.",
"entry": {

View File

@ -13,7 +13,8 @@ from scipy.interpolate import interp1d
from os import path
from senpy.plugins import SentimentBox, SenpyPlugin
from senpy.models import Results, Entry, Sentiment, Error
from senpy.models import Results, Entry, Sentiment
from senpy.errors import Error
if sys.version_info[0] >= 3:
unicode = str
@ -24,9 +25,9 @@ class SentimentBasic(SentimentBox):
Sentiment classifier using rule-based classification for Spanish. Based on english to spanish translation and SentiWordNet sentiment knowledge. This is a demo plugin that uses only some features from the TASS 2015 classifier. To use the entirely functional classifier you can use the service in: http://senpy.cluster.gsi.dit.upm.es.
'''
name = "sentiment-basic"
author = "github.com/nachtkatze"
version = "0.1.1"
extra_params = {
author: str = "github.com/nachtkatze"
version: str = "0.1.1"
extra_params: dict = {
"language": {
"description": "language of the text",
"aliases": ["language", "l"],
@ -36,29 +37,30 @@ class SentimentBasic(SentimentBox):
}
}
sentiword_path = "SentiWordNet_3.0.txt"
pos_path = "unigram_spanish.pickle"
maxPolarityValue = 1
minPolarityValue = -1
nltk_resources = ['punkt_tab','wordnet', 'omw', 'omw-1.4']
optional = True
requirements = ['nltk>=3.0.5', 'scipy>=0.14.0', 'textblob==0.17']
with_polarity = False
_pos_path = "unigram_spanish.pickle"
def __init__(self, **kwargs):
super().__init__(**kwargs)
self._swn = self._load_swn()
self._pos_tagger = self._load_pos_tagger()
def _load_swn(self):
self.swn_path = self.find_file(self.sentiword_path)
swn = SentiWordNet(self.swn_path)
self._swn_path = self.find_file(self.sentiword_path)
swn = SentiWordNet(self._swn_path)
return swn
def _load_pos_tagger(self):
self.pos_path = self.find_file(self.pos_path)
with open(self.pos_path, 'rb') as f:
self._pos_path = self.find_file(self._pos_path)
with open(self._pos_path, 'rb') as f:
tagger = pickle.load(f)
return tagger
def activate(self, *args, **kwargs):
self._swn = self._load_swn()
self._pos_tagger = self._load_pos_tagger()
def _remove_punctuation(self, tokens):
return [t for t in tokens if t not in string.punctuation]
@ -156,7 +158,7 @@ class SentimentBasic(SentimentBox):
return [0, 1, 0]
test_cases = [
test_cases: list[dict] = [
{
'input': 'Odio ir al cine',
'params': {'language': 'es'},

View File

@ -34,7 +34,8 @@ import os
from os import path
import time
from senpy.plugins import SentimentPlugin
from senpy.models import Results, Entry, Entity, Topic, Sentiment, Error
from senpy.models import Results, Entry, Entity, Topic, Sentiment
from senpy.errors import Error
from senpy.utils import check_template
@ -49,13 +50,13 @@ class MeaningCloudPlugin(SentimentPlugin):
http://senpy.cluster.gsi.dit.upm.es/api/?algo=meaningCloud&language=en&apiKey=YOUR_API_KEY&input=I%20love%20Madrid.
'''
name = 'sentiment-meaningcloud'
author = 'GSI UPM'
version = "1.1"
maxPolarityValue = 1
minPolarityValue = -1
name: str = 'sentiment-meaningcloud'
author: str = 'GSI UPM'
version: str = "1.1"
maxPolarityValue: float = 1
minPolarityValue: float = -1
extra_params = {
extra_params: dict = {
"language": {
"description": "language of the input",
"aliases": ["language", "l"],
@ -86,7 +87,7 @@ class MeaningCloudPlugin(SentimentPlugin):
def analyse_entry(self, entry, activity):
params = activity.params
txt = entry['nif:isString']
txt = entry.text
api = 'http://api.meaningcloud.com/'
lang = params.get("language")
model = "general"
@ -175,7 +176,7 @@ class MeaningCloudPlugin(SentimentPlugin):
entry['senpy:hasTopic'].append(concept)
yield entry
test_cases = [
test_cases: list[dict] = [
{
'params': {
'algo': 'sentiment-meaningCloud',

