remove pytest warning errors

In the previous commit I naively configured pytest to
treat any warning as an error, excep for numpy
pendingdeprecationwarning errors,
This causes the build in py2.7 to fail, due to some
warnings from nltk.

.gitlab-ci.yml

@@ -21,16 +21,15 @@ before_script:
   except:
     - tags # Avoid unnecessary double testing
     
-test-3.6:
+test-3.5:
   <<: *test_definition
   variables:
-    PYTHON_VERSION: "3.6"
+    PYTHON_VERSION: "3.5"
 
-test-3.7:
+test-2.7:
   <<: *test_definition
-  allow_failure: true
   variables:
-    PYTHON_VERSION: "3.7"
+    PYTHON_VERSION: "2.7"
 
 push:
   stage: push
@@ -101,3 +100,4 @@ 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

.makefiles/python.mk

@@ -29,7 +29,7 @@ build: $(addprefix build-, $(PYVERSIONS)) ## Build all images / python versions
 	docker tag $(IMAGEWTAG)-python$(PYMAIN) $(IMAGEWTAG)
 
 build-%: version Dockerfile-%  ## Build a specific version (e.g. build-2.7)
-	docker build --pull -t '$(IMAGEWTAG)-python$*' -f Dockerfile-$* .;
+	docker build -t '$(IMAGEWTAG)-python$*' -f Dockerfile-$* .;
 
 dev-%: ## Launch a specific development environment using docker (e.g. dev-2.7)
 	@docker start $(NAME)-dev$* || (\

.travis.yml

@@ -1,43 +1,12 @@
 sudo: required
 
-matrix:
-  allow_failures:
-    # Windows is experimental in Travis.
-    # As of this writing, senpy installs but hangs on tests that use the flask test client (e.g. blueprints)
-    - os: windows
-  include:
-    - os: linux
-      language: python
-      python: 3.4
-      before_install:
-        - pip install --upgrade --force-reinstall pandas
-    - os: linux
-      language: python
-      python: 3.5
-    - os: linux
-      language: python
-      python: 3.6
-    - os: linux
-      language: python
-      python: 3.7
-    - os: osx
-      language: generic
-      addons:
-        homebrew:
-          # update: true
-          packages: python3
-      before_install:
-        - python3 -m pip install --upgrade virtualenv
-        - virtualenv -p python3 --system-site-packages "$HOME/venv"
-        - source "$HOME/venv/bin/activate"
-    - os: windows
-      language: bash
-      before_install:
-        - choco install -y python3
-        - python -m pip install --upgrade pip
-      env: PATH=/c/Python37:/c/Python37/Scripts:$PATH
-# command to run tests
-# 'python' points to Python 2.7 on macOS but points to Python 3.7 on Linux and Windows
-# 'python3' is a 'command not found' error on Windows but 'py' works on Windows only
-script:
-  - python3 setup.py test || python setup.py test
+services:
+  - docker
+
+language: python
+
+env:
+  - PYV=2.7
+  - PYV=3.5
+# run nosetests - Tests
+script: make test-$PYV

CHANGELOG.md

@@ -1,67 +0,0 @@
-# Changelog
-All notable changes to this project will be documented in this file.
-
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
-and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
-
-## [1.0.1]
-### Added
-* License headers
-* Description for PyPI (setup.py)
-
-### Changed
-* The evaluation tab shows datasets inline, and a tooltip shows the number of instances
-* The docs should be clearer now
-
-## [1.0.0]
-### 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.
-```python
->>> class MyModel(senpy.models.BaseModel):
-...   _terse_keys = ['visible']
-...   invisible = 5
-...   visible = 1
-...
->>> m = MyModel(id='testing')
->>> m.jsonld()
-{'invisible': 5, 'visible': 1, '@id': 'testing'}
->>> m.jsonld(verbose=False)
-{'visible': 1}
-```
-* Configurable logging format.
-* Added default terse keys for the most common classes (entry, sentiment, emotion...).
-* Flag parameters (boolean) are set to true even when no value is added (e.g. `&verbose` is the same as `&verbose=true`).
-* 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.
-* Help is now provided verbosely by default
-* Other outputs are terse by default. This means some properties are now hidden unless verbose is set.
-* `sentiments` and `emotions` are now `marl:hasOpinion` and `onyx:hasEmotionSet`, respectively.
-* Nicer logging format
-* Context aliases (e.g. `sentiments` and `emotions` properties) have been replaced with the original properties (e.g. `marl:hasOpinion` and `onyx:hasEmotionSet**), to use aliases, pass the `aliases** parameter.
-* Several UI improvements
-  * Dedicated tab to show the list of plugins
-  * URLs in plugin descriptions are shown as links
-  * The format of the response is selected by clicking on a tab instead of selecting from a drop-down
-  * list of examples
-  * Bootstrap v4
-* RandEmotion and RandSentiment are no longer included in the base set of plugins
-* The `--plugin-folder` option can be used more than once, and every folder will be added to the app.
-
-### Deprecated
-### Removed
-* Python 2.7 is no longer test or officially supported
-### Fixed
-* Plugin descriptions are now dedented when they are extracted from the docstring.
-### Security
-

MANIFEST.in

@@ -2,10 +2,9 @@ include requirements.txt
 include test-requirements.txt
 include extra-requirements.txt
 include README.rst
-include LICENSE.txt
 include senpy/VERSION
 graft senpy/plugins
 graft senpy/schemas
 graft senpy/templates
 graft senpy/static
-graft img
+graft img

Makefile

@@ -5,7 +5,7 @@ IMAGENAME=gsiupm/senpy
 
 # The first version is the main one (used for quick builds)
 # See .makefiles/python.mk for more info
-PYVERSIONS=3.6 3.7
+PYVERSIONS=3.5 2.7
 
 DEVPORT=5000
 

Procfile

@@ -1 +1 @@
-web: python -m senpy --host 0.0.0.0 --port $PORT
+web: python -m senpy --host 0.0.0.0 --port $PORT --default-plugins

README.rst

@@ -1,25 +1,18 @@
 .. image:: img/header.png
    :width: 100%
-   :target: http://senpy.gsi.upm.es
+   :target: http://demos.gsi.dit.upm.es/senpy
 
-.. image:: https://readthedocs.org/projects/senpy/badge/?version=latest
-  :target: http://senpy.readthedocs.io/en/latest/
-.. image:: https://badge.fury.io/py/senpy.svg
-  :target: https://badge.fury.io/py/senpy
-.. image:: https://travis-ci.org/gsi-upm/senpy.svg
-  :target: https://github.com/gsi-upm/senpy/senpy/tree/master
-.. image:: https://img.shields.io/pypi/l/requests.svg
-  :target: https://lab.gsi.upm.es/senpy/senpy/
+.. image:: https://travis-ci.org/gsi-upm/senpy.svg?branch=master
+   :target: https://travis-ci.org/gsi-upm/senpy
 
-     
 Senpy lets you create sentiment analysis web services easily, fast and using a well known API.
-As a bonus, Senpy services use semantic vocabularies (e.g. `NIF <http://persistence.uni-leipzig.org/nlp2rdf/>`_, `Marl <http://www.gsi.dit.upm.es/ontologies/marl>`_, `Onyx <http://www.gsi.dit.upm.es/ontologies/onyx>`_) and formats (turtle, JSON-LD, xml-rdf).
+As a bonus, senpy services use semantic vocabularies (e.g. `NIF <http://persistence.uni-leipzig.org/nlp2rdf/>`_, `Marl <http://www.gsi.dit.upm.es/ontologies/marl>`_, `Onyx <http://www.gsi.dit.upm.es/ontologies/onyx>`_) and formats (turtle, JSON-LD, xml-rdf).
 
 Have you ever wanted to turn your sentiment analysis algorithms into a service?
-With Senpy, now you can.
+With senpy, now you can.
 It provides all the tools so you just have to worry about improving your algorithms:
 
-`See it in action. <http://senpy.gsi.upm.es/>`_
+`See it in action. <http://senpy.cluster.gsi.dit.upm.es/>`_
 
 Installation
 ------------
@@ -41,36 +34,20 @@ Alternatively, you can use the development version:
    cd senpy
    pip install --user .
 
-If you want to install Senpy globally, use sudo instead of the ``--user`` flag.
+If you want to install senpy globally, use sudo instead of the ``--user`` flag.
 
 Docker Image
 ************
-Build the image or use the pre-built one: ``docker run -ti -p 5000:5000 gsiupm/senpy``.
+Build the image or use the pre-built one: ``docker run -ti -p 5000:5000 gsiupm/senpy --default-plugins``.
 
-To add custom plugins, add a volume and tell Senpy where to find the plugins: ``docker run -ti -p 5000:5000 -v <PATH OF PLUGINS>:/plugins gsiupm/senpy -f /plugins``
+To add custom plugins, add a volume and tell senpy where to find the plugins: ``docker run -ti -p 5000:5000 -v <PATH OF PLUGINS>:/plugins gsiupm/senpy --default-plugins -f /plugins``
 
 
-Compatibility
--------------
-
-Senpy should run on any major operating system.
-Its code is pure Python, and the only limitations are imposed by its dependencies (e.g., nltk, pandas).
-
-Currently, the CI/CD pipeline tests the code on:
-
-* GNU/Linux with Python versions 3.4, 3.5, 3.6 and 3.7
-* MacOS and homebrew's python3
-* Windows 10 and chocolatey's python3
-
-The latest PyPI package is verified to install on Ubuntu, Debian and Arch Linux.
-
-If you have trouble installing Senpy on your platform, see `Having problems?`_.
-
 Developing
 ----------
 
-Running/debugging
-*****************
+Developing/debugging
+********************
 This command will run the senpy container using the latest image available, mounting your current folder so you get your latest code:
 
 .. code:: bash
@@ -133,7 +110,7 @@ or, alternatively:
 This will create a server with any modules found in the current path.
 For more options, see the `--help` page.
 
-Alternatively, you can use the modules included in Senpy to build your own application.
+Alternatively, you can use the modules included in senpy to build your own application.
 
 Deploying on Heroku
 -------------------
@@ -141,31 +118,13 @@ Use a free heroku instance to share your service with the world.
 Just use the example Procfile in this repository, or build your own.
 
 
+`DEMO on heroku <http://senpy.herokuapp.com>`_
+
+
 For more information, check out the `documentation <http://senpy.readthedocs.org>`_.
 ------------------------------------------------------------------------------------
 
 
-Python 2.x compatibility
-------------------------
-
-Keeping compatibility between python 2.7 and 3.x is not always easy, especially for a framework that deals both with text and web requests.
-Hence, starting February 2019, this project will no longer make efforts to support python 2.7, which will reach its end of life in 2020.
-Most of the functionality should still work, and the compatibility shims will remain for now, but we cannot make any guarantees at this point.
-Instead, the maintainers will focus their efforts on keeping the codebase compatible across different Python 3.3+ versions, including upcoming ones.
-We apologize for the inconvenience.
-
-
-Having problems?
-----------------
-
-Please, file a new issue `on GitHub <https://github.com/gsi-upm/senpy/issues>`_ including enough details to reproduce the bug, including:
-
-* Operating system
-* Version of Senpy (or docker tag)
-* Installed libraries
-* Relevant logs
-* A simple code example
-
 Acknowledgement
 ---------------
 This development has been partially funded by the European Union through the MixedEmotions Project (project number H2020 655632), as part of the `RIA ICT 15 Big data and Open Data Innovation and take-up` programme.

config.py

@@ -0,0 +1,4 @@
+import os
+
+SERVER_PORT = os.environ.get("SERVER_PORT", 5000)
+DEBUG = os.environ.get("DEBUG", True)

docs/Evaluation.ipynb

@@ -1,592 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Evaluating Services"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Sentiment analysis plugins can also be evaluated on a series of pre-defined datasets.\n",
-    "This can be done in three ways: through the Web UI (playground), through the web API and programmatically.\n",
-    "\n",
-    "Regardless of the way you perform the evaluation, you will need to specify a plugin (service) that you want to evaluate, and a series of datasets on which it should be evaluated.\n",
-    "\n",
-    "to evaluate a plugin on a dataset, senpy use the plugin to predict the sentiment in each entry in the dataset.\n",
-    "These predictions are compared with the expected values to produce several metrics, such as: accuracy, precision and f1-score.\n",
-    "\n",
-    "**note**: the evaluation process might take long for plugins that use external services, such as `sentiment140`.\n",
-    "\n",
-    "**note**: plugins are assumed to be pre-trained and invariant. i.e., the prediction for an entry should "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Web UI (Playground)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The playground should contain a tab for Evaluation, where you can select any plugin that can be evaluated, and the set of datasets that you want to test the plugin on.\n",
-    "\n",
-    "For example, the image below shows the results of the `sentiment-vader` plugin on the `vader` and `sts` datasets:\n",
-    "\n",
-    "\n",
-    "![](eval_table.png)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Web API"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The api exposes an endpoint (`/evaluate`), which accents the plugin and the set of datasets on which it should be evaluated."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The following code is not necessary, but it will display the results better:"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Here is a simple call using the requests library:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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-       ".output_html .il { color: #666666 } /* Literal.Number.Integer.Long */</style><div class=\"highlight\"><pre><span></span><span class=\"p\">{</span>\n",
-       "  <span class=\"nt\">&quot;@context&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;http://senpy.gsi.upm.es/api/contexts/YXBpL2V2YWx1YXRlLz9hbGdvPXNlbnRpbWVudC12YWRlciZkYXRhc2V0PXZhZGVyJTJDc3RzJm91dGZvcm1hdD1qc29uLWxkIw%3D%3D&quot;</span><span class=\"p\">,</span>\n",
-       "  <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;AggregatedEvaluation&quot;</span><span class=\"p\">,</span>\n",
-       "  <span class=\"nt\">&quot;senpy:evaluations&quot;</span><span class=\"p\">:</span> <span class=\"p\">[</span>\n",
-       "    <span class=\"p\">{</span>\n",
-       "      <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Evaluation&quot;</span><span class=\"p\">,</span>\n",
-       "      <span class=\"nt\">&quot;evaluates&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;endpoint:plugins/sentiment-vader_0.1.1__vader&quot;</span><span class=\"p\">,</span>\n",
-       "      <span class=\"nt\">&quot;evaluatesOn&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;vader&quot;</span><span class=\"p\">,</span>\n",
-       "      <span class=\"nt\">&quot;metrics&quot;</span><span class=\"p\">:</span> <span class=\"p\">[</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Accuracy&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.6907142857142857</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Precision_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.34535714285714286</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Recall_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.5</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
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-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.40853400929446554</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_weighted&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.5643605528396403</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_micro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.6907142857142857</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.40853400929446554</span>\n",
-       "        <span class=\"p\">}</span>\n",
-       "      <span class=\"p\">]</span>\n",
-       "    <span class=\"p\">},</span>\n",
-       "    <span class=\"p\">{</span>\n",
-       "      <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Evaluation&quot;</span><span class=\"p\">,</span>\n",
-       "      <span class=\"nt\">&quot;evaluates&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;endpoint:plugins/sentiment-vader_0.1.1__sts&quot;</span><span class=\"p\">,</span>\n",
-       "      <span class=\"nt\">&quot;evaluatesOn&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;sts&quot;</span><span class=\"p\">,</span>\n",
-       "      <span class=\"nt\">&quot;metrics&quot;</span><span class=\"p\">:</span> <span class=\"p\">[</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Accuracy&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.3107177974434612</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Precision_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.1553588987217306</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;Recall_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.5</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.23705926481620407</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_weighted&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.14731706525451424</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_micro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.3107177974434612</span>\n",
-       "        <span class=\"p\">},</span>\n",
-       "        <span class=\"p\">{</span>\n",
-       "          <span class=\"nt\">&quot;@type&quot;</span><span class=\"p\">:</span> <span class=\"s2\">&quot;F1_macro&quot;</span><span class=\"p\">,</span>\n",
-       "          <span class=\"nt\">&quot;value&quot;</span><span class=\"p\">:</span> <span class=\"mf\">0.23705926481620407</span>\n",
-       "        <span class=\"p\">}</span>\n",
-       "      <span class=\"p\">]</span>\n",
-       "    <span class=\"p\">}</span>\n",
-       "  <span class=\"p\">]</span>\n",
-       "<span class=\"p\">}</span>\n",
-       "</pre></div>\n"
-      ],
-      "text/latex": [
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-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.40853400929446554}\n",
-       "        \\PY{p}{\\PYZcb{}}\n",
-       "      \\PY{p}{]}\n",
-       "    \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "    \\PY{p}{\\PYZob{}}\n",
-       "      \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Evaluation\\PYZdq{}}\\PY{p}{,}\n",
-       "      \\PY{n+nt}{\\PYZdq{}evaluates\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}endpoint:plugins/sentiment\\PYZhy{}vader\\PYZus{}0.1.1\\PYZus{}\\PYZus{}sts\\PYZdq{}}\\PY{p}{,}\n",
-       "      \\PY{n+nt}{\\PYZdq{}evaluatesOn\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}sts\\PYZdq{}}\\PY{p}{,}\n",
-       "      \\PY{n+nt}{\\PYZdq{}metrics\\PYZdq{}}\\PY{p}{:} \\PY{p}{[}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Accuracy\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.3107177974434612}\n",
-       "        \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Precision\\PYZus{}macro\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.1553588987217306}\n",
-       "        \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Recall\\PYZus{}macro\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.5}\n",
-       "        \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}F1\\PYZus{}macro\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.23705926481620407}\n",
-       "        \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}F1\\PYZus{}weighted\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.14731706525451424}\n",
-       "        \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}F1\\PYZus{}micro\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.3107177974434612}\n",
-       "        \\PY{p}{\\PYZcb{}}\\PY{p}{,}\n",
-       "        \\PY{p}{\\PYZob{}}\n",
-       "          \\PY{n+nt}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}F1\\PYZus{}macro\\PYZdq{}}\\PY{p}{,}\n",
-       "          \\PY{n+nt}{\\PYZdq{}value\\PYZdq{}}\\PY{p}{:} \\PY{l+m+mf}{0.23705926481620407}\n",
-       "        \\PY{p}{\\PYZcb{}}\n",
-       "      \\PY{p}{]}\n",
-       "    \\PY{p}{\\PYZcb{}}\n",
-       "  \\PY{p}{]}\n",
-       "\\PY{p}{\\PYZcb{}}\n",
-       "\\end{Verbatim}\n"
-      ],
-      "text/plain": [
-       "{\n",
-       "  \"@context\": \"http://senpy.gsi.upm.es/api/contexts/YXBpL2V2YWx1YXRlLz9hbGdvPXNlbnRpbWVudC12YWRlciZkYXRhc2V0PXZhZGVyJTJDc3RzJm91dGZvcm1hdD1qc29uLWxkIw%3D%3D\",\n",
-       "  \"@type\": \"AggregatedEvaluation\",\n",
-       "  \"senpy:evaluations\": [\n",
-       "    {\n",
-       "      \"@type\": \"Evaluation\",\n",
-       "      \"evaluates\": \"endpoint:plugins/sentiment-vader_0.1.1__vader\",\n",
-       "      \"evaluatesOn\": \"vader\",\n",
-       "      \"metrics\": [\n",
-       "        {\n",
-       "          \"@type\": \"Accuracy\",\n",
-       "          \"value\": 0.6907142857142857\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"Precision_macro\",\n",
-       "          \"value\": 0.34535714285714286\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"Recall_macro\",\n",
-       "          \"value\": 0.5\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_macro\",\n",
-       "          \"value\": 0.40853400929446554\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_weighted\",\n",
-       "          \"value\": 0.5643605528396403\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_micro\",\n",
-       "          \"value\": 0.6907142857142857\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_macro\",\n",
-       "          \"value\": 0.40853400929446554\n",
-       "        }\n",
-       "      ]\n",
-       "    },\n",
-       "    {\n",
-       "      \"@type\": \"Evaluation\",\n",
-       "      \"evaluates\": \"endpoint:plugins/sentiment-vader_0.1.1__sts\",\n",
-       "      \"evaluatesOn\": \"sts\",\n",
-       "      \"metrics\": [\n",
-       "        {\n",
-       "          \"@type\": \"Accuracy\",\n",
-       "          \"value\": 0.3107177974434612\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"Precision_macro\",\n",
-       "          \"value\": 0.1553588987217306\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"Recall_macro\",\n",
-       "          \"value\": 0.5\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_macro\",\n",
-       "          \"value\": 0.23705926481620407\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_weighted\",\n",
-       "          \"value\": 0.14731706525451424\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_micro\",\n",
-       "          \"value\": 0.3107177974434612\n",
-       "        },\n",
-       "        {\n",
-       "          \"@type\": \"F1_macro\",\n",
-       "          \"value\": 0.23705926481620407\n",
-       "        }\n",
-       "      ]\n",
-       "    }\n",
-       "  ]\n",
-       "}"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import requests\n",
-    "from IPython.display import Code\n",
-    "\n",
-    "endpoint = 'http://senpy.gsi.upm.es/api'\n",
-    "res = requests.get(f'{endpoint}/evaluate',\n",
-    "                   params={\"algo\": \"sentiment-vader\",\n",
-    "                           \"dataset\": \"vader,sts\",\n",
-    "                           'outformat': 'json-ld'\n",
-    "                          })\n",
-    "Code(res.text, language='json')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Programmatically (expert)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A third option is to evaluate plugins manually without launching the server.\n",
-    "\n",
-    "This option is particularly interesting for advanced users that want faster iterations and evaluation results, and for automation.\n",
-    "\n",
-    "We would first need an instance of a plugin.\n",
-    "In this example we will use the Sentiment140 plugin that is included in every senpy installation:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from senpy.plugins.sentiment import sentiment140_plugin"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "s140 = sentiment140_plugin.Sentiment140()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Then, we need to know what datasets are available.\n",
-    "We can list all datasets and basic stats (e.g., number of instances and labels used) like this:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "vader {'instances': 4200, 'labels': [1, -1]}\n",
-      "sts {'instances': 4200, 'labels': [1, -1]}\n",
-      "imdb_unsup {'instances': 50000, 'labels': [1, -1]}\n",
-      "imdb {'instances': 50000, 'labels': [1, -1]}\n",
-      "sst {'instances': 11855, 'labels': [1, -1]}\n",
-      "multidomain {'instances': 38548, 'labels': [1, -1]}\n",
-      "sentiment140 {'instances': 1600000, 'labels': [1, -1]}\n",
-      "semeval07 {'instances': 'None', 'labels': [1, -1]}\n",
-      "semeval14 {'instances': 7838, 'labels': [1, -1]}\n",
-      "pl04 {'instances': 4000, 'labels': [1, -1]}\n",
-      "pl05 {'instances': 10662, 'labels': [1, -1]}\n",
-      "semeval13 {'instances': 6259, 'labels': [1, -1]}\n"
-     ]
-    }
-   ],
-   "source": [
-    "from senpy.gsitk_compat import datasets\n",
-    "for k, d in datasets.items():\n",
-    "    print(k, d['stats'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now, we will evaluate our plugin in one of the smallest datasets, `sts`:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[{\n",
-       "     \"@type\": \"Evaluation\",\n",
-       "     \"evaluates\": \"endpoint:plugins/sentiment140_0.2\",\n",
-       "     \"evaluatesOn\": \"sts\",\n",
-       "     \"metrics\": [\n",
-       "         {\n",
-       "             \"@type\": \"Accuracy\",\n",
-       "             \"value\": 0.872173058013766\n",
-       "         },\n",
-       "         {\n",
-       "             \"@type\": \"Precision_macro\",\n",
-       "             \"value\": 0.9035254323131467\n",
-       "         },\n",
-       "         {\n",
-       "             \"@type\": \"Recall_macro\",\n",
-       "             \"value\": 0.8021249029415483\n",
-       "         },\n",
-       "         {\n",
-       "             \"@type\": \"F1_macro\",\n",
-       "             \"value\": 0.8320673712021136\n",
-       "         },\n",
-       "         {\n",
-       "             \"@type\": \"F1_weighted\",\n",
-       "             \"value\": 0.8631351567604358\n",
-       "         },\n",
-       "         {\n",
-       "             \"@type\": \"F1_micro\",\n",
-       "             \"value\": 0.872173058013766\n",
-       "         },\n",
-       "         {\n",
-       "             \"@type\": \"F1_macro\",\n",
-       "             \"value\": 0.8320673712021136\n",
-       "         }\n",
-       "     ]\n",
-       " }]"
-      ]
-     },
-     "execution_count": 37,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "s140.evaluate(['sts', ])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "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
-}

docs/Makefile

@@ -24,7 +24,6 @@ I18NSPHINXOPTS  = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) .
 help:
 	@echo "Please use \`make <target>' where <target> is one of"
 	@echo "  html       to make standalone HTML files"
-	@echo "  entr       to watch for changes and continuously make HTML files"
 	@echo "  dirhtml    to make HTML files named index.html in directories"
 	@echo "  singlehtml to make a single large HTML file"
 	@echo "  pickle     to make pickle files"
@@ -50,9 +49,6 @@ help:
 clean:
 	rm -rf $(BUILDDIR)/*
 
