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4 Commits

Author SHA1 Message Date
J. Fernando Sánchez 45421f4613 Small tweaks in docs 5 years ago
J. Fernando Sánchez 7aa69e3d02 restore hash function in js 5 years ago
J. Fernando Sánchez a20252e4bd Update docs + notebooks 5 years ago
J. Fernando Sánchez 9758a2977f Release 0.20 5 years ago

@ -21,16 +21,16 @@ before_script:
except:
- tags # Avoid unnecessary double testing
test-3.5:
test-3.6:
<<: *test_definition
variables:
PYTHON_VERSION: "3.5"
PYTHON_VERSION: "3.6"
test-2.7:
test-3.7:
<<: *test_definition
allow_failure: true
variables:
PYTHON_VERSION: "2.7"
PYTHON_VERSION: "3.7"
push:
stage: push
@ -101,4 +101,3 @@ cleanup_py:
when: always # this is important; run even if preceding stages failed.
script:
- rm -vf ~/.pypirc # we don't want to leave these around, but GitLab may clean up anyway.
- docker logout

@ -6,7 +6,10 @@ services:
language: python
env:
- PYV=2.7
- PYV=3.4
- PYV=3.5
- PYV=3.6
- PYV=3.7
# - PYV=3.3 # Apt fails in this docker image
# run nosetests - Tests
script: make test-$PYV

@ -6,6 +6,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased]
### Fixed
* Restored hash changing function in `main.js`
## 0.20
### Added
* Objects can control the keys that will be used in `serialize`/`jsonld`/`as_dict` by specifying a list of keys in `terse_keys`.
e.g.
@ -27,6 +32,7 @@ e.g.
* Plugin and parameter descriptions are now formatted with (showdown)[https://github.com/showdownjs/showdown].
* The web UI requests extra_parameters from the server. This is useful for pipelines. See #52
* First batch of semantic tests (using SPARQL)
* `Plugin.path()` method to get a file path from a relative path (using the senpy data folder)
### Changed
* `install_deps` now checks what requirements are already met before installing with pip.

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@ -0,0 +1,152 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Senpy in 1 minute\n",
"\n",
"This mini-tutorial only shows how to annotate with a service.\n",
"We will use the [demo server](http://senpy.gsi.upm.es), which runs some open source plugins for sentiment and emotion analysis."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Annotating with senpy is as simple as issuing an HTTP request to the API using your favourite tool.\n",
"This is just an example using curl:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\r\n",
" \"@context\": \"http://senpy.gsi.upm.es/api/contexts/YXBpL3NlbnRpbWVudDE0MD8j\",\r\n",
" \"@type\": \"Results\",\r\n",
" \"entries\": [\r\n",
" {\r\n",
" \"@id\": \"prefix:\",\r\n",
" \"@type\": \"Entry\",\r\n",
" \"marl:hasOpinion\": [\r\n",
" {\r\n",
" \"@type\": \"Sentiment\",\r\n",
" \"marl:hasPolarity\": \"marl:Positive\",\r\n",
" \"prov:wasGeneratedBy\": \"prefix:Analysis_1554389334.6431913\"\r\n",
" }\r\n",
" ],\r\n",
" \"nif:isString\": \"Senpy is awesome\",\r\n",
" \"onyx:hasEmotionSet\": []\r\n",
" }\r\n",
" ]\r\n",
"}"
]
}
],
"source": [
"!curl \"http://senpy.gsi.upm.es/api/sentiment140\" --data-urlencode \"input=Senpy is awesome\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Congratulations**, you've used your first senpy service!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here is the equivalent using the `requests` library:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{\n",
" \"@context\": \"http://senpy.gsi.upm.es/api/contexts/YXBpL3NlbnRpbWVudDE0MD9pbnB1dD1TZW5weStpcythd2Vzb21lIw%3D%3D\",\n",
" \"@type\": \"Results\",\n",
" \"entries\": [\n",
" {\n",
" \"@id\": \"prefix:\",\n",
" \"@type\": \"Entry\",\n",
" \"marl:hasOpinion\": [\n",
" {\n",
" \"@type\": \"Sentiment\",\n",
" \"marl:hasPolarity\": \"marl:Positive\",\n",
" \"prov:wasGeneratedBy\": \"prefix:Analysis_1554389335.9803226\"\n",
" }\n",
" ],\n",
" \"nif:isString\": \"Senpy is awesome\",\n",
" \"onyx:hasEmotionSet\": []\n",
" }\n",
" ]\n",
"}\n"
]
}
],
"source": [
"import requests\n",
"res = requests.get('http://senpy.gsi.upm.es/api/sentiment140',\n",
" params={\"input\": \"Senpy is awesome\",})\n",
"print(res.text)"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
},
"toc": {
"colors": {
"hover_highlight": "#DAA520",
"running_highlight": "#FF0000",
"selected_highlight": "#FFD700"
},
"moveMenuLeft": true,
"nav_menu": {
"height": "68px",
"width": "252px"
},
"navigate_menu": true,
"number_sections": true,
"sideBar": true,
"threshold": 4,
"toc_cell": false,
"toc_section_display": "block",
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 1
}

