SQLBuild

Verify early. Test properly. Deploy reversibly. SQL pipelines with the rigor of real software.

Valid isn't the same as correct. Your SQL compiles, runs, and returns rows; none of that means the number is right, and a silently-wrong number a stakeholder already trusted is the bug that actually hurts.

SQLBuild brings software-engineering rigor to SQL pipelines: catch errors before the warehouse runs them, test your logic locally, and opt into change-aware execution when you need it. It is a standalone, open-source framework for building SQL and Python data pipelines.

All state is persisted as append-only tables in the warehouse alongside your data: no external state database, no manifest files, no paid add-on. Start with straightforward SQL models, then add ingestion, Python nodes, and opt-in virtual environments as your project grows.

Key features

  • Test your logic, not just your columns. Multi-model SQL tests resolve every intermediate model from its real SQL, plus end-to-end scenarios with local DuckDB replay for fast CI with no warehouse. Catch wrong logic before it ships, not just nulls.
  • Verify early. Define models as SQL files with MODEL() headers. SQLBuild resolves references, validates SQL, infers columns, checks contracts, and computes column lineage before anything runs, all offline. It fails at compile, not halfway through a warehouse run.
  • Fast and open static analysis. SQL parsing, validation, column inference, lineage, and transpilation run on Polyglot, a Rust SQL engine (MIT, 32+ dialects), so compile stays fast on large projects. The analysis is part of the Apache-2.0 core: no proprietary engine, no login, no paid tier.
  • Audits that block bad data. Audits run before data reaches the target table. Full table builds materialize into a staging table and only promote if audits pass; incremental models validate each batch before DML.
  • Deploy reversibly (opt-in). Virtual environments add instant low-copy branching, partial promotion, rollback, checkpoints, and reconciliation. Opt-in, not a tax you pay upfront.
  • Opt-in change-aware execution. Models, seeds, UDFs, and Python nodes are fingerprinted, and source freshness is tracked. In virtual environments, pass --changes-only or set changes_only = true to skip work that is already current; commands otherwise run the full selected scope.
  • Warehouse-native state. All change-tracking state lives in append-only tables (_sqlbuild_fingerprints, _sqlbuild_source_freshness, _sqlbuild_node_results) in your warehouse schemas. No external state machine, no corruption risk.
  • Cursor-based incremental processing. Automatic gap detection and resume, with microbatch mode for large ranges. No external checkpoint to maintain.
  • Ingestion and Python nodes. Load external data with Python @loader functions, and run @task, @asset, and @check nodes as first-class members of the same DAG as your SQL models.

See the documentation for the full feature set, including providers, lifecycle hooks, Python macros, UDFs, custom materializations, data diffs, zero-copy cloning, and virtual environments. To coordinate dbt and SQLBuild projects, see the dbt compatibility guide.

Quick start

pip install sqlbuild
# or
uv pip install sqlbuild

Create and run the included playground project:

sqb playground waffle-shop
cd waffle-shop
sqb plan
sqb build
sqb test

Example

A model is a SQL file with a MODEL() header and a SELECT. References use __ref() and __source(), and configuration, schema, and audits are declared inline:

MODEL (
  materialized table,
  columns (
    order_id (audits [not_null, unique]),
  ),
  tags [marts],
);

SELECT
  o.order_id,
  o.customer_id,
  p.amount_cents AS total_cents
FROM __ref("stg_orders") o
JOIN __ref("stg_payments") p USING (order_id)

A unit test mocks sources and asserts on the model, resolving every intermediate model automatically:

TEST();

WITH
__source__raw__orders AS (
  @mock_orders()
),
__source__raw__payments AS (
  SELECT
    1 AS payment_id,
    1 AS order_id,
    1500 AS amount_cents,
    'credit_card' AS method
),
__expected__fact_orders AS (
  SELECT 1 AS order_id, 100 AS customer_id, 1500 AS total_cents
)
SELECT 1

See the documentation for incremental models, scenarios, loaders, and more.

Kata SQL architecture checks

Kata is SQLBuild's opt-in, error-only SQL model shape checker. It runs offline over the compiled project, reports coded faults with remediations, and never rewrites SQL. Its built-in lifecycle is native: Rust resolves rule policy, parses each model, evaluates built-ins, applies suppressions, and owns the persistent cache and deterministic result ordering.

