oteapi-core 0.2.1

Open Translation Environment (OTE) API.

Open Translation Environment (OTE) API Core

Framework for accessing data resources, mapping data models, describing the data to ontologies and perform data transformations

We highly recommend reading this page in the official documentation.

About OTEAPI Core

OTEAPI Core provides the core functionality of OTEAPI, which stands for the Open Translation Environment API.

It uses the strategy software design pattern to implement a simple and easy to extend access to a large range of data resources. Semantic interoperability is supported via mapping of data models describing the data to ontologies. Transformations, mainly intended to transform data between representations, are also supported, but transformations can also be used for running simulations in a simple workflow.

OTEAPI Core includes:

• A set of standard strategies;
• A plugin system for loading the standard strategies, as well as third party strategies;
• Data models for configuring the strategies;
• A Python library, through which the data can be accessed; and
• An efficient data cache module that avoids downloading the same content several times.

Types of strategies

Download strategy

Download strategy patterns use a given protocol to download content into the data cache. They are configured with the ResourceConfig data model, using the scheme of the downloadUrl field for strategy selection. The configuration field can be used to configure how the downloaded content is stored in the cache using the DownloadConfig data model.

Standard downloaded strategies: file, https, http, sftp, ftp

Parse strategy

Parse strategy patterns convert content from the data cache to a Python dict. Like download strategies, they are configured with the ResourceConfig data model, using the mediaType field for strategy selection. Additional strategy-specific configurations can be provided via the configuration field.

Standard parse strategies: application/json, image/jpg, image/jpeg, image/jp2, image/png, image/gif, image/tiff, image/eps, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, application/vnd.sqlite3

Resource strategy

Resource strategy patterns can retrieve/upload data to external data services. They are configured with the ResourceConfig data model, using the scheme of the accessUrl and accessService fields. The scheme of the accessUrl is used for strategy selection.

Mapping strategy

Strategies for mapping fields/properties in data models to ontological concepts.

Filter strategy

Filter strategies can update the configuration of other strategies. They can also update values in the data cache.

Standard filter strategies: filter/crop, filter/sql

Function strategy

Function strategies are synchronous transformations that (normally) run directly on the server hosting the OTE service.

Transformation strategy

Transformation strategies are a special form of a function strategy intended for long-running transformations. In this sense, they represent asynchronous functions running in the background or on external resources.

Standard transformation strategies: celery/remote

Entry points for plugins

The way strategies are registered and found is through entry points.

Special group names allow understanding the strategy type and the entry point values allow understanding of what kind of strategy a specific class implements. A full overview of recognized entry point group names can be seen in Table of entry point strategies.

Defining entry points

In the following examples, let's imagine we have a package importable in Python through my_plugin and contains two download strategies and a single parse strategy:

1. A peer-2-peer download strategy, implemented in a class named Peer2PeerDownload importable from my_plugin.strategies.download.peer_2_peer.
2. A MongoDB download strategy, implemented in a class named MongoRetrieve importable from my_plugin.strategies.mongo.
3. A MongoDB parse strategy, implemented in a class named MongoParse importable from my_plugin.strategies.mongo.

There are now various different ways to let the Python environment know of these strategies through entry points.

setup.py

In the package's setup.py file, one can specify entry points.
Here, an example snippet is shown using setuptools:

# setup.py
from setuptools import setup

setup(
    # ...,
    entry_points={
        "oteapi.download": [
            "my_plugin.p2p = my_plugin.strategies.download.peer_2_peer:Peer2PeerDownload",
            "my_plugin.mongo = my_plugin.strategies.mongo:MongoRetrieve",
        ],
        "oteapi.parse": [
            "my_plugin.application/vnd.mongo+json = my_plugin.strategies.mongo:MongoParse",
        ]
    },
)

YAML/JSON custom files

Use custom files that are later parsed and used in a setup.py file.

entry_points:
  oteapi.download:
  - "my_plugin.p2p = my_plugin.strategies.download.peer_2_peer:Peer2PeerDownload"
  - "my_plugin.mongo = my_plugin.strategies.mongo:MongoRetrieve"
  oteapi.parse:
  - "my_plugin.application/vnd.mongo+json = my_plugin.strategies.mongo:MongoParse"

{
  "entry_points": {
    "oteapi.download": [
      "my_plugin.p2p = my_plugin.strategies.download.peer_2_peer:Peer2PeerDownload",
      "my_plugin.mongo = my_plugin.strategies.mongo:MongoRetrieve"
    ],
    "oteapi.parse": [
      "my_plugin.application/vnd.mongo+json = my_plugin.strategies.mongo:MongoParse"
    ]
  }
}

setup.cfg/pyproject.toml

A more modern approach is to use setup.cfg or pyproject.toml.

