Standard and idiosyncratic schemata for Sanskrit data, with a library of validation, (de-)serialization, a database interface and other utilities.
Project description
Introduction
This module defines: - schema - shared standard schema for communicating and storing Sanskrit data of various types. - various idiosyncratic notations used by various modules which deviate from the proposed standards. - python classes (corresponding to the schema) and shared libraries for validating, (de-)serializing and storing sanskrit data of various types. - a common database interface for accessing various databases (so that a downstream app can switch to a different database with a single line change).
Similar libraries in various other languages are being built: - Scala (likely compatible with Java): db-interface .
Motivation
Various sanskrit modules need to communicate data amongst each other (for example through a REST API or database stores or even function calls). Examples of the data being communicated could be:
Gramatical details of a given word
Sentences in a given book chapter
Annotations on a given phrase
When it comes to serialization formats - two distinct approaches present themselves to us:
One possible route is to have each project defining and using its own idiosyncratic notation. But this entails an additional burdens:
Each communicating module having to convert the data from one idiosyncratic notation to another.
Good schema design or notation is non trivial. Even if no external module is using the data, it is a waste to have to reinvent the wheel.
A superior route is to have a common, standard format for encoding various data-types for storage/ communication.
To the extant possible, we should take latter approach to data storage and communication.
Where idiosyncratic notations are adapted for various reasons, it is still desirable to collect such definitions in a single module - to facilitate conversion to the standard format.
For users
Installation
Latest release: sudo pip2 install sanskrit_data -U
Development copy: sudo pip2 install git+https://github.com/sanskrit-coders/sanskrit_data@master -U
Web.
Usage
Please see the generated python sphynx docs in one of the following places:
http://sanskrit-data.readthedocs.io - currently broken due to BUILD errors - see bug .
under docs/_build/html/index.html
Design considerations for data containers corresponding to the various submodules (such as books and annotations) are given below - or in the corresponding source files.
For contributors
Contact
Have a problem or question? Please head to github.
Packaging
~/.pypirc should have your pypi login credentials.
python setup.py bdist_wheel twine upload dist/* --skip-existing
Document generation
Sphynx html docs can be generated with cd docs; make html
http://sanskrit-data.readthedocs.io should automatically have good updated documentation - unless there are build errors.
Design principles
Data design
General principles
We want data to be stored and communicated between programs in a popular, extensible format - we want to take advantage of existing technologies to the maximum possible extant and not waste time reinventing associated (de)serialization, validation and other libraries.
But this does not prevent the data from being presented in a different format for human consumption.
While designing the JSON data-model: - Type-hint in JSON should be jsonClass (a language-independent name we’ve picked). - Try to avoid field-names which conflict with programming language keywords. (Eg. Prefer “source_type” to “type”). - In general, use camelCase or underscore_case for field names - both are fine. Where romanized (potentially mixed case) sanskrit words are used, the latter is the superior convention. - Where field names and values are to be automatically rendered into various scripts, as in case of sanskrit vyAkarana jargon (eg: vibhakti, lakAra), we prefer SLP1 transliteration (“viBakti”, “lakAra”). - PS: Convenient transliteration modules are available in various languages: please see them listed here. - A transliteration map for reference. - When in doubt, keep fields optional.
Books and annotations
Basic principles
Books are stored as a hierarchy of BookPortion objects - book containing many chapters containing many lines etc..
Annotations are stored in a similar hierarchy, for example - a TextAnnotation having PadaAnnotations having SamaasaAnnotations.
Some Annotations (eg. SandhiAnnotation, TextAnnotation) can have multiple “targets” (ie. other objects being annotated).
Rather than a simple tree, we end up with a Directed Acyclic Graph (DAG) of Annotation objects.
JSON schema mindmap here (Updated as needed).
The data containers are in a separate sanskrit_data module - so that it can be extracted and used outside this server.
Python data containers and utilities
For each JSON schema, we have a python class, at the root of which there is the generic JsonObject class with a lot of utilities. We define a hierarchy of classes so as to share validation and other code specific to certain data classes.
Separate Database-specific elements through an interface. We should be able to easily switch to a different database.
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