Kata is disabled until the project selects at least one rule. Select the complete built-in policy in sqlbuild_project.toml with its namespace prefix:

[kata]
select = ["SQBK"]

SQBK activates every built-in rule. Narrower prefixes such as SQBKS activate one family, exact codes select individual rules, and ignore removes matching rules. Audit, unit-test, and custom-rule test-case minimums each default to one and can be overridden under [kata.thresholds].

Kata also keeps model ownership shallow and explicit. Configured level paths separate warehouse layers from domain ownership; every owner is a leaf or a branch, subdomain depth defaults to one, and declaration roles remain bounded flat-or-grouped containers:

[kata.layout]
levels = ["staging", "intermediate/clean", "intermediate/enriched", "mart"]
domain_roots = ["market/betfair", "model/horsenet/ratings"] # optional disambiguation

[kata.thresholds]
max_subdomain_depth = 1
min_shared_owner_prefix_directories = 2

Run sqb kata, inspect metadata with sqb kata rule SQBKS101, and generate agent guidance from the same active ruleset with sqb kata skills. Use sqb kata skills --check in CI to detect stale guidance. --json, --select, and --exclude are available for automation and model scoping.

Repository rules use the public API:

from sqlbuild.kata import RuleContext, kata


@kata(
    code="XSQBKP001",
    family="prices",
    slug="typed-currency",
    message="price models must declare a currency column",
    remediation="Declare currency in the MODEL columns contract at this model path.",
)
def typed_currency(*, model, ctx: RuleContext):
    return [] if any(column.name == "currency" for column in ctx.declared_columns) else [
        ctx.path_fault()
    ]

Load repository-owned files through rule_paths = ["kata/rules"] or dotted packages through rule_modules. Test each custom rule with RuleCase and evaluate_rule. Selecting custom rules disables caching unless [kata.cache] require_cacheable = true; cacheable rules may import only the supported pure modules and must access project files through RuleContext.

Python is used only for the SQLBuild compiler adapter and selected custom rules. Built-in-only runs cross into the native engine once as a compiled model batch and do not materialize or walk Python AST objects. A selected custom rule can still use the public RuleContext and raw Polyglot AST escape hatch; its findings rejoin native suppression, ordering, and cache policy.

Exact rule_exceptions require a rule, file, and reason and fail when stale. Broader rule_ignores and lone-star allowances also require reasons but are intentionally not stale-checked.

Supported adapters

Adapter Status
DuckDB Supported
MotherDuck Supported
Snowflake Supported
BigQuery Supported
Databricks Supported
PostgreSQL Supported
SQL Server Supported

ClickHouse, Redshift, Trino, Spark, and Athena are on the way.

Snowflake cost estimates

Native Snowflake builds automatically show a compact per-run busy-compute estimate. SQLBuild attributes visible overlapping query intervals fairly across active queries, converts attributed seconds using the warehouse-size credit rate, and estimates USD from the configured rate:

[cost]
usd_per_credit = 3.00

The default is 3.00 USD per credit and is visibly marked as a default. Configure the value with your Snowflake contract rate. Use sqb cost, sqb cost latest, sqb cost <run_id>, or sqb cost history --since 7d to inspect persisted records. --json and --json-output PATH provide a versioned, decimal-safe output contract. Pending detail records are refreshed from Snowflake when inspected again.

These values are attributed compute credits and estimated cost, not Snowflake-billed credits or invoice reconciliation. The estimate uses only query history visible to the executing role and does not reconstruct invisible concurrent work, warehouse resume or idle tail, the 60-second minimum, cloud-services credits, contract adjustments, or multi-cluster billing. Run metadata and query IDs are stored under target/runs/<run_id>/; that statement ledger stores only an SQL digest, not SQL text. Executed SQL artifacts are stored separately under the sensitive target/run/ tree.

Documentation

Full documentation is available at docs.sqlbuild.com.

Runtime operator and extension contracts:

Contributing

We welcome contributions. Please see CONTRIBUTING.md for guidelines.