View File

@ -25,10 +25,10 @@ ENDPOINT = 'http://www.sentiment140.com/api/bulkClassifyJson'
class Sentiment140(SentimentBox):
'''Connects to the sentiment140 free API: http://sentiment140.com'''
author = "@balkian"
version = '0.2'
author: str = "@balkian"
version: str = '0.2'
url = "https://github.com/gsi-upm/senpy-plugins-community"
extra_params = {
extra_params: dict = {
'language': {
"@id": 'lang_sentiment140',
'description': 'language of the text',
@ -66,7 +66,7 @@ class Sentiment140(SentimentBox):
continue
yield [0, 1, 0]
test_cases = [
test_cases: list[dict] = [
{
'entry': {
'nif:isString': 'I love Titanic'

View File

@ -12,9 +12,9 @@ class VaderSentimentPlugin(SentimentBox):
'''
name = "sentiment-vader"
module = "sentiment-vader"
author = "@icorcuera"
version = "0.1.1"
extra_params = {
author: str = "@icorcuera"
version: str = "0.1.1"
extra_params: dict = {
"language": {
"description": "language of the input",
"@id": "lang_rand",
@ -51,9 +51,9 @@ class VaderSentimentPlugin(SentimentBox):
return sentiments
test_cases = []
test_cases: list[dict] = []
test_cases = [
test_cases: list[dict] = [
{
'input': 'I am tired :(',
'polarity': 'marl:Negative'

View File

@ -1,16 +1,26 @@
{
"@context": {
"@vocab": "http://www.gsi.upm.es/onto/senpy/ns#",
"@vocab": "http://www.gsi.upm.es/ontologies/senpy/ns#",
"amor": "http://www.gsi.upm.es/ontologies/amor/ns#",
"amor-bhv": "http://www.gsi.upm.es/ontologies/amor/models/bhv/ns#",
"amor-mft": "http://www.gsi.upm.es/ontologies/amor/models/mft/ns#",
"bhv": "http://www.gsi.upm.es/ontologies/bhv#",
"dc": "http://dublincore.org/2012/06/14/dcelements#",
"senpy": "http://www.gsi.upm.es/onto/senpy/ns#",
"prov": "http://www.w3.org/ns/prov#",
"nif": "http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#",
"marl": "http://www.gsi.upm.es/ontologies/marl/ns#",
"onyx": "http://www.gsi.upm.es/ontologies/onyx/ns#",
"wna": "http://www.gsi.upm.es/ontologies/wnaffect/ns#",
"emoml": "http://www.gsi.upm.es/ontologies/onyx/vocabularies/emotionml/ns#",
"xsd": "http://www.w3.org/2001/XMLSchema#",
"fam": "http://vocab.fusepool.info/fam#",
"marl": "http://www.gsi.upm.es/ontologies/marl/ns#",
"mft": "http://www.gsi.upm.es/ontologies/mft/ns#",
"mls": "http://www.w3.org/ns/mls#",
"nif": "http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#",
"onyx": "http://www.gsi.upm.es/ontologies/onyx/ns#",
"owl": "http://www.w3.org/2002/07/owl#",
"prov": "http://www.w3.org/ns/prov#",
"prov": "http://www.w3.org/ns/prov#",
"rdfs": "http://www.w3.org/2000/01/rdf-schema#",
"schema": "http://schema.org/",
"senpy": "http://www.gsi.upm.es/onto/senpy/ns#",
"wna": "http://www.gsi.upm.es/ontologies/wnaffect/ns#",
"xsd": "http://www.w3.org/2001/XMLSchema#",
"topics": {
"@id": "nif:topic",
"@container": "@set"
@ -71,7 +81,6 @@
},
"errors": {
"@type": "ParameterError"
},
"prefix": "http://senpy.invalid/"
}
}
}

View File

@ -83,7 +83,6 @@ def easy_load(app=None, plugin_list=None, plugin_folder=None, **kwargs):
for plugin in plugin_list:
sp.add_plugin(plugin)
sp.install_deps()
sp.activate_all()
return sp, app