-entr:
-	while true; do ag -g rst | entr -d make html; done 
-
 html:
 	$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
 	@echo

docs/SenpyClientUse.ipynb

@@ -0,0 +1,317 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:05:31.465571Z",
+     "start_time": "2017-04-10T19:05:31.458282+02:00"
+    },
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# Client"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "The built-in senpy client allows you to query any Senpy endpoint. We will illustrate how to use it with the public demo endpoint, and then show you how to spin up your own endpoint using docker."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Demo Endpoint\n",
+    "-------------"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "To start using senpy, simply create a new Client and point it to your endpoint. In this case, the latest version of Senpy at GSI."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:12.827640Z",
+     "start_time": "2017-04-10T19:29:12.818617+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "from senpy.client import Client\n",
+    "\n",
+    "c = Client('http://latest.senpy.cluster.gsi.dit.upm.es/api')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Now, let's use that client analyse some queries:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:14.011657Z",
+     "start_time": "2017-04-10T19:29:13.701808+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "r = c.analyse('I like sugar!!', algorithm='sentiment140')\n",
+    "r"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:08:19.616754Z",
+     "start_time": "2017-04-10T19:08:19.610767+02:00"
+    },
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "As you can see, that gave us the full JSON result. A more concise way to print it would be:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:14.854213Z",
+     "start_time": "2017-04-10T19:29:14.842068+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "for entry in r.entries:\n",
+    "      print('{} -> {}'.format(entry['text'], entry['sentiments'][0]['marl:hasPolarity']))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "We can also obtain a list of available plugins with the client:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:16.245198Z",
+     "start_time": "2017-04-10T19:29:16.056545+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "c.plugins()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Or, more concisely:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:17.663275Z",
+     "start_time": "2017-04-10T19:29:17.484623+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "c.plugins().keys()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "Local Endpoint\n",
+    "--------------"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "To run your own instance of senpy, just create a docker container with the latest Senpy image. Using `--default-plugins` you will get some extra plugins to start playing with the API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:20.637539Z",
+     "start_time": "2017-04-10T19:29:19.938322+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "!docker run -ti --name 'SenpyEndpoint' -d -p 6000:5000 gsiupm/senpy:0.8.6 --host 0.0.0.0 --default-plugins"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "To use this endpoint:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:21.263976Z",
+     "start_time": "2017-04-10T19:29:21.260595+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "c_local = Client('http://127.0.0.1:6000/api')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "That's all! After you are done with your analysis, stop the docker container:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2017-04-10T17:29:33.226686Z",
+     "start_time": "2017-04-10T19:29:22.392121+02:00"
+    },
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "!docker stop SenpyEndpoint\n",
+    "!docker rm SenpyEndpoint"
+   ]
+  }
+ ],
+ "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": "3.6.0"
+  },
+  "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
+}

docs/SenpyClientUse.rst

@@ -0,0 +1,106 @@
+
+Client
+======
+
+Demo Endpoint
+-------------
+
+Import Client and send a request
+
+.. code:: python
+
+    from senpy.client import Client
+    
+    c = Client('http://latest.senpy.cluster.gsi.dit.upm.es/api')
+    r = c.analyse('I like Pizza', algorithm='sentiment140')
+
+Print response
+
+.. code:: python
+
+    for entry in r.entries:
+          print('{} -> {}'.format(entry['text'], entry['sentiments'][0]['marl:hasPolarity']))
+
+
+.. parsed-literal::
+
+    I like Pizza -> marl:Positive
+
+
+Obtain a list of available plugins
+
+.. code:: python
+
+    for plugin in c.request('/plugins')['plugins']:
+        print(plugin['name'])
+
+
+.. parsed-literal::
+
+    emoRand
+    rand
+    sentiment140
+
+
+Local Endpoint
+--------------
+
+Run a docker container with Senpy image and default plugins
+
+.. code::
+
+    docker run -ti --name 'SenpyEndpoint' -d -p 5000:5000 gsiupm/senpy:0.8.6 --host 0.0.0.0 --default-plugins
+
+
+.. parsed-literal::
+
+    a0157cd98057072388bfebeed78a830da7cf0a796f4f1a3fd9188f9f2e5fe562
+
+
+Import client and send a request to localhost
+
+.. code:: python
+
+    c_local = Client('http://127.0.0.1:5000/api')
+    r = c_local.analyse('Hello world', algorithm='sentiment140')
+
+Print response
+
+.. code:: python
+
+    for entry in r.entries:
+          print('{} -> {}'.format(entry['text'], entry['sentiments'][0]['marl:hasPolarity']))
+
+
+.. parsed-literal::
+
+    Hello world -> marl:Neutral
+
+
+Obtain a list of available plugins deployed locally
+
+.. code:: python
+
+    c_local.plugins().keys()
+
+
+.. parsed-literal::
+
+    rand
+    sentiment140
+    emoRand
+
+
+Stop the docker container
+
+.. code:: python
+
+    !docker stop SenpyEndpoint
+    !docker rm SenpyEndpoint
+
+
+.. parsed-literal::
+
+    SenpyEndpoint
+    SenpyEndpoint
+

docs/about.rst

@@ -0,0 +1,11 @@
+About
+--------
+
+If you use Senpy in your research, please cite `Senpy: A Pragmatic Linked Sentiment Analysis Framework <http://gsi.dit.upm.es/index.php/es/investigacion/publicaciones?view=publication&task=show&id=417>`__ (`BibTex <http://gsi.dit.upm.es/index.php/es/investigacion/publicaciones?controller=publications&task=export&format=bibtex&id=417>`__):
+
+.. code-block:: text
+
+	Sánchez-Rada, J. F., Iglesias, C. A., Corcuera, I., & Araque, Ó. (2016, October).
+	Senpy: A Pragmatic Linked Sentiment Analysis Framework.
+	In Data Science and Advanced Analytics (DSAA),
+	2016 IEEE International Conference on (pp. 735-742). IEEE.

docs/api.rst

@@ -25,7 +25,7 @@ NIF API
         "@context":"http://127.0.0.1/api/contexts/Results.jsonld",
         "@id":"_:Results_11241245.22",
         "@type":"results"
-        "activities": [
+        "analysis": [
           "plugins/sentiment-140_0.1" 
         ],
         "entries": [
@@ -73,7 +73,7 @@ NIF API
 .. http:get:: /api/plugins
 
    Returns a list of installed plugins. 
-   **Example request and response**:
+   **Example request**:
 
    .. sourcecode:: http
 
@@ -82,6 +82,10 @@ NIF API
       Accept: application/json, text/javascript
 
 
+   **Example response**:
+
+   .. sourcecode:: http
+
       {
         "@id": "plugins/sentiment-140_0.1", 
         "@type": "sentimentPlugin", 
@@ -139,14 +143,19 @@ NIF API
 .. http:get:: /api/plugins/<pluginname>
 
    Returns the information of a specific plugin.
-   **Example request and response**:
+   **Example request**:
 
    .. sourcecode:: http
 
-      GET /api/plugins/sentiment-random/ HTTP/1.1
+      GET /api/plugins/rand/ HTTP/1.1
       Host: localhost
       Accept: application/json, text/javascript
 
+
+   **Example response**:
+
+   .. sourcecode:: http
+
       {
         "@context": "http://127.0.0.1/api/contexts/ExamplePlugin.jsonld", 
         "@id": "plugins/ExamplePlugin_0.1", 

docs/apischema.rst

@@ -1,6 +1,5 @@
-API and vocabularies
-####################
-
+API and Examples
+################
 .. toctree::
 
    vocabularies.rst

docs/bad-examples/results/example-analysis-as-id-FAIL.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
     "me:SAnalysis1",
     "me:SgAnalysis1",
     "me:EmotionAnalysis1",

docs/bad-examples/results/example-basic-FAIL.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "http://example.com#NIFExample",
   "@type": "results",
-  "activities": [
+  "analysis": [
   ],
   "entries": [
     {

docs/commandline.rst

@@ -0,0 +1,9 @@
+Command line
+============
+
+This video shows how to analyse text directly on the command line using the senpy tool.
+
+.. image:: https://asciinema.org/a/9uwef1ghkjk062cw2t4mhzpyk.png
+   :width: 100%
+   :target: https://asciinema.org/a/9uwef1ghkjk062cw2t4mhzpyk
+   :alt: CLI demo

docs/conf.py

@@ -38,8 +38,6 @@ extensions = [
     'sphinxcontrib.httpdomain',
     'sphinx.ext.coverage',
     'sphinx.ext.autosectionlabel',
-    'nbsphinx',
-    'sphinx.ext.mathjax',
 ]
 
 # Add any paths that contain templates here, relative to this directory.
@@ -56,7 +54,7 @@ master_doc = 'index'
 
 # General information about the project.
 project = u'Senpy'
-copyright = u'2019, J. Fernando Sánchez'
+copyright = u'2016, 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
@@ -81,9 +79,7 @@ language = None
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
-exclude_patterns = ['_build', '**.ipynb_checkpoints']
-
-
+exclude_patterns = ['_build']
 
 # The reST default role (used for this markup: `text`) to use for all
 # documents.
@@ -130,7 +126,6 @@ html_theme_options = {
     'github_user': 'gsi-upm',
     'github_repo': 'senpy',
     'github_banner': True,
-    'sidebar_collapse': True,
 }
 
 
@@ -291,12 +286,3 @@ texinfo_documents = [
 
 # If true, do not generate a @detailmenu in the "Top" node's menu.
 #texinfo_no_detailmenu = False
-
-nbsphinx_prolog = """
-.. note:: This is an `auto-generated <https://nbsphinx.readthedocs.io>`_ static view of a Jupyter notebook.
-
-    To run the code examples in your computer, you may download the original notebook from the repository: https://github.com/gsi-upm/senpy/tree/master/docs/{{ env.doc2path(env.docname, base=None) }}
-
-
-----
-"""

docs/conversion.rst

@@ -1,152 +1,93 @@
-Automatic Model Conversion
---------------------------
+Conversion
+----------
 
-Senpy includes support for emotion and sentiment conversion.
-When a user requests a specific model, senpy will choose a strategy to convert the model that the service usually outputs and the model requested by the user.
-
-Out of the box, senpy can convert from the `emotionml:pad` (pleasure-arousal-dominance) dimensional model to `emoml:big6` (Ekman's big-6) categories, and vice versa.
-This specific conversion uses a series of dimensional centroids (`emotionml:pad`) for each emotion category (`emotionml:big6`).
-A dimensional value is converted to a category by looking for the nearest centroid.
-The centroids are calculated according to this article:
-
-.. code-block:: text
-
-    Kim, S. M., Valitutti, A., & Calvo, R. A. (2010, June).
-    Evaluation of unsupervised emotion models to textual affect recognition.
-    In Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text (pp. 62-70).
-    Association for Computational Linguistics.
-
-
-
-It is possible to add new conversion strategies by `Developing a conversion plugin`_.
+Senpy includes experimental support for emotion/sentiment conversion plugins.
 
 
 Use
 ===
 
-Consider the following query to an emotion service:  http://senpy.gsi.upm.es/api/emotion-anew?i=good
+Consider the original query: http://127.0.0.1:5000/api/?i=hello&algo=emoRand
 
-The requested plugin (emotion-random) returns emotions using the VAD space (FSRE dimensions in EmotionML):
+The requested plugin (emoRand) returns emotions using Ekman's model (or big6 in EmotionML):
 
 .. code:: json
 
 
-   [
-     {
-       "@type": "EmotionSet",
-       "onyx:hasEmotion": [
-         {
-           "@type": "Emotion",
-           "emoml:pad-dimensions_arousal": 5.43,
-           "emoml:pad-dimensions_dominance": 6.41,
-           "emoml:pad-dimensions_pleasure": 7.47,
-           "prov:wasGeneratedBy": "prefix:Analysis_1562744784.8789825"
-         }
-       ],
-       "prov:wasGeneratedBy": "prefix:Analysis_1562744784.8789825"
-     }
-  ]
-  
+          ... rest of the document ...
+          {
+            "@type": "emotionSet",
+            "onyx:hasEmotion": {
+                "@type": "emotion",
+                "onyx:hasEmotionCategory": "emoml:big6anger"
+            },
+            "prov:wasGeneratedBy": "plugins/emoRand_0.1"
+          }
 
           
 
-To get the equivalent of these emotions in Ekman's categories (i.e., Ekman's Big 6 in EmotionML), we'd do this:
+To get these emotions in VAD space (FSRE dimensions in EmotionML), we'd do this:
 
-http://senpy.gsi.upm.es/api/emotion-anew?i=good&emotion-model=emoml:big6
+http://127.0.0.1:5000/api/?i=hello&algo=emoRand&emotionModel=emoml:fsre-dimensions
 
 This call, provided there is a valid conversion plugin from Ekman's to VAD, would return something like this:
 
 .. code:: json
 
-   [
-      {
-        "@type": "EmotionSet",
-        "onyx:hasEmotion": [
+
+          ... rest of the document ...
           {
-            "@type": "Emotion",
-            "onyx:algorithmConfidence": 4.4979,
-            "onyx:hasEmotionCategory": "emoml:big6happiness"
+            "@type": "emotionSet",
+            "onyx:hasEmotion": {
+                "@type": "emotion",
+                "onyx:hasEmotionCategory": "emoml:big6anger"
+                },
+            "prov:wasGeneratedBy": "plugins/emoRand_0.1"
+          }, {
+            "@type": "emotionSet",
+            "onyx:hasEmotion": {
+                "@type": "emotion",
+                "A": 7.22,
+                "D": 6.28,
+                "V": 8.6
+            },
+            "prov:wasGeneratedBy": "plugins/Ekman2VAD_0.1"
+
           }
-        ],
-        "prov:wasDerivedFrom": {
-          "@id": "Emotions0",
-          "@type": "EmotionSet",
-          "onyx:hasEmotion": [
-            {
-              "@id": "Emotion0",
-              "@type": "Emotion",
-              "emoml:pad-dimensions_arousal": 5.43,
-              "emoml:pad-dimensions_dominance": 6.41,
-              "emoml:pad-dimensions_pleasure": 7.47,
-              "prov:wasGeneratedBy": "prefix:Analysis_1562745220.1553965"
-            }
-          ],
-          "prov:wasGeneratedBy": "prefix:Analysis_1562745220.1553965"
-        },
-        "prov:wasGeneratedBy": "prefix:Analysis_1562745220.1570725"
-      }
-    ]
 
 
 That is called a *full* response, as it simply adds the converted emotion alongside.
 It is also possible to get the original emotion nested within the new converted emotion, using the `conversion=nested` parameter:
 
-http://senpy.gsi.upm.es/api/emotion-anew?i=good&emotion-model=emoml:big6&conversion=nested
-
 .. code:: json
 
-   [
-        {
-          "@type": "EmotionSet",
-          "onyx:hasEmotion": [
-            {
-              "@type": "Emotion",
-              "onyx:algorithmConfidence": 4.4979,
-              "onyx:hasEmotionCategory": "emoml:big6happiness"
-            }
-          ],
-          "prov:wasDerivedFrom": {
-            "@id": "Emotions0",
-            "@type": "EmotionSet",
-            "onyx:hasEmotion": [
-              {
-                "@id": "Emotion0",
-                "@type": "Emotion",
-                "emoml:pad-dimensions_arousal": 5.43,
-                "emoml:pad-dimensions_dominance": 6.41,
-                "emoml:pad-dimensions_pleasure": 7.47,
-                "prov:wasGeneratedBy": "prefix:Analysis_1562744962.896306"
-              }
-            ],
-            "prov:wasGeneratedBy": "prefix:Analysis_1562744962.896306"
-          },
-          "prov:wasGeneratedBy": "prefix:Analysis_1562744962.8978968"
-        }
-  ]
 
+          ... rest of the document ...
+          {
+            "@type": "emotionSet",
+            "onyx:hasEmotion": {
+                "@type": "emotion",
+                "onyx:hasEmotionCategory": "emoml:big6anger"
+                },
+            "prov:wasGeneratedBy": "plugins/emoRand_0.1"
+            "onyx:wasDerivedFrom": {
+                "@type": "emotionSet",
+                "onyx:hasEmotion": {
+                    "@type": "emotion",
+                    "A": 7.22,
+                    "D": 6.28,
+                    "V": 8.6
+                },
+                "prov:wasGeneratedBy": "plugins/Ekman2VAD_0.1"
+             }
+
+          }
 
 
 Lastly, `conversion=filtered` would only return the converted emotions.
 
-
-.. code:: json
-
-   [
-      {
-        "@type": "EmotionSet",
-        "onyx:hasEmotion": [
-          {
-            "@type": "Emotion",
-            "onyx:algorithmConfidence": 4.4979,
-            "onyx:hasEmotionCategory": "emoml:big6happiness"
-          }
-        ],
-        "prov:wasGeneratedBy": "prefix:Analysis_1562744925.7322266"
-      }
-   ]
-
 Developing a conversion plugin
-==============================
+================================
 
 Conversion plugins are discovered by the server just like any other plugin.
 The difference is the slightly different API, and the need to specify the `source` and `target` of the conversion.
@@ -165,6 +106,7 @@ For instance, an emotion conversion plugin needs the following:
 
 
 
+
 .. code:: python
 
 
@@ -172,6 +114,3 @@ For instance, an emotion conversion plugin needs the following:
 
               def convert(self, emotionSet, fromModel, toModel, params):
                   pass
-
-
-More implementation details are shown in the `centroids plugin <https://github.com/gsi-upm/senpy/blob/master/senpy/plugins/postprocessing/emotion/centroids.py>`_.

docs/demo.rst

@@ -1,13 +1,16 @@
 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 the HTTP API.
+There is a demo available on http://senpy.cluster.gsi.dit.upm.es/, where you can test a serie of different plugins.
+You can use the playground (a web interface) or make HTTP requests to the service API.
 
-.. image:: playground-0.20.png
-  :target: http://senpy.gsi.upm.es
+.. image:: senpy-playground.png
+  :height: 400px
   :width: 800px
+  :scale: 100 %
   :align: center
 
+Plugins Demo
+============
 
-The source code and description of the plugins used in the demo are available here: https://github.com/gsi-upm/senpy-plugins-community/.
+The source code and description of the plugins used in the demo is available here: https://lab.cluster.gsi.dit.upm.es/senpy/senpy-plugins-community/.

docs/development.rst

@@ -1,25 +0,0 @@
-Developing new services
------------------------
-
-Developing web services can be hard.
-A text analysis service must implement all the typical features, such as: extraction of parameters, validation, format conversion, visualization...
-
-Senpy implements all the common blocks, so developers can focus on what really matters: great analysis algorithms that solve real problems.
-Among other things, Senpy takes care of these tasks:
-
-  * Interfacing with the user: parameter validation, error handling.
-  * Formatting: JSON-LD, Turtle/n-triples input and output, or simple text input
-  * Linked Data: senpy results are semantically annotated, using a series of well established vocabularies, and sane default URIs.
-  * User interface: a web UI where users can explore your service and test different settings
-  * A client to interact with the service. Currently only available in Python.
-
-You only need to provide the algorithm to turn a piece of text into an annotation
-Sharing your sentiment analysis with the world has never been easier!
-
-.. toctree::
-    :maxdepth: 1
-
-    server-cli
-    plugins-quickstart
-    plugins-faq
-    plugins-definition

docs/examples.rst

@@ -1,6 +1,5 @@
 Examples
---------
-
+------
 All the examples in this page use the :download:`the main schema <_static/schemas/definitions.json>`.
 
 Simple NIF annotation
@@ -18,7 +17,6 @@ Sentiment Analysis
 .....................
 Description
 ,,,,,,,,,,,
-
 This annotation corresponds to the sentiment analysis of an input. The example shows the sentiment represented according to Marl format.
 The sentiments detected are contained in the Sentiments array with their related part of the text.
 
@@ -26,7 +24,20 @@ Representation
 ,,,,,,,,,,,,,,
 
 .. literalinclude:: examples/results/example-sentiment.json
-   :emphasize-lines: 5-11,20-30
+   :emphasize-lines: 5-10,25-33
+   :language: json-ld
+
+Suggestion Mining
+.................
+Description
+,,,,,,,,,,,
+The suggestions schema represented below shows the suggestions detected in the text. Within it, we can find the NIF fields highlighted that corresponds to the text of the detected suggestion. 
+
+Representation
+,,,,,,,,,,,,,,
+
+.. literalinclude:: examples/results/example-suggestion.json
+   :emphasize-lines: 5-8,22-27
    :language: json-ld
 
 Emotion Analysis
@@ -40,6 +51,28 @@ Representation
 
 .. literalinclude:: examples/results/example-emotion.json
    :language: json-ld
-   :emphasize-lines: 5-11,22-36
+   :emphasize-lines: 5-8,25-37
 
+Named Entity Recognition
+........................
+Description
+,,,,,,,,,,,
+The Named Entity Recognition is represented as follows. In this particular case, it can be seen within the entities array the entities recognised. For the example input, Microsoft and Windows Phone are the ones detected. 
+Representation
+,,,,,,,,,,,,,,
 
+.. literalinclude:: examples/results/example-ner.json
+   :emphasize-lines: 5-8,19-34
+   :language: json-ld
+
+Complete example
+................
+Description
+,,,,,,,,,,,
+This example covers all of the above cases, integrating all the annotations in the same document.
+
+Representation
+,,,,,,,,,,,,,,
+
+.. literalinclude:: examples/results/example-complete.json
+   :language: json-ld

docs/examples/results/example-analysis-as-id.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
       {
           "@id": "_:SAnalysis1_Activity",
           "@type": "marl:SentimentAnalysis",

docs/examples/results/example-basic.json

@@ -2,7 +2,7 @@
     "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
     "@id": "me:Result1",
     "@type": "results",
-    "activities": [ ],
+    "analysis": [ ],
     "entries": [
         {
             "@id": "http://example.org#char=0,40",

docs/examples/results/example-complete.json

@@ -2,7 +2,7 @@
     "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
     "@id": "me:Result1",
     "@type": "results",
-    "activities": [
+    "analysis": [
         {
             "@id": "_:SAnalysis1_Activity",
             "@type": "marl:SentimentAnalysis",

docs/examples/results/example-emotion.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
     {
       "@id": "me:EmotionAnalysis1_Activity",
       "@type": "me:EmotionAnalysis1",
@@ -17,6 +17,10 @@
         "nif:Context"
       ],
       "nif:isString": "Dear Microsoft, put your Windows Phone on your newest #open technology program. You'll be awesome. #opensource",
+      "entities": [
+      ],
+      "suggestions": [
+      ],
       "sentiments": [
       ],
       "emotions": [

docs/examples/results/example-ner.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
     {
       "@id": "_:NER1_Activity",
       "@type": "me:NERAnalysis",

docs/examples/results/example-pad.json

@@ -7,7 +7,7 @@
   ],
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
     {
       "@id": "me:HesamsAnalysis_Activity",
       "@type": "onyx:EmotionAnalysis",

docs/examples/results/example-sentiment.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
     {
       "@id": "_:SAnalysis1_Activity",
       "@type": "marl:SentimentAnalysis",
@@ -17,6 +17,10 @@
         "nif:Context"
       ],
       "nif:isString": "Dear Microsoft, put your Windows Phone on your newest #open technology program. You'll be awesome. #opensource",
+      "entities": [
+      ],
+      "suggestions": [
+      ],
       "sentiments": [
         {
           "@id": "http://micro.blog/status1#char=80,97",
@@ -28,7 +32,7 @@
           "prov:wasGeneratedBy": "_:SAnalysis1_Activity"
         }
       ],
-      "emotions": [
+      "emotionSets": [
       ]
     }
   ]

docs/examples/results/example-suggestion.json

@@ -2,7 +2,7 @@
   "@context": "http://mixedemotions-project.eu/ns/context.jsonld",
   "@id": "me:Result1",
   "@type": "results",
-  "activities": [
+  "analysis": [
     {
       "@id": "_:SgAnalysis1_Activity",
       "@type": "me:SuggestionAnalysis",

docs/index.rst

@@ -1,106 +1,35 @@
 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
-.. image:: https://travis-ci.org/gsi-upm/senpy.svg
-  :target: https://github.com/gsi-upm/senpy/senpy/tree/master
+   :target: https://badge.fury.io/py/senpy
+.. image:: https://lab.cluster.gsi.dit.upm.es/senpy/senpy/badges/master/build.svg
+   :target: https://lab.cluster.gsi.dit.upm.es/senpy/senpy/commits/master
+.. image:: https://lab.cluster.gsi.dit.upm.es/senpy/senpy/badges/master/coverage.svg
+   :target: https://lab.cluster.gsi.dit.upm.es/senpy/senpy/commits/master
 .. image:: https://img.shields.io/pypi/l/requests.svg
-  :target: https://lab.gsi.upm.es/senpy/senpy/
-
-Senpy is a framework to build sentiment and emotion analysis services.
-It provides functionalities for:
-
-- developing sentiment and emotion classifier and exposing them as an HTTP service
-- requesting sentiment and emotion analysis from different providers (i.e. Vader, Sentimet140, ...) using the same interface (:doc:`apischema`). In this way, applications do not depend on the API offered for these services.
-- combining services that use different sentiment model (e.g. polarity between [-1, 1] or [0,1] or emotion models (e.g. Ekkman or VAD)
-- evaluating sentiment algorithms with well known datasets
-
-
-Using senpy services is as simple as sending an HTTP request with your favourite tool or library.
-Let's analyze the sentiment of the text "Senpy is awesome".
-
-We can call the `Sentiment140 <http://www.sentiment140.com/>`_ service with an HTTP request using curl:
-
-
-.. code:: shell
-   :emphasize-lines: 14,18
-
-   $ curl "http://senpy.gsi.upm.es/api/sentiment140" \
-         --data-urlencode "input=Senpy is awesome"
-
-   {
-     "@context": "http://senpy.gsi.upm.es/api/contexts/YXBpL3NlbnRpbWVudDE0MD8j",
-     "@type": "Results",
-     "entries": [
-       {
-         "@id": "prefix:",
-         "@type": "Entry",
-         "marl:hasOpinion": [
-           {
-             "@type": "Sentiment",
-             "marl:hasPolarity": "marl:Positive",
-             "prov:wasGeneratedBy": "prefix:Analysis_1554389334.6431913"
-           }
-         ],
-         "nif:isString": "Senpy is awesome",
-         "onyx:hasEmotionSet": []
-       }
-     ]
-   }
-
-
-Congratulations, you’ve used your first senpy service!
-You can observe the result: the polarity is positive (marl:Positive). The reason of this prefix is that Senpy follows a linked data approach.
-
-You can analyze the same sentence using a different sentiment service (e.g. Vader) and requesting a different format (e.g. turtle):
+   :target: https://lab.cluster.gsi.dit.upm.es/senpy/senpy/
 
 
 
-.. code:: shell
+Senpy is a framework for sentiment and emotion analysis services.
+Services built with senpy are interchangeable and easy to use because they share a common :doc:`apischema`.
+It also simplifies service development.
 
