cognyx-bom-sdk 0.4.3

Cognyx BOM SDK

Cognyx Automation SDK

This repo contains a Cognyx' python BOM SDK. This library allows you to interact with the Cognyx BOM API when writing BOM automations in Cognyx.

Setup

Prerequisites

• Python 3.11.11
• uv package manager

Installation

Install uv if you don't have it already:

pip install uv

Install the package:

uv install .

For development, install with development dependencies:

uv install -e ".[dev]"

Tooling

This project uses uv for tooling. Dependencies are declared in pyproject.toml.

Run the following commands for development tasks:

# Run tests
uv run test
uv run coverage

# Run linting
uv run lint

# Run formatting
uv run format_code

# Run type checking
uv run typecheck

Architecture

The repo uses ADR (Architecture Decision Record). These can be found in the doc folder. The ADRs explain the philosophy of the project, and how it is supposed to be used.

The main usage of this SDK is to expose functions helping Cognyx users to write BOM automations. These run in a pyodide sandbox. The package exposes one main API to interact with a given Cognyx BOM, which data is passed when initializing the main Bom class. This class then provides a list of methods which are loaded as globals in the pyodide sandbox.

API Documentation

BomClient

The BomClient class is the main entry point for interacting with the Cognyx BOM API.

Initialization

When using the SDK in Cognyx automations, the initialization is already taken care of and is not needed. You will directly get an instance of the BomClient to interact with the selected bom. This section is provided for integration in other python projects.

from cognyx_bom_sdk.client import BomClient

# Initialize with BOM data

def process_update(update: dict) -> None:
    # ... implement update handling

client = BomClient(bom_data, update_callback=process_update)

• bom_data: The complete BOM data as a dictionary
• update_callback: Callback function that will be called with updates to apply to the BOM

Methods

get_bom_instance(name: str) -> BomInstance | None

Get a BOM instance by name.

instance = client.get_bom_instance("instance_name")

get_bom_instance_by_id(instance_id: str) -> BomInstance | None

Get a BOM instance by ID.

instance = client.get_bom_instance_by_id("instance_id")

find_bom_instance(predicate: Callable[[BomInstance], bool]) -> BomInstance | None

Find a BOM instance using a predicate function.

# Find an instance with a specific attribute value
instance = client.find_bom_instance(lambda i: i.name == "instance_name")

list_bom_instances() -> list[BomInstance]

List all BOM instances.

instances = client.list_bom_instances()

get_instance_attribute(instance_id: str, attribute_name: str) -> str | int | float | bool | dict | list | None

Get an attribute value from a BOM instance.

value = client.get_instance_attribute("instance_id", "attribute_name")

set_instance_attribute(instance_id: str, attribute_name: str, value: str | int | float | bool | dict | list | None) -> None

Set an attribute value on a BOM instance.

client.set_instance_attribute("instance_id", "attribute_name", "new_value")

update_bom_instance(instance_id: str, **kwargs) -> None

Update multiple attributes of a BOM instance.

client.update_bom_instance("instance_id", status="active", priority=1)

Models

The SDK provides a set of Pydantic models that represent the data structures used in the Cognyx BOM system.

Enums

BomUpdates

Enum for different types of BOM updates.

from cognyx_bom_sdk.models import BomUpdates

# Available values
BomUpdates.INSTANCE_UPDATE  # "instance_update"
BomUpdates.ATTRIBUTE_UPDATE  # "attribute_update"

BomReadinessStatus

Enum for different types of BOM readiness statuses.

from cognyx_bom_sdk.models import BomReadinessStatus

# Available values
BomReadinessStatus.NOT_STARTED  # "not_started"
BomReadinessStatus.IN_PROGRESS  # "in_progress"
BomReadinessStatus.DONE  # "done"

BomInstanceSystemStatus

Enum for different types of BOM instance system statuses.

from cognyx_bom_sdk.models import BomInstanceSystemStatus

# Available values
BomInstanceSystemStatus.IS_OPTIONAL  # "is_optional"
BomInstanceSystemStatus.HAS_VARIANTS  # "has_variants"
BomInstanceSystemStatus.HAS_WARNING_NO_VARIABILITY  # "has_warning_no_variability"
BomInstanceSystemStatus.IS_STANDARD  # "is_standard"

