sqlalchemy-tx-context 1.0.1

Context-local session manager for SQLAlchemy AsyncSession

SQLAlchemy Transaction Context

Minimalistic context-local session and transaction controller for SQLAlchemy AsyncSession.

sqlalchemy-tx-context provides context-aware session and transaction management using Python’s contextvars, eliminating the need to pass AsyncSession objects explicitly. Especially useful in code where database access should be decoupled from explicit session passing - such as service layers or background jobs.

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Features

• Context-local session management via contextvars, without relying on thread-locals or global session objects.
• Clean async with API for managing session and transaction scopes.
• Supports safe nesting of transactions.
• .execute(...) automatically creates a session or transaction if none is active (optional fallback).
• Explicit control over how sessions are scoped and reused.

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Installation

pip install sqlalchemy-tx-context

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Quick Example

from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy_tx_context import SQLAlchemyTransactionContext

engine = create_async_engine("postgresql+asyncpg://user:pass@host/db")

db = SQLAlchemyTransactionContext(engine)

async def create_user():
    async with db.transaction():
        await db.execute(insert(User).values(name="John"))

async def get_users():
    async with db.session():
        result = await db.execute(select(User))
        return result.scalars().all()

API Reference

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Constructor

SQLAlchemyTransactionContext(
    engine: AsyncEngine,
    *,
    default_session_maker: Optional[async_sessionmaker[AsyncSession]] = None,
    auto_context_on_execute: bool = False,
    auto_context_force_transaction: bool = False,
)

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Parameters:

• engine - SQLAlchemy AsyncEngine instance.
• default_session_maker - Optional async session factory. If omitted, uses async_sessionmaker(engine).
• auto_context_on_execute - If True, allows .execute() to run even without an active session by creating a temporary one.
• auto_context_force_transaction - If True, .execute() always runs inside a transaction when auto context is used. If False, it uses .session() for read-only queries (like Select or CompoundSelect), and .transaction() for everything else, including Insert, Update, and raw SQL.

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Session Methods:

• session(...) -> AsyncIterator[AsyncSession] - Enter a new session context, or reuse an existing one if reuse_if_exists=True.
• transaction(...) -> AsyncIterator[AsyncSession] - Enter a transactional context. Will nest if a transaction is already active.
• new_session(...) -> AsyncIterator[AsyncSession] - Create a new isolated session, even if another is already active. Overrides the context for the duration.
• new_transaction(...) -> AsyncIterator[AsyncSession] - Create a new transaction in an isolated session.
• get_session(strict: bool = True) -> AsyncSession | None - Return the current session from context. Raises NoSessionError if strict=True and no session exists.
• execute(...) -> Result - Execute a SQLAlchemy Executable using the current or temporary context. Uses the current session if one is active. Otherwise, behavior depends on auto_context_on_execute - a new session or transaction context may be created automatically.

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Auto-context Example

# Opens a temporary session or transaction depending on statement type
db = SQLAlchemyTransactionContext(engine, auto_context_on_execute=True)

await db.execute(insert(User).values(name="Alice"))
await db.execute(select(User))

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Full Example

For a complete working example using PostgreSQL, see example/. It demonstrates table creation, data insertion, transactional rollback, and querying.

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Exceptions

This library defines a few custom exceptions to help catch context-related mistakes:

• NoSessionError: Raised when attempting to access or use a session when none is active and fallback is disabled.
• SessionAlreadyActiveError: Raised when entering .session() while a session is already active (unless reuse_if_exists=True).
• TransactionAlreadyActiveError: Raised when entering .transaction() while a transaction is already active and nesting is disabled.

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Motivation

SQLAlchemy does not provide an out-of-the-box solution for context-local session tracking when working with AsyncSession. Passing sessions around explicitly can make service-layer code verbose and harder to maintain.

The library introduces a lightweight and predictable abstraction that:

• Stores current session in a ContextVar.
• Provides safe transactional/session boundaries.
• Exposes a unified execute(...) interface.
• Integrates with standard SQLAlchemy models, statements, and engines.

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When should you use this?

• You're writing service-layer logic and want to avoid passing session explicitly.
• You need nested transactional logic with clean context boundaries.
• You prefer explicit context management over dependency-injected sessions.
• You work with context-local transaction boundaries in background tasks or microservices.
• You need precise control over session lifecycle and scope.

This library is best suited for functional or script-style code where sessions are not injected via DI frameworks.

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Best Practices

• Use .transaction() or .session() explicitly in your service-layer or job code to clearly define execution boundaries.
• .execute(...) is ideal for small projects, functional-style code, or early-stage prototypes - it avoids boilerplate and makes code fast to write.
• As your project grows, you can gradually migrate to DI-based session and transaction management: just replace db.execute(...) with self._session.execute(...) and db.transaction() with your own context (e.g., UnitOfWork, session.begin()) - the query logic remains the same.
• This makes the library especially useful for bootstrapping or background scripts, where a full-blown DI setup would be overkill.

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Tests

pytest --cov=sqlalchemy_tx_context --cov-report=term-missing

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Compatibility

Tested on Python 3.9 - 3.12.

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License

MIT License