dbt-core-experimental-parser
Build analytics the way engineers build applications
Decision gist · record as of 2026-08-14
No, not for production use. This is an alpha package with unstable APIs and behavior; install only if you are actively testing dbt Core v2.0 or contributing feedback to dbt Labs. For current data transformation workflows, use the stable dbt Core v1 branch (1.latest) instead. Consider revisiting when v2.0 reaches stable release.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Python >=3.9 required.
- Alpha status means the API and on-disk formats may change before stable release; not recommended for production workflows without acceptance of breaking changes.
- High install friction: distributed as a beta tarball with no runtime dependencies listed, but requires Python >=3.9.
License · maintenance · safety
Apache-2.0 (permissive) — Apache 2.0 permissive license allows commercial and private use with attribution. Suitable for teams needing code review rights or open-source compliance.
last release 2026-08-10 (4 days) · last repo commit 2026-08-14 · 13,644 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,707,383 downloads/mo, #2,931 on PyPI
Alternatives
Verify before relying
# Install
pip install dbt-core-experimental-parser==2.0.0b1
# Import and initialize (exact usage depends on v2.0 alpha API)
import dbt_core_experimental_parser- Exact public API surface and entry points for the experimental parser module
- Whether this package is intended for direct use or as an internal dbt dependency
- Compatibility matrix with specific dbt adapters (Snowflake, BigQuery, Postgres, etc.)
- Performance benchmarks vs. dbt Core v1 on real-world projects
What it is and what it does
dbt-core-experimental-parser is the parsing component of dbt Core v2.0, a complete rewrite of the dbt framework in Rust. It handles the first phase of dbt project execution—reading and parsing dbt models, tests, and configuration files into an internal representation that the compiler and executor can work with. The package is part of dbt's shift toward performance and scalability: v2.0 aims to parse and compile projects dramatically faster than v1, especially on large codebases, while enforcing a stricter language specification to catch errors at parse time rather than runtime.
This is an alpha release, meaning the parser's behavior, APIs, and output formats are not yet stable. The broader v2.0 architecture produces Parquet artifacts (alongside JSON for backward compatibility) and is distributed as a self-contained binary with no external Python dependencies at runtime. The experimental parser package itself has no listed runtime dependencies, suggesting it may be a thin wrapper or internal module. It is intended for users willing to accept API changes and for teams evaluating the v2.0 rewrite before its stable release.
Use it for
- Evaluate dbt Core v2.0 performance on your existing dbt projects before the stable release
- Test compatibility of your dbt models and tests with the stricter v2.0 language specification
- Benchmark parse and compile times on large projects to assess v2.0 readiness for your team
- Contribute feedback to dbt Labs on the alpha parser behavior and API design
- Explore Parquet artifact output and new documentation capabilities in v2.0
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No, not for production use.
This is an alpha package with unstable APIs and behavior; install only if you are actively testing dbt Core v2.0 or contributing feedback to dbt Labs. For current data transformation workflows, use the stable dbt Core v1 branch (1.latest) instead. Consider revisiting when v2.0 reaches stable release.
Install
dbt-core-experimental-parser on PyPI
Before you install
High install friction: distributed as a beta tarball with no runtime dependencies listed, but requires Python >=3.9. Active maintenance (last commit 2026-08-14, released 2026-08-10), though alpha status means APIs and behavior may change before stable release.
Python >=3.9 required. Alpha status means the API and on-disk formats may change before stable release; not recommended for production workflows without acceptance of breaking changes.
License in practice
Apache 2.0 permissive license allows commercial and private use with attribution. Suitable for teams needing code review rights or open-source compliance.
Quickstart
# Install
pip install dbt-core-experimental-parser==2.0.0b1
# Import and initialize (exact usage depends on v2.0 alpha API)
import dbt_core_experimental_parserVerify before relying
- Exact public API surface and entry points for the experimental parser module
- Whether this package is intended for direct use or as an internal dbt dependency
- Compatibility matrix with specific dbt adapters (Snowflake, BigQuery, Postgres, etc.)
- Performance benchmarks vs. dbt Core v1 on real-world projects
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,707,383 / month, #2,931 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: RustTopic :: Software Development :: Build Tools |
Evidence: dbt_core_experimental_parser-2.0.0b1.tar.gz
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “dbt core v2 parser”
- dbt-core-experimental-parserExperimental parser for dbt Core v2.0 (alpha), a ground-up Rust…
- dbt-artifacts-parserParses dbt artifact JSON files (catalog, manifest, run-results,…
- collate-dbt-artifacts-parserParses dbt artifact JSON files (catalog, manifest, run-results,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Build Tools packages
Provides reusable utilities for Python packaging interoperability, including version handling, specifiers, markers, requirements, tags, and metadata parsing according to standards like PEP 440 and PEP 425.
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
pip is the standard installer for Python packages, enabling you to download and install packages from the Python Package Index and other indexes into your Python environment.
Hatchling is a standards-compliant Python build backend that handles packaging, metadata, and distribution of Python projects when configured in a project's pyproject.toml file.
Generates Python gRPC service stubs and message classes from Protocol Buffer definitions, enabling developers to build gRPC clients and servers.
pre-commit is a framework for installing and running git hooks written in any language before commits are made, automating code quality and validation checks across multi-language projects.
Install it if your team needs consistent, automated validation at commit time.
See also dbt-core · dbt-core-interface · dbt-autofix · dbt · dbt-snowflake · dbt-fusion-package-tools · dbt-extractor · dbt-dremio · dbt-mcp · dbt-loom