Tigrbl 🐅🐂

A high-leverage ASGI meta-framework that turns plain SQLAlchemy models into a fully-featured REST+RPC surface with near-zero boilerplate. 🚀

Features ✨

⚡ Zero-boilerplate CRUD for SQLAlchemy models
🔌 Unified REST and RPC endpoints from a single definition
🪝 Hookable phase system for deep customization
🧩 Pluggable engine and provider abstractions
🚀 Built as an ASGI-native framework with Pydantic-powered schema generation

Terminology 📚

Tenant 🏢 – a namespace used to group related resources.
Principal 👤 – an owner of resources, such as an individual user or an organization.
Resource 📦 – a logical collection of data or functionality exposed by the API.
Engine ⚙️ – the database connection and transaction manager backing a resource.
Model / Table 🧱 – the ORM or database representation of a resource's records.
Column 📏 – a field on a model that maps to a table column.
Operation 🛠️ – a verb-driven action executed against a resource.
Hook 🪝 – a callback that runs during a phase to customize behavior.
Phase ⏱️ – a step in the request lifecycle where hooks may run.
Verb 🔤 – the canonical name of an operation such as create or read.
Runtime 🧠 – orchestrates phases and hooks while processing a request.
Kernel 🧩 – the core dispatcher invoked by the runtime to handle operations.
Schema 🧬 – the structured shape of request or response data.
Request 📥 – inbound data and context provided to an operation.
Response 📤 – outbound result returned after an operation completes.

Built-in Verbs 🧰

Tigrbl exposes a canonical set of operations that surface as both REST and RPC endpoints. The table below summarizes the default REST routes, RPC methods, arity, and the expected input and output shapes for each verb. {resource} stands for the collection path and {id} is the primary key placeholder.

Verb	REST route	RPC method	Arity	Input type	Output type
`create` ➕	`POST /{resource}`	`Model.create`	collection	dict	dict
`read` 🔍	`GET /{resource}/__/{id}`	`Model.read`	member	–	dict
`update` ✏️	`PATCH /{resource}/__/{id}`	`Model.update`	member	dict	dict
`replace` ♻️	`PUT /{resource}/__/{id}`	`Model.replace`	member	dict	dict
`merge` 🧬	`PATCH /{resource}/__/{id}`	`Model.merge`	member	dict	dict
`delete` 🗑️	`DELETE /{resource}/__/{id}`	`Model.delete`	member	–	dict
`list` 📃	`GET /{resource}`	`Model.list`	collection	dict	array
`clear` 🧹	`DELETE /{resource}`	`Model.clear`	collection	dict	dict
`bulk_create` 📦➕	`POST /{resource}`	`Model.bulk_create`	collection	array	array
`bulk_update` 📦✏️	`PATCH /{resource}`	`Model.bulk_update`	collection	array	array
`bulk_replace` 📦♻️	`PUT /{resource}`	`Model.bulk_replace`	collection	array	array
`bulk_merge` 📦🧬	`PATCH /{resource}`	`Model.bulk_merge`	collection	array	array
`bulk_delete` 📦🗑️	`DELETE /{resource}`	`Model.bulk_delete`	collection	dict	dict
`bulk_read` –	–	–	–	–	–

Update, Merge, and Replace 🔄

update applies a shallow PATCH: only the supplied fields change and missing fields are left untouched. merge performs a deep merge with upsert semantics—if the target row is absent it is created, and nested mapping fields are merged rather than replaced. replace follows PUT semantics, overwriting the entire record and nulling any omitted attributes.

Verb Overrides 🧭

Because create and bulk_create share the same collection POST route, enabling bulk_create removes the REST create endpoint; the Model.create RPC method remains available. Likewise, bulk_delete supersedes clear by claiming the collection DELETE route. Only one of each conflicting pair can be exposed at a time. Other verbs coexist without conflict because they operate on distinct paths or HTTP methods.

Phase Lifecycle ⛓️

Tigrbl operations execute through a fixed sequence of phases. Hook chains can attach handlers at any phase to customize behavior or enforce policy.