-   $ curl "http://senpy.gsi.upm.es/api/sentiment-vader" \
-         --data-urlencode "input=Senpy is awesome" \
-         --data-urlencode "outformat=turtle"
-
-   @prefix : <http://www.gsi.upm.es/onto/senpy/ns#> .
-   @prefix endpoint: <http://senpy.gsi.upm.es/api/> .
-   @prefix marl: <http://www.gsi.dit.upm.es/ontologies/marl/ns#> .
-   @prefix nif: <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#> .
-   @prefix prefix: <http://senpy.invalid/> .
-   @prefix prov: <http://www.w3.org/ns/prov#> .
-   @prefix senpy: <http://www.gsi.upm.es/onto/senpy/ns#> .
-
-   prefix: a senpy:Entry ;
-       nif:isString "Senpy is awesome" ;
-       marl:hasOpinion [ a senpy:Sentiment ;
-               marl:hasPolarity "marl:Positive" ;
-               marl:polarityValue 6.72e-01 ;
-               prov:wasGeneratedBy prefix:Analysis_1562668175.9808676 ] .
-
-   [] a senpy:Results ;
-       prov:used prefix: .
-
-As you see, Vader returns also the polarity value (0.67) in addition to the category (positive).
-
-If you are 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.
+.. image:: senpy-architecture.png
+  :width: 100%
+  :align: center
 
 .. toctree::
-  :caption: Learn more about senpy:
-  :maxdepth: 2
-  :hidden:
+   :caption: Learn more about senpy:
+   :maxdepth: 2
 
-  senpy
-  demo
-  Quickstart.ipynb
-  installation
-  conversion
-  Evaluation.ipynb
-  apischema
-  development
-  publications
-  projects
+   senpy
+   installation
+   demo
+   usage
+   apischema
+   plugins
+   conversion
+   about

docs/installation.rst

@@ -1,10 +1,10 @@
 Installation
 ------------
-The stable version can be used in two ways: as a system/user library through pip, or from a docker image.
+The stable version can be used in two ways: as a system/user library through pip, or as a docker image.
 
-Using docker is recommended because the image is self-contained, reproducible and isolated from the system, which means:
+The docker image is the recommended way because it is self-contained and isolated from the system, which means:
 
-  * It can be downloaded and run with just one simple command
+  * Downloading and using it is just one command
   * All dependencies are included
   * It is OS-independent (MacOS, Windows, GNU/Linux)
   * Several versions may coexist in the same machine without additional virtual environments
@@ -17,39 +17,42 @@ Through PIP
 
 .. code:: bash
 
-   pip install senpy
-
-   # Or with --user if you get permission errors:
-
    pip install --user senpy
+
    
-..
-   Alternatively, you can use the development version:
+Alternatively, you can use the development version:
+ 
+.. code:: bash
 
-   .. code:: bash
-
-      git clone git@github.com:gsi-upm/senpy
-      cd senpy
-      pip install --user .
-
-Each version is automatically tested on GNU/Linux, macOS and Windows 10.
-If you have trouble with the installation, please file an `issue on GitHub <https://github.com/gsi-upm/senpy/issues>`_.
+   git clone git@github.com:gsi-upm/senpy
+   cd senpy
+   pip install --user .
 
+If you want to install senpy globally, use sudo instead of the ``--user`` flag.
 
 Docker Image
 ************
-
-The base image of senpy comes with some built-in plugins that you can use:   
+Build the image or use the pre-built one:   
 
 .. code:: bash
 
-   docker run -ti -p 5000:5000 gsiupm/senpy --host 0.0.0.0
+   docker run -ti -p 5000:5000 gsiupm/senpy --host 0.0.0.0 --default-plugins
 
-To use your custom plugins, you can add volume to the container: 
+To add custom plugins, use a docker volume: 
     
 .. code:: bash
 
-   docker run -ti -p 5000:5000 -v <PATH OF PLUGINS>:/plugins gsiupm/senpy --host 0.0.0.0 --plugins -f /plugins
+   docker run -ti -p 5000:5000 -v <PATH OF PLUGINS>:/plugins gsiupm/senpy --host 0.0.0.0 --default-plugins -f /plugins
+ 
+
+Python 2
+........
+
+There is a Senpy version for python2 too:
+    
+.. code:: bash
+
+   docker run -ti -p 5000:5000 gsiupm/senpy:python2.7 --host 0.0.0.0 --default-plugins
 
 
 Alias
@@ -59,7 +62,7 @@ If you are using the docker approach regularly, it is advisable to use a script
 
 .. code:: bash
 
-   alias senpy='docker run --rm -ti -p 5000:5000 -v $PWD:/senpy-plugins gsiupm/senpy'
+   alias senpy='docker run --rm -ti -p 5000:5000 -v $PWD:/senpy-plugins gsiupm/senpy --default-plugins'
 
 
 Now, you may run senpy from any folder in your computer like so:

docs/plugins-definition.rst

@@ -9,21 +9,20 @@ Lastly, it is also possible to add new plugins programmatically.
 
 .. contents:: :local:
 
-..
-   What is a plugin?
-   =================
+What is a plugin?
+=================
 
-   A plugin is a program that, given a text, will add annotations to it.
-   In practice, a plugin consists of at least two files:
+A plugin is a program that, given a text, will add annotations to it.
+In practice, a plugin consists of at least two files:
 
-   - Definition file: a `.senpy` file that describes the plugin (e.g. what input parameters it accepts, what emotion model it uses).
-   - Python module: the actual code that will add annotations to each input.
+- Definition file: a `.senpy` file that describes the plugin (e.g. what input parameters it accepts, what emotion model it uses).
+- Python module: the actual code that will add annotations to each input.
 
-   This separation allows us to deploy plugins that use the same code but employ different parameters.
-   For instance, one could use the same classifier and processing in several plugins, but train with different datasets.
-   This scenario is particularly useful for evaluation purposes.
+This separation allows us to deploy plugins that use the same code but employ different parameters.
+For instance, one could use the same classifier and processing in several plugins, but train with different datasets.
+This scenario is particularly useful for evaluation purposes.
 
-   The only limitation is that the name of each plugin needs to be unique.
+The only limitation is that the name of each plugin needs to be unique.
 
 Definition files
 ================
@@ -110,3 +109,5 @@ Now, in a file named ``helloworld.py``:
                       sentiment['marl:hasPolarity'] = 'marl:Negative'
                   entry.sentiments.append(sentiment)
                   yield entry
+
+The complete code of the example plugin is available `here <https://lab.cluster.gsi.dit.upm.es/senpy/plugin-prueba>`__.

docs/plugins-quickstart.rst

@@ -1,87 +0,0 @@
-Quickstart for service developers
-=================================
- 
-This document contains the minimum to get you started with developing new services using Senpy.
-
-For an example of conversion plugins, see :doc:`conversion`.
-For a description of definition files, see :doc:`plugins-definition`.
-
-A more step-by-step tutorial with slides is available `here <https://lab.gsi.upm.es/senpy/senpy-tutorial>`__ 
-
-.. contents:: :local:
-
-Installation
-############
-
-First of all, you need to install the package.
-See :doc:`installation` for instructions.
-Once installed, the `senpy` command should be available. 
-
-Architecture
-############
-
-The main component of a sentiment analysis service is the algorithm itself. However, for the algorithm to work, it needs to get the appropriate parameters from the user, format the results according to the defined API, interact with the user whn errors occur or more information is needed, etc.
-
-Senpy proposes a modular and dynamic architecture that allows:
-
-* Implementing different algorithms in a extensible way, yet offering a common interface.
-* Offering common services that facilitate development, so developers can focus on implementing new and better algorithms.
-
-The framework consists of two main modules: Senpy core, which is the building block of the service, and Senpy plugins, which consist of the analysis algorithm. The next figure depicts a simplified version of the processes involved in an analysis with the Senpy framework.
-
-.. image:: senpy-architecture.png
-  :width: 100%
-  :align: center
-
-
-What is a plugin?
-#################
-
-A plugin is a python object that can process entries.
-Given an entry, it will modify it, add annotations to it, or generate new entries.
-
-
-What is an entry?
-#################
-
-Entries are objects that can be annotated.
-In general, they will be a piece of text.
-By default, entries are `NIF contexts <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core/nif-core.html>`_ represented in JSON-LD format.
-It is a dictionary/JSON object that looks like this:
-
-  .. code:: python
-
-            {
-               "@id": "<unique identifier or blank node name>",
-               "nif:isString": "input text",
-               "sentiments": [ {
-                     ...
-               }
-               ],
-               ...
-            }
-
-Annotations are added to the object like this:
-
-.. code:: python
-
-   entry = Entry()
-   entry.vocabulary__annotationName = 'myvalue'
-   entry['vocabulary:annotationName'] = 'myvalue'
-   entry['annotationNameURI'] = 'myvalue'
-
-Where vocabulary is one of the prefixes defined in the default senpy context, and annotationURI is a full URI.
-The value may be any valid JSON-LD dictionary.
-For simplicity, senpy includes a series of models by default in the ``senpy.models`` module.
-
-Plugins Code
-############
-
-The basic methods in a plugin are:
-
-* analyse_entry: called in every user requests. It takes two parameters: ``Entry``, the entry object, and ``params``, the parameters supplied by the user. It should yield one or more ``Entry`` objects.
-* activate: used to load memory-hungry resources. For instance, to train a classifier.
-* deactivate: used to free up resources when the plugin is no longer needed.
-
-Plugins are loaded asynchronously, so don't worry if the activate method takes too long. The plugin will be marked as activated once it is finished executing the method.
-

docs/plugins.rst

@@ -1,18 +1,61 @@
-F.A.Q.
-======
+Developing new plugins
+----------------------
+This document contains the minimum to get you started with developing new analysis plugin.
+For an example of conversion plugins, see :doc:`conversion`.
+For a description of definition files, see :doc:`plugins-definition`.
+
+A more step-by-step tutorial with slides is available `here <https://lab.cluster.gsi.dit.upm.es/senpy/senpy-tutorial>`__ 
 
 .. contents:: :local:
 
+What is a plugin?
+=================
+
+A plugin is a python object that can process entries. Given an entry, it will modify it, add annotations to it, or generate new entries.
+
+
+What is an entry?
+=================
+
+Entries are objects that can be annotated.
+In general, they will be a piece of text.
+By default, entries are `NIF contexts <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core/nif-core.html>`_ represented in JSON-LD format.
+It is a dictionary/JSON object that looks like this:
+
+  .. code:: python
+
+            {
+               "@id": "<unique identifier or blank node name>",
+               "nif:isString": "input text",
+               "sentiments": [ {
+                     ...
+               }
+               ],
+               ...
+            }
+
+Annotations are added to the object like this:
+
+.. code:: python
+
+   entry = Entry()
+   entry.vocabulary__annotationName = 'myvalue'
+   entry['vocabulary:annotationName'] = 'myvalue'
+   entry['annotationNameURI'] = 'myvalue'
+
+Where vocabulary is one of the prefixes defined in the default senpy context, and annotationURI is a full URI.
+The value may be any valid JSON-LD dictionary.
+For simplicity, senpy includes a series of models by default in the ``senpy.models`` module.
 
 
 What are annotations?
-#####################
+=====================
 They are objects just like entries.
-Senpy ships with several default annotations, including ``Sentiment`` and ``Emotion``.
+Senpy ships with several default annotations, including: ``Sentiment``, ``Emotion``, ``EmotionSet``...jk bb
 
 
 What's a plugin made of?
-########################
+========================
 
 When receiving a query, senpy selects what plugin or plugins should process each entry, and in what order.
 It also makes sure the every entry and the parameters provided by the user meet the plugin requirements.
@@ -22,33 +65,45 @@ 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:: ../example-plugins/rand_plugin.py
-   :emphasize-lines: 21-28
+.. literalinclude:: ../senpy/plugins/example/rand_plugin.py
+   :emphasize-lines: 5-11
    :language: python
 
 
 The lines highlighted contain some information about the plugin.
 In particular, the following information is mandatory:
 
-* A unique name for the class. In our example, sentiment-random.
+* A unique name for the class. In our example, Rand.
 * The subclass/type of plugin. This is typically either `SentimentPlugin` or `EmotionPlugin`. However, new types of plugin can be created for different annotations. The only requirement is that these new types inherit from `senpy.Analysis`
 * A description of the plugin. This can be done simply by adding a doc to the class.
 * A version, which should get updated.
 * An author name.
 
 
+Plugins Code
+============
+
+The basic methods in a plugin are:
+
+* analyse_entry: called in every user requests. It takes two parameters: ``Entry``, the entry object, and ``params``, the parameters supplied by the user. It should yield one or more ``Entry`` objects.
+* activate: used to load memory-hungry resources. For instance, to train a classifier.
+* deactivate: used to free up resources when the plugin is no longer needed.
+
+Plugins are loaded asynchronously, so don't worry if the activate method takes too long. The plugin will be marked as activated once it is finished executing the method.
+
+
 How does senpy find modules?
-############################
+============================
 
 Senpy looks for files of two types:
 
 * Python files of the form `senpy_<NAME>.py` or `<NAME>_plugin.py`. In these files, it will look for: 1) Instances that inherit from `senpy.Plugin`, or subclasses of `senpy.Plugin` that can be initialized without a configuration file. i.e. classes that contain all the required attributes for a plugin.
-* Plugin definition files (see :doc:`plugins-definition`)
+* Plugin definition files (see :doc:`advanced-plugins`)
 
-How can I define additional parameters for my plugin?
-#####################################################
+Defining additional parameters
+==============================
 
-Your plugin may ask for additional parameters from users by using the attribute ``extra_params`` in your plugin definition.
+Your plugin may ask for additional parameters from the users of the service by using the attribute ``extra_params`` in your plugin definition.
 It takes a dictionary, where the keys are the name of the argument/parameter, and the value has the following fields:
 
 * aliases: the different names which can be used in the request to use the parameter.
@@ -69,16 +124,15 @@ It takes a dictionary, where the keys are the name of the argument/parameter, an
 
 
 
-How should I load external data and files
-#########################################
+Loading data and files
+======================
 
 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 look for the file if it exists, or open a new one if it doesn't:
+Plugins have a convenience function `self.open` which will automatically prepend the data folder to relative paths:
 
 
 .. code:: python
@@ -90,7 +144,7 @@ Plugins have a convenience function `self.open` which will automatically look fo
               file_in_data = <FILE PATH>
               file_in_sources = <FILE PATH>
 
-              def on activate(self):
+              def activate(self):
                   with self.open(self.file_in_data) as f:
                       self._classifier = train_from_file(f)
                   file_in_source = os.path.join(self.get_folder(), self.file_in_sources)
@@ -101,8 +155,8 @@ Plugins have a convenience function `self.open` which will automatically look fo
 It is good practice to specify the paths of these files in the plugin configuration, so the same code can be reused with different resources.
 
 
-Can I build a docker image for my plugin?
-#########################################
+Docker image
+============
 
 Add the following dockerfile to your project to generate a docker image with your plugin:
 
@@ -133,7 +187,7 @@ And you can run it with:
    docker run -p 5000:5000 gsiupm/exampleplugin
 
 
-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.
+If the plugin uses non-source files (:ref:`loading 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.
 
@@ -150,15 +204,17 @@ Adding data to the image:
    FROM gsiupm/senpy:1.0.1
    COPY data /
 
+F.A.Q.
+======
 What annotations can I use?
-###########################
+???????????????????????????
 
 You can add almost any annotation to an entry.
 The most common use cases are covered in the :doc:`apischema`.
 
 
 Why does the analyse function yield instead of return?
-######################################################
+??????????????????????????????????????????????????????
 
 This is so that plugins may add new entries to the response or filter some of them.
 For instance, a chunker may split one entry into several.
@@ -166,7 +222,7 @@ On the other hand, a conversion plugin may leave out those entries that do not c
 
 
 If I'm using a classifier, where should I train it?
-###################################################
+???????????????????????????????????????????????????
 
 Training a classifier can be time time consuming. To avoid running the training unnecessarily, you can use ShelfMixin to store the classifier. For instance:
 
@@ -200,7 +256,7 @@ A corrupt shelf prevents the plugin from loading.
 If you do not care about the data in the shelf, you can force your plugin to remove the corrupted file and load anyway, set the  'force_shelf' to True in your plugin and start it again.
 
 How can I turn an external service into a plugin?
-#################################################
+?????????????????????????????????????????????????
 
 This example ilustrate how to implement a plugin that accesses the Sentiment140 service.
 
@@ -236,8 +292,8 @@ This example ilustrate how to implement a plugin that accesses the Sentiment140
                   yield entry
 
 
-How can I activate a DEBUG mode for my plugin?
-###############################################
+Can I activate a DEBUG mode for my plugin?
+???????????????????????????????????????????
 
 You can activate the DEBUG mode by the command-line tool using the option -d.
 
@@ -253,6 +309,6 @@ Additionally, with the ``--pdb`` option you will be dropped into a pdb post mort
    python -m pdb yourplugin.py
 
 Where can I find more code examples?
-####################################
+????????????????????????????????????
 
 See: `<http://github.com/gsi-upm/senpy-plugins-community>`_.

docs/projects.rst

@@ -1,49 +0,0 @@
-Projects using Senpy
---------------------
-
-Are you using Senpy in your work?, we would love to hear from you!
-Here is a list of on-going and past projects that have benefited from senpy:
-
-
-MixedEmotions
-,,,,,,,,,,,,,
-
-`MixedEmotions <https://mixedemotions-project.eu/>`_ develops innovative multilingual multi-modal Big Data analytics applications.
-The analytics relies on a common toolbox for multi-modal sentiment and emotion analysis.
-The NLP parts of the toolbox are based on senpy and its API.
-
-The toolbox is featured in this publication:
-
-.. code-block:: text
-
-    Buitelaar, P., Wood, I. D., Arcan, M., McCrae, J. P., Abele, A., Robin, C., … Tummarello, G. (2018). 
-    MixedEmotions: An Open-Source Toolbox for Multi-Modal Emotion Analysis.
-    IEEE Transactions on Multimedia.
-
-EuroSentiment
-,,,,,,,,,,,,,
-
-The aim of the EUROSENTIMENT project was to create a pool for multilingual language resources and services for Sentiment Analysis.
-
-The EuroSentiment project was the main motivation behind the development of Senpy, and some early versions were used:
-
-.. code-block:: text
-
-    Sánchez-Rada, J. F., Vulcu, G., Iglesias, C. A., & Buitelaar, P. (2014).
-    EUROSENTIMENT: Linked Data Sentiment Analysis.
-    Proceedings of the ISWC 2014 Posters & Demonstrations Track
-    13th International Semantic Web Conference (ISWC 2014) (Vol. 1272, pp. 145–148).
-
-
-SoMeDi
-,,,,,,
-`SoMeDi <https://itea3.org/project/somedi.html>`_ is an ITEA3 project to research machine learning and artificial intelligence techniques that can be used to turn digital interaction data into Digital Interaction Intelligence and approaches that can be used to effectively enter and act in social media, and to automate this process.
-SoMeDi exploits senpy's interoperability of services in their customizable data enrichment and NLP workflows.
-
-TRIVALENT
-,,,,,,,,,
-
-`TRIVALENT <https://trivalent-project.eu/>`_ is an EU funded project which aims to a better understanding of root causes of the phenomenon of violent radicalisation in Europe in order to develop appropriate countermeasures, ranging from early detection methodologies to techniques of counter-narrative.
-
-In addition to sentiment and emotion analysis services, trivalent provides other types of senpy services such as radicalism and writing style analysis.
-

docs/publications.rst

@@ -1,36 +0,0 @@
-Publications
-============
-
-
-And if you use Senpy in your research, please cite `Senpy: A Pragmatic Linked Sentiment Analysis Framework <http://gsi.dit.upm.es/index.php/es/investigacion/publicaciones?view=publication&task=show&id=417>`__ (`BibTex <http://gsi.dit.upm.es/index.php/es/investigacion/publicaciones?controller=publications&task=export&format=bibtex&id=417>`__):
-
-.. code-block:: text
-
-	Sánchez-Rada, J. F., Iglesias, C. A., Corcuera, I., & Araque, Ó. (2016, October).
-	Senpy: A Pragmatic Linked Sentiment Analysis Framework.
-	In Data Science and Advanced Analytics (DSAA),
-	2016 IEEE International Conference on (pp. 735-742). IEEE.
-
-
-Senpy uses Onyx for emotion representation, first introduced in:
-
-.. code-block:: text
-
-    Sánchez-Rada, J. F., & Iglesias, C. A. (2016).
-    Onyx: A linked data approach to emotion representation.
-    Information Processing & Management, 52(1), 99-114.
-
-Senpy uses Marl for sentiment representation, which was presented in:
-
-.. code-block:: text
-
-    Westerski, A., Iglesias Fernandez, C. A., & Tapia Rico, F. (2011).
-    Linked opinions: Describing sentiments on the structured web of data.
-
-The representation models, formats and challenges are partially covered in a chapter of the book Sentiment Analysis in Social Networks:
-
-.. code-block:: text
-
-    Iglesias, C. A., Sánchez-Rada, J. F., Vulcu, G., & Buitelaar, P. (2017).
-    Linked Data Models for Sentiment and Emotion Analysis in Social Networks.
-    In Sentiment Analysis in Social Networks (pp. 49-69).

docs/requirements.txt

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

docs/senpy.rst

@@ -1,27 +1,54 @@
 What is Senpy?
 --------------
 
-Senpy is a framework for sentiment and emotion analysis services.
-Its goal is to produce analysis services that are interchangeable and fully interoperable.
+Senpy is a framework for text analysis using Linked Data. There are three main applications of Senpy so far: sentiment and emotion analysis, user profiling and entity recoginition. Annotations and Services are compliant with NIF (NLP Interchange Format).
+
+Senpy aims at providing a framework where analysis modules can be integrated easily as plugins, and providing a core functionality for managing tasks such as data validation, user interaction, formatting, logging, translation to linked data, etc. 
+
+The figure below summarizes the typical features in a text analysis service.
+Senpy implements all the common blocks, so developers can focus on what really matters: great analysis algorithms that solve real problems.
+
+.. image:: senpy-framework.png
+  :width: 60%
+  :align: center
+
+
+Senpy for end users
+===================
+
+All services built using senpy share a common interface.
+This allows users to use them (almost) interchangeably.
+Senpy comes with a :ref:`built-in client`.
+
+
+Senpy for service developers
+============================
+
+Senpy is a framework that turns your sentiment or emotion analysis algorithm into a full blown semantic service.
+Senpy takes care of:
+
+  * Interfacing with the user: parameter validation, error handling.
+  * Formatting: JSON-LD, Turtle/n-triples input and output, or simple text input
+  * Linked Data: senpy results are semantically annotated, using a series of well established vocabularies, and sane default URIs.
+  * User interface: a web UI where users can explore your service and test different settings
+  * A client to interact with the service. Currently only available in Python.
+
+Sharing your sentiment analysis with the world has never been easier!
+
+Check out the :doc:`plugins` if you have developed an analysis algorithm (e.g. sentiment analysis) and you want to publish it as a service.
+
+Architecture
+============
+
+The main component of a sentiment analysis service is the algorithm itself. However, for the algorithm to work, it needs to get the appropriate parameters from the user, format the results according to the defined API, interact with the user whn errors occur or more information is needed, etc.
+
+Senpy proposes a modular and dynamic architecture that allows:
+
+* Implementing different algorithms in a extensible way, yet offering a common interface.
+* Offering common services that facilitate development, so developers can focus on implementing new and better algorithms.
+
+The framework consists of two main modules: Senpy core, which is the building block of the service, and Senpy plugins, which consist of the analysis algorithm. The next figure depicts a simplified version of the processes involved in an analysis with the Senpy framework.
 
