Request and Query Lifecycle

March 5, 2026 · View on GitHub

This page explains the normal lifecycle of an Edgy-backed request/query execution path.

If you are troubleshooting lifecycle issues, read this together with Connection Management and Troubleshooting.

What

The lifecycle is the path from:

starting the application lifecycle,
executing queries,
parsing model instances,
closing registry/database scopes cleanly.

Why

Understanding this flow helps you avoid:

repeated connection setup overhead,
DatabaseNotConnectedWarning,
schema/database context mistakes in multi-tenant and multi-db setups.

When

You usually need this model when:

integrating with ASGI lifecycle hooks,
running queries from sync code with run_sync,
debugging query behavior across schemas/databases.

How

ASGI lifecycle path

In ASGI-native applications, the registry lifecycle is attached to the app lifecycle.

{!> ../docs_src/connections/asgi.py !}

Query execution path

During request handling:

Model.query builds a QuerySet.
QuerySet methods clone/compose the query state.
Execution happens on await (all, get, create, etc.).
Rows are parsed back into model instances.
Related loading and signal hooks run where applicable.

sequenceDiagram
    participant App
    participant Registry
    participant QuerySet
    participant DB as Database
    participant Model

    App->>Registry: enter lifecycle (connect)
    App->>QuerySet: build query (Model.query...)
    QuerySet->>DB: compile + execute SQL
    DB-->>QuerySet: rows
    QuerySet-->>Model: parse rows to instances
    Model-->>App: return model objects
    App->>Registry: exit lifecycle (disconnect)

Sync lifecycle path

In sync-first code, wrap execution with with_async_env and call run_sync inside that scope.

{!> ../docs_src/connections/contextmanager.py !}

Example

For database/schema-aware querying, use:

Model.query.using(database=..., schema=...)
with_schema(...) / set_schema(...) scoped helpers

See Also