[options.entry_points]
oteapi.download =
    my_plugin.p2p = my_plugin.strategies.download.peer_2_peer:Peer2PeerDownload
    my_plugin.mongo = my_plugin.strategies.mongo:MongoRetrieve
oteapi.parse =
    my_plugin.application/vnd.mongo+json = my_plugin.strategies.mongo:MongoParse

Syntax and semantics

As seen above, there are a few different syntactical flavors of how to list the entry points. However, the "value" stays the same throughout.

General Python entry points

The general syntax for entry points is based on ini files and parsed using the built-in configparser module described here. Specifically for entry points the nomenclature is the following:

[options.entry_points]
GROUP =
    NAME = VALUE

The VALUE is then further split into: PACKAGE.MODULE:OBJECT.ATTRIBUTE [EXTRA1, EXTRA2].

OTEAPI strategy entry points

From the general syntax outlined above, OTEAPI Core then implements rules and requirements regarding the syntax for strategies.

1. A class MUST be specified (as an OBJECT).
2. The NAME MUST consist of exactly two parts: PACKAGE and strategy type value in the form of PACKAGE.STRATEGY_TYPE_VALUE.
3. The GROUP MUST be a valid OTEAPI entry point group, see Table of entry point strategies for a full list of valid OTEAPI entry point group values.

To understand what the strategy type value should be, see Table of entry point strategies.

Table of entry point strategies

Strategy Type Name	Strategy Type Value	Entry Point Group	Documentation Reference
Download	scheme	oteapi.download	Download strategy
Filter	filterType	oteapi.filter	Filter strategy
Function	functionType	oteapi.function	Function strategy
Mapping	mappingType	oteapi.mapping	Mapping strategy
Parse	mediaType	oteapi.parse	Parse strategy
Resource	accessService	oteapi.resource	Resource strategy
Transformation	transformationType	oteapi.transformation	Transformation strategy

Other OTEAPI-related repositories

• OTEAPI Services - a RESTful interface to OTEAPI Core
• OTELib - a Python interface to OTEAPI Services
• OTEAPI Plugin Template - a cookiecutter template for OTEAPI Plugins

Installation

OTEAPI Core can be installed with:

pip install oteapi-core

For developers

If you want to install OTEAPI Core to have a developer environment, please clone down the repository from GitHub and install:

git clone https://github.com/EMMC-ASBL/oteapi-core /path/to/oteapi-core
pip install -U --upgrade-strategy=eager -e /path/to/oteapi-core[dev]

Note, /path/to/oteapi-core can be left out of the first line, but then it must be updated in the second line, either to ./oteapi-core/oteapi-core or . if you cd into the generated folder wherein the repository has been cloned.

The --upgrade-strategy=eager part can be left out. We recommend installing within a dedicated virtual environment.

To test the installation, you can run:

cd /path/to/oteapi-core
pytest

If you run into issues at this stage, please open an issue.

License

OTEAPI Core is released under the MIT license with copyright © SINTEF.

Acknowledgment

OTEAPI Core has been supported by the following projects:

• OntoTrans (2020-2024) that receives funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement no. 862136.

• VIPCOAT (2021-2025) receives funding from the European Union’s Horizon 2020 Research and Innovation Programme - DT-NMBP-11-2020 Open Innovation Platform for Materials Modelling, under Grant Agreement no: 952903.

• OpenModel (2021-2025) receives funding from the European Union’s Horizon 2020 Research and Innovation Programme - DT-NMBP-11-2020 Open Innovation Platform for Materials Modelling, under Grant Agreement no: 953167.