API Definition¶

App Kernel Engine¶

Bootstraps and manages the FastAPI application. Initialises MongoDB, registers models as REST services, sets up security and locale middleware, and starts the Uvicorn server.

Example:

from appkernel import AppKernelEngine, Model, MongoRepository
from typing import Annotated
from appkernel import Required, Generator, create_uuid_generator

class User(Model, MongoRepository):
    id: Annotated[str | None, Required(), Generator(create_uuid_generator('U'))] = None
    name: Annotated[str | None, Required()] = None

kernel = AppKernelEngine('my-service')
kernel.register(User, methods=['GET', 'POST', 'PUT', 'DELETE'])
kernel.run()

class appkernel.AppKernelEngine(app_id: str, app: FastAPI | None = None, root_url: str = '/', log_level: int = 10, cfg_dir: str | None = None, development: bool = False, enable_defaults: bool = True, http_client_config: HttpClientConfig | None = None)¶

enable_cors(cfg: CorsConfig | None = None) → AppKernelEngine¶

Enable CORS support for browser-based cross-origin clients.

Installs Starlette’s CORSMiddleware with the provided configuration. Call this last in the middleware chain — middleware added last executes first, so CORS headers are set and preflight OPTIONS requests are resolved before security or rate-limiting checks run.

Parameters:: cfg – CORS configuration. Defaults to CorsConfig() (empty allow_origins list — same-origin only).
Raises:: ValueError – If allow_origins=['*'] and allow_credentials=True are combined (rejected by browsers).

Example:

kernel = AppKernelEngine('my-app', cfg_dir='./config')
kernel.enable_security()
kernel.enable_rate_limiting()
kernel.enable_cors(CorsConfig(
    allow_origins=['https://app.example.com'],
    allow_credentials=False,
))

Returns:: self for fluent chaining.

enable_file_storage(backend: Any = None, validation_chain: Any = None, url_base: str = '/files', tags: list[str] | None = None) → AppKernelEngine¶

Register streaming file upload, download, and delete endpoints.

Instantiates a FileService and mounts it at url_base. Four routes are added:

POST {url_base}/ — upload (multipart/form-data)
GET {url_base}/{file_id} — metadata JSON
GET {url_base}/{file_id}/content — binary download (streaming)
DELETE {url_base}/{file_id} — delete file + metadata

Parameters:

backend – A StorageBackend instance. Defaults to FilesystemBackend writing to a ./uploads directory.
validation_chain – Head of a FileValidator chain, or None to skip validation.
url_base – URL prefix for the four routes. Defaults to '/files'.
tags – OpenAPI tags applied to all file routes.

Returns:

self for fluent chaining.

Example:

from appkernel import AppKernelEngine
from appkernel.file_storage import (
    FilesystemBackend, SizeValidator, MimeTypeValidator,
)

kernel = AppKernelEngine('my-app', cfg_dir='./config')

chain = SizeValidator(max_bytes=10 * 1024 * 1024)
chain.set_next(MimeTypeValidator(['image/jpeg', 'image/png']))

kernel.enable_file_storage(
    backend=FilesystemBackend('/var/uploads'),
    validation_chain=chain,
    url_base='/files',
)

enable_openapi(title: str | None = None, version: str = '1.0.0', description: str = '', include_docs: bool = True) → AppKernelEngine¶

Register /openapi.json and optionally /docs and /redoc endpoints.

Must be called after all services have been registered so the service registry is fully populated when the spec is first requested.

Parameters:

title – API title shown in the spec and UI. Defaults to app_id.
version – Semantic version string for info.version.
description – Optional API-level description shown in the UI.
include_docs – When True (default), also register Swagger UI at /docs and ReDoc at /redoc.

Returns:

self for fluent chaining.

Example:

kernel = AppKernelEngine('my-app', cfg_dir='./config')
kernel.register(User, methods=['GET', 'POST', 'PUT', 'DELETE'])
kernel.enable_openapi(title='My API', version='2.0.0')

enable_rate_limiting(cfg: RateLimitConfig | None = None) → AppKernelEngine¶

Enable in-process fixed-window rate limiting.

Call this after enable_security() so that the rate-limit middleware is added last and therefore executes first — throttling requests before JWT validation is attempted.