 .. image:: senpy-architecture.png
   :width: 100%
   :align: center
-
-All services built using senpy share a common interface.
-This allows users to use them (almost) interchangeably, with the same API and tools, simply by pointing to a different URL or changing a parameter.
-The common schema also makes it easier to evaluate the performance of different algorithms and services.
-In fact, Senpy has a built-in evaluation API you can use to compare results with different algorithms.
-
-Services can also use the common interface to communicate with each other.
-And higher level features can be built on top of these services, such as automatic fusion of results, emotion model conversion, and service discovery.
-
-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 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:`development` if you have developed an analysis algorithm (e.g. sentiment analysis) and you want to publish it as a service.

docs/server.rst

@@ -1,18 +1,14 @@
-Command line tool
-=================
-
-Basic usage
------------
+Server
+======
 
 The senpy server is launched via the `senpy` command:
 
 .. code:: text
 
-    usage: senpy [-h] [--level logging_level] [--log-format log_format] [--debug]
-                [--no-default-plugins] [--host HOST] [--port PORT]
-                [--plugins-folder PLUGINS_FOLDER] [--only-install] [--only-test]
-                [--test] [--only-list] [--data-folder DATA_FOLDER]
-                [--no-threaded] [--no-deps] [--version] [--allow-fail]
+    usage: senpy [-h] [--level logging_level] [--debug] [--default-plugins]
+                [--host HOST] [--port PORT] [--plugins-folder PLUGINS_FOLDER]
+                [--only-install] [--only-list] [--data-folder DATA_FOLDER]
+                [--threaded] [--version]
 
     Run a Senpy server
 
@@ -20,25 +16,20 @@ The senpy server is launched via the `senpy` command:
       -h, --help            show this help message and exit
       --level logging_level, -l logging_level
                             Logging level
-      --log-format log_format
-                            Logging format
       --debug, -d           Run the application in debug mode
-      --no-default-plugins  Do not load the default plugins
+      --default-plugins     Load the default plugins
       --host HOST           Use 0.0.0.0 to accept requests from any host.
       --port PORT, -p PORT  Port to listen on.
       --plugins-folder PLUGINS_FOLDER, -f PLUGINS_FOLDER
                             Where to look for plugins.
       --only-install, -i    Do not run a server, only install plugin dependencies
-      --only-test           Do not run a server, just test all plugins
-      --test, -t            Test all plugins before launching the server
       --only-list, --list   Do not run a server, only list plugins found
       --data-folder DATA_FOLDER, --data DATA_FOLDER
                             Where to look for data. It be set with the SENPY_DATA
                             environment variable as well.
-      --no-threaded         Run the server without threading
-      --no-deps, -n         Skip installing dependencies
+      --threaded            Run a threaded server
       --version, -v         Output the senpy version and exit
-      --allow-fail, --fail  Do not exit if some plugins fail to activate
+
 
 
 When launched, the server will recursively look for plugins in the specified plugins folder (the current working directory by default).
@@ -49,9 +40,9 @@ Let's run senpy with the default plugins:
 
 .. code:: bash
 
-    senpy -f .
+    senpy -f . --default-plugins
 
-Now open your browser and go to `http://localhost:5000 <http://localhost:5000>`_, where you should be greeted by the senpy playground:
+Now go to `http://localhost:5000 <http://localhost:5000>`_, you should be greeted by the senpy playground:
 
 .. image:: senpy-playground.png
    :width: 100%
@@ -60,9 +51,9 @@ Now open your browser and go to `http://localhost:5000 <http://localhost:5000>`_
 The playground is a user-friendly way to test your plugins, but you can always use the service directly:  `http://localhost:5000/api?input=hello <http://localhost:5000/api?input=hello>`_.
 
 
-By default, senpy will listen only on `127.0.0.1`.
-That means you can only access the API from your PC (i.e. localhost).
-You can listen on a different address using the `--host` flag (e.g., 0.0.0.0, to allow any computer to access it).
+By default, senpy will listen only on the `127.0.0.1` address.
+That means you can only access the API from your (or localhost).
+You can listen on a different address using the `--host` flag (e.g., 0.0.0.0).
 The default port is 5000.
 You can change it with the `--port` flag. 
 
@@ -73,14 +64,3 @@ For instance, to accept connections on port 6000 on any interface:
     senpy --host 0.0.0.0 --port 6000
 
 For more options, see the `--help` page.
-
-Sentiment analysis in the command line
---------------------------------------
-
-Although the main use of senpy is to publish services, the tool can also be used locally to analyze text in the command line.
-This is a short video demonstration:
-
-.. image:: https://asciinema.org/a/9uwef1ghkjk062cw2t4mhzpyk.png
-   :width: 100%
-   :target: https://asciinema.org/a/9uwef1ghkjk062cw2t4mhzpyk
-   :alt: CLI demo

docs/usage.rst

@@ -0,0 +1,15 @@
+Usage
+-----
+
+First of all, you need to install the package.
+See :doc:`installation` for instructions.
+Once installed, the `senpy` command should be available. 
+
+.. toctree::
+   :maxdepth: 1
+
+   server
+   SenpyClientUse
+   commandline
+
+

example-plugins/README.md

@@ -1,6 +1,6 @@
 This is a collection of plugins that exemplify certain aspects of plugin development with senpy.
 
-The first series of plugins are the `basic` ones.
+The first series of plugins the `basic` ones.
 Their starting point is a classification function defined in `basic.py`.
 They all include testing and running them as a script will run all tests.
 In ascending order of customization, the plugins are:
@@ -19,5 +19,5 @@ In rest of the plugins show advanced topics:
 
 All of the plugins in this folder include a set of test cases and they are periodically tested with the latest version of senpy.
 
-Additioanlly, for an example of stand-alone plugin that can be tested and deployed with docker, take a look at: lab.gsi.upm.es/senpy/plugin-example
+Additioanlly, for an example of stand-alone plugin that can be tested and deployed with docker, take a look at: lab.cluster.gsi.dit.upm.es/senpy/plugin-example
  bbm

example-plugins/async_plugin.py

@@ -1,19 +1,3 @@
-#
-#    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

example-plugins/basic.py

@@ -1,21 +1,5 @@
 #!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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.
-#
-
+# coding: utf-8
 
 emoticons = {
     'pos': [':)', ':]', '=)', ':D'],
@@ -23,19 +7,17 @@ emoticons = {
 }
 
 emojis = {
-    'pos': [u'😁', u'😂', u'😃', u'😄', u'😆', u'😅', u'😄', u'😍'],
-    'neg': [u'😢', u'😡', u'😠', u'😞', u'😖', u'😔', u'😓', u'😒']
+    'pos': ['😁', '😂', '😃', '😄', '😆', '😅', '😄' '😍'],
+    'neg': ['😢', '😡', '😠', '😞', '😖', '😔', '😓', '😒']
 }
 
 
 def get_polarity(text, dictionaries=[emoticons, emojis]):
     polarity = 'marl:Neutral'
-    print('Input for get_polarity', text)
     for dictionary in dictionaries:
         for label, values in dictionary.items():
             for emoticon in values:
                 if emoticon and emoticon in text:
                     polarity = label
                     break
-    print('Polarity', polarity)
     return polarity

example-plugins/basic_analyse_entry_plugin.py

@@ -1,20 +1,5 @@
 #!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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.
-#
+# coding: utf-8
 
 from senpy import easy_test, models, plugins
 
@@ -33,13 +18,13 @@ class BasicAnalyseEntry(plugins.SentimentPlugin):
         'default': 'marl:Neutral'
     }
 
-    def analyse_entry(self, entry, activity):
+    def analyse_entry(self, entry, params):
         polarity = basic.get_polarity(entry.text)
 
         polarity = self.mappings.get(polarity, self.mappings['default'])
 
         s = models.Sentiment(marl__hasPolarity=polarity)
-        s.prov(activity)
+        s.prov(self)
         entry.sentiments.append(s)
         yield entry
 

example-plugins/basic_box_plugin.py

@@ -1,20 +1,5 @@
 #!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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.
-#
+# coding: utf-8
 
 from senpy import easy_test, SentimentBox
 
@@ -27,13 +12,15 @@ class BasicBox(SentimentBox):
     author = '@balkian'
     version = '0.1'
 
-    def predict_one(self, features, **kwargs):
-        output = basic.get_polarity(features[0])
-        if output == 'pos':
-            return [1, 0, 0]
-        if output == 'neg':
-            return [0, 0, 1]
-        return [0, 1, 0]
+    mappings = {
+        'pos': 'marl:Positive',
+        'neg': 'marl:Negative',
+        'default': 'marl:Neutral'
+    }
+
+    def predict_one(self, input):
+        output = basic.get_polarity(input)
+        return self.mappings.get(output, self.mappings['default'])
 
     test_cases = [{
         'input': 'Hello :)',

example-plugins/basic_plugin.py

@@ -1,52 +1,37 @@
 #!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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.
-#
+# coding: utf-8
 
-
-from senpy import easy_test, SentimentBox
+from senpy import easy_test, SentimentBox, MappingMixin
 
 import basic
 
 
-class Basic(SentimentBox):
+class Basic(MappingMixin, SentimentBox):
     '''Provides sentiment annotation using a lexicon'''
 
     author = '@balkian'
     version = '0.1'
 
-    def predict_one(self, features, **kwargs):
-        output = basic.get_polarity(features[0])
-        if output == 'pos':
-            return [1, 0, 0]
-        if output == 'neu':
-            return [0, 1, 0]
-        return [0, 0, 1]
+    mappings = {
+        'pos': 'marl:Positive',
+        'neg': 'marl:Negative',
+        'default': 'marl:Neutral'
+    }
+
+    def predict_one(self, input):
+        return basic.get_polarity(input)
 
     test_cases = [{
-        'input': u'Hello :)',
+        'input': 'Hello :)',
         'polarity': 'marl:Positive'
     }, {
-        'input': u'So sad :(',
+        'input': 'So sad :(',
         'polarity': 'marl:Negative'
     }, {
-        'input': u'Yay! Emojis  😁',
+        'input': 'Yay! Emojis  😁',
         'polarity': 'marl:Positive'
     }, {
-        'input': u'But no emoticons 😢',
+        'input': 'But no emoticons 😢',
         'polarity': 'marl:Negative'
     }]
 

example-plugins/configurable_plugin.py

@@ -1,21 +1,5 @@
 #!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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.
-#
-
+# coding: utf-8
 
 from senpy import easy_test, models, plugins
 
@@ -32,7 +16,7 @@ class Dictionary(plugins.SentimentPlugin):
 
     mappings = {'pos': 'marl:Positive', 'neg': 'marl:Negative'}
 
-    def analyse_entry(self, entry, *args, **kwargs):
+    def analyse_entry(self, entry, params):
         polarity = basic.get_polarity(entry.text, self.dictionaries)
         if polarity in self.mappings:
             polarity = self.mappings[polarity]

example-plugins/dummy_plugin.py

@@ -1,19 +1,3 @@
-#
-#    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, easy
 
 

example-plugins/dummy_required_plugin.py

@@ -1,19 +1,3 @@
-#
-#    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, easy
 
 

example-plugins/mynoop.py

@@ -1,19 +1,3 @@
-#
-#    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.
-#
-
 import noop
 from senpy.plugins import SentimentPlugin
 

example-plugins/parameterized_plugin.py

@@ -1,21 +1,5 @@
 #!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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.
-#
-
+# coding: utf-8
 
 from senpy import easy_test, models, plugins
 
@@ -41,8 +25,7 @@ class ParameterizedDictionary(plugins.SentimentPlugin):
         }
     }
 
-    def analyse_entry(self, entry, activity):
-        params = activity.params
+    def analyse_entry(self, entry, params):
         positive_words = params['positive-words'].split(',')
         negative_words = params['negative-words'].split(',')
         dictionary = {
@@ -52,7 +35,7 @@ class ParameterizedDictionary(plugins.SentimentPlugin):
         polarity = basic.get_polarity(entry.text, [dictionary])
 
         s = models.Sentiment(marl__hasPolarity=polarity)
-        s.prov(activity)
+        s.prov(self)
         entry.sentiments.append(s)
         yield entry
 

example-plugins/sklearn/mydata.py

@@ -1,19 +1,3 @@
-#
-#    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.
-#
-
 '''
 Create a dummy dataset.
 Messages with a happy emoticon are labelled positive

example-plugins/sklearn/mypipeline.py

@@ -1,19 +1,3 @@
-#
-#    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 sklearn.pipeline import Pipeline
 from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.model_selection import train_test_split

example-plugins/sklearn/pipeline_plugin.py

@@ -1,36 +1,25 @@
-#
-#    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 SentimentBox, easy_test
+from senpy import SentimentBox, MappingMixin, easy_test
 
 from mypipeline import pipeline
 
 
-class PipelineSentiment(SentimentBox):
-    '''This is a pipeline plugin that wraps a classifier defined in another module
-(mypipeline).'''
+class PipelineSentiment(MappingMixin, SentimentBox):
+    '''
+    This is a pipeline plugin that wraps a classifier defined in another module
+    (mypipeline).
+    '''
     author = '@balkian'
     version = 0.1
     maxPolarityValue = 1
     minPolarityValue = -1
 
-    def predict_one(self, features, **kwargs):
-        if pipeline.predict(features) > 0:
-            return [1, 0, 0]
-        return [0, 0, 1]
+    mappings = {
+        1: 'marl:Positive',
+        -1: 'marl:Negative'
+    }
+
+    def predict_one(self, input):
+        return pipeline.predict([input, ])[0]
 
     test_cases = [
         {

example-plugins/sleep_plugin.py

@@ -1,19 +1,3 @@
-#
-#    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.plugins import AnalysisPlugin
 from time import sleep
 

extra-requirements.txt

@@ -1 +1 @@
-gsitk>0.1.9.1
+gsitk

k8s/senpy-deployment.yaml

@@ -15,6 +15,8 @@ spec:
       - name: senpy-latest
         image: $IMAGEWTAG
         imagePullPolicy: Always
+        args:
+          - "--default-plugins"
         resources:
           limits:
             memory: "512Mi"

k8s/senpy-ingress.yaml

@@ -12,10 +12,3 @@ spec:
         backend:
           serviceName: senpy-latest
           servicePort: 5000
-  - host: latest.senpy.gsi.upm.es
-    http:
-      paths:
-      - path: /
-        backend:
-          serviceName: senpy-latest
-          servicePort: 5000

requirements.txt

@@ -11,6 +11,5 @@ rdflib
 rdflib-jsonld
 numpy
 scipy
-scikit-learn>=0.20
+scikit-learn
 responses
-jmespath

senpy/__init__.py

@@ -1,7 +1,7 @@
 #!/usr/bin/python
 # -*- coding: utf-8 -*-
-#
-#    Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
+#    Copyright 2014 J. Fernando Sánchez Rada - Grupo de Sistemas Inteligentes
+#                                                       DIT, UPM
 #
 #    Licensed under the Apache License, Version 2.0 (the "License");
 #    you may not use this file except in compliance with the License.
@@ -14,7 +14,6 @@
 #    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.
-#
 """
 Sentiment analysis server in Python
 """

senpy/__main__.py

@@ -1,6 +1,7 @@
 #!/usr/bin/python
 # -*- coding: utf-8 -*-
-#    Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
+#    Copyright 2014 J. Fernando Sánchez Rada - Grupo de Sistemas Inteligentes
+#                                                       DIT, UPM
 #
 #    Licensed under the Apache License, Version 2.0 (the "License");
 #    you may not use this file except in compliance with the License.
@@ -39,14 +40,8 @@ def main():
         '-l',
         metavar='logging_level',
         type=str,
-        default="INFO",
+        default="WARN",
         help='Logging level')
-    parser.add_argument(
-        '--log-format',
-        metavar='log_format',
-        type=str,
-        default='%(asctime)s %(levelname)-10s %(name)-30s \t %(message)s',
-        help='Logging format')
     parser.add_argument(
         '--debug',
         '-d',
@@ -54,10 +49,10 @@ def main():
         default=False,
         help='Run the application in debug mode')
     parser.add_argument(
-        '--no-default-plugins',
+        '--default-plugins',
         action='store_true',
         default=False,
-        help='Do not load the default plugins')
+        help='Load the default plugins')
     parser.add_argument(
         '--host',
         type=str,
@@ -73,7 +68,7 @@ def main():
         '--plugins-folder',
         '-f',
         type=str,
-        action='append',
+        default='.',
         help='Where to look for plugins.')
     parser.add_argument(
         '--only-install',
@@ -105,10 +100,10 @@ def main():
         default=None,
         help='Where to look for data. It be set with the SENPY_DATA environment variable as well.')
     parser.add_argument(
-        '--no-threaded',
-        action='store_true',
-        default=False,
-        help='Run a single-threaded server')
+        '--threaded',
+        action='store_false',
+        default=True,
+        help='Run a threaded server')
     parser.add_argument(
         '--no-deps',
         '-n',
@@ -128,42 +123,30 @@ def main():
         default=False,
         help='Do not exit if some plugins fail to activate')
     args = parser.parse_args()
-    print('Senpy version {}'.format(senpy.__version__))
-    print(sys.version)
     if args.version:
+        print('Senpy version {}'.format(senpy.__version__))
+        print(sys.version)
         exit(1)
     rl = logging.getLogger()
     rl.setLevel(getattr(logging, args.level))
-    logger_handler = rl.handlers[0]
-
-    # First, generic formatter:
-    logger_handler.setFormatter(logging.Formatter(args.log_format))
-
     app = Flask(__name__)
     app.debug = args.debug
-    sp = Senpy(app,
-               plugin_folder=None,
-               default_plugins=not args.no_default_plugins,
+    sp = Senpy(app, args.plugins_folder,
+               default_plugins=args.default_plugins,
                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)
-    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)))
-    for plugin in plugins:
-        import inspect
-        fpath = inspect.getfile(plugin.__class__)
-        print('\t{: <{maxname}} @ {: <{maxversion}} -> {}'.format(plugin.name,
-                                                                  plugin.version,
-                                                                  fpath,
-                                                                  maxname=maxname,
-                                                                  maxversion=maxversion))
     if args.only_list:
+        plugins = sp.plugins()
+        maxname = max(len(x.name) for x in plugins)
+        maxversion = max(len(x.version) for x in plugins)
+        print('Found {} plugins:'.format(len(plugins)))
+        for plugin in plugins:
+            import inspect
+            fpath = inspect.getfile(plugin.__class__)
+            print('\t{: <{maxname}} @ {: <{maxversion}} -> {}'.format(plugin.name,
+                                                                      plugin.version,
+                                                                      fpath,
+                                                                      maxname=maxname,
+                                                                      maxversion=maxversion))
         return
     if not args.no_deps:
         sp.install_deps()
@@ -177,13 +160,10 @@ def main():
     print('Senpy version {}'.format(senpy.__version__))
     print('Server running on port %s:%d. Ctrl+C to quit' % (args.host,
                                                             args.port))
-    try:
-        app.run(args.host,
-                args.port,
-                threaded=not args.no_threaded,
-                debug=app.debug)
-    except KeyboardInterrupt:
-        print('Bye!')
+    app.run(args.host,
+            args.port,
+            threaded=args.threaded,
+            debug=app.debug)
     sp.deactivate_all()
 
 

senpy/api.py

@@ -1,51 +1,28 @@
-#
-#    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.utils import iteritems
-from .models import Error, Results, Entry, from_string
+from .models import Analysis, Error, Results, Entry, from_string
 import logging
 logger = logging.getLogger(__name__)
 
 boolean = [True, False]
 