View File

@ -21,7 +21,8 @@ logger = logging.getLogger(__name__)
from unittest import TestCase
from senpy.api import (boolean, parse_params, get_extra_params, parse_analyses,
API_PARAMS, NIF_PARAMS, WEB_PARAMS)
from senpy.models import Error, Plugin
from senpy.errors import Error
from senpy.models import Plugin
class APITest(TestCase):
@ -72,7 +73,7 @@ class APITest(TestCase):
in2 = {
'apikey': 25
}
extra_params = {
extra_params: dict = {
"apikey": {
"aliases": [
"apikey",
@ -110,7 +111,7 @@ class APITest(TestCase):
def test_parse_analyses(self):
'''The API should parse user parameters and return them in a format that plugins can use'''
plugins = [
Plugin({
Plugin.parse_obj({
'name': 'plugin1',
'extra_params': {
# Incompatible parameter
@ -133,7 +134,7 @@ class APITest(TestCase):
'options': ['value2_1', 'value2_2', 'value3_3']
}
}
}), Plugin({
}), Plugin.parse_obj({
'name': 'plugin2',
'extra_params': {
'param0': {
@ -186,7 +187,7 @@ class APITest(TestCase):
def test_get_extra_params(self):
'''The API should return the list of valid parameters for a set of plugins'''
plugins = [
Plugin({
Plugin.parse_obj({
'name': 'plugin1',
'extra_params': {
# Incompatible parameter
@ -208,7 +209,7 @@ class APITest(TestCase):
'options': ['value2_1', 'value2_2', 'value3_3']
}
}
}), Plugin({
}), Plugin.parse_obj({
'name': 'plugin2',
'extra_params': {
'param0': {
@ -234,14 +235,14 @@ class APITest(TestCase):
expected = {
# Overlapping parameters
'plugin1.param0': plugins[0]['extra_params']['param0'],
'plugin1.param1': plugins[0]['extra_params']['param1'],
'plugin2.param0': plugins[1]['extra_params']['param0'],
'plugin2.param1': plugins[1]['extra_params']['param1'],
'plugin1.param0': plugins[0].extra_params['param0'],
'plugin1.param1': plugins[0].extra_params['param1'],
'plugin2.param0': plugins[1].extra_params['param0'],
'plugin2.param1': plugins[1].extra_params['param1'],
# Non-overlapping parameters
'param2': plugins[0]['extra_params']['param2'],
'param3': plugins[1]['extra_params']['param3'],
'param2': plugins[0].extra_params['param2'],
'param3': plugins[1].extra_params['param3'],
# Intersection of overlapping parameters
'param1': {

View File

@ -38,11 +38,8 @@ class BlueprintsTest(TestCase):
"""Set up only once, and re-use in every individual test"""
cls.app = Flask("test_extensions")
cls.client = cls.app.test_client()
cls.senpy = Senpy(default_plugins=True, strict=False) # Ignore any optional plugins
cls.senpy.init_app(cls.app)
cls.dir = os.path.join(os.path.dirname(__file__), "..")
cls.senpy.add_folder(cls.dir)
cls.senpy.activate_all()
cls.senpy = Senpy(default_plugins=True, app=cls.app, plugin_folders=[cls.dir, "."], strict=False) # Ignore any optional plugins
cls.senpy.default_plugin = 'Dummy'
def setUp(self):

View File

@ -21,7 +21,7 @@ logger = logging.getLogger(__name__)
from unittest import TestCase
from senpy.cli import main_function
from senpy.models import Error
from senpy.errors import Error
class CLITest(TestCase):

View File

@ -18,7 +18,8 @@ from unittest import TestCase
from senpy.testing import patch_requests
from senpy.client import Client
from senpy.models import Results, Plugins, Error
from senpy.models import Results, Plugins
from senpy.errors import Error
from senpy.plugins import AnalysisPlugin

