in-layers-core 0.4.20

The Python port of Node in Layers Core.

In Layers Core

Python port of the Node-in-Layers core framework. Supports Domains, config and layers loading, and cross-layer logging.

Key points:

• Domains explicitly provided in config (no convention discovery)
• Layers are loaded in configured order (supports composite layers)
• Cross-layer logging with automatic id propagation and function wraps

Pecularities, Limitations, and Recommendations

No Keyword Arguments for Layer level Functions

For the public functions for a given layer, the arguments cannot use kwargs. The reason behind this is it creates a consistent interface to allow the framework and other tools to work.

We recommend making arguments an object (class instance, dict), and making the last argument a "cross_layer_props" object, that can pass along across layers.

Contributing

Running Unit Tests

poetry run pytest --cov=. --cov-report=term-missing --cov-report=html -q

Auto-Cleaning / Checking Tools

./bin/lint.sh

Publishing

./bin/deploy.sh

Models and Persistence Backends

Overview

• Models are standard Pydantic classes decorated with @model(domain=..., plural_name=...).
• When a domain’s services layer is loaded, the framework discovers the domain’s models and exposes them as SimpleModel wrappers under:
  • context.models.<domain>.get_models() -> Box, keyed by the model’s plural name
  • Example access: context.models.mydomain.get_models().MyModels
• Each entry in this mapping is a SimpleModel wrapper with:
  • instance(data | **kwargs) to wrap raw data
  • create(data | **kwargs) to persist through a backend
  • retrieve(id), update(id, **kwargs), delete(id), search(query)
  • get_model_definition(), get_primary_key_name(), get_primary_key(data)
• A SimpleModel instance supports zero-arg getters for its data via instance.get.<field>().

Important: Persistence uses a backend returned by a model backend provider living in the services of the domain named by in_layers_core.models.model_backend. If none is provided, a core fallback uses a no-op backend (CRUD operations will raise NotImplemented).

Declaring a Model

from pydantic import BaseModel, Field
from in_layers.core.models.libs import model

@model(domain="pipeline", plural_name="PipelineJobs")
class PipelineJob(BaseModel):
    id: str = Field(...)
    name: str = Field(...)

Providing a Model Backend (via a Domain’s Services)

You must provide, in the configured domain’s services layer, a method that returns a backend for each model. The service needs a method:

• get_model_backend(model_definition) -> BackendProtocol

For example:

# services.py

class MyDomainServices:
    def __init__(self, ctx):
        self._ctx = ctx

    def get_model_backend(self, model_definition):
        # you can check the domain, the name of the model (if it is model/domain specific)
        # return your BackendProtocol implementation (e.g., Mongo, SQL, etc.)
        return MyConcreteBackend(...)


Then tell the framework which backend provider to use via config:
```python
config = Box(
    system_name="test",
    environment="test",
    in_layers_core=Box(
        logging=Box(...),
        layer_order=["services", "features"],
        domains=[...],
        models=Box(
            # Choose your model backend by telling the framework which domain it lives in.
            # The framework will call mydomain.services.get_model_backend(model_definition)
            model_backend="mydomain",
            # Optional: surface CRUD wrappers in services/features
            model_services_cruds=True,
            model_features_cruds=False,
        ),
    ),
)

Notes:

• Ensure the configured domain’s services are loaded before domains whose models you want to wrap (via domain ordering and layer_order).
• If not provided, the framework falls back to a core default provider, which uses a no-op backend (CRUD is not implemented).
• If model_features_cruds is true, model_services_cruds is implicitly treated as true and both layers expose cruds.<Plural> wrappers.

Using Models in Services

from pydantic import BaseModel
from in_layers.core.models.libs import model
# ./mydomain/models.py
@model(domain="mydomain", plural_name="MyModels")
class MyModel(BaseModel):
    id: str
    name: str

# ./mydomain/services.py
from types import SimpleNamespace

class MyServices:
    def __init__(self, ctx):
        self._ctx = ctx

    def return_a_model_instance(self):
        models = self._ctx.models.mydomain.get_models()
        MyModels = models.MyModels
        # Create a non-persisted instance via kwargs (or Mapping)
        inst = MyModels.instance(id="123", name="John Doe")
        # Access fields
        assert inst.get.id() == "123"
        assert inst.get.name() == "John Doe"
        return inst

# ./mydomain/__init__.py
from . import services, models
name = "mydomain"
__all__ = ['name', 'services', 'models']

Backends

Backends implement BackendProtocol:

• create(model, data) -> Mapping
• retrieve(model, id) -> Mapping | None
• update(model, id, data) -> Mapping
• delete(model, id) -> None
• search(model, query) -> ModelSearchResult

Your persistence factory decides which backend to return per model class (e.g., route different models to different datastores).

Instance Creation Options

• Mapping:
  • MyModels.instance({"id": "123", "name": "John"})
  • MyModels.create({"id": "123", "name": "John"})
• Keywords:
  • MyModels.instance(id="123", name="John")
  • MyModels.create(id="123", name="John")

When both are provided, keyword arguments override keys in the mapping.