-processors = {
-    'string_to_tuple': lambda p: p if isinstance(p, (tuple, list)) else tuple(p.split(','))
-}
-
 API_PARAMS = {
     "algorithm": {
         "aliases": ["algorithms", "a", "algo"],
         "required": True,
         "default": 'default',
-        "processor": 'string_to_tuple',
         "description": ("Algorithms that will be used to process the request."
                         "It may be a list of comma-separated names."),
     },
     "expanded-jsonld": {
         "@id": "expanded-jsonld",
-        "description": "use JSON-LD expansion to get full URIs",
-        "aliases": ["expanded", "expanded_jsonld"],
+        "aliases": ["expanded"],
         "options": boolean,
         "required": True,
         "default": False
     },
-    "with-parameters": {
+    "with_parameters": {
         "aliases": ['withparameters',
-                    'with_parameters'],
-        "description": "include initial parameters in the response",
+                    'with-parameters'],
         "options": boolean,
         "default": False,
         "required": True
@@ -54,67 +31,9 @@ API_PARAMS = {
         "@id": "outformat",
         "aliases": ["o"],
         "default": "json-ld",
-        "description": """The data can be semantically formatted (JSON-LD, turtle or n-triples),
-given as a list of comma-separated fields (see the fields option) or constructed from a Jinja2
-template (see the template option).""",
         "required": True,
         "options": ["json-ld", "turtle", "ntriples"],
     },
-    "template": {
-        "@id": "template",
-        "required": False,
-        "description": """Jinja2 template for the result. The input data for the template will
-be the results as a dictionary.
-For example:
-
-Consider the results before templating:
-
-```
-[{
-    "@type": "entry",
-    "onyx:hasEmotionSet": [],
-    "nif:isString": "testing the template",
-    "marl:hasOpinion": [
-        {
-            "@type": "sentiment",
-            "marl:hasPolarity": "marl:Positive"
-        }
-    ]
-}]
-```
-
-
-And the template:
-
-```
-{% for entry in entries %}
-{{ entry["nif:isString"] | upper }},{{entry.sentiments[0]["marl:hasPolarity"].split(":")[1]}}
-{% endfor %}
-```
-
-The final result would be:
-
-```
-TESTING THE TEMPLATE,Positive
-```
-"""
-
-    },
-    "fields": {
-        "@id": "fields",
-        "required": False,
-        "description": """A jmespath selector, that can be used to extract a new dictionary, array or value
-from the results.
-jmespath is a powerful query language for json and/or dictionaries.
-It allows you to change the structure (and data) of your objects through queries.
-
-e.g., the following expression gets a list of `[emotion label, intensity]` for each entry:
-`entries[]."onyx:hasEmotionSet"[]."onyx:hasEmotion"[]["onyx:hasEmotionCategory","onyx:hasEmotionIntensity"]`
-
-For more information, see: https://jmespath.org
-
-"""
-    },
     "help": {
         "@id": "help",
         "description": "Show additional help to know more about the possible parameters",
@@ -125,39 +44,20 @@ For more information, see: https://jmespath.org
     },
     "verbose": {
         "@id": "verbose",
-        "description": "Show all properties in the result",
+        "description": "Show all help, including the common API parameters, or only plugin-related info",
         "aliases": ["v"],
         "required": True,
         "options": boolean,
-        "default": False
+        "default": True
     },
-    "aliases": {
-        "@id": "aliases",
-        "description": "Replace JSON properties with their aliases",
-        "aliases": [],
-        "required": True,
-        "options": boolean,
-        "default": False
-    },
-    "emotion-model": {
+    "emotionModel": {
         "@id": "emotionModel",
-        "description": """Emotion model to use in the response.
-Senpy will try to convert the output to this model automatically.
-
-Examples: `wna:liking` and `emoml:big6`.
-        """,
-        "aliases": ["emoModel", "emotionModel"],
+        "aliases": ["emoModel"],
         "required": False
     },
     "conversion": {
         "@id": "conversion",
-        "description": """How to show the elements that have (not) been converted.
-
-* full: converted and original elements will appear side-by-side
-* filtered: only converted elements will be shown
-* nested: converted elements will be shown, and they will include a link to the original element
-(using `prov:wasGeneratedBy`).
-""",
+        "description": "How to show the elements that have (not) been converted",
         "required": True,
         "options": ["filtered", "nested", "full"],
         "default": "full"
@@ -167,10 +67,9 @@ Examples: `wna:liking` and `emoml:big6`.
 EVAL_PARAMS = {
     "algorithm": {
         "aliases": ["plug", "p", "plugins", "algorithms", 'algo', 'a', 'plugin'],
-        "description": "Plugins to evaluate",
+        "description": "Plugins to be evaluated",
         "required": True,
-        "help": "See activated plugins in /plugins",
-        "processor": API_PARAMS['algorithm']['processor']
+        "help": "See activated plugins in /plugins"
     },
     "dataset": {
         "aliases": ["datasets", "data", "d"],
@@ -181,19 +80,18 @@ EVAL_PARAMS = {
 }
 
 PLUGINS_PARAMS = {
-    "plugin-type": {
+    "plugin_type": {
         "@id": "pluginType",
         "description": 'What kind of plugins to list',
-        "aliases": ["pluginType", "plugin_type"],
+        "aliases": ["pluginType"],
         "required": True,
         "default": 'analysisPlugin'
     }
 }
 
 WEB_PARAMS = {
-    "in-headers": {
-        "aliases": ["headers", "inheaders", "inHeaders", "in-headers", "in_headers"],
-        "description": "Only include the JSON-LD context in the headers",
+    "inHeaders": {
+        "aliases": ["headers"],
         "required": True,
         "default": False,
         "options": boolean
@@ -201,8 +99,8 @@ WEB_PARAMS = {
 }
 
 CLI_PARAMS = {
-    "plugin-folder": {
-        "aliases": ["folder", "plugin_folder"],
+    "plugin_folder": {
+        "aliases": ["folder"],
         "required": True,
         "default": "."
     },
@@ -217,7 +115,6 @@ NIF_PARAMS = {
     },
     "intype": {
         "@id": "intype",
-        "description": "input type",
         "aliases": ["t"],
         "required": False,
         "default": "direct",
@@ -225,7 +122,6 @@ NIF_PARAMS = {
     },
     "informat": {
         "@id": "informat",
-        "description": "input format",
         "aliases": ["f"],
         "required": False,
         "default": "text",
@@ -233,20 +129,17 @@ NIF_PARAMS = {
     },
     "language": {
         "@id": "language",
-        "description": "language of the input",
         "aliases": ["l"],
         "required": False,
     },
     "prefix": {
         "@id": "prefix",
-        "description": "prefix to use for new entities",
         "aliases": ["p"],
         "required": True,
         "default": "",
     },
     "urischeme": {
         "@id": "urischeme",
-        "description": "scheme for NIF URIs",
         "aliases": ["u"],
         "required": False,
         "default": "RFC5147String",
@@ -277,19 +170,16 @@ def parse_params(indict, *specs):
                 if alias in indict and alias != param:
                     outdict[param] = indict[alias]
                     del outdict[alias]
-                    break
+                    continue
             if param not in outdict:
                 if "default" in options:
                     # We assume the default is correct
                     outdict[param] = options["default"]
                 elif options.get("required", False):
                     wrong_params[param] = spec[param]
-                continue
-            if 'processor' in options:
-                outdict[param] = processors[options['processor']](outdict[param])
-            if "options" in options:
+            elif "options" in options:
                 if options["options"] == boolean:
-                    outdict[param] = str(outdict[param]).lower() in ['true', '1', '']
+                    outdict[param] = str(outdict[param]).lower() in ['true', '1']
                 elif outdict[param] not in options["options"]:
                     wrong_params[param] = spec[param]
     if wrong_params:
@@ -362,7 +252,7 @@ def get_extra_params(plugins):
     return params
 
 
-def parse_analyses(params, plugins):
+def parse_analysis(params, plugins):
     '''
     Parse the given parameters individually for each plugin, and get a list of the parameters that
     belong to each of the plugins. Each item can then be used in the plugin.analyse_entries method.
@@ -414,7 +304,7 @@ 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(nif__isString=params['input'], id='#')  # Use @base
         results.entries.append(entry)
     elif params['informat'] == 'json-ld':
         results = from_string(params['input'], cls=Results)

senpy/blueprints.py

@@ -1,20 +1,19 @@
 #!/usr/bin/python
 # -*- coding: utf-8 -*-
+# Copyright 2014 J. Fernando Sánchez Rada - Grupo de Sistemas Inteligentes
+# DIT, UPM
 #
-#    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
 #
-#    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
 #
-#        http://www.apache.org/licenses/LICENSE-2.0
-#
-#    Unless required by applicable law or agreed to in writing, software
+# 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.
-#
 """
 Blueprints for Senpy
 """
@@ -25,8 +24,6 @@ from . import api
 from .version import __version__
 from functools import wraps
 
-from .gsitk_compat import GSITK_AVAILABLE, datasets
-
 import logging
 import json
 import base64
@@ -66,44 +63,44 @@ def get_params(req):
     return indict
 
 
-def encode_url(url=None):
+def encoded_url(url=None, base=None):
     code = ''
     if not url:
-        url = request.parameters.get('prefix', request.full_path[1:] + '#')
-    return code or base64.urlsafe_b64encode(url.encode()).decode()
+        if request.method == 'GET':
+            url = request.full_path[1:]  # Remove the first slash
+        else:
+            hash(frozenset(tuple(request.parameters.items())))
+            code = 'hash:{}'.format(hash)
 
+    code = code or base64.urlsafe_b64encode(url.encode()).decode()
 
-def url_for_code(code, base=None):
-    # if base:
-    #     return base + code
-    # return url_for('api.decode', code=code, _external=True)
-    # This was producing unique yet very long URIs, which wasn't ideal for visualization.
-    return 'http://senpy.invalid/'
+    if base:
+        return base + code
+    return url_for('api.decode', code=code, _external=True)
 
 
 def decoded_url(code, base=None):
-    path = base64.urlsafe_b64decode(code.encode()).decode()
-    if path[:4] == 'http':
-        return path
+    if code.startswith('hash:'):
+        raise Exception('Can not decode a URL for a POST request')
     base = base or request.url_root
+    path = base64.urlsafe_b64decode(code.encode()).decode()
     return base + path
 
 
 @demo_blueprint.route('/')
 def index():
-    # ev = str(get_params(request).get('evaluation', True))
-    # evaluation_enabled = ev.lower() not in ['false', 'no', 'none']
-    evaluation_enabled = GSITK_AVAILABLE
+    ev = str(get_params(request).get('evaluation', False))
+    evaluation_enabled = ev.lower() not in ['false', 'no', 'none']
 
     return render_template("index.html",
                            evaluation=evaluation_enabled,
                            version=__version__)
 
 
-@api_blueprint.route('/contexts/<code>')
-def context(code=''):
+@api_blueprint.route('/contexts/<entity>.jsonld')
+def context(entity="context"):
     context = Response._context
-    context['@base'] = url_for('api.decode', code=code, _external=True)
+    context['@vocab'] = url_for('ns.index', _external=True)
     context['endpoint'] = url_for('api.api_root', _external=True)
     return jsonify({"@context": context})
 
@@ -133,59 +130,26 @@ def schema(schema="definitions"):
 
 def basic_api(f):
     default_params = {
-        'in-headers': False,
+        'inHeaders': False,
         'expanded-jsonld': False,
         'outformat': None,
-        'with-parameters': True,
+        'with_parameters': True,
     }
 
     @wraps(f)
     def decorated_function(*args, **kwargs):
         raw_params = get_params(request)
-        # logger.info('Getting request: {}'.format(raw_params))
-        logger.debug('Getting request. Params: {}'.format(raw_params))
+        logger.info('Getting request: {}'.format(raw_params))
         headers = {'X-ORIGINAL-PARAMS': json.dumps(raw_params)}
         params = default_params
 
-        mime = request.accept_mimetypes\
-                      .best_match(MIMETYPES.keys(),
-                                  DEFAULT_MIMETYPE)
-
-        mimeformat = MIMETYPES.get(mime, DEFAULT_FORMAT)
-        outformat = mimeformat
-
         try:
             params = api.parse_params(raw_params, api.WEB_PARAMS, api.API_PARAMS)
-            outformat = params.get('outformat', mimeformat)
             if hasattr(request, 'parameters'):
                 request.parameters.update(params)
             else:
                 request.parameters = params
             response = f(*args, **kwargs)
-
-            if 'parameters' in response and not params['with-parameters']:
-                del response.parameters
-
-            logger.debug('Response: {}'.format(response))
-
-            prefix = params.get('prefix')
-            code = encode_url(prefix)
-
-            return response.flask(
-                in_headers=params['in-headers'],
-                headers=headers,
-                prefix=prefix or url_for_code(code),
-                base=prefix,
-                context_uri=url_for('api.context',
-                                    code=code,
-                                    _external=True),
-                outformat=outformat,
-                expanded=params['expanded-jsonld'],
-                template=params.get('template'),
-                verbose=params['verbose'],
-                aliases=params['aliases'],
-                fields=params.get('fields'))
-
         except (Exception) as ex:
             if current_app.debug or current_app.config['TESTING']:
                 raise
@@ -195,48 +159,57 @@ def basic_api(f):
             response = ex
             response.parameters = raw_params
             logger.exception(ex)
-            return response.flask(
-                outformat=outformat,
-                expanded=params['expanded-jsonld'],
-                verbose=params.get('verbose', True),
-            )
+
+        if 'parameters' in response and not params['with_parameters']:
+            del response.parameters
+
+        logger.info('Response: {}'.format(response))
+        mime = request.accept_mimetypes\
+                      .best_match(MIMETYPES.keys(),
+                                  DEFAULT_MIMETYPE)
+
+        mimeformat = MIMETYPES.get(mime, DEFAULT_FORMAT)
+        outformat = params['outformat'] or mimeformat
+
+        return response.flask(
+            in_headers=params['inHeaders'],
+            headers=headers,
+            prefix=params.get('prefix', encoded_url()),
+            context_uri=url_for('api.context',
+                                entity=type(response).__name__,
+                                _external=True),
+            outformat=outformat,
+            expanded=params['expanded-jsonld'])
 
     return decorated_function
 
 
-@api_blueprint.route('/', defaults={'plugins': None}, methods=['POST', 'GET'])
-@api_blueprint.route('/<path:plugins>', methods=['POST', 'GET'])
+@api_blueprint.route('/', defaults={'plugin': None}, methods=['POST', 'GET'])
+@api_blueprint.route('/<path:plugin>', methods=['POST', 'GET'])
 @basic_api
-def api_root(plugins):
-    if plugins:
+def api_root(plugin):
+    if plugin:
         if request.parameters['algorithm'] != api.API_PARAMS['algorithm']['default']:
             raise Error('You cannot specify the algorithm with a parameter and a URL variable.'
                         ' Please, remove one of them')
-        plugins = plugins.replace('+', ',').replace('/', ',')
-        plugins = api.processors['string_to_tuple'](plugins)
-    else:
-        plugins = request.parameters['algorithm']
+        request.parameters['algorithm'] =  tuple(plugin.replace('+', '/').split('/'))
 
-    print(plugins)
+    params = request.parameters
+    plugin = request.parameters['algorithm']
 
     sp = current_app.senpy
-    plugins = sp.get_plugins(plugins)
+    plugins = sp.get_plugins(plugin)
 
     if request.parameters['help']:
-        apis = [api.WEB_PARAMS, api.API_PARAMS, api.NIF_PARAMS]
-        # Verbose is set to False as default, but we want it to default to
-        # True for help. This checks the original value, to make sure it wasn't
-        # set by default.
-        if not request.parameters['verbose'] and get_params(request).get('verbose'):
-            apis = []
-        if request.parameters['algorithm'] == ['default', ]:
-            plugins = []
+        apis = []
+        if request.parameters['verbose']:
+            apis.append(api.BUILTIN_PARAMS)
         allparameters = api.get_all_params(plugins, *apis)
         response = Help(valid_parameters=allparameters)
         return response
     req = api.parse_call(request.parameters)
-    analyses = api.parse_analyses(req.parameters, plugins)
-    results = current_app.senpy.analyse(req, analyses)
+    analysis = api.parse_analysis(req.parameters, plugins)
+    results = current_app.senpy.analyse(req, analysis)
     return results
 
 
@@ -258,8 +231,8 @@ def evaluate():
 def plugins():
     sp = current_app.senpy
     params = api.parse_params(request.parameters, api.PLUGINS_PARAMS)
-    ptype = params.get('plugin-type')
-    plugins = list(sp.analysis_plugins(plugin_type=ptype))
+    ptype = params.get('plugin_type')
+    plugins = list(sp.plugins(plugin_type=ptype))
     dic = Plugins(plugins=plugins)
     return dic
 
@@ -273,6 +246,8 @@ def plugin(plugin):
 
 @api_blueprint.route('/datasets/', methods=['POST', 'GET'])
 @basic_api
-def get_datasets():
+def datasets():
+    sp = current_app.senpy
+    datasets = sp.datasets
     dic = Datasets(datasets=list(datasets.values()))
     return dic

senpy/cli.py

@@ -1,20 +1,3 @@
-#
-#    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 sys
 from .models import Error
 from .extensions import Senpy
@@ -44,8 +27,8 @@ def main_function(argv):
                               api.CLI_PARAMS,
                               api.API_PARAMS,
                               api.NIF_PARAMS)
-    plugin_folder = params['plugin-folder']
-    default_plugins = not params.get('no-default-plugins', False)
+    plugin_folder = params['plugin_folder']
+    default_plugins = params.get('default-plugins', False)
     sp = Senpy(default_plugins=default_plugins, plugin_folder=plugin_folder)
     request = api.parse_call(params)
     algos = sp.get_plugins(request.parameters.get('algorithm', None))
@@ -65,7 +48,7 @@ def main():
         res = main_function(sys.argv[1:])
         print(res.serialize())
     except Error as err:
-        print(err.serialize(), file=sys.stderr)
+        print(err.serialize())
         sys.exit(2)
 
 

senpy/client.py

@@ -1,19 +1,3 @@
-#
-#    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.
-#
-
 import requests
 import logging
 from . import models

senpy/extensions.py

@@ -1,18 +1,3 @@
-#
-#    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.
-#
 """
 Main class for Senpy.
 It orchestrates plugin (de)activation and analysis.
@@ -22,7 +7,6 @@ standard_library.install_aliases()
 
 from . import plugins, api
 from .models import Error, AggregatedEvaluation
-from .plugins import AnalysisPlugin
 from .blueprints import api_blueprint, demo_blueprint, ns_blueprint
 
 from threading import Thread
@@ -70,7 +54,6 @@ class Senpy(object):
         self.app = app
         if app is not None:
             self.init_app(app)
-        self._conversion_candidates = {}
 
     def init_app(self, app):
         """ Initialise a flask app to add plugins to its context """
@@ -91,18 +74,14 @@ class Senpy(object):
 
     def add_plugin(self, plugin):
         self._plugins[plugin.name.lower()] = 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):
         """ 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)
+        return list(plugins.pfilter(self._plugins, plugin_type=plugin_type,
+                                    is_activated=is_activated, **kwargs))
 
     def get_plugin(self, name, default=None):
         if name == 'default':
@@ -125,7 +104,7 @@ class Senpy(object):
 
         msg = ("Plugin not found: '{}'\n"
                "Make sure it is ACTIVATED\n"
-               "Valid algorithms: {}").format(name,
+                "Valid algorithms: {}").format(name,
                                               self._plugins.keys())
         raise Error(message=msg, status=404)
 
@@ -136,10 +115,10 @@ class Senpy(object):
             pass  # Assume it is a tuple or a list
         return tuple(self.get_plugin(n) for n in name)
 
-    def analysis_plugins(self, **kwargs):
+    @property
+    def analysis_plugins(self):
         """ Return only the analysis plugins that are active"""
-        candidates = self.plugins(**kwargs)
-        return list(plugins.pfilter(candidates, plugin_type=AnalysisPlugin))
+        return self.plugins(plugin_type='analysisPlugin', is_activated=True)
 
     def add_folder(self, folder, from_root=False):
         """ Find plugins in this folder and add them to this instance """
@@ -154,6 +133,23 @@ class Senpy(object):
         else:
             raise AttributeError("Not a folder or does not exist: %s", folder)
 
+    # def check_analysis_request(self, analysis):
+    #     '''Check if the analysis request can be fulfilled'''
+    #     if not self.plugins():
+    #         raise Error(
+    #             status=404,
+    #             message=("No plugins found."
+    #                      " Please install one."))
+    #     for a in analysis:
+    #         algo = a.algorithm
+    #         if algo == 'default' and not self.default_plugin:
+    #             raise Error(
+    #                 status=404,
+    #                 message="No default plugin found, and None provided")
+    #         else:
+    #             self.get_plugin(algo)
+
+
     def _process(self, req, pending, done=None):
         """
         Recursively process the entries with the first plugin in the list, and pass the results
@@ -165,17 +161,14 @@ class Senpy(object):
 
         analysis = pending[0]
         results = analysis.run(req)
-        results.activities.append(analysis)
+        results.analysis.append(analysis)
         done += analysis
         return self._process(results, pending[1:], done)
 
     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(is_activated=False))
+        plugins.install_deps(*self.plugins())
 
-    def analyse(self, request, analyses=None):
+    def analyse(self, request, analysis=None):
         """
         Main method that analyses a request, either from CLI or HTTP.
         It takes a processed request, provided by the user, as returned
@@ -186,17 +179,18 @@ class Senpy(object):
                 status=404,
                 message=("No plugins found."
                          " Please install one."))
-        if analyses is None:
+        if analysis is None:
+            params = str(request)
             plugins = self.get_plugins(request.parameters['algorithm'])
-            analyses = api.parse_analyses(request.parameters, plugins)
+            analysis = api.parse_analysis(request.parameters, plugins)
         logger.debug("analysing request: {}".format(request))
-        results = self._process(request, analyses)
+        results = self._process(request, analysis)
         logger.debug("Got analysis result: {}".format(results))
-        results = self.postprocess(results, analyses)
+        results = self.postprocess(results)
         logger.debug("Returning post-processed result: {}".format(results))
         return results
 
-    def convert_emotions(self, resp, analyses):
+    def convert_emotions(self, resp):
         """
         Conversion of all emotions in a response **in place**.
         In addition to converting from one model to another, it has
@@ -204,50 +198,45 @@ class Senpy(object):
         Needless to say, this is far from an elegant solution, but it works.
         @todo refactor and clean up
         """
+        plugins = resp.analysis
 
-        logger.debug("Converting emotions")
         if 'parameters' not in resp:
-            logger.debug("NO PARAMETERS")
             return resp
 
         params = resp['parameters']
-        toModel = params.get('emotion-model', None)
+        toModel = params.get('emotionModel', None)
         if not toModel:
-            logger.debug("NO tomodel PARAMETER")
             return resp
 
         logger.debug('Asked for model: {}'.format(toModel))
         output = params.get('conversion', None)
-
+        candidates = {}
+        for plugin in plugins:
+            try:
+                fromModel = plugin.get('onyx:usesEmotionModel', None)
+                candidates[plugin.id] = next(self._conversion_candidates(fromModel, toModel))
+                logger.debug('Analysis plugin {} uses model: {}'.format(
+                    plugin.id, fromModel))
+            except StopIteration:
+                e = Error(('No conversion plugin found for: '
+                           '{} -> {}'.format(fromModel, toModel)),
+                          status=404)
+                e.original_response = resp
+                e.parameters = params
+                raise e
         newentries = []
         done = []
         for i in resp.entries:
-
             if output == "full":
                 newemotions = copy.deepcopy(i.emotions)
             else:
                 newemotions = []
             for j in i.emotions:
-                activity = j['prov:wasGeneratedBy']
-                act = resp.activity(activity)
-                if not act:
-                    raise Error('Could not find the emotion model for {}'.format(activity))
-                fromModel = act.plugin['onyx:usesEmotionModel']
-                if toModel == fromModel:
-                    continue
-                candidate = self._conversion_candidate(fromModel, toModel)
-                if not candidate:
-                    e = Error(('No conversion plugin found for: '
-                              '{} -> {}'.format(fromModel, toModel)),
-                              status=404)
-                    e.original_response = resp
-                    e.parameters = params
-                    raise e
-
-                analysis = candidate.activity(params)
-                done.append(analysis)
+                plugname = j['prov:wasGeneratedBy']
+                candidate = candidates[plugname]
+                done.append({'plugin': candidate, 'parameters': params})
                 for k in candidate.convert(j, fromModel, toModel, params):
-                    k.prov__wasGeneratedBy = analysis.id
+                    k.prov__wasGeneratedBy = candidate.id
                     if output == 'nested':
                         k.prov__wasDerivedFrom = j
                     newemotions.append(k)
@@ -256,65 +245,72 @@ class Senpy(object):
         resp.entries = newentries
         return resp
 
-    def _conversion_candidate(self, fromModel, toModel):
-        if not self._conversion_candidates:
-            candidates = {}
-            for conv in self.plugins(plugin_type=plugins.EmotionConversion):
-                for pair in conv.onyx__doesConversion:
-                    logging.debug(pair)
-                    key = (pair['onyx:conversionFrom'], pair['onyx:conversionTo'])
-                    if key not in candidates:
-                        candidates[key] = []
-                    candidates[key].append(conv)
-            self._conversion_candidates = candidates
+    def _conversion_candidates(self, fromModel, toModel):
+        candidates = self.plugins(plugin_type=plugins.EmotionConversion)
+        for candidate in candidates:
+            for pair in candidate.onyx__doesConversion:
+                logging.debug(pair)
+                if candidate.can_convert(fromModel, toModel):
+                    yield candidate
 
-        key = (fromModel, toModel)
-        if key not in self._conversion_candidates:
-            return None
-        return self._conversion_candidates[key][0]
-
-    def postprocess(self, response, analyses):
+    def postprocess(self, response):
         '''
         Transform the results from the analysis plugins.
         It has some pre-defined post-processing like emotion conversion,
         and it also allows plugins to auto-select themselves.
         '''
 