Phase	Description
`PRE_TX_BEGIN` ⏳	Pre-transaction checks before a database session is used.
`START_TX` 🚦	Open a new transaction when one is not already active.
`PRE_HANDLER` 🧹	Validate the request and prepare resources for the handler.
`HANDLER` ▶️	Execute the core operation logic within the transaction.
`POST_HANDLER` 🔧	Post-processing while still inside the transaction.
`PRE_COMMIT` ✅	Final verification before committing; writes are frozen.
`END_TX` 🧾	Commit and close the transaction.
`POST_COMMIT` 📌	Steps that run after commit but before the response is returned.
`POST_RESPONSE` 📮	Fire-and-forget work after the response has been sent.
`ON_ERROR` 🛑	Fallback error handler when no phase-specific chain matches.
`ON_PRE_TX_BEGIN_ERROR` 🧯	Handle errors raised during `PRE_TX_BEGIN`.
`ON_START_TX_ERROR` 🧯	Handle errors raised during `START_TX`.
`ON_PRE_HANDLER_ERROR` 🧯	Handle errors raised during `PRE_HANDLER`.
`ON_HANDLER_ERROR` 🧯	Handle errors raised during `HANDLER`.
`ON_POST_HANDLER_ERROR` 🧯	Handle errors raised during `POST_HANDLER`.
`ON_PRE_COMMIT_ERROR` 🧯	Handle errors raised during `PRE_COMMIT`.
`ON_END_TX_ERROR` 🧯	Handle errors raised during `END_TX`.
`ON_POST_COMMIT_ERROR` 🧯	Handle errors raised during `POST_COMMIT`.
`ON_POST_RESPONSE_ERROR` 🧯	Handle errors raised during `POST_RESPONSE`.
`ON_ROLLBACK` ↩️	Run when the transaction rolls back to perform cleanup.

Happy-path flow


PRE\_TX\_BEGIN
|
START\_TX
|
PRE\_HANDLER
|
HANDLER
|
POST\_HANDLER
|
PRE\_COMMIT
|
END\_TX
|
POST\_COMMIT
|
POST\_RESPONSE

If a phase raises an exception, control transfers to the matching ON_<PHASE>_ERROR chain or falls back to ON_ERROR, with ON_ROLLBACK executing when the transaction is rolled back.

Request → Response Flow Examples 🔀

REST example


Client
|
v
HTTP Request
|
v
ASGI Router
|
v
Tigrbl Runtime
|
v
Operation Handler
|
v
HTTP Response

RPC example


Client
|
v
JSON-RPC Request
|
v
RPC Dispatcher
|
v
Tigrbl Runtime
|
v
Operation Handler
|
v
JSON-RPC Response

Hooks 🪝

Hooks allow you to plug custom logic into any phase of a verb. Use the hook_ctx decorator to declare context-only hooks:

from tigrbl import Base, hook_ctx

class Item(Base):
    __tablename__ = "items"

    @hook_ctx(ops="create", phase="PRE_HANDLER")
    async def validate(cls, ctx):
        if ctx["request"].payload.get("name") == "bad":
            raise ValueError("invalid name")

The function runs during the PRE_HANDLER phase of create. The ctx mapping provides request and response objects, a database session, and values from earlier hooks.

Hooks can also be registered imperatively:

async def audit(ctx):
    ...

class Item(Base):
    __tigrbl_hooks__ = {"delete": {"POST_COMMIT": [audit]}}

Running apps expose a /system/hookz route that lists all registered hooks. 📋

Step Types 🧱

Tigrbl orders work into labeled steps that control how phases run:

secdeps 🔐 – security dependencies executed before other checks. Downstream applications declare these to enforce auth or policy.
deps 🧩 – general dependencies resolved ahead of phase handlers. Downstream code provides these to inject request context or resources.
sys 🏗️ – system steps bundled with Tigrbl that drive core behavior. Maintainers own these and downstream packages should not modify them.
atoms ⚛️ – built-in runtime units such as schema collectors or wire validators. These are maintained by the core team.
hooks 🪝 – extension points that downstream packages register to customize phase behavior.

Only secdeps, deps, and hooks are expected to be configured downstream; sys and atom steps are maintained by the Tigrbl maintainers.

Kernelz Labeling 🔎

Running apps expose a /system/kernelz diagnostics endpoint that returns the kernel's phase plan for each model and operation. Every entry is prefixed by its phase and a descriptive label, for example:

PRE_TX:secdep:myapp.auth.require_user
HANDLER:hook:wire:myapp.handlers.audit@HANDLER
END_TX:hook:sys:txn:commit@END_TX
POST_HANDLER:atom:wire:dump@POST_HANDLER

The token after the phase identifies the step type:

secdep and dep – security and general dependencies as PRE_TX:secdep:<callable> and PRE_TX:dep:<callable>.
hook:sys – built-in system hooks shipped with Tigrbl.
hook:wire – default label for user hooks including module/function name + phase.
atom:{domain}:{subject} – runtime atoms, e.g. atom:wire:dump.

