test local install for doc

Author: yomguy

.readthedocs.yml

@@ -11,14 +11,14 @@ sphinx:
     configuration: docs/source/conf.py
     fail_on_warning: false
 
-# Build documentation with MkDocs
-#mkdocs:
-#  configuration: mkdocs.yml
-
-# Optionally build your docs in additional formats such as PDF and ePub
-formats: all
+build:
+  os: debian
+  tools:
+    python: '3.9'
 
 # Optionally set the version of Python and requirements required to build your docs
 python:
   install:
-    - requirements: docs/requirements-docs.txt
+    - requirements: requirements.txt
+    - method: pip
+      path: .

docs/source/core_api/processors_list/processors_list.rst

@@ -3,67 +3,67 @@ List of available processors
 
 Encoder
 --------
-* **flac_aubio_encoder** **1.0**: FLAC encoder based on aubio
-* **vorbis_aubio_encoder** **1.0**: OGG Vorbis encoder based on aubio
-* **wav_aubio_encoder** **1.0**: Wav encoder based on aubio
-* **live_encoder** **1.0**: Gstreamer-based Audio Sink
-* **flac_encoder** **1.0**: FLAC encoder based on Gstreamer
-* **aac_encoder** **1.0**: AAC encoder based on Gstreamer
-* **mp3_encoder** **1.0**: MP3 encoder based on Gstreamer
-* **vorbis_encoder** **1.0**: OGG Vorbis encoder based on Gstreamer
-* **opus_encoder** **1.0**: Opus encoder based on Gstreamer
-* **wav_encoder** **1.0**: WAV encoder based on Gstreamer
-* **webm_encoder** **1.0**: WebM encoder based on Gstreamer
+- **flac_aubio_encoder** **1.0**: FLAC encoder based on aubio
+- **vorbis_aubio_encoder** **1.0**: OGG Vorbis encoder based on aubio
+- **wav_aubio_encoder** **1.0**: Wav encoder based on aubio
+- **live_encoder** **1.0**: Gstreamer-based Audio Sink
+- **flac_encoder** **1.0**: FLAC encoder based on Gstreamer
+- **aac_encoder** **1.0**: AAC encoder based on Gstreamer
+- **mp3_encoder** **1.0**: MP3 encoder based on Gstreamer
+- **vorbis_encoder** **1.0**: OGG Vorbis encoder based on Gstreamer
+- **opus_encoder** **1.0**: Opus encoder based on Gstreamer
+- **wav_encoder** **1.0**: WAV encoder based on Gstreamer
+- **webm_encoder** **1.0**: WebM encoder based on Gstreamer
 
 Decoder
 --------
-* **array_decoder** **1.0**: Decoder taking Numpy array as input
-* **aubio_decoder** **1.0**: File decoder based on aubio
-* **file_decoder** **1.0**: File Decoder based on Gstreamer
+- **array_decoder** **1.0**: Decoder taking Numpy array as input
+- **aubio_decoder** **1.0**: File decoder based on aubio
+- **file_decoder** **1.0**: File Decoder based on Gstreamer
 