-        response = self.convert_emotions(response, analyses)
+        response = self.convert_emotions(response)
 
         for plug in self.plugins(plugin_type=plugins.PostProcessing):
-            if plug.check(response, response.activities):
-                activity = plug.activity(response.parameters)
-                response = plug.process(response, activity)
+            if plug.check(response, response.analysis):
+                response = plug.process(response)
         return response
 
     def _get_datasets(self, request):
+        if not self.datasets:
+            raise Error(
+                status=404,
+                message=("No datasets found."
+                         " Please verify DatasetManager"))
         datasets_name = request.parameters.get('dataset', None).split(',')
         for dataset in datasets_name:
-            if dataset not in gsitk_compat.datasets:
+            if dataset not in self.datasets:
                 logger.debug(("The dataset '{}' is not valid\n"
                               "Valid datasets: {}").format(
-                                  dataset, gsitk_compat.datasets.keys()))
+                                  dataset, self.datasets.keys()))
                 raise Error(
                     status=404,
                     message="The dataset '{}' is not valid".format(dataset))
-        return datasets_name
+        dm = gsitk_compat.DatasetManager()
+        datasets = dm.prepare_datasets(datasets_name)
+        return datasets
+
+    @property
+    def datasets(self):
+        self._dataset_list = {}
+        dm = gsitk_compat.DatasetManager()
+        for item in dm.get_datasets():
+            for key in item:
+                if key in self._dataset_list:
+                    continue
+                properties = item[key]
+                properties['@id'] = key
+                self._dataset_list[key] = properties
+        return self._dataset_list
 
     def evaluate(self, params):
         logger.debug("evaluating request: {}".format(params))
         results = AggregatedEvaluation()
         results.parameters = params
         datasets = self._get_datasets(results)
-        plugs = []
-        for plugname in params['algorithm']:
-            plugs = self.get_plugins(plugname)
-        for plug in plugs:
-            if not isinstance(plug, plugins.Evaluable):
-                raise Exception('Plugin {} can not be evaluated', plug.id)
+        plugins = []
+        for plugname in params.algorithm:
+            plugins = self.get_plugin(plugname)
 
-        for eval in plugins.evaluate(plugs, datasets):
+        for eval in plugins.evaluate(plugins, datasets):
             results.evaluations.append(eval)
-        if 'with-parameters' not in results.parameters:
+        if 'with_parameters' not in results.parameters:
             del results.parameters
         logger.debug("Returning evaluation result: {}".format(results))
         return results
@@ -322,7 +318,8 @@ class Senpy(object):
     @property
     def default_plugin(self):
         if not self._default or not self._default.is_activated:
-            candidates = self.analysis_plugins()
+            candidates = self.plugins(
+                plugin_type='analysisPlugin', is_activated=True)
             if len(candidates) > 0:
                 self._default = candidates[0]
             else:
@@ -357,15 +354,22 @@ class Senpy(object):
             ps.append(self.deactivate_plugin(plug, sync=sync))
         return ps
 
+    def _set_active(self, plugin, active=True, *args, **kwargs):
+        ''' We're using a variable in the plugin itself to activate/deactivate plugins.\
+        Note that plugins may activate themselves by setting this variable.
+        '''
+        plugin.is_activated = active
+
     def _activate(self, plugin):
         success = False
         with plugin._lock:
             if plugin.is_activated:
                 return
-            plugin._activate()
+            plugin.activate()
             msg = "Plugin activated: {}".format(plugin.name)
             logger.info(msg)
-            success = plugin.is_activated
+            success = True
+            self._set_active(plugin, success)
         return success
 
     def activate_plugin(self, plugin_name, sync=True):
@@ -389,7 +393,7 @@ class Senpy(object):
         with plugin._lock:
             if not plugin.is_activated:
                 return
-            plugin._deactivate()
+            plugin.deactivate()
             logger.info("Plugin deactivated: {}".format(plugin.name))
 
     def deactivate_plugin(self, plugin_name, sync=True):
@@ -399,11 +403,13 @@ class Senpy(object):
                 message="Plugin not found: {}".format(plugin_name), status=404)
         plugin = self._plugins[plugin_name]
 
+        self._set_active(plugin, False)
+
         if sync or not getattr(plugin, 'async', True) or not getattr(
                 plugin, 'sync', False):
-            plugin._deactivate()
+            self._deactivate(plugin)
         else:
-            th = Thread(target=plugin.deactivate)
+            th = Thread(target=partial(self._deactivate, plugin))
             th.start()
             return th
 

senpy/gsitk_compat.py

@@ -1,21 +1,4 @@
-#
-#    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.
-#
-
 import logging
-import os
 
 from pkg_resources import parse_version, get_distribution, DistributionNotFound
 
@@ -33,35 +16,16 @@ def raise_exception(*args, **kwargs):
 try:
     gsitk_distro = get_distribution("gsitk")
     GSITK_VERSION = parse_version(gsitk_distro.version)
-
-    if not os.environ.get('DATA_PATH'):
-        os.environ['DATA_PATH'] = os.environ.get('SENPY_DATA', 'senpy_data')
-
-    from gsitk.datasets.datasets import DatasetManager
-    from gsitk.evaluation.evaluation import Evaluation as Eval  # noqa: F401
-    from gsitk.evaluation.evaluation import EvalPipeline  # noqa: F401
-    from sklearn.pipeline import Pipeline
-    modules = locals()
-    GSITK_AVAILABLE = True
-    datasets = {}
-    manager = DatasetManager()
-
-    for item in manager.get_datasets():
-        for key in item:
-            if key in datasets:
-                continue
-            properties = item[key]
-            properties['@id'] = key
-            datasets[key] = properties
-
-    def prepare(ds, *args, **kwargs):
-        return manager.prepare_datasets(ds, *args, **kwargs)
-
-
-except (DistributionNotFound, ImportError) as err:
-    logger.debug('Error importing GSITK: {}'.format(err))
-    logger.warning(IMPORTMSG)
+    GSITK_AVAILABLE = GSITK_VERSION > parse_version("0.1.9.1")  # Earlier versions have a bug
+except DistributionNotFound:
     GSITK_AVAILABLE = False
     GSITK_VERSION = ()
-    DatasetManager = Eval = Pipeline = prepare = raise_exception
-    datasets = {}
+
+if GSITK_AVAILABLE:
+    from gsitk.datasets.datasets import DatasetManager
+    from gsitk.evaluation.evaluation import Evaluation as Eval
+    from sklearn.pipeline import Pipeline
+    modules = locals()
+else:
+    logger.warning(IMPORTMSG)
+    DatasetManager = Eval = Pipeline = raise_exception

senpy/meta.py

@@ -1,18 +1,3 @@
-#
-#    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.
 '''
@@ -49,7 +34,6 @@ class BaseMeta(ABCMeta):
     def __new__(mcs, name, bases, attrs, **kwargs):
         register_afterwards = False
         defaults = {}
-        aliases = {}
 
         attrs = mcs.expand_with_schema(name, attrs)
         if 'schema' in attrs:
@@ -57,21 +41,17 @@ class BaseMeta(ABCMeta):
         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
+                fget, fset, fdel = make_property(info[i].indict)
+                rest[i] = property(fget=fget, fset=fset, fdel=fdel)
             else:
                 defaults[i] = info[i]
 
         rest['_defaults'] = defaults
-        rest['_aliases'] = aliases
 
         cls = super(BaseMeta, mcs).__new__(mcs, name, tuple(bases), rest)
 
@@ -106,7 +86,7 @@ class BaseMeta(ABCMeta):
 
         resolver = jsonschema.RefResolver(schema_path, schema)
         if '@type' not in attrs:
-            attrs['@type'] = name
+            attrs['@type'] = "".join((name[0].lower(), name[1:]))
         attrs['_schema_file'] = schema_file
         attrs['schema'] = schema
         attrs['_validator'] = jsonschema.Draft4Validator(schema, resolver=resolver)
@@ -160,11 +140,9 @@ class BaseMeta(ABCMeta):
         return temp
 
 
-def make_property(key, default=None):
+def make_property(key):
 
     def fget(self):
-        if default:
-            return self.get(key, copy.copy(default))
         return self[key]
 
     def fdel(self):
@@ -190,7 +168,7 @@ class CustomDict(MutableMapping, object):
     '''
 
     _defaults = {}
-    _aliases = {'id': '@id'}
+    _map_attr_key = {'id': '@id'}
 
     def __init__(self, *args, **kwargs):
         super(CustomDict, self).__init__()
@@ -199,13 +177,13 @@ class CustomDict(MutableMapping, object):
         for arg in args:
             self.update(arg)
         for k, v in kwargs.items():
-            self[k] = v
+            self[self._attr_to_key(k)] = v
         return self
 
-    def serializable(self, **kwargs):
+    def serializable(self):
         def ser_or_down(item):
             if hasattr(item, 'serializable'):
-                return item.serializable(**kwargs)
+                return item.serializable()
             elif isinstance(item, dict):
                 temp = dict()
                 for kp in item:
@@ -217,9 +195,10 @@ class CustomDict(MutableMapping, object):
             else:
                 return item
 
-        return ser_or_down(self.as_dict(**kwargs))
+        return ser_or_down(self.as_dict())
 
     def __getitem__(self, key):
+        key = self._key_to_attr(key)
         return self.__dict__[key]
 
     def __setitem__(self, key, value):
@@ -227,23 +206,9 @@ class CustomDict(MutableMapping, object):
         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 as_dict(self):
+        return {self._attr_to_key(k): v for k, v in self.__dict__.items()
+                if not self._internal_key(k)}
 
     def __iter__(self):
         return (k for k in self.__dict__ if not self._internal_key(k))
@@ -251,38 +216,29 @@ class CustomDict(MutableMapping, object):
     def __len__(self):
         return len(self.__dict__)
 
+    def __delitem__(self, key):
+        del self.__dict__[key]
+
     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)
+        key = self._map_attr_key.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)
+        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))
+        try:
+            return self.__dict__[self._attr_to_key(key)]
+        except KeyError:
+            raise AttributeError
 
     @staticmethod
     def _internal_key(key):
@@ -295,8 +251,8 @@ class CustomDict(MutableMapping, object):
         return json.dumps(self.serializable(), sort_keys=True, indent=4)
 
 
-_Alias = namedtuple('Alias', ['indict', 'default'])
+_Alias = namedtuple('Alias', 'indict')
 
 
-def alias(key, default=None):
-    return _Alias(key, default)
+def alias(key):
+    return _Alias(key)

senpy/models.py

@@ -1,18 +1,3 @@
-#
-#    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.
-#
 '''
 Senpy Models.
 
@@ -27,8 +12,6 @@ standard_library.install_aliases()
 from future.utils import with_metaclass
 from past.builtins import basestring
 
-from jinja2 import Environment, BaseLoader
-
 import time
 import copy
 import json
@@ -38,7 +21,6 @@ from flask import Response as FlaskResponse
 from pyld import jsonld
 
 import logging
-import jmespath
 
 logging.getLogger('rdflib').setLevel(logging.WARN)
 logger = logging.getLogger(__name__)
@@ -49,9 +31,8 @@ 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')
+CONTEXT_PATH = os.path.join(
+    os.path.dirname(os.path.realpath(__file__)), 'schemas', 'context.jsonld')
 
 
 def get_schema_path(schema_file, absolute=False):
@@ -151,10 +132,13 @@ class BaseModel(with_metaclass(BaseMeta, CustomDict)):
         if auto_id:
             self.id
 
+        if '@type' not in self:
+            logger.warning('Created an instance of an unknown model')
+
     @property
     def id(self):
         if '@id' not in self:
-            self['@id'] = 'prefix:{}_{}'.format(type(self).__name__, time.time())
+            self['@id'] = '_:{}_{}'.format(type(self).__name__, time.time())
         return self['@id']
 
     @id.setter
@@ -190,33 +174,24 @@ class BaseModel(with_metaclass(BaseMeta, CustomDict)):
             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)
-        if template is not None:
-            rtemplate = Environment(loader=BaseLoader).from_string(template)
-            content = rtemplate.render(**self)
-            mimetype = 'text'
-        elif fields is not None:
-            # Emulate field selection by constructing a template
-            content = json.dumps(jmespath.search(fields, js))
-            mimetype = 'text'
-        elif format == 'json-ld':
-            content = json.dumps(js, indent=2, sort_keys=True)
+    def serialize(self, format='json-ld', with_mime=False, **kwargs):
+        js = self.jsonld(**kwargs)
+        content = json.dumps(js, indent=2, sort_keys=True)
+        if format == 'json-ld':
             mimetype = "application/json"
         elif format in ['turtle', 'ntriples']:
-            content = json.dumps(js, indent=2, sort_keys=True)
             logger.debug(js)
-            context = [self._context, {'prefix': prefix, '@base': prefix}]
+            base = kwargs.get('prefix')
             g = Graph().parse(
                 data=content,
                 format='json-ld',
-                prefix=prefix,
-                context=context)
+                base=base,
+                context=[self._context,
+                         {'@base': base}])
             logger.debug(
                 'Parsing with prefix: {}'.format(kwargs.get('prefix')))
             content = g.serialize(format=format,
-                                  prefix=prefix).decode('utf-8')
+                                  base=base).decode('utf-8')
             mimetype = 'text/{}'.format(format)
         else:
             raise Error('Unknown outformat: {}'.format(format))
@@ -229,25 +204,14 @@ class BaseModel(with_metaclass(BaseMeta, CustomDict)):
                with_context=False,
                context_uri=None,
                prefix=None,
-               base=None,
-               expanded=False,
-               **kwargs):
+               expanded=False):
 
-        result = self.serializable(**kwargs)
+        result = self.serializable()
 
         if expanded:
             result = jsonld.expand(
-                result,
-                options={
-                    'expandContext': [
-                        self._context,
-                        {
-                            'prefix': prefix,
-                            'endpoint': prefix
-                        }
-                    ]
-                }
-            )[0]
+                result, options={'base': prefix,
+                                 'expandContext': self._context})[0]
         if not with_context:
             try:
                 del result['@context']
@@ -275,7 +239,7 @@ def subtypes():
     return BaseMeta._subtypes
 
 
-def from_dict(indict, cls=None, warn=True):
+def from_dict(indict, cls=None):
     if not cls:
         target = indict.get('@type', None)
         cls = BaseModel
@@ -283,10 +247,6 @@ def from_dict(indict, cls=None, warn=True):
             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':
@@ -306,24 +266,22 @@ def from_string(string, **kwargs):
     return from_dict(json.loads(string), **kwargs)
 
 
-def from_json(injson, **kwargs):
+def from_json(injson):
     indict = json.loads(injson)
-    return from_dict(indict, **kwargs)
+    return from_dict(indict)
 
 
 class Entry(BaseModel):
     schema = 'entry'
 
     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')
+    polarityValue = alias('marl:hasPolarityValue')
 
 
 class Error(BaseModel, Exception):
@@ -343,173 +301,7 @@ class Error(BaseModel, Exception):
         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 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'
-
-
-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
-
-    def run(self, request):
-        return self.plugin.process(request, self)
-
-
-class Plugin(BaseModel):
-    schema = 'plugin'
-    extra_params = {}
-
-    def activity(self, parameters=None):
-        '''Generate an Analysis (prov:Activity) from this plugin and the given parameters'''
-        a = Analysis()
-        a.plugin = self
-        if parameters:
-            a.params = parameters
-        return a
-
-
-# More classes could be added programmatically
+# Add the remaining schemas programmatically
 
 def _class_from_schema(name, schema=None, schema_file=None, base_classes=None):
     base_classes = base_classes or []
@@ -529,3 +321,82 @@ def _add_class_from_schema(*args, **kwargs):
     generatedClass = _class_from_schema(*args, **kwargs)
     globals()[generatedClass.__name__] = generatedClass
     del generatedClass
+
+
+for i in [
+        'aggregatedEvaluation',
+        'dataset',
+        'datasets',
+        'emotion',
+        'emotionConversion',
+        'emotionConversionPlugin',
+        'emotionAnalysis',
+        'emotionModel',
+        'emotionPlugin',
+        'emotionSet',
+        'evaluation',
+        'entity',
+        'help',
+        'metric',
+        'parameter',
+        'plugins',
+        'response',
+        'results',
+        'sentimentPlugin',
+        'suggestion',
+        'topic',
+
+]:
+    _add_class_from_schema(i)
+
+
+class Analysis(BaseModel):
+    schema = 'analysis'
+
+    parameters  = alias('prov:used')
+
+    @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))
+
+    @property
+    def algorithm(self):
+        return self['prov:wasAssociatedWith']
+
+    @property
+    def plugin(self):
+        return self._plugin
+
+    @plugin.setter
+    def plugin(self, value):
+        self._plugin = value
+        self['prov:wasAssociatedWith'] = value.id
+
+    def run(self, request):
+        return self.plugin.process(request, self.params)
+
+
+class Plugin(BaseModel):
+    schema = 'plugin'
+
+    def activity(self, parameters):
+        '''Generate a prov:Activity from this plugin and the '''
+        a = Analysis()
+        a.plugin = self
+        a.params = parameters
+        return a
+

senpy/plugins/__init__.py

@@ -1,21 +1,3 @@
-#!/usr/local/bin/python
-# -*- coding: utf-8 -*-
-#
-#    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 standard_library
 standard_library.install_aliases()
 
@@ -35,12 +17,7 @@ import subprocess
 import importlib
 import yaml
 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 .. import api
@@ -54,19 +31,17 @@ 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)
+        plugin_type = []
+        if hasattr(bases[0], 'plugin_type'):
+            plugin_type += bases[0].plugin_type
+        plugin_type.append(name)
+        alias = attrs.get('name', name)
+        attrs['plugin_type'] = plugin_type
         attrs['name'] = alias
         if 'description' not in attrs:
             doc = attrs.get('__doc__', None)
             if doc:
-                attrs['description'] = dedent(doc)
+                attrs['description'] = doc
             else:
                 logger.warning(
                     ('Plugin {} does not have a description. '
@@ -102,15 +77,12 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
 
     '''
 
-    _terse_keys = ['name', '@id', '@type', 'author', 'description',
-                   'extra_params', 'is_activated', 'url', 'version']
-
     def __init__(self, info=None, data_folder=None, **kwargs):
         """
         Provides a canonical name for plugins and serves as base for other
         kinds of plugins.
         """
-        logger.debug("Initialising %s", info)
+        logger.debug("Initialising {}".format(info))
         super(Plugin, self).__init__(**kwargs)
         if info:
             self.update(info)
@@ -154,41 +126,33 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
     def get_folder(self):
         return os.path.dirname(inspect.getfile(self.__class__))
 
-    def _activate(self):
-        self.activate()
-        self.is_activated = True
-
-    def _deactivate(self):
-        self.is_activated = False
-        self.deactivate()
-
     def activate(self):
         pass
 
     def deactivate(self):
         pass
 
-    def process(self, request, activity, **kwargs):
+    def process(self, request, parameters, **kwargs):
         """
         An implemented plugin should override this method.
-        Here, we assume that a process_entries method exists.
-        """
+        Here, we assume that a process_entries method exists."""
         newentries = list(
-            self.process_entries(request.entries, activity))
+            self.process_entries(request.entries, parameters))
         request.entries = newentries
         return request
 
-    def process_entries(self, entries, activity):
+    def process_entries(self, entries, parameters):
         for entry in entries:
-            self.log.debug('Processing entry with plugin %s: %s', self, entry)
-            results = self.process_entry(entry, activity)
+            self.log.debug('Processing entry with plugin {}: {}'.format(
+                self, entry))
+            results = self.process_entry(entry, parameters)
             if inspect.isgenerator(results):
                 for result in results:
                     yield result
             else:
                 yield results
 
-    def process_entry(self, entry, activity):
+    def process_entry(self, entry, parameters):
         """
         This base method is here to adapt plugins which only
         implement the *process* function.
@@ -209,12 +173,9 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
             test_cases = self.test_cases
         for case in test_cases:
             try:
-                fmt = 'case: {}'.format(case.get('name', case))
-                if 'name' in case:
-                    self.log.info('Test case: {}'.format(case['name']))
-                self.log.debug('Test case:\n\t{}'.format(
-                    pprint.pformat(fmt)))
                 self.test_case(case)
+                self.log.debug('Test case passed:\n{}'.format(
+                    pprint.pformat(case)))
             except Exception as ex:
                 self.log.warning('Test case failed:\n{}'.format(
                     pprint.pformat(case)))
@@ -239,9 +200,7 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
                 entry,
             ]
 
-            activity = self.activity(parameters)
-
-            method = partial(self.process, request, activity)
+            method = partial(self.process, request, parameters)
 
             if mock:
                 res = method()
@@ -266,15 +225,11 @@ 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
-            fpath = self.path(fpath)
+            if not os.path.isabs(fpath):
+                fpath = os.path.join(self.data_folder, fpath)
         else:
             fpath = self.find_file(fpath)
 
@@ -288,41 +243,34 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
 SenpyPlugin = Plugin
 
 
-class Analyser(Plugin):
+class Analysis(Plugin):
     '''
     A subclass of Plugin that analyses text and provides an annotation.
     '''
 
-    # Deprecated
-    def analyse(self, request, activity):
-        return super(Analyser, self).process(request, activity)
+    def analyse(self, request, parameters):
+        return super(Analysis, self).process(request, parameters)
 
-    # Deprecated
-    def analyse_entries(self, entries, activity):
-        for i in super(Analyser, self).process_entries(entries, activity):
+    def analyse_entries(self, entries, parameters):
+        for i in super(Analysis, self).process_entries(entries, parameters):
             yield i
 
-    def process(self, request, activity, **kwargs):
-        return self.analyse(request, activity)
+    def process(self, request, parameters, **kwargs):
+        return self.analyse(request, parameters)
 
-    def process_entries(self, entries, activity):
-        for i in self.analyse_entries(entries, activity):
+    def process_entries(self, entries, parameters):
+        for i in self.analyse_entries(entries, parameters):
             yield i
 
-    def process_entry(self, entry, activity, **kwargs):
+    def process_entry(self, entry, parameters, **kwargs):
         if hasattr(self, 'analyse_entry'):
-            for i in self.analyse_entry(entry, activity):
+            for i in self.analyse_entry(entry, parameters):
                 yield i
         else:
-            super(Analyser, self).process_entry(entry, activity, **kwargs)
+            super(Analysis, self).process_entry(entry, parameters, **kwargs)
 
 
-AnalysisPlugin = Analyser
-
-
-class Transformation(AnalysisPlugin):
-    '''Empty'''
-    pass
+AnalysisPlugin = Analysis
 
 
 class Conversion(Plugin):
@@ -349,84 +297,32 @@ class Conversion(Plugin):
 ConversionPlugin = Conversion
 
 
-class Evaluable(Plugin):
-    '''
-    Common class for plugins that can be evaluated with GSITK.
-
-    They should implement the methods below.
-    '''
-
-    def as_pipe(self):
-        raise Exception('Implement the as_pipe function')
-
-    def evaluate_func(self, X, activity=None):
-        raise Exception('Implement the evaluate_func function')
-
-    def evaluate(self, *args, **kwargs):
-        return evaluate([self], *args, **kwargs)
-
-
-class SentimentPlugin(Analyser, Evaluable, models.SentimentPlugin):
+class SentimentPlugin(Analysis, models.SentimentPlugin):
     '''
     Sentiment plugins provide sentiment annotation (using Marl)
     '''
     minPolarityValue = 0
     maxPolarityValue = 1
 
-    _terse_keys = Analyser._terse_keys + ['minPolarityValue', 'maxPolarityValue']
-
     def test_case(self, case):
         if 'polarity' in case:
             expected = case.get('expected', {})
             s = models.Sentiment(_auto_id=False)
             s.marl__hasPolarity = case['polarity']
-            if 'marl:hasOpinion' not in expected:
-                expected['marl:hasOpinion'] = []
-            expected['marl:hasOpinion'].append(s)
+            if 'sentiments' not in expected:
+                expected['sentiments'] = []
+            expected['sentiments'].append(s)
             case['expected'] = expected
         super(SentimentPlugin, self).test_case(case)
 
