Skip to main content

Python port of Google's ZetaSQL - SQL analysis and parsing library

Project description

ZetaSQL Python

Python 3.10+ License: Apache 2.0

Python port of Google's ZetaSQL - a powerful SQL analysis and parsing library.

Overview

ZetaSQL Python brings Google's SQL analyzer to the Python ecosystem, providing:

  • SQL Analysis: Parse and analyze SQL statements with full type checking
  • Name Resolution: Resolve table and column references against catalogs
  • Query Building: Construct and manipulate SQL AST programmatically
  • Expression Evaluation: Execute queries and expressions with parameter binding
  • Java-like API: Familiar builder patterns and fluent interfaces

This project is built on top of zetasql-wasi, which provides the WebAssembly build of ZetaSQL, enabling ZetaSQL functionality in Python environments.

Installation

pip install zetasql

Requirements: Python 3.10+

Quick Start

from zetasql.api import Analyzer, CatalogBuilder, TableBuilder
from zetasql.types import AnalyzerOptions, LanguageOptions, TypeKind, ZetaSQLBuiltinFunctionOptions

# Create a catalog with a table
table = (
    TableBuilder("users")
    .add_column("id", TypeKind.TYPE_INT64)
    .add_column("name", TypeKind.TYPE_STRING)
    .add_column("email", TypeKind.TYPE_STRING)
    .build()
)

# Build catalog with builtin functions
lang_opts = LanguageOptions.maximum_features()
builtin_opts = ZetaSQLBuiltinFunctionOptions(language_options=lang_opts)

catalog = (
    CatalogBuilder("mydb")
    .add_table(table)
    .with_builtin_functions(builtin_opts)
    .build()
)

# Analyze SQL
options = AnalyzerOptions(language_options=lang_opts)
analyzer = Analyzer(options, catalog)
stmt = analyzer.analyze_statement("SELECT name, email FROM users WHERE id > 100")

print(f"Analyzed {len(stmt.output_column_list)} output columns")
# Output: Analyzed 2 output columns

Key Features

🔍 SQL Analysis

Analyze SQL statements and expressions with full semantic understanding:

from zetasql.api import Analyzer

# Assuming analyzer is configured with catalog and builtin functions
stmt = analyzer.analyze_statement("SELECT * FROM users")
expr = analyzer.analyze_expression("price * quantity")

🏗️ Builder Pattern APIs

Fluent interfaces for constructing catalogs, tables, and functions:

from zetasql.api import CatalogBuilder
from zetasql.types import LanguageOptions, ZetaSQLBuiltinFunctionOptions

lang_opts = LanguageOptions.maximum_features()
builtin_opts = ZetaSQLBuiltinFunctionOptions(language_options=lang_opts)

catalog = (
    CatalogBuilder("shop")
    .add_table(orders_table)
    .add_table(products_table)
    .with_builtin_functions(builtin_opts)
    .build()
)

Query Execution

Execute queries with parameter binding and table data:

from zetasql.api import PreparedQuery, create_table_content

data = create_table_content([[1, "Alice"], [2, "Bob"]])
query = PreparedQuery("SELECT * FROM users WHERE id = @user_id", options, catalog)
result = query.execute(parameters={"user_id": 1}, table_content={"users": data})

🎯 Type-Safe Values

Create and manipulate typed SQL values:

from zetasql.api import Value

int_val = Value.int64(42)
str_val = Value.string("hello")
array_val = Value.array([Value.int64(1), Value.int64(2)])

📦 ProtoModel System

Pythonic wrappers around protobuf messages with real inheritance:

from zetasql.types import ResolvedLiteral

literal = ResolvedLiteral(...)
type_kind = literal.type.type_kind  # Direct access, no parent chain
isinstance(literal, ResolvedExpr)   # True - real inheritance!

Documentation

Development

# Clone the repository
git clone https://github.com/heoh/zetasql-py.git
cd zetasql-py

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest

# Run linter
ruff check src/ tests/

See CONTRIBUTING.md for detailed contribution guidelines.

Project Status

This project is in alpha stage. The API is functional but may change as we refine the design. Feedback and contributions are welcome!

License

Apache License 2.0 - see LICENSE file for details.

This is an unofficial Python port of Google's ZetaSQL (also Apache 2.0 licensed) and is not affiliated with Google.

Acknowledgments

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

zetasql-0.1.0.tar.gz (7.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

zetasql-0.1.0-py3-none-any.whl (7.8 MB view details)

Uploaded Python 3

File details

Details for the file zetasql-0.1.0.tar.gz.

File metadata

  • Download URL: zetasql-0.1.0.tar.gz
  • Upload date:
  • Size: 7.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for zetasql-0.1.0.tar.gz
Algorithm Hash digest
SHA256 9232e5f35c087051485c3cdf8af03a97cc90e4a610f81dd18df173a04a198fc9
MD5 a32fb35bfe98ce22548f6f118a8a47a7
BLAKE2b-256 8eef14bc398767bffb98b89133d20ef04671d82077448113442d79537e93bd97

See more details on using hashes here.

File details

Details for the file zetasql-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: zetasql-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 7.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for zetasql-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 559a9f0f7e77915c2943a811d98aea154970320ad63760388df8f7bb999a073f
MD5 604a8293d456140484eb2e6edfca79e5
BLAKE2b-256 69e2c06c2bf898ebfb78077726e5f97c8f3c3379427793477da66769cfd84a33

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page