Parameters:: cfg – Pool and window settings. Defaults to RateLimitConfig() (medium-traffic profile: 100 req / 60 s per client IP).
Returns:: self for fluent chaining.

Example:

from appkernel import AppKernelEngine, RateLimitConfig

kernel = AppKernelEngine('my-app', cfg_dir='./config')
kernel.enable_security()
kernel.enable_rate_limiting(
    RateLimitConfig(
        requests_per_window=100,
        window_seconds=60,
        endpoint_limits={'/auth': 10},
        exclude_paths=['/health'],
    )
)

register(service_class_or_instance: type | object, url_base: str | None = None, methods: list[str] | None = None, enable_hateoas: bool = True, tags: list[str] | None = None) → ResourceController¶

Register a Model class or service instance as a set of REST endpoints.

Parameters:

service_class_or_instance – A Model subclass for automatic CRUD, or a plain service instance decorated with @resource / @action methods.
url_base – URL prefix for all generated routes (e.g. '/v1/'). Defaults to the engine’s root_url.
methods – HTTP methods to expose for CRUD models (e.g. ['GET', 'POST', 'PUT', 'PATCH', 'DELETE']). Defaults to ['GET'].
enable_hateoas – Include _links in responses. Defaults to True.
tags –
OpenAPI tag strings applied to every endpoint registered for this service. Merged with per-decorator tags (registration tags come first, decorator tags appended). Useful for grouping all endpoints of a version together:
```
kernel.register(UserV1Service(), url_base='/v1/', tags=['v1'])
kernel.register(UserV2Service(), url_base='/v2/', tags=['v2'])
```

Returns:

ResourceController for fluent RBAC chaining.

Model¶

The base class for all domain objects. Provides JSON serialisation, metadata generation, validation, and list manipulation helpers. Extend with MongoRepository or AuditableRepository for persistence.

class appkernel.Model(**kwargs: Any)¶

The base class of all Model objects which are intended to be persisted in the database or served via REST. Built on Pydantic BaseModel.

Returns a copy of the model.

!!! warning “Deprecated”: This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

include – Optional set or mapping specifying which fields to include in the copied model.
exclude – Optional set or mapping specifying which fields to exclude in the copied model.
update – Optional dictionary of field-value pairs to override field values in the copied model.
deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

finalise_and_validate() → None¶: Runs generators, defaults, converters, and validators. Called before persistence (save/to_dict).

model_config = {'arbitrary_types_allowed': True, 'extra': 'allow', 'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self¶

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note: model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

_fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.
values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

model_copy(*, update: Mapping[str, Any] | None = None, deep: bool = False) → Self¶

!!! abstract “Usage Documentation”: [model_copy](../concepts/models.md#model-copy)

Returns a copy of the model.

!!! note: The underlying instance’s [__dict__][object.__dict__] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

update – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.
deep – Set to True to make a deep copy of the model.

Returns:

New model instance.

!!! abstract “Usage Documentation”: [model_dump](../concepts/serialization.md#python-mode)

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

mode – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.
include – A set of fields to include in the output.
exclude – A set of fields to exclude from the output.
context – Additional context to pass to the serializer.
by_alias – Whether to use the field’s alias in the dictionary key if defined.
exclude_unset – Whether to exclude fields that have not been explicitly set.
exclude_defaults – Whether to exclude fields that are set to their default value.
exclude_none – Whether to exclude fields that have a value of None.
exclude_computed_fields – Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.
round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
fallback – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A dictionary representation of the model.

!!! abstract “Usage Documentation”: [model_dump_json](../concepts/serialization.md#json-mode)

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

indent – Indentation to use in the JSON output. If None is passed, the output will be compact.
ensure_ascii – If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.
include – Field(s) to include in the JSON output.
exclude – Field(s) to exclude from the JSON output.
context – Additional context to pass to the serializer.
by_alias – Whether to serialize using field aliases.
exclude_unset – Whether to exclude fields that have not been explicitly set.
exclude_defaults – Whether to exclude fields that are set to their default value.
exclude_none – Whether to exclude fields that have a value of None.
exclude_computed_fields – Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.
round_trip – If True, dumped values should be valid as input for non-idempotent types such as Json[T].
warnings – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
fallback – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.
serialize_as_any – Whether to serialize fields with duck-typing serialization behavior.

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None¶

Get extra fields set during validation.