These labels allow downstream services to inspect execution order and debug how work is scheduled. 🧭

Configuration Overview ⚙️

Operation Config Precedence 🧮

When merging configuration for a given operation, Tigrbl layers settings in increasing order of precedence:

defaults
app config
API config
table config
column .cfg entries
operation spec
per-request overrides

Later entries override earlier ones, so request overrides win over all other sources. This can be summarized as overrides > opspec > colspecs > tabspec > apispec > appspec > defaults.

Schema Config Precedence 🧬

Tigrbl merges schema configuration from several scopes. Later layers override earlier ones, with the precedence order:

defaults (lowest)
app configuration
API configuration
table configuration
column-level cfg values
op-specific cfg
per-request overrides (highest)

This hierarchy ensures that the most specific settings always win. 🥇

Table-Level 🧾

__tigrbl_request_extras__ – verb-scoped virtual request fields.
__tigrbl_response_extras__ – verb-scoped virtual response fields.
__tigrbl_register_hooks__ – hook registration entry point.
__tigrbl_nested_paths__ – nested REST path segments.
__tigrbl_allow_anon__ – verbs permitted without auth.
__tigrbl_owner_policy__ / __tigrbl_tenant_policy__ – server vs client field injection.
__tigrbl_verb_aliases__ & __tigrbl_verb_alias_policy__ – custom verb names.

Routing 🧭

__tigrbl_nested_paths__ for hierarchical routing.
__tigrbl_verb_aliases__ for custom verbs.
__tigrbl_verb_alias_policy__ to scope alias application.

Persistence 💾

Mixins such as Upsertable, Bootstrappable, GUIDPk, Timestamped.
Policies __tigrbl_owner_policy__ and __tigrbl_tenant_policy__.
transactional decorator for atomic RPC + REST endpoints.

Security 🔐

Pluggable AuthNProvider interface.
__tigrbl_allow_anon__ to permit anonymous access.

Default Precedence 🔧

When assembling values for persistence, defaults are resolved in this order:

Client-supplied value
API default_factory
ORM default
Database server_default
HTTP 422 if the field is required and still missing

Database Guards 🛡️

Tigrbl executes each phase under database guards that temporarily replace commit and flush on the SQLAlchemy session. Guards prevent writes or commits outside their allowed phases and only permit commits when Tigrbl owns the transaction. See the runtime documentation for the full matrix of phase policies.

The START_TX phase opens a transaction and disables session.flush, allowing validation and hooks to run before any statements hit the database. Once the transaction exists, PRE_HANDLER, HANDLER, and POST_HANDLER phases permit flushes so pending writes reach the database without committing. The workflow concludes in END_TX, which performs a final flush and commits the transaction when the runtime owns it. ✅

Response and Template Specs 📑

Customize outbound responses with ResponseSpec and TemplateSpec. These dataclasses control headers, status codes, and optional template rendering. See tigrbl/v3/response/README.md for field descriptions and examples.

Dependencies 📦

SQLAlchemy for ORM integration.
Pydantic for schema generation.
ASGI-native routing and dependency injection.

Best Design Practices ✅

The following practices are the canonical, production-ready patterns for building on Tigrbl. Each rule is explained and demonstrated with approved usage. These are not optional—adhering to them keeps the runtime predictable, preserves hook lifecycle guarantees, and ensures schema consistency across REST and RPC surfaces.

1) Never import SQLAlchemy directly or bypass Tigrbl APIs

Why: Direct imports bypass Tigrbl's compatibility layer and make it harder to evolve internal dependencies. Use the Tigrbl exports so your code stays aligned with the framework’s versioned ASGI API.

✅ Preferred:

from tigrbl import Base, TigrblApp, TigrblApi
from tigrbl.types import Integer, String, Mapped
from tigrbl.types import Depends, HTTPException, Request

🚫 Avoid:

from sqlalchemy import Integer, String
from some_framework import Depends

2) Do not coerce UUIDs manually

Why: Tigrbl schemas and types already normalize UUIDs. Manual coercion creates inconsistent behavior across engines and breaks schema-level validation.

✅ Preferred:

from tigrbl.types import PgUUID, uuid4, Mapped

class Item(Table):
    __tablename__ = "items"
    id: Mapped[PgUUID] = acol(primary_key=True, default=uuid4)

🚫 Avoid:

from uuid import UUID

item_id = UUID(str(payload["id"]))

3) Use engine specs for persistence, not ad-hoc engines

Why: Engine specs make persistence declarative, testable, and compatible with engine resolution across app, API, table, and op scopes.

✅ Preferred:

from tigrbl.engine.shortcuts import engine_spec
from tigrbl.engine.decorators import engine_ctx

spec = engine_spec(kind="postgres", async_=True, host="db", name="app_db")

@engine_ctx(spec)
class App:
    ...