View File

@ -23,7 +23,8 @@ import logging
from functools import partial
from senpy.extensions import Senpy
from senpy import plugins, config, api
from senpy.models import Error, Results, Entry, EmotionSet, Emotion, Plugin
from senpy.models import Results, Entry, EmotionSet, Emotion, Plugin
from senpy.errors import Error
from flask import Flask
from unittest import TestCase
@ -41,8 +42,7 @@ class ExtensionsTest(TestCase):
self.senpy = Senpy(plugin_folder=self.examples_dir,
app=self.app,
default_plugins=False)
self.senpy.deactivate_all()
self.senpy.activate_plugin("Dummy", sync=True)
self.senpy.default_plugin = "Dummy"
self.app.config['TESTING'] = True # Tell Flask not to catch Exceptions
def test_init(self):
@ -62,9 +62,9 @@ class ExtensionsTest(TestCase):
'''Should be able to add and delete new plugins. '''
new = plugins.Analyser(name='new', description='new', version=0)
self.senpy.add_plugin(new)
assert new in self.senpy.plugins(is_activated=False)
assert new in self.senpy.plugins()
self.senpy.delete_plugin(new)
assert new not in self.senpy.plugins(is_activated=False)
assert new not in self.senpy.plugins()
def test_adding_folder(self):
""" It should be possible for senpy to look for plugins in more folders. """
@ -74,7 +74,7 @@ class ExtensionsTest(TestCase):
default_plugins=False)
assert not senpy.analysis_plugins()
senpy.add_folder(self.examples_dir)
assert senpy.plugins(plugin_type=plugins.Analyser, is_activated=False)
assert senpy.plugins(plugin_type=plugins.Analyser)
self.assertRaises(AttributeError, senpy.add_folder, 'DOES NOT EXIST')
def test_installing(self):
@ -94,9 +94,8 @@ class ExtensionsTest(TestCase):
def test_enabling(self):
""" Enabling a plugin """
self.senpy.activate_all(sync=True)
assert len(self.senpy.plugins()) >= 3
assert self.senpy.get_plugin("Sleep").is_activated
assert self.senpy.get_plugin("Sleep")
def test_installing_nonexistent(self):
""" Fail if the dependencies cannot be met """
@ -110,23 +109,14 @@ class ExtensionsTest(TestCase):
with self.assertRaises(Error):
plugins.install_deps(info)
def test_disabling(self):
""" Disabling a plugin """
self.senpy.deactivate_all(sync=True)
assert not self.senpy.get_plugin("dummy").is_activated
assert not self.senpy.get_plugin("sleep").is_activated
def test_default(self):
""" Default plugin should be set """
assert self.senpy.default_plugin
assert self.senpy.default_plugin.name == "dummy"
self.senpy.deactivate_all(sync=True)
logging.debug("Default: {}".format(self.senpy.default_plugin))
assert self.senpy.default_plugin is None
def test_noplugin(self):
""" Don't analyse if there isn't any plugin installed """
self.senpy.deactivate_all(sync=True)
nosenpy = Senpy(default_plugins=False, plugin_folders=[])
self.assertRaises(Error, partial(analyse, self.senpy, input="tupni"))
def test_analyse(self):
@ -177,7 +167,7 @@ class ExtensionsTest(TestCase):
def test_analyse_error(self):
class ErrorPlugin(plugins.Analyser):
author = 'nobody'
author: str = 'nobody'
version = 0
ex = Error()
@ -205,17 +195,12 @@ class ExtensionsTest(TestCase):
""" Filtering plugins """
assert len(self.senpy.plugins(name="Dummy")) > 0
assert not len(self.senpy.plugins(name="NotDummy"))
assert self.senpy.plugins(name="Dummy", is_activated=True)
self.senpy.deactivate_plugin("Dummy", sync=True)
assert not len(self.senpy.plugins(name="Dummy",
is_activated=True))
def test_load_default_plugins(self):
senpy = Senpy(plugin_folder=self.examples_dir, default_plugins=True)
assert len(senpy.plugins(is_activated=False)) > 1
assert len(senpy.plugins()) > 1
def test_convert_emotions(self):
self.senpy.activate_all(sync=True)
plugin = Plugin({
'id': 'imaginary',
'onyx:usesEmotionModel': 'emoml:fsre-dimensions'

View File

@ -26,14 +26,14 @@ from senpy.models import (Analysis,
EmotionAnalysis,
EmotionSet,
Entry,
Error,
ErrorResponse,
Results,
Sentiment,
SentimentPlugin,
Plugins,
from_string,
from_dict,
subtypes)
from_dict)
from senpy.errors import Error
from senpy import plugins
from pprint import pprint
@ -117,7 +117,7 @@ class ModelsTest(TestCase):
def test_plugins(self):
self.assertRaises(Error, plugins.Plugin)
p = plugins.SentimentPlugin({"name": "dummy",
p = plugins.SentimentPlugin.parse_obj({"name": "dummy",
"description": "I do nothing",
"version": 0,
"extra_params": {
@ -152,11 +152,6 @@ class ModelsTest(TestCase):
s = str(r)
assert "_testing" not in s
def test_serialize(self):
for k, v in subtypes().items():
e = v()
e.serialize()
def test_turtle(self):
"""Any model should be serializable as a turtle file"""
ana = EmotionAnalysis()