Returns:: A dictionary of extra fields, or None if config.extra is not set to “allow”.

property model_fields_set: set[str]¶

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,: i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias: bool = True, ref_template: str = '#/$defs/{model}', schema_generator: type[GenerateJsonSchema] = <class 'pydantic.json_schema.GenerateJsonSchema'>, mode: Literal['validation', 'serialization']='validation', *, union_format: Literal['any_of', 'primitive_type_array']='any_of') → dict[str, Any]¶

Generates a JSON schema for a model class.

Parameters:

by_alias – Whether to use attribute aliases or not.
ref_template – The reference template.
union_format –
The format to use when combining schemas from unions together. Can be one of:
- ’any_of’: Use the [anyOf](https://json-schema.org/understanding-json-schema/reference/combining#anyOf)
keyword to combine schemas (the default). - ‘primitive_type_array’: Use the [type](https://json-schema.org/understanding-json-schema/reference/type) keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.
schema_generator – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications
mode – The mode in which to generate the schema.

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params: tuple[type[Any], ...]) → str¶

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:: params – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.
Returns:: String representing the new class where params are passed to cls as type variables.
Raises:: TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(context: Any, /) → None¶: Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: MappingNamespace | None = None) → bool | None¶

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

force – Whether to force the rebuilding of the model schema, defaults to False.
raise_errors – Whether to raise errors, defaults to True.
_parent_namespace_depth – The depth level of the parent namespace, defaults to 2.
_types_namespace – The types namespace, defaults to None.

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

Validate a pydantic model instance.

Parameters:

obj – The object to validate.
strict – Whether to enforce types strictly.
extra – Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
from_attributes – Whether to extract data from object attributes.
context – Additional context to pass to the validator.
by_alias – Whether to use the field’s alias when validating against the provided input data.
by_name – Whether to use the field’s name when validating against the provided input data.

Raises:

ValidationError – If the object could not be validated.

Returns:

The validated model instance.

!!! abstract “Usage Documentation”: [JSON Parsing](../concepts/json.md#json-parsing)

Validate the given JSON data against the Pydantic model.

Parameters:

json_data – The JSON data to validate.
strict – Whether to enforce types strictly.
extra – Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
context – Extra variables to pass to the validator.
by_alias – Whether to use the field’s alias when validating against the provided input data.
by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

Validate the given object with string data against the Pydantic model.

Parameters:

obj – The object containing string data to validate.
strict – Whether to enforce types strictly.
extra – Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.
context – Extra variables to pass to the validator.
by_alias – Whether to use the field’s alias when validating against the provided input data.
by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

update(**kwargs: Any) → Model¶

Set one or more attributes and return self for method chaining.

Parameters:: **kwargs – attribute names and values to set on this instance.
Returns:: This Model instance, enabling fluent calls like user.update(name='John').update(password='secret').

Field Metadata¶

Fields are declared using Python’s typing.Annotated with one or more metadata markers. All fields should default to None — the deferred validation pattern runs validation explicitly via finalise_and_validate() or implicitly via save() / dumps().

Example:

from typing import Annotated
from pydantic import Field
from appkernel import Required, Generator, Converter, Default, Validators, Marshal
from appkernel import MongoIndex, MongoUniqueIndex, MongoTextIndex
from appkernel import create_uuid_generator, content_hasher, Email, NotEmpty

class User(Model, MongoRepository):
    id: Annotated[str | None, Required(), Generator(create_uuid_generator('U'))] = None
    name: Annotated[str | None, Required(), MongoUniqueIndex()] = None
    email: Annotated[str | None, Validators(Email), MongoUniqueIndex()] = None
    password: Annotated[str | None, Validators(NotEmpty), Converter(content_hasher()), Field(exclude=True)] = None

Required marker¶

class appkernel.Required¶: Marks a field as required. Checked by finalise_and_validate().

Generator marker¶

class appkernel.Generator(func: Callable)¶: Auto-generate field value when None at validation time.

Converter marker¶

class appkernel.Converter(func: Callable)¶: Convert field value during finalise_and_validate().

Default marker¶

class appkernel.Default(value: Any)¶: Default value applied when field is None at validation time.

Validators marker¶

class appkernel.Validators(*validators)¶: List of AppKernel Validator instances for validation and parameter spec.