🚫 Avoid:

from sqlalchemy.ext.asyncio import create_async_engine

engine = create_async_engine("postgresql+asyncpg://...")

4) Never call DB session methods directly

Why: Direct calls bypass the hook lifecycle and the database guards. Use model handlers or app.<Model>.handlers.<op> so hooks, policies, and schema enforcement run consistently.

✅ Preferred:

result = await Item.handlers.create(payload, ctx=request_ctx)
# or from a Tigrbl app instance:
result = await app.Item.handlers.create(payload, ctx=request_ctx)

🚫 Avoid:

db.add(item)
await db.execute(statement)

5) Always use encapsulated payloads as inputs and outputs

Why: Tigrbl expects request/response envelopes to preserve metadata, support policy enforcement, and keep REST/RPC in lockstep.

✅ Preferred:

from tigrbl import get_schema

CreateIn = get_schema(Item, "create", "in")
CreateOut = get_schema(Item, "create", "out")

payload = CreateIn(name="Widget")
result = await Item.handlers.create(payload, ctx=request_ctx)
response = CreateOut(result=result)

🚫 Avoid:

payload = {"name": "Widget"}
result = await Item.handlers.create(payload)

6) Encapsulation must use `get_schema(...)`

Why: get_schema guarantees the envelope is aligned to the configured schema and respects schema overrides, request extras, and response extras.

✅ Preferred:

ListIn = get_schema(Item, "list", "in")
ListOut = get_schema(Item, "list", "out")

🚫 Avoid:

from pydantic import BaseModel

class ListIn(BaseModel):
    payload: dict

7) `Table` must be the first inherited class for all models

Why: Tigrbl inspects base classes for lifecycle and configuration. Putting Table first preserves deterministic MRO behavior.

✅ Preferred:

from tigrbl.orm.tables import Table
from tigrbl.orm.mixins import Timestamped

class Item(Table, Timestamped):
    __tablename__ = "items"

🚫 Avoid:

class Item(Timestamped, Table):
    __tablename__ = "items"

8) Never call `db.flush()` or `db.commit()`

Why: The hook lifecycle owns transactional boundaries. Manual flush or commit short-circuits phase guards and can corrupt the request lifecycle.

✅ Preferred:

@hook_ctx(ops="create", phase="HANDLER")
async def handler(ctx):
    await Item.handlers.create(ctx["request"].payload, ctx=ctx)

🚫 Avoid:

db.flush()
db.commit()

9) Use ops for new REST/RPC methods—never add ad-hoc framework routes

Why: Ops keep routing, schemas, hooks, and policies unified. Custom custom framework routes bypass these guarantees.

✅ Preferred:

from tigrbl import op_ctx

@op_ctx(name="rotate_keys", method="POST", path="/keys/rotate")
async def rotate_keys(payload, *, ctx):
    return await Key.handlers.rotate(payload, ctx=ctx)

🚫 Avoid:

from some_framework import APIRouter

router = APIRouter()

@router.post("/keys/rotate")
async def rotate_keys(payload):
    ...

10) Use context decorators where appropriate

Why: Context decorators (engine_ctx, schema_ctx, op_ctx, hook_ctx) provide explicit, declarative binding of behavior and are resolved deterministically by the runtime.

✅ Preferred:

from tigrbl import hook_ctx, op_ctx, schema_ctx
from tigrbl.engine.decorators import engine_ctx

@engine_ctx(kind="sqlite", mode="memory")
class Item(Table):
    __tablename__ = "items"

@schema_ctx(ops="create", cfg={"exclude": {"id"}})
class ItemCreateSchema:
    model = Item

@op_ctx(name="export", method="GET", path="/items/export")
async def export_items(payload, *, ctx):
    return await Item.handlers.list(payload, ctx=ctx)

@hook_ctx(ops="create", phase="PRE_HANDLER")
async def validate(ctx):
    ...

Engine & Provider examples 🛠️

from tigrbl.engine.shortcuts import engine_spec, prov
from tigrbl.engine._engine import Engine, Provider

# Build an EngineSpec from a DSN string
spec = engine_spec("sqlite://:memory:")

# Or from keyword arguments
spec_pg = engine_spec(kind="postgres", async_=True, host="db", name="app_db")

# Lazy Provider from the spec
provider = prov(spec)            # same as Provider(spec)
with provider.session() as session:
    session.execute("SELECT 1")

# Engine façade wrapping a Provider
eng = Engine(spec_pg)
async with eng.asession() as session:
    await session.execute("SELECT 1")

# Direct Provider construction is also supported
provider_pg = Provider(spec_pg)

Attaching engine contexts 🔌

engine_ctx binds database configuration to different layers. It accepts a DSN string, a mapping, an EngineSpec, a Provider, or an Engine. The resolver chooses the most specific binding in the order op > table > api > app.