View File

@ -35,24 +35,23 @@ ROOT = os.path.join(os.path.dirname(__file__), '..')
class ShelfDummyPlugin(plugins.SentimentPlugin, plugins.ShelfMixin):
'''Dummy plugin for tests.'''
name = 'Shelf'
version = 0
author = 'the senpy community'
name: str = 'Shelf'
version: str = '0'
author: str = 'the senpy community'
def activate(self, *args, **kwargs):
def __init__(self, **kwargs):
super().__init__(**kwargs)
if 'counter' not in self.sh:
self.sh['counter'] = 0
self.save()
def deactivate(self, *args, **kwargs):
self.save()
def analyse(self, *args, **kwargs):
self.sh['counter'] = self.sh['counter'] + 1
e = Entry()
e.nif__isString = self.sh['counter']
r = Results()
r.entries.append(e)
self.save()
return r
@ -82,7 +81,6 @@ class PluginsTest(TestCase):
info={'name': 'default_shelve_file',
'description': 'Dummy plugin for tests',
'version': 'test'})
a.activate()
assert os.path.isfile(a.shelf_file)
os.remove(a.shelf_file)
@ -114,8 +112,6 @@ class PluginsTest(TestCase):
'version': 'test',
'shelf_file': newfile
})
assert a.sh == {}
a.activate()
assert a.sh == {'counter': 0}
assert a.shelf_file == newfile
@ -137,12 +133,10 @@ class PluginsTest(TestCase):
'shelf_file': self.shelf_file,
'version': 'test'
})
a.activate()
assert a.shelf_file == self.shelf_file
res1 = a.analyse(input=1)
assert res1.entries[0].nif__isString == 100
a.deactivate()
del a
with open(self.shelf_file, 'rb') as f:
@ -190,7 +184,6 @@ class PluginsTest(TestCase):
'version': 'test',
'shelf_file': self.shelf_file
})
a.activate()
print('Shelf file: %s' % a.shelf_file)
a.sh['a'] = 'fromA'
a.save()
@ -201,7 +194,6 @@ class PluginsTest(TestCase):
'version': 'test',
'shelf_file': self.shelf_file
})
b.activate()
assert b.sh['a'] == 'fromA'
b.sh['a'] = 'fromB'
assert b.sh['a'] == 'fromB'
@ -228,8 +220,8 @@ class PluginsTest(TestCase):
class MyBox(plugins.Box):
''' Vague description'''
author = 'me'
version = 0
author: str = 'me'
version: str = 0
def to_features(self, entry, **kwargs):
return entry.text.split()
@ -243,7 +235,7 @@ class PluginsTest(TestCase):
entry.myAnnotation = 'DETECTED'
return entry
test_cases = [
test_cases: list[dict] = [
{
'input': "nothing here",
'expected': {'myAnnotation': 'DETECTED'},
@ -260,8 +252,8 @@ class PluginsTest(TestCase):
class SentimentBox(plugins.SentimentBox):
''' Vague description'''
author = 'me'
version = 0
author: str = 'me'
version: str = 0
def predict_one(self, features, **kwargs):
text = ' '.join(features)
@ -269,7 +261,7 @@ class PluginsTest(TestCase):
return [1, 0, 0]
return [0, 0, 1]
test_cases = [
test_cases: list[dict] = [
{
'input': 'a happy face :)',
'polarity': 'marl:Positive'
@ -355,7 +347,7 @@ class PluginsTest(TestCase):
class DummyPlugin(plugins.SentimentBox):
description = 'Plugin to test evaluation'
version = 0
version: str = 0
classes = ['marl:Positive', 'marl:Negative']
@ -365,7 +357,7 @@ class PluginsTest(TestCase):
class SmartPlugin(plugins.SentimentBox):
description = 'Plugin to test evaluation'
version = 0
version: str = 0
classes = ['marl:Positive', 'marl:Negative']