License

SQLBuild is licensed under the Apache License 2.0.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.83.2)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for kvlonge from gravatar.com kvlonge

Requires

Python >=3.12

Provides Extra

bigquery dagster databricks dbt dlt ingestr postgres rivers snowflake sqlserver

Report project as malware

Download files

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

Source Distribution

sqlbuild-0.76.3.tar.gz (1.4 MB view details)

Uploaded Source

Built Distributions

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

sqlbuild-0.76.3-cp312-abi3-win_amd64.whl (5.5 MB view details)

Uploaded CPython 3.12+Windows x86-64

sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.8 MB view details)

Uploaded CPython 3.12+manylinux: glibc 2.17+ x86-64

sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (5.7 MB view details)

Uploaded CPython 3.12+manylinux: glibc 2.17+ ARM64

sqlbuild-0.76.3-cp312-abi3-macosx_11_0_arm64.whl (5.4 MB view details)

Uploaded CPython 3.12+macOS 11.0+ ARM64

sqlbuild-0.76.3-cp312-abi3-macosx_10_12_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.12+macOS 10.12+ x86-64

File details

Details for the file sqlbuild-0.76.3.tar.gz.

File metadata

  • Download URL: sqlbuild-0.76.3.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for sqlbuild-0.76.3.tar.gz
Algorithm Hash digest
SHA256 a504e28ddcd1adfd6b39beffa4465287c4e807dc2c304fc68698b5bccc3a565e
MD5 e9c3313f1e63a15a3410476ae93285ce
BLAKE2b-256 74afcea279d2925ae7a145a56824112b1be33e2d2b5ac82000507fc5f05e0e4f

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlbuild-0.76.3.tar.gz:

Publisher: publish.yml on chio-labs/sqlbuild

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sqlbuild-0.76.3-cp312-abi3-win_amd64.whl.

File metadata

  • Download URL: sqlbuild-0.76.3-cp312-abi3-win_amd64.whl
  • Upload date:
  • Size: 5.5 MB
  • Tags: CPython 3.12+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for sqlbuild-0.76.3-cp312-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 9bc5480d8876efea75ed119e999ad3b488def2d997a7171739b3a6a665f554a4
MD5 1077e4bc12ad2534cd6efbe37e82662e
BLAKE2b-256 60a53ef5df908324ef9e39fbf98b8e465cffc9009b49f3332f4b84db87108b70

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlbuild-0.76.3-cp312-abi3-win_amd64.whl:

Publisher: publish.yml on chio-labs/sqlbuild

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3ff08ed152a82fac8db4ec29b94bccc59762600d3c6f9b68bf7d22c84a7e7ed9
MD5 fcf77d92aa589839cb14883abdde0fce
BLAKE2b-256 743c1c7fb17260795d686fd20ecc134fec9d324c90940db5af951c8d3e0622ea

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: publish.yml on chio-labs/sqlbuild

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 11e6762b3850a95382b811349c4c2de5c096ec7f4baf9476e16d339e40aac2ea
MD5 1676f08912ec4006571db647d2928313
BLAKE2b-256 bfcd385f12f0ed31c5f464e29e377bcca9bb47e8820edd0c0ad8e9662140b8b8

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlbuild-0.76.3-cp312-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl:

Publisher: publish.yml on chio-labs/sqlbuild

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sqlbuild-0.76.3-cp312-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for sqlbuild-0.76.3-cp312-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1032cf63a109ca86f568829dd501f160dd46b2be5f3f056e73951ffc75652b9c
MD5 f50dbb8641301c649894982d7cf377de
BLAKE2b-256 1ca372d0e3951964653b07781d2fdb3c93cdd9645edab6a4e6f7123b895b17a6

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlbuild-0.76.3-cp312-abi3-macosx_11_0_arm64.whl:

Publisher: publish.yml on chio-labs/sqlbuild

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sqlbuild-0.76.3-cp312-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for sqlbuild-0.76.3-cp312-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 0add13f7367c5e222d82aee0a2ca0e5a68cd7ea46d1d6c46938ee67197720fa4
MD5 8a3a1fcb08763044de010db0a41d8dec
BLAKE2b-256 cef0f94778161184de3815f353203d9b0f8c7759ba0f30de02403a41ba33c0aa

See more details on using hashes here.

