worker.py

# -*- coding: utf-8 -*-
import argparse
import json
import logging
import os
import sys
import uuid
from enum import Enum

from apistar.exceptions import ErrorResponse

from arkindex import ArkindexClient, options_from_env
from arkindex_worker import logger
from arkindex_worker.models import Element
from arkindex_worker.reporting import Reporter


class BaseWorker(object):
    def __init__(self, description="Arkindex Base Worker"):
        self.parser = argparse.ArgumentParser(description=description)

        # Setup workdir either in Ponos environment or on host's home
        if os.environ.get("PONOS_DATA"):
            self.work_dir = os.path.join(os.environ["PONOS_DATA"], "current")
        else:
            # We use the official XDG convention to store file for developers
            # https://specifications.freedesktop.org/basedir-spec/basedir-spec-latest.html
            xdg_data_home = os.environ.get(
                "XDG_DATA_HOME", os.path.expanduser("~/.local/share")
            )
            self.work_dir = os.path.join(xdg_data_home, "arkindex")
            os.makedirs(self.work_dir, exist_ok=True)

        self.worker_version_id = os.environ.get("WORKER_VERSION_ID")
        if not self.worker_version_id:
            raise Exception(
                "Missing WORKER_VERSION_ID environment variable to start the Worker"
            )

        logger.info(f"Worker will use {self.work_dir} as working directory")

    def configure(self):
        """
        Configure worker using cli args and environment variables
        """
        self.parser.add_argument(
            "-v",
            "--verbose",
            help="Display more information on events and errors",
            action="store_true",
            default=False,
        )

        # Call potential extra arguments
        self.add_arguments()

        # CLI args are stored on the instance so that implementations can access them
        self.args = self.parser.parse_args()

        # Setup logging level
        if self.args.verbose:
            logger.setLevel(logging.DEBUG)
            logger.debug("Debug output enabled")

        # Build Arkindex API client from environment variables
        self.api_client = ArkindexClient(**options_from_env())
        logger.debug(f"Setup Arkindex API client on {self.api_client.document.url}")

    def add_arguments(self):
        """Override this method to add argparse argument to this worker"""

    def run(self):
        """Override this method to implement your own process"""


class TranscriptionType(Enum):
    Page = "page"
    Paragraph = "paragraph"
    Line = "line"
    Word = "word"
    Character = "character"


class EntityType(Enum):
    Person = "person"
    Location = "location"
    Subject = "subject"
    Organization = "organization"
    Misc = "misc"
    Number = "number"
    Date = "date"


class ElementsWorker(BaseWorker):
    def __init__(self, description="Arkindex Elements Worker"):
        super().__init__(description)

        # Add report concerning elements
        self.report = Reporter("unknown worker")

        # Add mandatory argument to process elements
        self.parser.add_argument(
            "--elements-list",
            help="JSON elements list to use",
            type=open,
            default=os.environ.get("TASK_ELEMENTS"),
        )
        self.parser.add_argument(
            "--element",
            type=uuid.UUID,
            nargs="+",
            help="One or more Arkindex element ID",
        )

    def list_elements(self):
        assert not (
            self.args.elements_list and self.args.element
        ), "elements-list and element CLI args shouldn't be both set"
        out = []

        # Process elements from JSON file
        if self.args.elements_list:
            data = json.load(self.args.elements_list)
            assert isinstance(data, list), "Elements list must be a list"
            assert len(data), "No elements in elements list"
            out += list(filter(None, [element.get("id") for element in data]))
        # Add any extra element from CLI
        elif self.args.element:
            out += self.args.element

        return out

    def run(self):
        """
        Process every elements from the provided list
        """
        self.configure()

        # List all elements either from JSON file
        # or direct list of elements on CLI
        elements = self.list_elements()
        if not elements:
            logger.warning("No elements to process, stopping.")
            sys.exit(1)

        # Process every element
        count = len(elements)
        failed = 0
        for i, element_id in enumerate(elements, start=1):
            try:
                # Load element using Arkindex API
                element = Element(
                    **self.api_client.request("RetrieveElement", id=element_id)
                )
                logger.info(f"Processing {element} ({i}/{count})")
                self.process_element(element)
            except ErrorResponse as e:
                failed += 1
                logger.warning(
                    f"An API error occurred while processing element {element_id}: {e.title} - {e.content}",
                    exc_info=e if self.args.verbose else None,
                )
                self.report.error(element_id, e)
            except Exception as e:
                failed += 1
                logger.warning(
                    f"Failed running worker on element {element_id}: {e}",
                    exc_info=e if self.args.verbose else None,
                )
                self.report.error(element_id, e)