View File

@ -1,80 +0,0 @@
#
# Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from __future__ import print_function
import json
import unittest
import os
from os import path
from fnmatch import fnmatch
from jsonschema import RefResolver, Draft4Validator, ValidationError
from senpy.models import read_schema
root_path = path.join(path.dirname(path.realpath(__file__)), '..')
schema_folder = path.join(root_path, 'senpy', 'schemas')
examples_path = path.join(root_path, 'docs', 'examples')
bad_examples_path = path.join(root_path, 'docs', 'bad-examples')
class JSONSchemaTests(unittest.TestCase):
def test_definitions(self):
read_schema('definitions.json')
def do_create_(jsfile, success):
def do_expected(self):
with open(jsfile) as f:
js = json.load(f)
try:
assert '@type' in js
schema_name = js['@type']
with open(os.path.join(schema_folder, schema_name +
".json")) as file_object:
schema = json.load(file_object)
resolver = RefResolver('file://' + schema_folder + '/', schema)
validator = Draft4Validator(schema, resolver=resolver)
validator.validate(js)
except (AssertionError, ValidationError, KeyError) as ex:
if success:
raise
return
assert success
return do_expected
def add_examples(dirname, success):
for dirpath, dirnames, filenames in os.walk(dirname):
for i in filenames:
if fnmatch(i, '*.json'):
filename = path.join(dirpath, i)
test_method = do_create_(filename, success)
test_method.__name__ = 'test_file_%s_success_%s' % (filename,
success)
test_method.__doc__ = '%s should %svalidate' % (filename, ''
if success else
'not')
setattr(JSONSchemaTests, test_method.__name__, test_method)
del test_method
add_examples(examples_path, True)
add_examples(bad_examples_path, False)
if __name__ == '__main__':
unittest.main()