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@ -6,4 +6,5 @@ Advanced usage
server-cli
conversion
commandline
commandline
development

@ -38,6 +38,8 @@ extensions = [
'sphinxcontrib.httpdomain',
'sphinx.ext.coverage',
'sphinx.ext.autosectionlabel',
'nbsphinx',
'sphinx.ext.mathjax',
]
# Add any paths that contain templates here, relative to this directory.
@ -54,7 +56,7 @@ master_doc = 'index'
# General information about the project.
project = u'Senpy'
copyright = u'2016, J. Fernando Sánchez'
copyright = u'2019, J. Fernando Sánchez'
description = u'A framework for sentiment and emotion analysis services'
# The version info for the project you're documenting, acts as replacement for
@ -79,7 +81,9 @@ language = None
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ['_build']
exclude_patterns = ['_build', '**.ipynb_checkpoints']
# The reST default role (used for this markup: `text`) to use for all
# documents.
@ -286,3 +290,13 @@ texinfo_documents = [
# If true, do not generate a @detailmenu in the "Top" node's menu.
#texinfo_no_detailmenu = False
nbsphinx_prolog = """
.. note:: This page has been auto-generated from a Jupyter notebook using nbsphinx_.
The original source is available at: https://github.com/gsi-upm/senpy/tree/master/docs//{{ env.doc2path(env.docname, base=None) }}
.. _nbsphinx: https://nbsphinx.readthedocs.io/
----
"""

@ -4,11 +4,10 @@ Demo
There is a demo available on http://senpy.gsi.upm.es/, where you can test a live instance of Senpy, with several open source plugins.
You can use the playground (a web interface) or make HTTP requests to the service API.
.. image:: senpy-playground.png
:height: 400px
.. image:: playground-0.20.png
:target: http://senpy.gsi.upm.es
:width: 800px
:scale: 100 %
:align: center
The source code and description of the plugins used in the demo are available here: https://lab.gsi.upm.es/senpy/senpy-plugins-community/.
The source code and description of the plugins used in the demo are available here: https://github.com/gsi-upm/senpy-plugins-community/.

@ -1,16 +1,16 @@
Welcome to Senpy's documentation!
=================================
.. image:: https://readthedocs.org/projects/senpy/badge/?version=latest
:target: http://senpy.readthedocs.io/en/latest/
:target: http://senpy.readthedocs.io/en/latest/
.. image:: https://badge.fury.io/py/senpy.svg
:target: https://badge.fury.io/py/senpy
:target: https://badge.fury.io/py/senpy
.. image:: https://lab.gsi.upm.es/senpy/senpy/badges/master/build.svg
:target: https://lab.gsi.upm.es/senpy/senpy/commits/master
:target: https://lab.gsi.upm.es/senpy/senpy/commits/master
.. image:: https://lab.gsi.upm.es/senpy/senpy/badges/master/coverage.svg
:target: https://lab.gsi.upm.es/senpy/senpy/commits/master
:target: https://lab.gsi.upm.es/senpy/senpy/commits/master
.. image:: https://img.shields.io/pypi/l/requests.svg
:target: https://lab.gsi.upm.es/senpy/senpy/
:target: https://lab.gsi.upm.es/senpy/senpy/
Senpy is a framework for sentiment and emotion analysis services.
@ -20,15 +20,16 @@ If you interested in consuming Senpy services, read :doc:`Quickstart`.
To get familiar with the concepts behind Senpy, and what it can offer for service developers, check out :doc:`development`.
:doc:`apischema` contains information about the semantic models and vocabularies used by Senpy.
.. toctree::
:caption: Learn more about senpy:
:maxdepth: 2
senpy
Quickstart
installation
development
apischema
advanced
demo
publications
:caption: Learn more about senpy:
:maxdepth: 2
senpy
demo
Quickstart.ipynb
installation
apischema
advanced
publications

