OpenFactory Shared Schemas#

Shared Deployment Configuration Schemas for OpenFactory

This module defines reusable Pydantic models that represent container deployment settings and resource constraints. These models are intended to be shared across device and connector configuration schemas.

Components:#

  • ResourcesDefinition: Represents CPU and memory values for a container.

  • Resources: Groups reservations and limits for container resources.

  • Placement: Defines constraints for container placement on specific nodes.

  • Deploy: Complete deployment configuration including replicas, resource configs, and placement rules.

Key Features:#

  • Express CPU and memory constraints using common formats (e.g., 0.5 CPUs, “1Gi” memory)

  • Define both resource requests and limits for containers

  • Support placement constraints for scheduling on labeled nodes

  • Modular, reusable across multiple OpenFactory schema modules

Example Usage:#

Define a deployment configuration:

>>> Deploy(
...     replicas=2,
...     resources=Resources(
...         reservations=ResourcesDefinition(cpus=0.5, memory="512Mi"),
...         limits=ResourcesDefinition(cpus=1.0, memory="1Gi")
...     ),
...     placement=Placement(
...         constraints=["node.labels.zone == eu-west"]
...     )
... )

This module is typically used as part of device, connector, or application schemas that involve resource scheduling or orchestration.

class openfactory.schemas.common.Deploy(**data)[source]#

Bases: BaseModel

Defines deployment configuration such as replicas, resources, and placement.

model_config: ClassVar[ConfigDict] = {}#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

placement: Placement | None#
replicas: int | None#
resources: Resources | None#
class openfactory.schemas.common.Placement(**data)[source]#

Bases: BaseModel

Defines placement constraints for scheduling containers.

constraints: List[str] | None#
model_config: ClassVar[ConfigDict] = {}#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class openfactory.schemas.common.Resources(**data)[source]#

Bases: BaseModel

Specifies resource requests and limits for a container deployment.

limits: ResourcesDefinition | None#
model_config: ClassVar[ConfigDict] = {}#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

reservations: ResourcesDefinition | None#
class openfactory.schemas.common.ResourcesDefinition(**data)[source]#

Bases: BaseModel

Defines resource limits or reservations such as CPU and memory.

cpus: float | None#
memory: str | None#
model_config: ClassVar[ConfigDict] = {}#

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

openfactory.schemas.common.constraints(deploy)[source]#

Extract placement constraints from a Deploy object and format them for use in Python Docker deployments.

Docker Engine and Docker Swarm APIs expect placement constraints to use == for equality checks (e.g., node labels). This function transforms any single = signs in constraint expressions into the required == syntax, ensuring the constraints are correctly interpreted when creating containers or services programmatically using Python Docker clients.

Return type:

Optional[List[str]]

Parameters:

deploy (Optional[Deploy]) – The deployment configuration object.

Returns:

Optional[List[str]] – A list of constraints formatted for Docker/Docker Swarm API usage, or None if no constraints are provided.

openfactory.schemas.common.cpus_limit(deploy, default=1.0)[source]#

Retrieve the CPU limit value from a Deploy object, returning a default if unavailable.

Return type:

float

Parameters:
  • deploy (Optional[Deploy]) – The deployment configuration object.

  • default (float) – The default CPU limit value to return if not set. Defaults to 1.0.

Returns:

float – The CPU limit value from the deployment or the default if not specified.

openfactory.schemas.common.cpus_reservation(deploy, default=0.5)[source]#

Retrieve the CPU reservation value from a Deploy object, returning a default if unavailable.

Return type:

float

Parameters:
  • deploy (Optional[Deploy]) – The deployment configuration object.

  • default (float) – The default CPU reservation value to return if not set. Defaults to 0.5.

Returns:

float – The CPU reservation value from the deployment or the default if not specified.