View File

@ -42,12 +42,10 @@ class SemanticsTest(TestCase):
"""Set up only once, and re-use in every individual test"""
cls.app = Flask("test_extensions")
cls.client = cls.app.test_client()
cls.senpy = Senpy(default_plugins=True)
cls.senpy = Senpy(plugin_folder=None, default_plugins=True)
cls.senpy.init_app(cls.app)
cls.dir = os.path.join(os.path.dirname(__file__), "..")
cls.senpy.add_folder(cls.dir)
cls.senpy.activate_all()
cls.senpy.default_plugin = 'Dummy'
#cls.dir = os.path.join(os.path.dirname(__file__), "..")
#cls.senpy.add_folder(cls.dir)
def setUp(self):
self.app.config['TESTING'] = True # Tell Flask not to catch Exceptions
@ -57,10 +55,10 @@ class SemanticsTest(TestCase):
def test_sentiment(self):
"""
A sentiment analysis call in JSON-LD
a sentiment analysis call in json-ld
"""
# We use expanded JSON-LD and ignore the context, because in general
# the context is a URIS to the service and that URI is not
# we use expanded json-ld and ignore the context, because in general
# the context is a uris to the service and that uri is not
# available outside of self.client
params = {
'input': 'hello',
@ -69,28 +67,28 @@ class SemanticsTest(TestCase):
'expanded': True,
'prefix': 'http://default.example/#'
}
resp = self.client.get("/api/basic?{}".format(urlencode(params)))
resp = self.client.get("/api/sentiment-basic?{}".format(urlencode(params)))
self.assertCode(resp, 200)
g = parse_resp(resp, fmt='json-ld')
print('Got this graph: ', g.serialize(format='ttl'))
assert g
qres = g.query("""
PREFIX prov: <http://www.w3.org/ns/prov#>
PREFIX marl: <http://www.gsi.upm.es/ontologies/marl/ns#>
PREFIX nif: <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#>
PREFIX onyx: <http://www.gsi.upm.es/ontologies/onyx/ns#>
PREFIX senpy: <http://www.gsi.upm.es/onto/senpy/ns#>
prefix prov: <http://www.w3.org/ns/prov#>
prefix marl: <http://www.gsi.upm.es/ontologies/marl/ns#>
prefix nif: <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#>
prefix onyx: <http://www.gsi.upm.es/ontologies/onyx/ns#>
prefix senpy: <http://www.gsi.upm.es/ontologies/senpy/ns#>
SELECT DISTINCT ?entry ?text ?sentiment
SELECT distinct ?entry ?text ?sentiment
WHERE {
?entry a senpy:Entry .
?entry marl:hasOpinion ?o .
?entry nif:isString ?text .
?o marl:hasPolarity ?sentiment .
}""")
assert len(qres) == 1
assert len(qres) == 1, "There should only be one result"
entry, text, sentiment = list(qres)[0]
assert entry
assert str(text) == 'hello'
assert str(text) == 'hello', "The returned text does not match the input text."
assert str(sentiment) in ['marl:Positive', 'marl:Neutral', 'marl:Negative']
def test_sentiment_turtle(self):
@ -104,25 +102,75 @@ class SemanticsTest(TestCase):
'expanded': True,
'prefix': 'http://default.example/#'
}
resp = self.client.get("/api/basic?{}".format(urlencode(params)))
resp = self.client.get("/api/sentiment-basic?{}".format(urlencode(params)))
self.assertCode(resp, 200)
g = parse_resp(resp, 'ttl')
print('Got this graph: ', g.serialize(format='ttl'))
qres = g.query("""
PREFIX prov: <http://www.w3.org/ns/prov#>
PREFIX marl: <http://www.gsi.upm.es/ontologies/marl/ns#>
PREFIX nif: <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#>
PREFIX onyx: <http://www.gsi.upm.es/ontologies/onyx/ns#>
PREFIX senpy: <http://www.gsi.upm.es/onto/senpy/ns#>
PREFIX senpy: <http://www.gsi.upm.es/ontologies/senpy/ns#>
SELECT DISTINCT ?entry ?text ?sentiment
WHERE {
?entry a senpy:Entry .
?entry marl:hasOpinion ?o .
?entry nif:isString ?text .
?o marl:hasPolarity ?sentiment .
?entry a senpy:Entry ;
nif:isString ?text ;
marl:hasOpinion [
marl:hasPolarity ?sentiment
] .
}""")
assert len(qres) == 1, "There should only be one row in the result"
entry, text, sentiment = list(qres)[0]
assert str(text) == 'hello', "Returned text does not match input text"
assert str(sentiment) in ['marl:Positive', 'marl:Neutral', 'marl:Negative']
def test_moral(self):
"""
An example of a moral analysis, adapted from the examples for the AMOR project:
http://www.gsi.upm.es/ontologies/amor/examples
"""
# we use expanded json-ld and ignore the context, because in general
# the context is a uris to the service and that uri is not
# available outside of self.client
params = {
'input': 'hello',
'in-headers': True,
'outformat': 'json-ld',
'expanded': True,
'prefix': 'http://default.example/#'
}
resp = self.client.get("/api/sentiment-basic?{}".format(urlencode(params)))
self.assertCode(resp, 200)
g = parse_resp(resp, fmt='json-ld')
print('Got this graph: ', g.serialize(format='ttl'))
assert g
qres = g.query("""
prefix : <http://www.gsi.upm.es/ontologies/amor/examples#>
prefix amor: <http://www.gsi.upm.es/ontologies/amor/ns#>
prefix amor-bhv: <http://www.gsi.upm.es/ontologies/amor/models/bhv/ns#>
prefix amor-mft: <http://www.gsi.upm.es/ontologies/amor/models/mft/ns#>
prefix bhv: <http://www.gsi.upm.es/ontologies/bhv#>
prefix mft: <http://www.gsi.upm.es/ontologies/mft/ns#>
prefix mls: <http://www.w3.org/ns/mls#>
prefix owl: <http://www.w3.org/2002/07/owl#>
prefix prov: <http://www.w3.org/ns/prov#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
prefix schema: <http://schema.org/>
SELECT ?analysis ?agent ?model ?annotation ?origin ?category
WHERE {
?analysis a amor:MoralValueAnalysis ;
prov:wasAssociatedWith ?agent ;
amor:usedMoralValueModel ?model ;
amor:analysed ?origin ;
prov:generated ?annotation .
?annotation a amor:MoralValueAnnotation ;
amor:hasMoralValueCategory ?category .
}""")
assert len(qres) == 1
entry, text, sentiment = list(qres)[0]
assert entry
assert str(text) == 'hello'
assert str(sentiment) in ['marl:Positive', 'marl:Neutral', 'marl:Negative']
assert str(sentiment) in ['marl:positive', 'marl:neutral', 'marl:negative']