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@ -22,7 +22,7 @@ Hence, two parts are necessary: 1) the code that will process the entry, and 2)
In practice, this is what a plugin looks like, tests included:
.. literalinclude:: ../senpy/plugins/example/rand_plugin.py
.. literalinclude:: ../example-plugins/rand_plugin.py
:emphasize-lines: 5-11
:language: python
@ -76,8 +76,9 @@ Most plugins will need access to files (dictionaries, lexicons, etc.).
These files are usually heavy or under a license that does not allow redistribution.
For this reason, senpy has a `data_folder` that is separated from the source files.
The location of this folder is controlled programmatically or by setting the `SENPY_DATA` environment variable.
You can use the `self.path(filepath)` function to get the path of a given `filepath` within the data folder.
Plugins have a convenience function `self.open` which will automatically prepend the data folder to relative paths:
Plugins have a convenience function `self.open` which will automatically look for the file if it exists, or open a new one if it doesn't:
.. code:: python
@ -132,7 +133,7 @@ And you can run it with:
docker run -p 5000:5000 gsiupm/exampleplugin
If the plugin uses non-source files (:ref:`loading data and files`), the recommended way is to use `SENPY_DATA` folder.
If the plugin uses non-source files (:ref:`How should I load external data and files`), the recommended way is to use `SENPY_DATA` folder.
Data can then be mounted in the container or added to the image.
The former is recommended for open source plugins with licensed resources, whereas the latter is the most convenient and can be used for private images.

@ -1,2 +1,3 @@
sphinxcontrib-httpdomain>=1.4
ipykernel
nbsphinx

@ -18,10 +18,10 @@ And higher level features can be built on top of these services, such as automat
These benefits are not limited to new services.
The community has developed wrappers for some proprietary and commercial services (such as sentiment140 and Meaning Cloud), so you can consult them as.
Senpy comes with a :ref:`built-in client`.
Senpy comes with a built-in client in the client package.
To achieve this goal, Senpy uses a Linked Data principled approach, based on the NIF (NLP Interchange Format) specification, and open vocabularies such as Marl and Onyx.
You can learn more about this in :doc:`vocabularies`.
Check out :doc:`plugins` if you have developed an analysis algorithm (e.g. sentiment analysis) and you want to publish it as a service.
Check out :doc:`development` if you have developed an analysis algorithm (e.g. sentiment analysis) and you want to publish it as a service.

@ -251,11 +251,15 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
return alternative
raise IOError('File does not exist: {}'.format(fname))
def path(self, fpath):
if not os.path.isabs(fpath):
fpath = os.path.join(self.data_folder, fpath)
return fpath
def open(self, fpath, mode='r'):
if 'w' in mode:
# When writing, only use absolute paths or data_folder
if not os.path.isabs(fpath):
fpath = os.path.join(self.data_folder, fpath)
fpath = self.path(fpath)
else:
fpath = self.find_file(fpath)
@ -381,7 +385,9 @@ class SentimentPlugin(Analyser, Evaluable, models.SentimentPlugin):
activity = self.activity(parameters)
entries = []
for feat in X:
entries.append(models.Entry(nif__isString=feat[0]))
if isinstance(feat, list):
feat = ' '.join(feat)
entries.append(models.Entry(nif__isString=feat))
labels = []
for e in self.process_entries(entries, activity):
sent = e.sentiments[0].polarity

@ -203,8 +203,8 @@ $(document).ready(function() {
draw_datasets();
}
// $(window).on('hashchange', hashchanged);
// hashchanged();
$(window).on('hashchange', hashchanged);
hashchanged();
$('.tooltip-form').tooltip();
$('.nav-pills a').on('shown.bs.tab', function (e) {

@ -320,24 +320,32 @@ class PluginsTest(TestCase):
for i in range(50):
testdata.append(["good", 1])
for i in range(50):
testdata.append(["bad", 0])
testdata.append(["bad", -1])
dataset = pd.DataFrame(testdata, columns=['text', 'polarity'])
class DummyPlugin(plugins.SentimentBox):
description = 'Plugin to test evaluation'
version = 0
classes = ['marl:Positive', 'marl:Negative']
def predict_one(self, features, **kwargs):
return 0
print(features[0])
return [0, 1]
class SmartPlugin(plugins.SentimentBox):
description = 'Plugin to test evaluation'
version = 0
classes = ['marl:Positive', 'marl:Negative']
def predict_one(self, features, **kwargs):
print(features[0])
if features[0] == 'good':
return 1
return 0
print('positive')
return [1, 0]
print('negative')
return [0, 1]
dpipe = DummyPlugin()
results = plugins.evaluate(datasets={'testdata': dataset}, plugins=[dpipe], flatten=True)

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