-    def normalize(self, value, minValue, maxValue):
-        nv = minValue + (value - self.minPolarityValue) * (
-            self.maxPolarityValue - self.minPolarityValue) / (maxValue - minValue)
-        return nv
 
-    def as_pipe(self):
-        pipe = gsitk_compat.Pipeline([('senpy-plugin', ScikitWrapper(self))])
-        pipe.name = self.id
-        return pipe
-
-    def evaluate_func(self, X, activity=None):
-        if activity is None:
-            parameters = api.parse_params({},
-                                          self.extra_params)
-            activity = self.activity(parameters)
-        entries = []
-        for feat in X:
-            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
-            label = -1
-            if sent == 'marl:Positive':
-                label = 1
-            elif sent == 'marl:Negative':
-                label = -1
-            labels.append(label)
-        return labels
-
-
-class EmotionPlugin(Analyser, models.EmotionPlugin):
+class EmotionPlugin(Analysis, models.EmotionPlugin):
     '''
     Emotion plugins provide emotion annotation (using Onyx)
     '''
     minEmotionValue = 0
     maxEmotionValue = 1
 
-    _terse_keys = Analyser._terse_keys + ['minEmotionValue', 'maxEmotionValue']
-
 
 class EmotionConversion(Conversion):
     '''
@@ -449,67 +345,69 @@ EmotionConversionPlugin = EmotionConversion
 
 
 class PostProcessing(Plugin):
-    '''
-    A plugin that converts the output of other plugins (post-processing).
-    '''
     def check(self, request, plugins):
         '''Should this plugin be run for this request?'''
         return False
 
 
-class Box(Analyser):
+class Box(AnalysisPlugin):
     '''
     Black box plugins delegate analysis to a function.
-    The flow is like this:
+    The flow is like so:
 
     .. code-block::
 
-                   entries --> to_features() --> predict_many() --> to_entry() --> entries'
+                   entry --> input() --> predict_one() --> output() --> entry'
 
 
-    In other words: their ``to_features`` method converts a query (entry and a set of parameters)
-    into the input to the `predict_one` method, which only uses an array of features.
-    The ``to_entry`` method converts the results given by the box into an entry that senpy can
-    handle.
+    In other words: their ``input`` method convers a query (entry and a set of parameters) into
+    the input to the box method. The ``output`` method convers the results given by the box into
+    an entry that senpy can handle.
     '''
 
-    def to_features(self, entry, activity=None):
+    def input(self, entry, params=None):
         '''Transforms a query (entry+param) into an input for the black box'''
         return entry
 
-    def to_entry(self, features, entry=None, activity=None):
+    def output(self, output, entry=None, params=None):
         '''Transforms the results of the black box into an entry'''
-        return entry
+        return output
 
-    def predict_one(self, features, activity=None):
+    def predict_one(self, input):
         raise NotImplementedError(
             'You should define the behavior of this plugin')
 
-    def predict_many(self, features, activity=None):
-        results = []
-        for feat in features:
-            results.append(self.predict_one(features=feat, activity=activity))
-        return results
-
-    def process_entry(self, entry, activity):
-        for i in self.process_entries([entry], activity):
-            yield i
-
-    def process_entries(self, entries, activity):
-        features = []
+    def process_entries(self, entries, params):
         for entry in entries:
-            features.append(self.to_features(entry=entry, activity=activity))
-        results = self.predict_many(features=features, activity=activity)
+            input = self.input(entry=entry, params=params)
+            results = self.predict_one(input=input)
+            yield self.output(output=results, entry=entry, params=params)
 
-        for (result, entry) in zip(results, entries):
-            yield self.to_entry(features=result, entry=entry, activity=activity)
+    def fit(self, X=None, y=None):
+        return self
+
+    def transform(self, X):
+        return [self.predict_one(x) for x in X]
+
+    def predict(self, X):
+        return self.transform(X)
+
+    def fit_transform(self, X, y):
+        self.fit(X, y)
+        return self.transform(X)
+
+    def as_pipe(self):
+        pipe = gsitk_compat.Pipeline([('plugin', self)])
+        pipe.name = self.name
+        return pipe
 
 
 class TextBox(Box):
     '''A black box plugin that takes only text as input'''
 
-    def to_features(self, entry, activity):
-        return [entry['nif:isString']]
+    def input(self, entry, params):
+        entry = super(TextBox, self).input(entry, params)
+        return entry['nif:isString']
 
 
 class SentimentBox(TextBox, SentimentPlugin):
@@ -517,35 +415,17 @@ 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
-
-    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 '
-                               '(plugin.classes ({})'.format(len(features), len(self.classes)))
-
-        minValue = activity.param('marl:minPolarityValue', 0)
-        maxValue = activity.param('marl:minPolarityValue', 1)
-        activity['marl:minPolarityValue'] = minValue
-        activity['marl:maxPolarityValue'] = maxValue
-
-        for k, v in zip(self.classes, features):
-            s = models.Sentiment()
-            if self.binary:
-                if not v:  # Carry on if the value is 0
-                    continue
-                s['marl:hasPolarity'] = k
-            else:
-                if v is not None:
-                    s['marl:hasPolarity'] = k
-                    nv = self.normalize(v, minValue, maxValue)
-                    s['marl:polarityValue'] = nv
-            s.prov(activity)
-
-            entry.sentiments.append(s)
-
+    def output(self, output, entry, **kwargs):
+        s = models.Sentiment()
+        try:
+            label, value = output
+        except ValueError:
+            label, value = output, None
+        s.prov(self)
+        s.polarity = label
+        if value is not None:
+            s.polarityValue = value
+        entry.sentiments.append(s)
         return entry
 
 
@@ -554,23 +434,14 @@ class EmotionBox(TextBox, EmotionPlugin):
     A box plugin where the output is only an a tuple of emotion labels
     '''
 
-    EMOTIONS = []
-    with_intensity = True
-
-    def to_entry(self, features, entry, activity, **kwargs):
+    def output(self, output, entry, **kwargs):
+        if not isinstance(output, list):
+            output = [output]
         s = models.EmotionSet()
-
-        if len(features) != len(self.EMOTIONS):
-            raise Exception(('The number of classes in the plugin and the number of features '
-                             'do not match'))
-
-        for label, intensity in zip(self.EMOTIONS, features):
-            e = models.Emotion(onyx__hasEmotionCategory=label)
-            if self.with_intensity:
-                e.onyx__hasEmotionIntensity = intensity
-            s.onyx__hasEmotion.append(e)
-        s.prov(activity)
         entry.emotions.append(s)
+        for label in output:
+            e = models.Emotion(onyx__hasEmotionCategory=label)
+            s.append(e)
         return entry
 
 
@@ -583,15 +454,11 @@ class MappingMixin(object):
     def mappings(self, value):
         self._mappings = value
 
-    def to_entry(self, features, entry, activity):
-        features = list(features)
-        for i, feat in enumerate(features):
-            features[i] = self.mappings.get(feat,
-                                            self.mappings.get('default',
-                                                              feat))
-        return super(MappingMixin, self).to_entry(features=features,
-                                                  entry=entry,
-                                                  activity=activity)
+    def output(self, output, entry, params):
+        output = self.mappings.get(output, self.mappings.get(
+            'default', output))
+        return super(MappingMixin, self).output(
+            output=output, entry=entry, params=params)
 
 
 class ShelfMixin(object):
@@ -638,7 +505,7 @@ class ShelfMixin(object):
                 pickle.dump(self._sh, f)
 
 
-def pfilter(plugins, plugin_type=Analyser, **kwargs):
+def pfilter(plugins, plugin_type=Analysis, **kwargs):
     """ Filter plugins by different criteria """
     if isinstance(plugins, models.Plugins):
         plugins = plugins.plugins
@@ -659,9 +526,6 @@ def pfilter(plugins, plugin_type=Analyser, **kwargs):
     else:
         candidates = plugins
 
-    if 'name' in kwargs:
-        kwargs['name'] = kwargs['name'].lower()
-
     logger.debug(candidates)
 
     def matches(plug):
@@ -685,48 +549,31 @@ def load_module(name, root=None):
 
 def _log_subprocess_output(process):
     for line in iter(process.stdout.readline, b''):
-        logger.info('%s', line.decode())
+        logger.info('%r', line)
     for line in iter(process.stderr.readline, b''):
-        logger.error('%s', line.decode())
-
-
-def missing_requirements(reqs):
-    queue = []
-    pool = multiprocessing.Pool(4)
-    for req in reqs:
-        res = pool.apply_async(pkg_resources.get_distribution, (req,))
-        queue.append((req, res))
-    missing = []
-    for req, job in queue:
-        try:
-            job.get(1)
-        except Exception:
-            missing.append(req)
-    return missing
+        logger.error('%r', line)
 
 
 def install_deps(*plugins):
     installed = False
     nltk_resources = set()
-    requirements = []
     for info in plugins:
         requirements = info.get('requirements', [])
         if requirements:
-            requirements += missing_requirements(requirements)
+            pip_args = [sys.executable, '-m', 'pip', 'install']
+            for req in requirements:
+                pip_args.append(req)
+            logger.info('Installing requirements: ' + str(requirements))
+            process = subprocess.Popen(
+                pip_args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+            _log_subprocess_output(process)
+            exitcode = process.wait()
+            installed = True
+            if exitcode != 0:
+                raise models.Error(
+                    "Dependencies not properly installed: {}".format(pip_args))
         nltk_resources |= set(info.get('nltk_resources', []))
-    if requirements:
-        logger.info('Installing requirements: ' + str(requirements))
-        pip_args = [sys.executable, '-m', 'pip', 'install']
-        for req in requirements:
-            pip_args.append(req)
-        process = subprocess.Popen(
-            pip_args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-        _log_subprocess_output(process)
-        exitcode = process.wait()
-        installed = True
-        if exitcode != 0:
-            raise models.Error(
-                "Dependencies not properly installed: {}".format(pip_args))
+
     installed |= download(list(nltk_resources))
     return installed
 
@@ -785,7 +632,7 @@ def from_info(info, root=None, install_on_fail=True, **kwargs):
 def parse_plugin_info(fpath):
     logger.debug("Parsing plugin info: {}".format(fpath))
     with open(fpath, 'r') as f:
-        info = yaml.load(f, Loader=yaml.FullLoader)
+        info = yaml.load(f)
     info['_path'] = fpath
     return info
 
@@ -841,37 +688,14 @@ def _from_loaded_module(module, info=None, **kwargs):
         yield instance
 
 
-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))
-
-    if not isinstance(datasets, dict):
-        datasets = gsitk_compat.prepare(datasets, download=True)
-
-    tuples = list(product(plugins, datasets))
-    missing = []
-    for (p, d) in tuples:
-        if (p.id, d) not in cached_evs:
-            pipe = p.as_pipe()
-            missing.append(gsitk_compat.EvalPipeline(pipe, d))
-    if missing:
-        ev = gsitk_compat.Eval(tuples=missing, datasets=datasets)
-        ev.evaluate()
-        results = ev.results
-        new_ev = evaluations_to_JSONLD(results, **kwargs)
-        for ev in new_ev:
-            dataset = ev.evaluatesOn
-            model = ev.evaluates
-            cached_evs[(model, dataset)] = ev
-    evaluations = []
-    logger.debug('%s. Cached evs: %s', tuples, cached_evs)
-    for (p, d) in tuples:
-        logger.debug('Adding %s, %s', d, p)
-        evaluations.append(cached_evs[(p.id, d)])
+    ev = gsitk_compat.Eval(
+        tuples=None,
+        datasets=datasets,
+        pipelines=[plugin.as_pipe() for plugin in plugins])
+    ev.evaluate()
+    results = ev.results
+    evaluations = evaluations_to_JSONLD(results, **kwargs)
     return evaluations
 
 
@@ -884,12 +708,12 @@ def evaluations_to_JSONLD(results, flatten=False):
     metric_names = ['accuracy', 'precision_macro', 'recall_macro',
                     'f1_macro', 'f1_weighted', 'f1_micro', 'f1_macro']
 
-    for index, row in results.fillna('Not Available').iterrows():
+    for index, row in results.iterrows():
         evaluation = models.Evaluation()
         if row.get('CV', True):
             evaluation['@type'] = ['StaticCV', 'Evaluation']
         evaluation.evaluatesOn = row['Dataset']
-        evaluation.evaluates = row['Model'].rstrip('__' + row['Dataset'])
+        evaluation.evaluates = row['Model']
         i = 0
         if flatten:
             metric = models.Metric()
@@ -900,29 +724,10 @@ def evaluations_to_JSONLD(results, flatten=False):
             # We should probably discontinue this representation
             for name in metric_names:
                 metric = models.Metric()
+                metric['@id'] = 'Metric' + str(i)
                 metric['@type'] = name.capitalize()
                 metric.value = row[name]
                 evaluation.metrics.append(metric)
                 i += 1
         evaluations.append(evaluation)
     return evaluations
-
-
-class ScikitWrapper(BaseEstimator, TransformerMixin):
-    def __init__(self, plugin=None):
-        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):
-        return self.plugin.evaluate_func(X, None)
-
-    def predict(self, X):
-        return self.transform(X)
-
-    def fit_transform(self, X, y):
-        self.fit(X, y)
-        return self.transform(X)

senpy/plugins/example/emoRand/emoRand.py

@@ -0,0 +1,34 @@
+import random
+
+from senpy.plugins import EmotionPlugin
+from senpy.models import EmotionSet, Emotion, Entry
+
+
+class EmoRand(EmotionPlugin):
+    name = "emoRand"
+    description = 'A sample plugin that returns a random emotion annotation'
+    author = '@balkian'
+    version = '0.1'
+    url = "https://github.com/gsi-upm/senpy-plugins-community"
+    requirements = {}
+    onyx__usesEmotionModel = "emoml:big6"
+
+    def analyse_entry(self, entry, params):
+        category = "emoml:big6happiness"
+        number = max(-1, min(1, random.gauss(0, 0.5)))
+        if number > 0:
+            category = "emoml:big6anger"
+        emotionSet = EmotionSet()
+        emotion = Emotion({"onyx:hasEmotionCategory": category})
+        emotionSet.onyx__hasEmotion.append(emotion)
+        emotionSet.prov__wasGeneratedBy = self.id
+        entry.emotions.append(emotionSet)
+        yield entry
+
+    def test(self):
+        params = dict()
+        results = list()
+        for i in range(100):
+            res = next(self.analyse_entry(Entry(nif__isString="Hello"), params))
+            res.validate()
+            results.append(res.emotions[0]['onyx:hasEmotion'][0]['onyx:hasEmotionCategory'])

senpy/plugins/example/emorand_plugin.py

@@ -1,19 +1,3 @@
-#
-#    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.
-#
-
 import random
 
 from senpy.plugins import EmotionPlugin
@@ -22,13 +6,12 @@ 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"
 
-    def analyse_entry(self, entry, activity):
+    def analyse_entry(self, entry, params):
         category = "emoml:big6happiness"
         number = max(-1, min(1, random.gauss(0, 0.5)))
         if number > 0:
@@ -36,7 +19,7 @@ class EmoRand(EmotionPlugin):
         emotionSet = EmotionSet()
         emotion = Emotion({"onyx:hasEmotionCategory": category})
         emotionSet.onyx__hasEmotion.append(emotion)
-        emotionSet.prov(activity)
+        emotionSet.prov__wasGeneratedBy = self.id
         entry.emotions.append(emotionSet)
         yield entry
 
@@ -44,6 +27,6 @@ class EmoRand(EmotionPlugin):
         params = dict()
         results = list()
         for i in range(100):
-            res = next(self.analyse_entry(Entry(nif__isString="Hello"), self.activity(params)))
+            res = next(self.analyse_entry(Entry(nif__isString="Hello"), params))
             res.validate()
             results.append(res.emotions[0]['onyx:hasEmotion'][0]['onyx:hasEmotionCategory'])

senpy/plugins/example/rand_plugin.py

@@ -1,33 +1,16 @@
-#
-#    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.
-#
-
 import random
 from senpy import SentimentPlugin, Sentiment, Entry
 
 
-class RandSent(SentimentPlugin):
+class Rand(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"
 
-    def analyse_entry(self, entry, activity):
+    def analyse_entry(self, entry, params):
         polarity_value = max(-1, min(1, random.gauss(0.2, 0.2)))
         polarity = "marl:Neutral"
         if polarity_value > 0:
@@ -36,7 +19,7 @@ class RandSent(SentimentPlugin):
             polarity = "marl:Negative"
         sentiment = Sentiment(marl__hasPolarity=polarity,
                               marl__polarityValue=polarity_value)
-        sentiment.prov(activity)
+        sentiment.prov(self)
         entry.sentiments.append(sentiment)
         yield entry
 
@@ -45,9 +28,8 @@ class RandSent(SentimentPlugin):
         params = dict()
         results = list()
         for i in range(50):
-            activity = self.activity(params)
             res = next(self.analyse_entry(Entry(nif__isString="Hello"),
-                                          activity))
+                                          params))
             res.validate()
             results.append(res.sentiments[0]['marl:hasPolarity'])
         assert 'marl:Positive' in results

senpy/plugins/misc/split_plugin.py

@@ -1,42 +1,19 @@
-#
-#    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.plugins import Transformation
+from senpy.plugins import AnalysisPlugin
 from senpy.models import Entry
 from nltk.tokenize.punkt import PunktSentenceTokenizer
 from nltk.tokenize.simple import LineTokenizer
+import nltk
 
 
-class Split(Transformation):
-    '''
-    A plugin that chunks input text, into paragraphs or sentences.
-
-    It does not provide any sort of annotation, and it is meant to precede
-    other annotation plugins, when the annotation of individual sentences
-    (or paragraphs) is required.
-    '''
+class Split(AnalysisPlugin):
+    '''description: A sample plugin that chunks input text'''
 
     author = ["@militarpancho", '@balkian']
     version = '0.3'
     url = "https://github.com/gsi-upm/senpy"
-    nltk_resources = ['punkt']
 
     extra_params = {
         'delimiter': {
-            'description': 'Split text into paragraphs or sentences.',
             'aliases': ['type', 't'],
             'required': False,
             'default': 'sentence',
@@ -44,9 +21,12 @@ class Split(Transformation):
         },
     }
 
-    def analyse_entry(self, entry, activity):
+    def activate(self):
+        nltk.download('punkt')
+
+    def analyse_entry(self, entry, params):
         yield entry
-        chunker_type = activity.params["delimiter"]
+        chunker_type = params["delimiter"]
         original_text = entry['nif:isString']
         if chunker_type == "sentence":
             tokenizer = PunktSentenceTokenizer()

senpy/plugins/postprocessing/emotion/centroids.py

@@ -1,19 +1,3 @@
-#
-#    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.plugins import EmotionConversionPlugin
 from senpy.models import EmotionSet, Emotion, Error
 
@@ -101,13 +85,7 @@ class CentroidConversion(EmotionConversionPlugin):
         def distance(centroid):
             return sum(distance_k(centroid, original, k) for k in dimensions)
 
-        distances = {k: distance(centroids[k]) for k in centroids}
-
-        logger.debug('Converting %s', original)
-        logger.debug('Centroids: %s', centroids)
-        logger.debug('Distances: %s', distances)
-
-        emotion = min(distances, key=lambda x: distances[x])
+        emotion = min(centroids, key=lambda x: distance(centroids[x]))
 
         result = Emotion(onyx__hasEmotionCategory=emotion)
         result.onyx__algorithmConfidence = distance(centroids[emotion])
@@ -125,9 +103,7 @@ class CentroidConversion(EmotionConversionPlugin):
             for i in emotionSet.onyx__hasEmotion:
                 e.onyx__hasEmotion.append(self._backwards_conversion(i))
         else:
-            raise Error('EMOTION MODEL NOT KNOWN. '
-                        'Cannot convert from {} to {}'.format(fromModel,
-                                                              toModel))
+            raise Error('EMOTION MODEL NOT KNOWN')
         yield e
 
     def test(self, info=None):

senpy/plugins/postprocessing/emotion/ekman2vad.senpy

@@ -9,30 +9,30 @@ centroids:
   anger:
     A: 6.95
     D: 5.1
-    P: 2.7
+    V: 2.7
   disgust:
     A: 5.3
     D: 8.05
-    P: 2.7
+    V: 2.7
   fear:
     A: 6.5
     D: 3.6
-    P: 3.2
+    V: 3.2
   happiness:
     A: 7.22
     D: 6.28
-    P: 8.6
+    V: 8.6
   sadness:
     A: 5.21
     D: 2.82
-    P: 2.21
+    V: 2.21
 centroids_direction:
   - emoml:big6
-  - emoml:pad-dimensions
+  - emoml:pad
 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
+  A: emoml:pad-dimensions:arousal
+  V: emoml:pad-dimensions:pleasure
+  D: emoml:pad-dimensions:dominance
   anger: emoml:big6anger
   disgust: emoml:big6disgust
   fear: emoml:big6fear

senpy/plugins/postprocessing/emotion/maxEmotion_plugin.py

@@ -1,19 +1,3 @@
-#
-#    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 PostProcessing, easy_test
 
 
@@ -22,7 +6,7 @@ class MaxEmotion(PostProcessing):
     author = '@dsuarezsouto'
     version = '0.1'
 
-    def process_entry(self, entry, activity):
+    def process_entry(self, entry, params):
         if len(entry.emotions) < 1:
             yield entry
             return
@@ -48,7 +32,7 @@ class MaxEmotion(PostProcessing):
 
         entry.emotions[0]['onyx:hasEmotion'] = [max_emotion]
 