 Grapher
 --------
-* **grapher_aubio_pitch** **1.0**: Image representing Pitch
-* **grapher_aubio_silence** **1.0**: Image representing Aubio Silence
-* **grapher_dissonance** **1.0**: Image representing Dissonance
-* **grapher_vamp_cqt** **1.0**: Image representing Constant Q Transform
-* **grapher_loudness_itu** **1.0**: Image representing Loudness ITU
-* **spectrogram** **1.0**: Image representing Linear Spectrogram
-* **grapher_onset_detection_function** **1.0**: Image representing Onset detection
-* **grapher_waveform** **1.0**: Image representing Waveform from Analyzer
-* **spectrogram_log** **1.0**: Logarithmic scaled spectrogram (level vs. frequency vs. time).
-* **spectrogram_lin** **1.0**: Linear scaled spectrogram (level vs. frequency vs. time).
-* **waveform_simple** **1.0**: Simple monochrome waveform image.
-* **waveform_centroid** **1.0**: Waveform where peaks are colored relatively to the spectral centroids of each frame buffer.
-* **waveform_contour_black** **1.0**: Black amplitude contour waveform.
-* **waveform_contour_white** **1.0**: an white amplitude contour wavform.
-* **waveform_transparent** **1.0**: Transparent waveform.
+- **grapher_aubio_pitch** **1.0**: Image representing Pitch
+- **grapher_aubio_silence** **1.0**: Image representing Aubio Silence
+- **grapher_dissonance** **1.0**: Image representing Dissonance
+- **grapher_vamp_cqt** **1.0**: Image representing Constant Q Transform
+- **grapher_loudness_itu** **1.0**: Image representing Loudness ITU
+- **spectrogram** **1.0**: Image representing Linear Spectrogram
+- **grapher_onset_detection_function** **1.0**: Image representing Onset detection
+- **grapher_waveform** **1.0**: Image representing Waveform from Analyzer
+- **spectrogram_log** **1.0**: Logarithmic scaled spectrogram (level vs. frequency vs. time).
+- **spectrogram_lin** **1.0**: Linear scaled spectrogram (level vs. frequency vs. time).
+- **waveform_simple** **1.0**: Simple monochrome waveform image.
+- **waveform_centroid** **1.0**: Waveform where peaks are colored relatively to the spectral centroids of each frame buffer.
+- **waveform_contour_black** **1.0**: Black amplitude contour waveform.
+- **waveform_contour_white** **1.0**: an white amplitude contour wavform.
+- **waveform_transparent** **1.0**: Transparent waveform.
 
 Analyzer
 ---------
-* **aubio_melenergy** **0.4.6**: Aubio Mel Energy analyzer
-* **aubio_mfcc** **0.4.6**: Aubio MFCC analyzer
-* **aubio_pitch** **0.4.6**: Aubio Pitch estimation analyzer
-* **aubio_silence** **0.4.6**: Aubio Silence detection analyzer
-* **aubio_specdesc** **0.4.6**: Aubio Spectral Descriptors collection analyzer
-* **aubio_temporal** **0.4.6**: Aubio Temporal analyzer
-* **essentia_dissonance** **2.1b5.dev416**: Dissonance from Essentia
-* **vamp_constantq** **1.1.0**: Constant Q transform from QMUL vamp plugins
-* **vamp_simple_host** **1.1.0**: Vamp plugins library interface analyzer
-* **loudness_itu** **1.0**: Measure of audio loudness using standard ITU-R BS.1770-3
-* **spectrogram_analyzer** **1.0**: Spectrogram image builder with an extensible buffer based on tables
-* **onset_detection_function** **1.0**: Onset Detection Function analyzer
-* **spectrogram_analyzer_buffer** **1.0**: Spectrogram image builder with an extensible buffer based on tables
-* **waveform_analyzer** **1.0**: Waveform analyzer
+- **aubio_melenergy** **0.4.6**: Aubio Mel Energy analyzer
+- **aubio_mfcc** **0.4.6**: Aubio MFCC analyzer
+- **aubio_pitch** **0.4.6**: Aubio Pitch estimation analyzer
+- **aubio_silence** **0.4.6**: Aubio Silence detection analyzer
+- **aubio_specdesc** **0.4.6**: Aubio Spectral Descriptors collection analyzer
+- **aubio_temporal** **0.4.6**: Aubio Temporal analyzer
+- **essentia_dissonance** **2.1b5.dev416**: Dissonance from Essentia
+- **vamp_constantq** **1.1.0**: Constant Q transform from QMUL vamp plugins
+- **vamp_simple_host** **1.1.0**: Vamp plugins library interface analyzer
+- **loudness_itu** **1.0**: Measure of audio loudness using standard ITU-R BS.1770-3
+- **spectrogram_analyzer** **1.0**: Spectrogram image builder with an extensible buffer based on tables
+- **onset_detection_function** **1.0**: Onset Detection Function analyzer
+- **spectrogram_analyzer_buffer** **1.0**: Spectrogram image builder with an extensible buffer based on tables
+- **waveform_analyzer** **1.0**: Waveform analyzer
 