        # Save report as local artifact
        self.report.save(os.path.join(self.work_dir, "ml_report.json"))

        if failed:
            logger.error(
                "Ran on {} elements: {} completed, {} failed".format(
                    count, count - failed, failed
                )
            )
            if failed >= count:  # Everything failed!
                sys.exit(1)

    def process_element(self, element):
        """Override this method to analyze an Arkindex element from the provided list"""

    def create_sub_element(self, element, type, name, polygon):
        """
        Create a child element on the given element through API
        """
        assert element and isinstance(
            element, Element
        ), "element shouldn't be null and should be of type Element"
        assert type and isinstance(
            type, str
        ), "type shouldn't be null and should be of type str"
        assert name and isinstance(
            name, str
        ), "name shouldn't be null and should be of type str"
        assert polygon and isinstance(
            polygon, list
        ), "polygon shouldn't be null and should be of type list"
        assert len(polygon) >= 3, "polygon should have at least three points"
        assert all(
            isinstance(point, list) and len(point) == 2 for point in polygon
        ), "polygon points should be lists of two items"
        assert all(
            isinstance(coord, (int, float)) for point in polygon for coord in point
        ), "polygon points should be lists of two numbers"

        self.api_client.request(
            "CreateElement",
            body={
                "type": type,
                "name": name,
                "image": element.zone.image.id,
                "corpus": element.corpus.id,
                "polygon": polygon,
                "parent": element.id,
                "worker_version": self.worker_version_id,
            },
        )
        self.report.add_element(element.id, type)

    def create_transcription(self, element, text, type, score):
        """
        Create a transcription on the given element through API
        """
        assert element and isinstance(
            element, Element
        ), "element shouldn't be null and should be of type Element"
        assert type and isinstance(
            type, TranscriptionType
        ), "type shouldn't be null and should be of type TranscriptionType"
        assert text and isinstance(
            text, str
        ), "text shouldn't be null and should be of type str"
        assert (
            score and isinstance(score, float) and 0 <= score <= 1
        ), "score shouldn't be null and should be a float in [0..1] range"

        self.api_client.request(
            "CreateTranscription",
            id=element.id,
            body={
                "text": text,
                "type": type.value,
                "worker_version": self.worker_version_id,
                "score": score,
            },
        )
        self.report.add_transcription(element.id, type.value)

    def create_classification(
        self, element, ml_class, confidence, high_confidence=False
    ):
        """
        Create a classification on the given element through API
        """
        assert element and isinstance(
            element, Element
        ), "element shouldn't be null and should be of type Element"
        assert ml_class and isinstance(
            ml_class, str
        ), "ml_class shouldn't be null and should be of type str"
        assert (
            confidence and isinstance(confidence, float) and 0 <= confidence <= 1
        ), "confidence shouldn't be null and should be a float in [0..1] range"
        assert high_confidence and isinstance(
            high_confidence, bool
        ), "high_confidence shouldn't be null and should be of type bool"

        self.api_client.request(
            "CreateClassification",
            body={
                "element": element.id,
                "ml_class": ml_class,
                "worker_version": self.worker_version_id,
                "confidence": confidence,
                "high_confidence": high_confidence,
            },
        )
        self.report.add_classification(element.id, ml_class)

    def create_entity(self, element, name, type, corpus, metas=None, validated=None):
        """
        Create an entity on the given corpus through API
        """
        assert element and isinstance(
            element, Element
        ), "element shouldn't be null and should be of type Element"
        assert name and isinstance(
            name, str
        ), "name shouldn't be null and should be of type str"
        assert type and isinstance(
            type, EntityType
        ), "type shouldn't be null and should be of type EntityType"
        assert corpus and isinstance(
            corpus, str
        ), "corpus shouldn't be null and should be of type str"
        if metas:
            assert isinstance(metas, dict), "metas should be of type dict"
        if validated:
            assert isinstance(validated, bool), "validated should be of type bool"

        entity = self.api_client.request(
            "CreateEntity",
            body={
                "name": name,
                "type": type.value,
                "metas": metas,
                "validated": validated,
                "corpus": corpus,
                "worker_version": self.worker_version_id,
            },
        )
        self.report.add_entity(element.id, entity["id"], type.value, name)