Skip to main content

A Python parser for Blacklab Corpus Query Language

Project description

A Python parser for BlackLab Corpus Query Language

Documentation codecov License PyPI - Python Version

A full-coverage Python parser for the BlackLab Corpus Query Language (BCQL) that converts query strings into a Pydantic v2 AST (Abstract Syntax Tree) with lossless round-trip reconstruction and structured error reporting.

To get started, you can check out:

Features

  • Complete BCQL coverage: token queries, sequences, repetitions, spans, lookarounds, captures, global constraints, relations, alignments, and built-in functions.
  • Immutable Pydantic v2 AST: every node is a frozen BaseModel subclass with a node_type discriminator, making inspection and pattern matching straightforward.
  • Lossless BCQL round-trip: to_bcql() reproduces the original query (preserving shorthand forms, quote characters, sensitivity flags, etc.).
  • Position-aware syntax errors: BCQLSyntaxError carries the original query, the 0-based offset, and a caret-annotated message: ready to forward to a user or LLM.
  • Optional semantic validation: a CorpusSpec describes which annotations, span tags, alignment fields, and dependency relations your corpus supports. Pass it as parse(query, spec=spec) to catch typos and unsupported features before they reach the corpus. See the tagset validation guide.
  • Zero runtime dependencies beyond Pydantic.

Installation

pip install bcql_py

Or with uv:

uv add bcql_py

Try the demo

A small Gradio app under app/ lets you paste a BCQL query, pick or build a CorpusSpec, and inspect parse + validation results. The hosted demo runs on Hugging Face Spaces at BramVanroy/bcql_py_validation.

To run it locally:

uv sync --group app
uv run python app/app.py

Supported BCQL constructs

Category Examples
Token queries [word="man"], "man", [], [pos != "noun"]
Regex & literal strings "(wo)?man", l"e.g.", "(?-i)Panama"
Boolean constraints [lemma="search" & pos="noun"], [a="x" | b="y"]
Sequences "the" "tall" "man"
Repetitions [pos="ADJ"]+, []{2,5}, "word"?
Spans <s/>, <s>, </s>, <ne type="PERS"/>
Position filters "baker" within <person/>, <s/> containing "dog"
Captures A:[pos="ADJ"], A:[] "by" B:[] :: A.word = B.word
Relations _ -obj-> _, _ -subj-> _ ; -obj-> _, ^--> "have"
Alignments "cat" ==>nl _, "cat" ==>nl? _
Lookaround (?= "next"), (?<= "prev"), (?! "not")
Functions meet(...), rspan(...), rfield(...)

See the cheatsheet for a quick-reference table of every operator.

Development

git clone https://github.com/BramVanroy/bcql_py.git
cd bcql_py
uv sync

# Run tests and doctests
uv run pytest

# Lint and format
make quality   # check only
make style     # auto-fix

ANTLR to generate the needed tools

BlackLab uses ANTLR to generate the parser/lexer in Java based on a g4 file. We could similarly generate Python files. However, after trying it out, I find the files obfuscated and unclear and I'm not fond of requiring an extra external (Java-based) library. That is not a slight to ANTLR; I am simply not familiar with the tool: I am sure it is incredibly powerful and useful if you know how to use it. To keep a clearer view of this library I therefore strive to make a Python-native implementation that is true to spec. It's also just a fun project that I do not wish to "automate away" (though I might regret that later). At a later time (TODO) I might implement functionality to cross-validate our implementation with the generated ANTLR parser and lexer. For now I will be satisfied with high coverage testing. In case of doubt I have followed the Bcql.g4 file.

If you'd like to try the ANTLR route yourself, you can try it as follows:

  1. Install requirements (not included in our pyproject.toml file, you'll need to download these yourself!)

    uv pip install requests antlr4-tools antlr4-python3-runtime
    
  2. Download the BlackLab G4 definition from GitHub. You can optionally specify a --branch or --tag, defaults to --branch dev.

    uv run python scripts/get_bcql_g4.py
    # Saved to parser/Bcql.g4
    cd parser/
    
  3. Run ANTLR (you can update -v to the latest version if needed)

    antlr4 -v 4.13.2 -Dlanguage=Python3 Bcql.g4
    

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

bcql_py-0.1.6.tar.gz (232.6 kB view details)

Uploaded Source

Built Distribution

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

bcql_py-0.1.6-py3-none-any.whl (61.0 kB view details)

Uploaded Python 3

File details

Details for the file bcql_py-0.1.6.tar.gz.

File metadata

  • Download URL: bcql_py-0.1.6.tar.gz
  • Upload date:
  • Size: 232.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.8 {"installer":{"name":"uv","version":"0.11.8","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for bcql_py-0.1.6.tar.gz
Algorithm Hash digest
SHA256 b03aead7885d0db34763fdb9d65df390dd2ba6ab1dd22c6372dd21466c4ace46
MD5 897ec94196167333a591169a03417d46
BLAKE2b-256 05903792ffb74ed0752fd748fb936ed20e0e838ff3767506052b4abe37aa8634

See more details on using hashes here.

File details

Details for the file bcql_py-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: bcql_py-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 61.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.8 {"installer":{"name":"uv","version":"0.11.8","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for bcql_py-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 ee505a082c6ca8f4b6c9e519f8fd71793c2b66032a3f2c7b8946477d73b7c550
MD5 1b1a47e08eb1b07ebd2b09abd4198119
BLAKE2b-256 c861dafd60a5c022c075d918a39b1eac491c50b7e8512c9d3255144f128b376f

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