proligent-xml-generator 1.0.0

Python library for generating Proligent™ XML files.

Proligent™ XML Generator for Python™

Python™ library for generating Proligent™ XML files. It provides a simple, structured API for building valid import files, reducing manual XML writing and ensuring consistent data formatting. These files are used to import data into Proligent™ Cloud and Proligent™ Analytics.

Tip: Refer to the Proligent™ Manufacturing Information Model to learn how to structure and map your data in Proligent™.

Proligent™ software are designed for Operations Managers, Quality Engineers, Manufacturing Engineers and Test Engineers. This easy-to-use software solution monitors test stations and provides valuable insight into your product line.

Installation instructions

First, install a compatible python version from Python.org.

Then, to install the package in your (virtual) environment, run the following command:

pip install proligent-xml-generator

Getting started

Each layer of the Proligent™ Manufacturing Information Model is represented in the package by an equivalent class. Typing hints are used to indicate what data types are accepted by the objects.

Example 1

from proligent.model import (
    DataWareHouse,
    ExecutionStatusKind,
    Limit,
    LimitExpression,
    Measure,
    OperationRun,
    ProcessRun,
    ProductUnit,
    SequenceRun,
    StepRun,
)
import datetime

if __name__ == "__main__":
    limit = Limit(
        LimitExpression.LOWERBOUND_LEQ_X_LE_HIGHER_BOUND,
        lower_bound=10,
        higher_bound=25,
    )
    measure = Measure(
        value=15,
        status=ExecutionStatusKind.PASS,
        limit=limit,
        time=datetime.datetime.now(),
    )
    step = StepRun(
        name="Step1",
        status=ExecutionStatusKind.PASS,
        measure=measure
    )

    # Create sequence run: remember to keep track of start and end time

    sequence = SequenceRun(
        name="Sequence1",
        status=ExecutionStatusKind.PASS,
        steps=[step],
    )

    # Create operation run: remember to keep track of start and end time

    operation = OperationRun(
        name="Operation1",
        station="Station/readme_example",
        status=ExecutionStatusKind.PASS,
        sequences=[sequence],
    )

    # Create process run: remember to keep track of start and end time

    process = ProcessRun(
        product_unit_identifier="DutSerialNumber",
        product_full_name="Product/readme_example",
        operations=[operation],
        name="Process/readme_example",
        process_mode="PROD",
        status=ExecutionStatusKind.PASS,
    )

    product = ProductUnit(
        product_unit_identifier="DutSerialNumber",
        product_full_name="Product/readme_example",
        manufacturer="Averna",
    )

    warehouse = DataWareHouse(top_process=process, product_unit=product)
    warehouse.save_xml()

Note: For simplicity this example omits the start and end times, so they default to datetime.now. It is highly recommended to set these values with real timestamps when used in the real world.

You can also provide the output path for the XML:

from proligent.model import DataWareHouse
warehouse = DataWareHouse()
warehouse.save_xml(destination=r'C:\path_to\Proligent_file_name.xml')

Example 2

This example shows a second way of ordering calls and constructors, from top to bottom.

from proligent.model import (
    DataWareHouse,
    ExecutionStatusKind,
    Limit,
    LimitExpression,
    Measure,
    OperationRun,
    ProcessRun,
    ProductUnit,
    SequenceRun,
    StepRun,
)
import datetime

if __name__ == "__main__":
    warehouse = DataWareHouse()

    product = warehouse.set_product_unit(
        ProductUnit(
            product_unit_identifier="UutSerialNumber",
            product_full_name="Product/readme_example",
            manufacturer="Averna",
        )
    )

    process = warehouse.set_process_run(
        ProcessRun(
            name="Process/readme_example",
            process_mode="PROD",
            product_unit_identifier="DutSerialNumber",
            product_full_name="Product/readme_example",
        )
    )

    operation = process.add_operation_run(
        OperationRun(
            name="Operation1",
            station="Station/readme_example",
        )
    )

    sequence = operation.add_sequence_run(
        SequenceRun(
            name="Sequence1",
        )
    )

    sequence.add_step_run(
        StepRun(
            name="Step1",
            status=ExecutionStatusKind.PASS,
            measure=Measure(
                value=15,
                time=datetime.datetime.now(),
                status=ExecutionStatusKind.PASS,
                limit=Limit(
                    LimitExpression.LOWERBOUND_LEQ_X_LE_HIGHER_BOUND,
                    lower_bound=10,
                    higher_bound=25,
                ),
            ),
        )
    )

    sequence.complete(status=ExecutionStatusKind.PASS)
    operation.complete(status=ExecutionStatusKind.PASS)
    process.complete(status=ExecutionStatusKind.PASS)
    warehouse.save_xml()

XML Validation

Generated XML can be validated for safety.

from proligent.xml_validate import validate_xml

# This raises an exception if the XML is invalid

validate_xml(r"C:\path_to\Proligent_file_name.xml")

# This safe call returns the status and meta-data about a failure, if any

is_valid, metadata = validate_xml_safe(r"C:\path_to\Proligent_file_name.xml")

if not is_valid:
    print(metadata.path)
    print(metadata.reason)

Configuration

A few parameters are configurable in the package through the use of the UTIL object.

• destination_dir: Specify a different destination directory for the XML files, aside from the default C:\Proligent\IntegrationService\Acquisition.
• timezone: Specify a different timezone for the provided datetimes (default is the TZ of the local machine). pytz is used for timezone handling. It provides pytz.all_timezones and pytz.common_timezones to list all possible timezones. Alternatively, you can look at this list on Wikipedia.

from src.proligent.model import UTIL

if __name__ == '__main__':
    UTIL.destination_dir = r'\\NETWORK_SHARE\Acquisition'
    UTIL.timezone = 'America/New_York'

Trademarks

Proligent is a registered trademark, and Averna is a trademark, of Averna Technologies Inc.

Python is a trademark of the Python Software Foundation.

Other product and company names mentioned herein are trademarks or trade names of their respective companies.