Engine precedence 🥇

When engine contexts are declared at multiple scopes, Tigrbl resolves them with strict precedence:

Op level – bindings attached directly to an operation take highest priority.
Table/Model level – definitions on a model or table override API and app defaults.
API level – bindings on the API class apply when no model-specific context exists.
App level – the default engine supplied to the application is used last.

This ordering ensures that the most specific engine context always wins.

Declarative bindings 📝

from types import SimpleNamespace
from tigrbl.engine.shortcuts import prov, engine

app = SimpleNamespace(db=prov(kind="sqlite", mode="memory"))
alt = SimpleNamespace(db=engine(kind="sqlite", mode="memory"))

class API:
    db = {"kind": "sqlite", "memory": True}

class Item:
    __tablename__ = "items"
    table_config = {"db": {"kind": "sqlite", "memory": True}}

async def create(payload, *, db=None):
    ...

create.__tigrbl_engine_ctx__ = {
    "kind": "postgres",
    "async": True,
    "host": "db",
    "name": "op_db",
}

Decorative bindings 🎛️

from tigrbl.engine.decorators import engine_ctx
from tigrbl.engine.shortcuts import prov, engine

@engine_ctx(prov(kind="sqlite", mode="memory"))
class App:
    pass

@engine_ctx(engine(kind="sqlite", mode="memory"))
class DecoratedAPI:
    pass

@engine_ctx(kind="sqlite", mode="memory")
class DecoratedItem:
    __tablename__ = "items"

@engine_ctx(kind="postgres", async_=True, host="db", name="op_db")
async def decorated_create(payload, *, db=None):
    ...

Swarmauri class + Tigrbl lifecycle integration 🧬

If you need to run concrete Swarmauri classes inside Tigrbl's runtime, see:

The bridge examples cover two integration styles:

Factory + schema-rich envelope (swarmauri_tigrbl_bridge.py)
- Swarmauri Pydantic JSON workflows (model_validate_json, model_dump_json, model_json_schema) with HumanMessage.
- A Swarmauri Factory invocation during PRE_HANDLER via hook_ctx.
- Tigrbl default verbs (create, get, list, update, delete) plus a custom op.
- engine_ctx at model and operation scope.
- Generated OpenAPI and OpenRPC documents mounted from the same model bindings.
Smoother direct-model flow (swarmauri_tigrbl_bridge_smooth.py)
- Uses hooks + default create persistence to normalize Swarmauri payloads.
- Adds a Conversation table with a persisted one-to-many relationship to messages.
- Avoids extra json_schema fields in request/response payload contracts.
- Returns HumanMessage.model_validate_json(...) directly from a custom op.
- Uses the concrete model classes themselves to derive input/output schema docs.

Glossary 📖

Tables
Schemas
Schema Overlays (Request Extras)
Phases
Phase Lifecycle
Request
Request Ctx
Default Flush
Core
Core_Raw

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Tigrbl 🐅🐂

Features ✨

Terminology 📚

Built-in Verbs 🧰

Update, Merge, and Replace 🔄

Verb Overrides 🧭

Phase Lifecycle ⛓️

Happy-path flow

Request → Response Flow Examples 🔀

REST example

RPC example

Hooks 🪝

Step Types 🧱

Kernelz Labeling 🔎

Configuration Overview ⚙️

Operation Config Precedence 🧮

Schema Config Precedence 🧬

Table-Level 🧾

Routing 🧭

Persistence 💾

Security 🔐

Default Precedence 🔧

Database Guards 🛡️

Response and Template Specs 📑

Dependencies 📦

Best Design Practices ✅

1) Never import SQLAlchemy directly or bypass Tigrbl APIs

2) Do not coerce UUIDs manually

3) Use engine specs for persistence, not ad-hoc engines

4) Never call DB session methods directly

5) Always use encapsulated payloads as inputs and outputs

6) Encapsulation must use get_schema(...)

7) Table must be the first inherited class for all models

8) Never call db.flush() or db.commit()

9) Use ops for new REST/RPC methods—never add ad-hoc framework routes

10) Use context decorators where appropriate

Engine & Provider examples 🛠️

Attaching engine contexts 🔌

Engine precedence 🥇

Declarative bindings 📝

Decorative bindings 🎛️

Swarmauri class + Tigrbl lifecycle integration 🧬

Glossary 📖

6) Encapsulation must use `get_schema(...)`

7) `Table` must be the first inherited class for all models

8) Never call `db.flush()` or `db.commit()`