Marshal marker¶

class appkernel.Marshal(marshaller: Any)¶: Bidirectional wire-format converter (Marshaller class or instance).

MongoDB index markers¶

class appkernel.MongoIndex(sort_order: SortOrder = SortOrder.ASC)¶: Regular MongoDB index on a field.

class appkernel.MongoUniqueIndex(sort_order: SortOrder = SortOrder.ASC)¶: Unique constraint index.

class appkernel.MongoTextIndex(sort_order: SortOrder = SortOrder.ASC)¶: Full-text search index.

Validators¶

The base Validator class¶

class appkernel.Validator(validator_type: ValidatorType, value: Any = None, message: str | None = None)¶

a root object for different type of validators

__init__(validator_type: ValidatorType, value: Any = None, message: str | None = None) → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Not Empty¶

class appkernel.NotEmpty¶

Used for string types to make sure that there’s a string with length longer than 0. Also checks lists for a size.

__init__() → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Regular Expression¶

class appkernel.Regexp(regexp: str)¶

__init__(regexp: str) → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Email¶

class appkernel.Email¶

It is a convenience validator extending the Regexp validator and initialising it with an e-mail regular expression.

__init__() → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Minimum¶

class appkernel.Min(minimum: int | float)¶

__init__(minimum: int | float) → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Maximum¶

class appkernel.Max(maximum: int | float)¶

__init__(maximum: int | float) → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Past¶

class appkernel.Past¶

__init__() → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Future¶

class appkernel.Future¶

__init__() → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Unique¶

class appkernel.Unique¶

__init__() → None¶

validate(parameter_name: str, validable_object: Any) → None¶

Validates and object against the validation parameters.

Parameters:

parameter_name
validable_object

Raises:

ValidationException –

Generators¶

UUID Generator¶

appkernel.create_uuid_generator(prefix: str | None = None) → Callable[[], str]¶

Date generator¶

appkernel.date_now_generator() → datetime¶

Password hasher¶

appkernel.content_hasher(rounds: int = 12) → Callable[[str], str]¶

Repository¶

class appkernel.Repository¶

Query¶

class appkernel.Query(*expressions: Expression)¶

a class representing the query

__init__(*expressions: Expression) → None¶

MongoRepository¶

class appkernel.MongoRepository¶

async classmethod aggregate(pipe: list[dict[str, Any]] = [], allow_disk_use: bool = True, batch_size: int = 100, max_results: int | None = 10000, trusted: bool = False) → list[dict[str, Any]]¶

Run an aggregation pipeline.

Parameters:

pipe – Aggregation stages. When called over HTTP (trusted=False), only stages in _HTTP_ALLOWED_STAGES are permitted. Cross-collection stages ($lookup, $graphLookup, $unionWith) and write/JS stages are always blocked from HTTP.
trusted – Set to True for internal application code that constructs the pipeline itself. Bypasses the HTTP stage allowlist while still blocking $out, $merge, $function, and $accumulator.
max_results – Caps the result set by appending a $limit stage. Pass None to disable for pipelines with a bounded result (e.g. those already containing $limit or $count).

classmethod stream_by_query(query: dict[str, Any], batch_size: int = 500) → AsyncGenerator[Model, None]¶: Async generator that streams all matching documents in batches without loading the full result set into memory. Use for bulk processing, exports, and migrations where create_cursor_by_query’s page limit is not appropriate.

Auditable Repository¶

class appkernel.AuditableRepository(**kwargs: Any)¶

MongoQuery¶

class appkernel.MongoQuery(connection_object: AsyncIOMotorCollection, user_class: type, *expressions: Expression)¶

__init__(connection_object: AsyncIOMotorCollection, user_class: type, *expressions: Expression) → None¶

API Definition¶

App Kernel Engine¶

Model¶

Field Metadata¶

Required marker¶

Generator marker¶

Converter marker¶

Default marker¶

Validators marker¶

Marshal marker¶

MongoDB index markers¶

Validators¶

The base Validator class¶

Not Empty¶

Regular Expression¶

Email¶

Minimum¶

Maximum¶

Past¶

Future¶

Unique¶

Generators¶

UUID Generator¶

Date generator¶

Password hasher¶

Repository¶

Query¶

MongoRepository¶

Auditable Repository¶

MongoQuery¶

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