SQLSpec is a SQL execution layer for Python. You write the SQL -- as strings, through a builder API, or loaded from files. SQLSpec handles connections, parameter binding, and dialect translation. It maps results back to typed Python objects. It uses sqlglot under the hood. Queries are parsed, validated, and optimized before they hit the database.
| Area | Support |
|---|---|
| One API | The same session and result APIs with sync or async drivers. |
| Databases | PostgreSQL, SQLite, DuckDB, MySQL, SQL Server, Oracle, CockroachDB, BigQuery, Spanner, and supported Arrow Database Connectivity backends such as Snowflake, Flight SQL, and GizmoSQL. |
| Data tools | Typed result mapping, Arrow export, built-in storage, and native bulk ingest where the adapter supports it. |
| Frameworks | Litestar, FastAPI, Flask, Sanic, and Starlette. |
Quick Start
uv add sqlspec
# or
pip install sqlspec
from dataclasses import dataclass
from sqlspec import SQLSpec
from sqlspec.adapters.sqlite import SqliteConfig
@dataclass
class Greeting:
message: str
spec = SQLSpec()
db = spec.add_config(SqliteConfig(connection_config={"database": ":memory:"}))
with spec.provide_session(db) as session:
greeting = session.select_one("SELECT 'Hello, SQLSpec!' AS message", schema_type=Greeting)
print(greeting.message)
Write SQL, define a schema, get typed objects back. The getting started guide covers adapter installation and the query builder.
Features
- Session lifecycle -- sync and async sessions with pooling where the adapter supports it
- Parameter binding and dialect translation -- powered by sqlglot, with a fluent query builder and
.sqlfile loader - Result mapping -- map rows to Pydantic, msgspec, attrs, or dataclass models, or export to Arrow tables for pandas and Polars
- Storage layer -- read and write Arrow tables to local files, fsspec, or object stores
- Framework integrations -- Litestar plugin with DI, Starlette/FastAPI/Sanic middleware, Flask extension
- Google ADK -- SQLSpec-backed session, event, memory, and artifact services
- Observability -- OpenTelemetry and Prometheus instrumentation, structured logging with correlation IDs
- Event channels -- LISTEN/NOTIFY, Oracle AQ/TxEventQ, and durable table-backed queues with polling fallback
- Migrations -- native schema migration CLI backed by SQLSpec's SQL file loader
Documentation
- Getting Started -- installation, adapter selection, first steps
- Usage Guides -- adapters, configuration, SQL file loader, and more
- Recipes -- production patterns (DI, service layers, multi-tenancy)
- API Reference -- full API docs
- CLI Reference -- migration and management commands
Playground
Want to try it without installing anything? The interactive playground runs SQLSpec in your browser with a sandboxed Python runtime.
Reference Applications
- PostgreSQL + Vertex AI Demo -- Vector search with pgvector and real-time chat using Litestar and Google ADK. Shows connection pooling, migrations, type-safe result mapping, vector embeddings, and response caching.
- Oracle + Vertex AI Demo -- Oracle 23ai vector search with semantic similarity using HNSW indexes. Demonstrates NumPy array conversion, large object handling, and real-time performance metrics.
Contributing
Contributions are welcome -- whether that's bug reports, new adapter ideas, or pull requests. Take a look at the contributor guide to get started.
License
MIT
Release files for sqlspec 0.63.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sqlspec-0.63.0.tar.gz | 3.5 MB | Details |
Built distributions (wheels)
Total release size: 173.0 MB
Release files / sqlspec-0.63.0.tar.gz
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| Tags | Source |
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Transparency logRelease files / sqlspec-0.63.0-cp310-cp310-macosx_11_0_arm64.whl
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