-        entry.emotions[0]['prov:wasGeneratedBy'] = activity.id
+        entry.emotions[0]['prov:wasGeneratedBy'] = "maxSentiment"
         yield entry
 
     def check(self, request, plugins):
@@ -59,11 +43,12 @@ class MaxEmotion(PostProcessing):
     #   2 Case to return a Neutral Emotion.
     test_cases = [
         {
-            "name": "If there are several emotions within an emotion set, reduce it to one.",
+            "name":
+            "If there are several emotions within an emotion set, reduce it to one.",
             "entry": {
                 "@type":
                 "entry",
-                "onyx:hasEmotionSet": [
+                "emotions": [
                     {
                         "@id":
                         "Emotions0",
@@ -109,7 +94,7 @@ class MaxEmotion(PostProcessing):
             'expected': {
                 "@type":
                 "entry",
-                "onyx:hasEmotionSet": [
+                "emotions": [
                     {
                         "@id":
                         "Emotions0",
@@ -122,7 +107,9 @@ class MaxEmotion(PostProcessing):
                                 "onyx:hasEmotionCategory": "joy",
                                 "onyx:hasEmotionIntensity": 0.3333333333333333
                             }
-                        ]
+                        ],
+                        "prov:wasGeneratedBy":
+                        'maxSentiment'
                     }
                 ],
                 "nif:isString":
@@ -135,7 +122,7 @@ class MaxEmotion(PostProcessing):
             "entry": {
                 "@type":
                 "entry",
-                "onyx:hasEmotionSet": [{
+                "emotions": [{
                     "@id":
                     "Emotions0",
                     "@type":
@@ -184,7 +171,7 @@ class MaxEmotion(PostProcessing):
             'expected': {
                 "@type":
                 "entry",
-                "onyx:hasEmotionSet": [{
+                "emotions": [{
                     "@id":
                     "Emotions0",
                     "@type":
@@ -194,7 +181,9 @@ class MaxEmotion(PostProcessing):
                         "@type": "emotion",
                         "onyx:hasEmotionCategory": "neutral",
                         "onyx:hasEmotionIntensity": 1
-                    }]
+                    }],
+                    "prov:wasGeneratedBy":
+                    'maxSentiment'
                 }],
                 "nif:isString":
                 "Test"

senpy/plugins/sentiment/sentiment140/sentiment140_plugin.py

@@ -0,0 +1,75 @@
+import requests
+import json
+
+from senpy.plugins import SentimentPlugin
+from senpy.models import Sentiment
+
+ENDPOINT = 'http://www.sentiment140.com/api/bulkClassifyJson'
+
+
+class Sentiment140(SentimentPlugin):
+    '''Connects to the sentiment140 free API: http://sentiment140.com'''
+
+    author = "@balkian"
+    version = '0.2'
+    url = "https://github.com/gsi-upm/senpy-plugins-community"
+    extra_params = {
+        'language': {
+            "@id": 'lang_sentiment140',
+            'aliases': ['language', 'l'],
+            'required': False,
+            'default': 'auto',
+            'options': ['es', 'en', 'auto']
+        }
+    }
+
+    maxPolarityValue = 1
+    minPolarityValue = 0
+
+    def analyse_entry(self, entry, params):
+        lang = params["language"]
+        res = requests.post(ENDPOINT,
+                            json.dumps({
+                                "language": lang,
+                                "data": [{
+                                    "text": entry['nif:isString']
+                                }]
+                            }))
+        p = params.get("prefix", None)
+        polarity_value = self.maxPolarityValue * int(
+            res.json()["data"][0]["polarity"]) * 0.25
+        polarity = "marl:Neutral"
+        neutral_value = self.maxPolarityValue / 2.0
+        if polarity_value > neutral_value:
+            polarity = "marl:Positive"
+        elif polarity_value < neutral_value:
+            polarity = "marl:Negative"
+
+        sentiment = Sentiment(
+            prefix=p,
+            marl__hasPolarity=polarity,
+            marl__polarityValue=polarity_value)
+        sentiment.prov__wasGeneratedBy = self.id
+        entry.sentiments.append(sentiment)
+        entry.language = lang
+        yield entry
+
+    test_cases = [
+        {
+            'entry': {
+                'nif:isString': 'I love Titanic'
+            },
+            'params': {},
+            'expected': {
+                "nif:isString": "I love Titanic",
+                'sentiments': [
+                    {
+                        'marl:hasPolarity': 'marl:Positive',
+                    }
+                ]
+            },
+            'responses': [{'url': ENDPOINT,
+                           'method': 'POST',
+                           'json': {'data': [{'polarity': 4}]}}]
+        }
+    ]

senpy/plugins/sentiment/sentiment140_plugin.py

@@ -1,87 +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.
-#
-
-import requests
-import json
-
-from senpy.plugins import SentimentBox
-
-ENDPOINT = 'http://www.sentiment140.com/api/bulkClassifyJson'
-
-
-class Sentiment140(SentimentBox):
-    '''Connects to the sentiment140 free API: http://sentiment140.com'''
-
-    author = "@balkian"
-    version = '0.2'
-    url = "https://github.com/gsi-upm/senpy-plugins-community"
-    extra_params = {
-        'language': {
-            "@id": 'lang_sentiment140',
-            'description': 'language of the text',
-            'aliases': ['language', 'l'],
-            'required': True,
-            'default': 'auto',
-            'options': ['es', 'en', 'auto']
-        }
-    }
-
-    classes = ['marl:Positive', 'marl:Neutral', 'marl:Negative']
-    binary = True
-
-    def predict_many(self, features, activity):
-        lang = activity.params["language"]
-        data = []
-
-        for feature in features:
-            data.append({'text': feature[0]})
-
-        res = requests.post(ENDPOINT,
-                            json.dumps({
-                                "language": lang,
-                                "data": data
-                            }))
-
-        for res in res.json()["data"]:
-            polarity = int(res['polarity'])
-            neutral_value = 2
-            if polarity > neutral_value:
-                yield [1, 0, 0]
-                continue
-            elif polarity < neutral_value:
-                yield [0, 0, 1]
-                continue
-            yield [0, 1, 0]
-
-    test_cases = [
-        {
-            'entry': {
-                'nif:isString': 'I love Titanic'
-            },
-            'params': {},
-            'expected': {
-                "nif:isString": "I love Titanic",
-                'marl:hasOpinion': [
-                    {
-                        'marl:hasPolarity': 'marl:Positive',
-                    }
-                ]
-            },
-            'responses': [{'url': ENDPOINT,
-                           'method': 'POST',
-                           'json': {'data': [{'polarity': 4}]}}]
-        }
-    ]

senpy/schemas/aggregatedEvaluation.json

@@ -11,12 +11,14 @@
           "$ref": "context.json"
         },
         "@type": {
+          "default": "AggregatedEvaluation"
         },
         "@id": {
           "description": "ID of the aggregated evaluation",
           "type": "string"
         },
         "evaluations": {
+          "default": [],
           "type": "array",
           "items": {
             "anyOf": [

senpy/schemas/analysis.json

@@ -17,6 +17,7 @@
     "prov:used": {
         "description": "Parameters of the algorithm",
         "@type": "array",
+        "default": [],
         "type": "array",
         "items": {
             "$ref": "parameter.json"

senpy/schemas/context.jsonld

@@ -1,8 +1,8 @@
 {
   "@context": {
-    "@vocab": "http://www.gsi.upm.es/onto/senpy/ns#",
+    "@vocab": "http://www.gsi.dit.upm.es/ontologies/senpy#",
     "dc": "http://dublincore.org/2012/06/14/dcelements#",
-    "senpy": "http://www.gsi.upm.es/onto/senpy/ns#",
+    "me": "http://www.mixedemotions-project.eu/ns/model#",
     "prov": "http://www.w3.org/ns/prov#",
     "nif": "http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#",
     "marl": "http://www.gsi.dit.upm.es/ontologies/marl/ns#",
@@ -16,10 +16,10 @@
       "@container": "@set"
     },
     "entities": {
-      "@id": "senpy:hasEntities"
+      "@id": "me:hasEntities"
     },
     "suggestions": {
-      "@id": "senpy:hasSuggestions",
+      "@id": "me:hasSuggestions",
       "@container": "@set"
     },
     "onyx:hasEmotion": {
@@ -40,7 +40,7 @@
       "@id": "prov:used",
       "@container": "@set"
     },
-    "activities": {
+    "analysis": {
       "@id": "prov:wasInformedBy",
       "@type": "@id",
       "@container": "@set"
@@ -65,13 +65,6 @@
     },
     "onyx:conversionTo": {
       "@type": "@id"
-    },
-    "parameters": {
-        "@type": "Parameter"
-    },
-    "errors": {
-        "@type": "ParameterError"
-    },
-    "prefix": "http://senpy.invalid/"
+    }
   }
 }

senpy/schemas/datasets.json

@@ -7,6 +7,7 @@
       "properties": {
         "datasets": {
           "type": "array",
+          "default": [],
           "items": {
             "$ref": "dataset.json"
           }

senpy/schemas/emotionModel.json

@@ -19,7 +19,8 @@
       "type": "array",
       "items": {
         "$ref": "emotion.json"
-      }
+      },
+      "default": []
     }
   },
   "required": ["@id", "onyx:hasEmotion"]

senpy/schemas/emotionSet.json

@@ -12,7 +12,8 @@
       "type": "array",
       "items": {
         "$ref": "emotion.json"
-      }
+      },
+      "default": []
     },
     "prov:wasGeneratedBy": {
       "type": "string",

senpy/schemas/entry.json

@@ -9,13 +9,30 @@
       "description": "String contained in this Context. Alternative: nif:isString",
       "type": "string"
     },
-    "marl:hasOpinion": {
+    "sentiments": {
       "type": "array",
-      "items": {"$ref": "sentiment.json" }
+      "items": {"$ref": "sentiment.json" },
+      "default": []
     },
-    "onyx:hasEmotionSet": {
+    "emotions": {
       "type": "array",
-      "items": {"$ref": "emotionSet.json" }
+      "items": {"$ref": "emotionSet.json" },
+      "default": []
+    },
+    "entities": {
+      "type": "array",
+      "items": {"$ref": "entity.json" },
+      "default": []
+    },
+    "topics": {
+      "type": "array",
+      "items": {"$ref": "topic.json" },
+      "default": []
+    },
+    "suggestions": {
+      "type": "array",
+      "items": {"$ref": "suggestion.json" },
+      "default": []
     }
   },
   "required": ["nif:isString"]

senpy/schemas/evaluation.json

@@ -6,7 +6,8 @@
       "type": "string"
     },
     "@type": {
-      "type": "array"
+      "type": "array",
+      "default": "Evaluation"
 
     },
     "metrics": {

senpy/schemas/plugin.json

@@ -24,7 +24,8 @@
       "description": "Sub-type of plugin. e.g. sentimentPlugin"
     },
     "extra_params": {
-      "type": "object"
+      "type": "object",
+      "default": {}
     }
   }
 }

senpy/schemas/plugins.json

@@ -7,15 +7,9 @@
       "properties": {
         "plugins": {
           "type": "array",
+          "default": [],
           "items": {
-            "anyOf": [
-              {
-                "type": "string"
-              },
-              {
-                "$ref": "plugin.json"
-              }
-            ]
+            "$ref": "plugin.json"
           }
         }
       }

senpy/schemas/results.json

@@ -1,6 +1,5 @@
 {
   "$schema": "http://json-schema.org/draft-04/schema#",
-  "name": "Entry",
   "allOf": [
     {"$ref": "response.json"},
     {
@@ -11,11 +10,15 @@
         "@context": {
           "$ref": "context.json"
         },
+        "@type": {
+          "default": "results"
+        },
         "@id": {
           "description": "ID of the analysis",
           "type": "string"
         },
-        "activities": {
+        "analysis": {
+          "default": [],
           "type": "array",
           "items": {
               "$ref": "analysis.json"
@@ -23,13 +26,14 @@
         },
         "entries": {
           "type": "array",
+          "default": [],
           "items": {
             "$ref": "entry.json"
           }
         }
 
       },
-      "required": ["@id", "activities", "entries"]
+      "required": ["@id", "analysis", "entries"]
     }
   ]
 }

senpy/static/css/bootstrap-theme.css

@@ -0,0 +1,347 @@
+/*!
+ * Bootstrap v3.1.1 (http://getbootstrap.com)
+ * Copyright 2011-2014 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ */
+
+.btn-default,
+.btn-primary,
+.btn-success,
+.btn-info,
+.btn-warning,
+.btn-danger {
+  text-shadow: 0 -1px 0 rgba(0, 0, 0, .2);
+  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 1px rgba(0, 0, 0, .075);
+          box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 1px rgba(0, 0, 0, .075);
+}
+.btn-default:active,
+.btn-primary:active,
+.btn-success:active,
+.btn-info:active,
+.btn-warning:active,
+.btn-danger:active,
+.btn-default.active,
+.btn-primary.active,
+.btn-success.active,
+.btn-info.active,
+.btn-warning.active,
+.btn-danger.active {
+  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, .125);
+          box-shadow: inset 0 3px 5px rgba(0, 0, 0, .125);
+}
+.btn:active,
+.btn.active {
+  background-image: none;
+}
+.btn-default {
+  text-shadow: 0 1px 0 #fff;
+  background-image: -webkit-linear-gradient(top, #fff 0%, #e0e0e0 100%);
+  background-image:         linear-gradient(to bottom, #fff 0%, #e0e0e0 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffffffff', endColorstr='#ffe0e0e0', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-color: #dbdbdb;
+  border-color: #ccc;
+}
+.btn-default:hover,
+.btn-default:focus {
+  background-color: #e0e0e0;
+  background-position: 0 -15px;
+}
+.btn-default:active,
+.btn-default.active {
+  background-color: #e0e0e0;
+  border-color: #dbdbdb;
+}
+.btn-primary {
+  background-image: -webkit-linear-gradient(top, #428bca 0%, #2d6ca2 100%);
+  background-image:         linear-gradient(to bottom, #428bca 0%, #2d6ca2 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff428bca', endColorstr='#ff2d6ca2', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-color: #2b669a;
+}
+.btn-primary:hover,
+.btn-primary:focus {
+  background-color: #2d6ca2;
+  background-position: 0 -15px;
+}
+.btn-primary:active,
+.btn-primary.active {
+  background-color: #2d6ca2;
+  border-color: #2b669a;
+}
+.btn-success {
+  background-image: -webkit-linear-gradient(top, #5cb85c 0%, #419641 100%);
+  background-image:         linear-gradient(to bottom, #5cb85c 0%, #419641 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5cb85c', endColorstr='#ff419641', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-color: #3e8f3e;
+}
+.btn-success:hover,
+.btn-success:focus {
+  background-color: #419641;
+  background-position: 0 -15px;
+}
+.btn-success:active,
+.btn-success.active {
+  background-color: #419641;
+  border-color: #3e8f3e;
+}
+.btn-info {
+  background-image: -webkit-linear-gradient(top, #5bc0de 0%, #2aabd2 100%);
+  background-image:         linear-gradient(to bottom, #5bc0de 0%, #2aabd2 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5bc0de', endColorstr='#ff2aabd2', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-color: #28a4c9;
+}
+.btn-info:hover,
+.btn-info:focus {
+  background-color: #2aabd2;
+  background-position: 0 -15px;
+}
+.btn-info:active,
+.btn-info.active {
+  background-color: #2aabd2;
+  border-color: #28a4c9;
+}
+.btn-warning {
+  background-image: -webkit-linear-gradient(top, #f0ad4e 0%, #eb9316 100%);
+  background-image:         linear-gradient(to bottom, #f0ad4e 0%, #eb9316 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff0ad4e', endColorstr='#ffeb9316', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-color: #e38d13;
+}
+.btn-warning:hover,
+.btn-warning:focus {
+  background-color: #eb9316;
+  background-position: 0 -15px;
+}
+.btn-warning:active,
+.btn-warning.active {
+  background-color: #eb9316;
+  border-color: #e38d13;
+}
+.btn-danger {
+  background-image: -webkit-linear-gradient(top, #d9534f 0%, #c12e2a 100%);
+  background-image:         linear-gradient(to bottom, #d9534f 0%, #c12e2a 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9534f', endColorstr='#ffc12e2a', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-color: #b92c28;
+}
+.btn-danger:hover,
+.btn-danger:focus {
+  background-color: #c12e2a;
+  background-position: 0 -15px;
+}
+.btn-danger:active,
+.btn-danger.active {
+  background-color: #c12e2a;
+  border-color: #b92c28;
+}
+.thumbnail,
+.img-thumbnail {
+  -webkit-box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
+          box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
+}
+.dropdown-menu > li > a:hover,
+.dropdown-menu > li > a:focus {
+  background-color: #e8e8e8;
+  background-image: -webkit-linear-gradient(top, #f5f5f5 0%, #e8e8e8 100%);
+  background-image:         linear-gradient(to bottom, #f5f5f5 0%, #e8e8e8 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#ffe8e8e8', GradientType=0);
+  background-repeat: repeat-x;
+}
+.dropdown-menu > .active > a,
+.dropdown-menu > .active > a:hover,
+.dropdown-menu > .active > a:focus {
+  background-color: #357ebd;
+  background-image: -webkit-linear-gradient(top, #428bca 0%, #357ebd 100%);
+  background-image:         linear-gradient(to bottom, #428bca 0%, #357ebd 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff428bca', endColorstr='#ff357ebd', GradientType=0);
+  background-repeat: repeat-x;
+}
+.navbar-default {
+  background-image: -webkit-linear-gradient(top, #fff 0%, #f8f8f8 100%);
+  background-image:         linear-gradient(to bottom, #fff 0%, #f8f8f8 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffffffff', endColorstr='#fff8f8f8', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+  border-radius: 4px;
+  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 5px rgba(0, 0, 0, .075);
+          box-shadow: inset 0 1px 0 rgba(255, 255, 255, .15), 0 1px 5px rgba(0, 0, 0, .075);
+}
+.navbar-default .navbar-nav > .active > a {
+  background-image: -webkit-linear-gradient(top, #ebebeb 0%, #f3f3f3 100%);
+  background-image:         linear-gradient(to bottom, #ebebeb 0%, #f3f3f3 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffebebeb', endColorstr='#fff3f3f3', GradientType=0);
+  background-repeat: repeat-x;
+  -webkit-box-shadow: inset 0 3px 9px rgba(0, 0, 0, .075);
+          box-shadow: inset 0 3px 9px rgba(0, 0, 0, .075);
+}
+.navbar-brand,
+.navbar-nav > li > a {
+  text-shadow: 0 1px 0 rgba(255, 255, 255, .25);
+}
+.navbar-inverse {
+  background-image: -webkit-linear-gradient(top, #3c3c3c 0%, #222 100%);
+  background-image:         linear-gradient(to bottom, #3c3c3c 0%, #222 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff3c3c3c', endColorstr='#ff222222', GradientType=0);
+  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+  background-repeat: repeat-x;
+}
+.navbar-inverse .navbar-nav > .active > a {
+  background-image: -webkit-linear-gradient(top, #222 0%, #282828 100%);
+  background-image:         linear-gradient(to bottom, #222 0%, #282828 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff222222', endColorstr='#ff282828', GradientType=0);
+  background-repeat: repeat-x;
+  -webkit-box-shadow: inset 0 3px 9px rgba(0, 0, 0, .25);
+          box-shadow: inset 0 3px 9px rgba(0, 0, 0, .25);
+}
+.navbar-inverse .navbar-brand,
+.navbar-inverse .navbar-nav > li > a {
+  text-shadow: 0 -1px 0 rgba(0, 0, 0, .25);
+}
+.navbar-static-top,
+.navbar-fixed-top,
+.navbar-fixed-bottom {
+  border-radius: 0;
+}
+.alert {
+  text-shadow: 0 1px 0 rgba(255, 255, 255, .2);
+  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, .25), 0 1px 2px rgba(0, 0, 0, .05);
+          box-shadow: inset 0 1px 0 rgba(255, 255, 255, .25), 0 1px 2px rgba(0, 0, 0, .05);
+}
+.alert-success {
+  background-image: -webkit-linear-gradient(top, #dff0d8 0%, #c8e5bc 100%);
+  background-image:         linear-gradient(to bottom, #dff0d8 0%, #c8e5bc 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffdff0d8', endColorstr='#ffc8e5bc', GradientType=0);
+  background-repeat: repeat-x;
+  border-color: #b2dba1;
+}
+.alert-info {
+  background-image: -webkit-linear-gradient(top, #d9edf7 0%, #b9def0 100%);
+  background-image:         linear-gradient(to bottom, #d9edf7 0%, #b9def0 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9edf7', endColorstr='#ffb9def0', GradientType=0);
+  background-repeat: repeat-x;
+  border-color: #9acfea;
+}
+.alert-warning {
+  background-image: -webkit-linear-gradient(top, #fcf8e3 0%, #f8efc0 100%);
+  background-image:         linear-gradient(to bottom, #fcf8e3 0%, #f8efc0 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fffcf8e3', endColorstr='#fff8efc0', GradientType=0);
+  background-repeat: repeat-x;
+  border-color: #f5e79e;
+}
+.alert-danger {
+  background-image: -webkit-linear-gradient(top, #f2dede 0%, #e7c3c3 100%);
+  background-image:         linear-gradient(to bottom, #f2dede 0%, #e7c3c3 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff2dede', endColorstr='#ffe7c3c3', GradientType=0);
+  background-repeat: repeat-x;
+  border-color: #dca7a7;
+}
+.progress {
+  background-image: -webkit-linear-gradient(top, #ebebeb 0%, #f5f5f5 100%);
+  background-image:         linear-gradient(to bottom, #ebebeb 0%, #f5f5f5 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffebebeb', endColorstr='#fff5f5f5', GradientType=0);
+  background-repeat: repeat-x;
+}
+.progress-bar {
+  background-image: -webkit-linear-gradient(top, #428bca 0%, #3071a9 100%);
+  background-image:         linear-gradient(to bottom, #428bca 0%, #3071a9 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff428bca', endColorstr='#ff3071a9', GradientType=0);
+  background-repeat: repeat-x;
+}
+.progress-bar-success {
+  background-image: -webkit-linear-gradient(top, #5cb85c 0%, #449d44 100%);
+  background-image:         linear-gradient(to bottom, #5cb85c 0%, #449d44 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5cb85c', endColorstr='#ff449d44', GradientType=0);
+  background-repeat: repeat-x;
+}
+.progress-bar-info {
+  background-image: -webkit-linear-gradient(top, #5bc0de 0%, #31b0d5 100%);
+  background-image:         linear-gradient(to bottom, #5bc0de 0%, #31b0d5 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff5bc0de', endColorstr='#ff31b0d5', GradientType=0);
+  background-repeat: repeat-x;
+}
+.progress-bar-warning {
+  background-image: -webkit-linear-gradient(top, #f0ad4e 0%, #ec971f 100%);
+  background-image:         linear-gradient(to bottom, #f0ad4e 0%, #ec971f 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff0ad4e', endColorstr='#ffec971f', GradientType=0);
+  background-repeat: repeat-x;
+}
+.progress-bar-danger {
+  background-image: -webkit-linear-gradient(top, #d9534f 0%, #c9302c 100%);
+  background-image:         linear-gradient(to bottom, #d9534f 0%, #c9302c 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9534f', endColorstr='#ffc9302c', GradientType=0);
+  background-repeat: repeat-x;
+}
+.list-group {
+  border-radius: 4px;
+  -webkit-box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
+          box-shadow: 0 1px 2px rgba(0, 0, 0, .075);
+}
+.list-group-item.active,
+.list-group-item.active:hover,
+.list-group-item.active:focus {
+  text-shadow: 0 -1px 0 #3071a9;
+  background-image: -webkit-linear-gradient(top, #428bca 0%, #3278b3 100%);
+  background-image:         linear-gradient(to bottom, #428bca 0%, #3278b3 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff428bca', endColorstr='#ff3278b3', GradientType=0);
+  background-repeat: repeat-x;
+  border-color: #3278b3;
+}
+.panel {
+  -webkit-box-shadow: 0 1px 2px rgba(0, 0, 0, .05);
+          box-shadow: 0 1px 2px rgba(0, 0, 0, .05);
+}
+.panel-default > .panel-heading {
+  background-image: -webkit-linear-gradient(top, #f5f5f5 0%, #e8e8e8 100%);
+  background-image:         linear-gradient(to bottom, #f5f5f5 0%, #e8e8e8 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff5f5f5', endColorstr='#ffe8e8e8', GradientType=0);
+  background-repeat: repeat-x;
+}
+.panel-primary > .panel-heading {
+  background-image: -webkit-linear-gradient(top, #428bca 0%, #357ebd 100%);
+  background-image:         linear-gradient(to bottom, #428bca 0%, #357ebd 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ff428bca', endColorstr='#ff357ebd', GradientType=0);
+  background-repeat: repeat-x;
+}
+.panel-success > .panel-heading {
+  background-image: -webkit-linear-gradient(top, #dff0d8 0%, #d0e9c6 100%);
+  background-image:         linear-gradient(to bottom, #dff0d8 0%, #d0e9c6 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffdff0d8', endColorstr='#ffd0e9c6', GradientType=0);
+  background-repeat: repeat-x;
+}
+.panel-info > .panel-heading {
+  background-image: -webkit-linear-gradient(top, #d9edf7 0%, #c4e3f3 100%);
+  background-image:         linear-gradient(to bottom, #d9edf7 0%, #c4e3f3 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffd9edf7', endColorstr='#ffc4e3f3', GradientType=0);
+  background-repeat: repeat-x;
+}
+.panel-warning > .panel-heading {
+  background-image: -webkit-linear-gradient(top, #fcf8e3 0%, #faf2cc 100%);
+  background-image:         linear-gradient(to bottom, #fcf8e3 0%, #faf2cc 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fffcf8e3', endColorstr='#fffaf2cc', GradientType=0);
+  background-repeat: repeat-x;
+}
+.panel-danger > .panel-heading {
+  background-image: -webkit-linear-gradient(top, #f2dede 0%, #ebcccc 100%);
+  background-image:         linear-gradient(to bottom, #f2dede 0%, #ebcccc 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#fff2dede', endColorstr='#ffebcccc', GradientType=0);
+  background-repeat: repeat-x;
+}
+.well {
+  background-image: -webkit-linear-gradient(top, #e8e8e8 0%, #f5f5f5 100%);
+  background-image:         linear-gradient(to bottom, #e8e8e8 0%, #f5f5f5 100%);
+  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#ffe8e8e8', endColorstr='#fff5f5f5', GradientType=0);
+  background-repeat: repeat-x;
+  border-color: #dcdcdc;
+  -webkit-box-shadow: inset 0 1px 3px rgba(0, 0, 0, .05), 0 1px 0 rgba(255, 255, 255, .1);
+          box-shadow: inset 0 1px 3px rgba(0, 0, 0, .05), 0 1px 0 rgba(255, 255, 255, .1);
+}
+/*# sourceMappingURL=bootstrap-theme.css.map */