GraphGlot

Parse, validate, transpile, and analyze graph query languages.

GraphGlot is a pure-Python toolkit for GQL (ISO/IEC 39075:2024) and Neo4j Cypher. It lets you parse queries into ASTs, transpile between dialects, validate syntax and feature compatibility, and analyze data lineage without requiring a database.

GraphGlot is pre-v1 and evolving quickly. APIs and behavior may still change as coverage and semantics expand.

Why GraphGlot?

• GQL parser — parses the GQL language defined by ISO/IEC 39075:2024, including the core language and many optional language features
• Standards-aligned feature flagging — reports which optional GQL features a query uses, following the GQL Flagger model in the standard
• Validate queries — check syntax, feature compatibility, and semantic rules before hitting the database
• Transpile between dialects — parse Neo4j Cypher and generate standard GQL, or vice versa
• 100% openCypher TCK parse rate — parses all 3,897 tracked conformance scenarios
• Track data lineage — understand how data flows from MATCH patterns to RETURN outputs
• Build tooling — power linters, formatters, migration tools, and IDE integrations with a complete AST

Playground

Try it online here.

Validation

Check if a query is valid for a specific dialect and see which GQL features it requires:

from graphglot.dialect import Dialect

neo4j = Dialect.get_or_raise("neo4j")
result = neo4j.validate("MATCH (n:Person) RETURN n.name")

print(result.success)      # True
print(result.features)     # Set of required GQL features
print(result.diagnostics)  # Semantic warnings/errors

Transpilation

Parse a query with one dialect, generate it in another:

from graphglot.dialect import Dialect

neo4j = Dialect.get_or_raise("neo4j")
gql = Dialect.get_or_raise("fullgql")  # standard GQL

# Parse Cypher, generate GQL
ast = neo4j.parse("UNWIND [1, 2, 3] AS x RETURN x")
print(gql.generate(ast[0]))
# FOR x IN [1, 2, 3] RETURN x

ast = neo4j.parse("MATCH (n)-[r:KNOWS*1..3]->(m) RETURN n, m")
print(gql.generate(ast[0]))
# MATCH (n) -[r :KNOWS]-> {1,3} (m) RETURN n, m

ast = neo4j.parse("MATCH (n) WHERE n.score ^ 2 > 100 RETURN n")
print(gql.generate(ast[0]))
# MATCH (n) WHERE POWER(n.score, 2) > 100 RETURN n

Cypher-specific syntax is automatically converted to GQL equivalents: UNWIND becomes FOR...IN, variable-length paths [*1..3] become quantifiers {1,3}, ^ becomes POWER(), and more.

Data Lineage

Track how data flows through a query — which patterns introduce which variables, what each output depends on:

from graphglot.dialect import Dialect
from graphglot.lineage import LineageAnalyzer

query = "MATCH (n:Person)-[r:KNOWS]->(m:Person) WHERE n.age > 21 RETURN n.name AS person, m.name AS friend"

neo4j = Dialect.get_or_raise("neo4j")
ast = neo4j.parse(query)

analyzer = LineageAnalyzer()
result = analyzer.analyze(ast[0], query_text=query)

for b in result.bindings.values():
    print(f"{b.name}: {b.kind.value} label_expression={b.label_expression}")
# n: node label_expression=Person
# r: edge label_expression=KNOWS
# m: node label_expression=Person

for o in result.outputs.values():
    print(f"{o.alias}: {o.id}")
# person: o_0
# friend: o_1

Export lineage as JSON or upstream summary:

gg lineage "MATCH (n:Person)-[r:KNOWS]->(m) RETURN n.name" -o json
gg lineage "MATCH (n:Person)-[r:KNOWS]->(m) RETURN n.name" -o upstream

CLI

GraphGlot ships with the gg command-line tool:

# Parse and visualize the AST
gg tree "MATCH (n:Person)-[r:KNOWS]->(m) RETURN n.name, m.name"

# Validate against a dialect
gg validate --dialect neo4j "MATCH (n:Person) RETURN n.name"

# Tokenize
gg tokenize "MATCH (n:Person) RETURN n"

# Lineage analysis
gg lineage "MATCH (n:Person)-[r:KNOWS]->(m) RETURN n.name"

# Transpile between dialects
gg transpile -r neo4j -w fullgql "MATCH (n) WITH n.age AS age RETURN age"

# Parse and display the raw AST (JSON)
gg parse "MATCH (n) RETURN n"

# Infer types
gg type "MATCH (n:Person) RETURN n.name"

# List available dialects and features
gg dialects
gg features --dialect neo4j

Supported Dialects

Dialect	Description
fullgql	Full GQL — all extension and optional features enabled
coregql	Core GQL — mandatory extension features only, no optional features
neo4j	Neo4j Cypher 2025+ — GQL subset plus Cypher extensions

The dialect system is extensible. To add a new dialect (e.g., Memgraph, Amazon Neptune), subclass Dialect or CypherDialect and declare your supported features:

from graphglot.dialect.base import Dialect
from graphglot.features import ALL_FEATURES, G002

class MyDialect(Dialect):
    SUPPORTED_FEATURES = ALL_FEATURES - {G002}
    KEYWORD_OVERRIDES = {"OFFSET": "SKIP"}

Installation

pip install graphglot

For development:

pip install -e ".[dev]"

Documentation

• Getting Started — first query, CLI tour
• Dialect Guide — the dialect system and feature validation
• Lineage Analysis — data flow tracking and export formats
• AST Overview — working with the abstract syntax tree
• Architecture — module structure and design patterns

Contributing

See CONTRIBUTING.md for guidelines. We use:

make test      # unit tests (pytest)
make pre       # linter/formatter (ruff + pre-commit)
make type      # type checking (mypy)
make neo4j     # integration tests (requires Neo4j)
make tck       # openCypher TCK conformance

Acknowledgments

GraphGlot is inspired by SQLGlot, the excellent SQL parser and transpiler. SQLGlot demonstrated that a pure-Python, dialect-aware parser with AST-based transpilation is a powerful and practical approach. GraphGlot applies the same philosophy to graph query languages.

License

Apache 2.0, see LICENSE.