 ValueAnalyzer
 --------------
-* **mean_dc_shift** **1.0**: Mean DC shift analyzer
-* **essentia_dissonance_value** **2.1b5.dev416**: Mean Dissonance Value from Essentia
-* **vamp_tempo** **1.1.0**: Tempo from QMUL vamp plugins
-* **vamp_tuning** **1.1.0**: Tuning from NNLS Chroma vamp plugins
-* **level** **1.0**: Audio level analyzer
+- **mean_dc_shift** **1.0**: Mean DC shift analyzer
+- **essentia_dissonance_value** **2.1b5.dev416**: Mean Dissonance Value from Essentia
+- **vamp_tempo** **1.1.0**: Tempo from QMUL vamp plugins
+- **vamp_tuning** **1.1.0**: Tuning from NNLS Chroma vamp plugins
+- **level** **1.0**: Audio level analyzer
 
 Effect
 -------
-* **fx_gain** **1.0**: Gain effect processor
+- **fx_gain** **1.0**: Gain effect processor

docs/source/server_api/introduction.rst

@@ -10,7 +10,7 @@ In addition to be usable as a library, TimeSide has furthermore been built into
 - collect tags and indices on tracks to build annotated audio corpora for further machine learning purpose.
 
 Models and Serializers
------------------------
+======================
 
 The models of the backend are defined as usual Django models and are all stored with a UUID. Here is a list of the main ones:
 
@@ -21,12 +21,23 @@ The models of the backend are defined as usual Django models and are all stored
 - Experience: a list of Presets
 - Task: a list of Selection linked to an Experience to run
 
-This modelization allows to define some specific precessing \textit{Experiences} that can be re-processed on any new \textit{Selection} which is espacially convenient for analysis on growing datasets. All model instances and related data are accesible through a REST API with authentication. This ensures that a client can consume TimeSide as a dedicated and autonomous web service.
+This modelization allows to define some specific precessing *Experiences* that can be re-processed on any new *Selection* which is espacially convenient for analysis on growing datasets. All model instances and related data are accesible through a REST API with authentication. This ensures that a client can consume TimeSide as a dedicated and autonomous web service.
 
-The API full documentation is there: https://timeside.ircam.fr/timeside/api/docs/
+Results and Formats
+====================
 
+All processing results are accesible in a \verb|AnalyzerResult| python object containing a structured and documented data dictionary which can be serialized, stored and restored in HDF5, JSON, YAML or XML formats. The file contains all the preset parameters and data structure so that, if a process is requested for the same media file, same processors type and same version, the data will be automatically retrieve from the databasen and eventualluy re-processed in another child processor or serializer. The TimeSide server also embeds a full relational database to store any lighter data that has be be linked to models.
 
-Results and Formats
---------------------
 
-All processing results are accesible in a \verb|AnalyzerResult| python object containing a structured and documented data dictionary which can be serialized, stored and restored in HDF5, JSON, YAML or XML formats. The file contains all the preset parameters and data structure so that, if a process is requested for the same media file, same processors type and same version, the data will be automatically retrieve from the databasen and eventualluy re-processed in another child processor or serializer. The TimeSide server also embeds a full relational database to store any lighter data that has be be linked to models.
+API documentation
+==================
+
+The `API full documentation is available online <https://timeside.ircam.fr/timeside/api/docs/>`_
+
+
+Javascript SDK
+===============
+
+In order to build frontends on top of this web API, a `Software Development Kit (SDK) is available <https://github.com/Ircam-WAM/timeside-sdk-js>`_ for the Javascript and Typescript languages. It has been created from the  routes of the OpenAPI schema automatically exported from the backend thanks to the OpenAPI Generator. The SDK proposes  some examples for clients to reach the server and request some processing.
+
+As an example, an augmented HTML5 player is presented in the "User Interfaces" section.

requirements.txt

@@ -150,7 +150,7 @@ six==1.12.0
 snowballstemmer==2.0.0
 SoundFile==0.10.3.post1
 Sphinx==2.4.1
-sphinx-rtd-theme==0.4.3
+sphinx-rtd-theme>=0.5.1
 sphinxcontrib-applehelp==1.0.1
 sphinxcontrib-devhelp==1.0.1
 sphinxcontrib-htmlhelp==1.0.2