Core Models

Attribute

Represents an attribute in the Cognyx system.

from cognyx_bom_sdk.models import Attribute

attribute = Attribute(
    id="attr_id",
    name="attr_name",
    description="attr_description",
    value="attr_value"
)

Key fields:

• id: Unique identifier for the attribute
• name: Name of the attribute
• description: Description of the attribute
• value: Value of the attribute (can be any type)
• options: Available options for the attribute (if applicable)

ObjectType

Represents an object type in the Cognyx system.

from cognyx_bom_sdk.models import ObjectType

object_type = ObjectType(
    id="type_id",
    name="type_name",
    description="type_description",
    slug="type_slug",
    base_unit="unit",
    display_name="display_name",
    bom_attributes=[...],  # List of Attribute objects
    catalog_attributes=[...],  # List of Attribute objects
)

Key methods:

• get_attribute_id(attribute_name: str) -> str | None: Get an attribute ID by name

BomInstance

Represents a BOM instance in the Cognyx system.

from cognyx_bom_sdk.models import BomInstance

instance = BomInstance(
    id="instance_id",
    name="instance_name",
    description="instance_description",
    bom_id="bom_id",
    view_id="view_id",
    parent_id="parent_id",
    reference="reference",
    status="status",
    object_type=object_type,  # ObjectType instance
    object_type_id="object_type_id",
    quantity=1,
    custom_attributes=[...],  # List of Attribute objects
    variability_configurations=[...],  # List of VariabilityConfiguration objects
)

Key methods:

• get_attribute(attribute_name: str) -> Any: Get an attribute value by name
• set_attribute(attribute_name: str, value: Any) -> None: Set an attribute value
• set_property(property_name: str, value: str | int) -> None: Set a property value
• is_optional() -> bool: Check if the instance is optional
• has_variants() -> bool: Check if the instance has variants
• is_standard() -> bool: Check if the instance is standard
• has_warning_no_variability() -> bool: Check if the instance has a warning due to no variability

Bom

Represents a complete BOM with all its instances.

from cognyx_bom_sdk.models import Bom

bom = Bom(
    id="bom_id",
    name="bom_name",
    reference="reference",
    description="description",
    status="status",
    instances=[...],  # List of BomInstance objects
)

Key methods:

• get_instance(name: str) -> BomInstance | None: Get a BOM instance by name
• get_instance_by_id(instance_id: str) -> BomInstance | None: Get a BOM instance by ID

VariabilityConfiguration

Represents a configuration for a BOM instance.

from cognyx_bom_sdk.models import VariabilityConfiguration

config = VariabilityConfiguration(
    id="config_id",
    variability_id="variability_id",
    variability=diversity,  # Diversity instance
    object_id="object_id",
    object=object,  # Object instance
)

Update Models

BomInstanceUpdate

TypedDict for BomInstance update properties.

from cognyx_bom_sdk.models import BomInstanceUpdate

update: BomInstanceUpdate = {
    "name": "new_name",
    "description": "new_description",
    "quantity": 2,
}

UpdatePayload

TypedDict for update payload with discriminated union pattern.

from cognyx_bom_sdk.models import UpdatePayload, BomUpdates, AttributeUpdatePayload

update_payload: UpdatePayload = {
    "type": BomUpdates.ATTRIBUTE_UPDATE,
    "payload": {
        "instance_id": "instance_id",
        "attribute_id": "attribute_id",
        "attribute_value": "new_value",
    },
}

Project Guidelines

• Always write semantic, modern and performant Python code, with type hints and inline documentation
• Always define Models when relevant instead of relying on abstract List & dictionaries. These should be exposed by the library to help the consumers of the SDK
• All code should be correctly formatted and linted using ruff. Functions should be tested
• Try to use as little dependencies as possible to keep it lightweight and safe to integrate in the pyodide sandbox
• When writing tests on existing code, avoid changing the existing code to pass your test. Instead, modify the test so that it passes

CI/CD

This project uses GitHub Actions for CI/CD. It automatically tests, lints, and publishes the package.