Provenance

The following attestation bundles were made for sqlbuild-0.76.3-cp312-abi3-macosx_10_12_x86_64.whl:

Publisher: publish.yml on chio-labs/sqlbuild

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.83.2

6 files

0.83.1

6 files

0.83.0

6 files

0.82.6

6 files

0.82.5

6 files

0.82.4

6 files

0.82.3

6 files

0.82.2

6 files

0.82.1

6 files

0.82.0

6 files

0.81.2

6 files

0.81.1

6 files

0.81.0

6 files

0.80.2

6 files

0.80.1

6 files

0.80.0

6 files

0.79.0

6 files

0.78.0

6 files

0.77.2

6 files

0.77.1

6 files

0.77.0

6 files

0.76.9

6 files

0.76.8

6 files

0.76.7

6 files

0.76.6

6 files

0.76.5

6 files

0.76.4

6 files

This release

0.76.3 This release

6 files

0.76.2

6 files

0.76.1

6 files

0.76.0

6 files

0.75.1

6 files

0.75.0

6 files

0.74.4

6 files

0.74.3

6 files

0.74.2

6 files

0.74.1

6 files

0.74.0

6 files

0.73.0

6 files

0.72.2

6 files

0.72.1

6 files

0.72.0

6 files

0.71.6

6 files

0.71.5

6 files

0.71.4

6 files

0.71.3

6 files

0.71.2

6 files

0.71.1

6 files

0.71.0

6 files

0.70.0

6 files

0.69.0

6 files

0.68.0

6 files

0.67.2

6 files

0.67.1

6 files

0.67.0

6 files

0.66.6

6 files

0.66.5

6 files

0.66.4

6 files

0.66.3

6 files

0.66.2

6 files

0.66.1

6 files

0.66.0

6 files

0.65.6

6 files

0.65.5

6 files

0.65.4

6 files

0.65.3

6 files

0.65.2

6 files

0.65.1

6 files

0.65.0

6 files

0.64.0

6 files

0.63.8

6 files

0.63.7

6 files

0.63.6

6 files

0.63.5

6 files

0.63.4

6 files

0.63.3

6 files

0.63.2

6 files

0.63.1

6 files

0.63.0

6 files

0.62.2

6 files

0.62.1

6 files

0.62.0

6 files

0.61.0

6 files

0.60.0

6 files

0.59.0

6 files

0.58.0

6 files

0.57.0

6 files

0.56.2

6 files

0.56.1

6 files

0.56.0

6 files

0.55.9

6 files

0.55.8

6 files

0.55.7

6 files

0.55.6

6 files

0.55.5

6 files

0.55.4

6 files

0.55.3

6 files

0.55.2

6 files

0.55.1

6 files

0.55.0

6 files

0.54.2

6 files

0.54.1

6 files

0.54.0

5 files

0.53.0

2 files

0.52.0

2 files

0.51.0

2 files

0.50.0

2 files

0.49.0

2 files

0.48.7

2 files

0.48.6

2 files

0.48.5

2 files

0.48.4

2 files

0.48.3

2 files

0.48.2

2 files

0.48.1

2 files

0.48.0

2 files

0.47.0

2 files

0.46.0

2 files

0.45.5

2 files

0.45.4

2 files

0.45.3

2 files

0.45.2

2 files

0.45.1

2 files

0.45.0

2 files

0.44.4

2 files

0.41.1

2 files

0.41.0

2 files

Yanked

0.40.1

2 files

Yanked reason: Just a shitty release

Yanked

0.40.0

2 files

Yanked reason: shitty release

0.39.3

2 files

0.39.2

2 files

0.39.1

2 files

0.39.0

2 files

0.38.6

2 files

0.38.5

2 files

0.38.4

2 files

0.38.3

2 files

0.38.2

2 files

0.38.1

2 files

0.38.0

2 files

0.37.7

2 files

0.37.6

2 files

0.37.5

2 files

0.37.4

2 files

0.37.3

2 files

0.37.2

2 files

0.37.1

2 files

0.36.0

2 files

0.35.0

2 files

0.34.0

2 files

0.33.0

2 files

0.32.0

2 files

0.31.0

2 files

0.30.1

2 files

0.30.0

2 files

0.29.0

2 files

0.28.1

2 files

0.28.0

2 files

0.27.0

2 files

0.26.2

2 files

0.26.1

2 files

0.26.0

2 files

0.25.1

2 files

0.25.0

2 files

0.24.0

2 files

0.23.0

2 files

0.22.1

2 files

0.22.0

2 files

0.21.0

2 files

0.20.1

2 files

0.20.0

2 files

0.19.0

2 files

0.18.0

2 files

0.16.2

2 files

0.16.1

2 files

0.15.0

2 files

0.14.0

2 files

0.13.0

2 files

0.12.0

2 files

0.10.0

2 files

0.9.0

2 files

0.8.0

2 files

0.7.0

2 files

0.4.0

2 files

0.3.0

2 files

0.2.1

2 files

0.2.0

2 files

0.0.1

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page