froGQL
Embedded GQL graph database with single-file storage. Rust core, Python bindings via PyO3.
froGQL implements ISO GQL path pattern matching: MATCH, comma-joins, unions, repetitions ({n,m}), OPTIONAL MATCH, EXISTS / NOT EXISTS, WHERE, RETURN, LIMIT. The runtime uses Leapfrog Triejoin (CompactLTJ) as its primary join strategy — worst-case-optimal for multi-way joins, with measured 14×–4000× speedups over pairwise hash-join on social-graph workloads.
Install
pip install frogql
Wheels ship for CPython 3.8+ on Linux (x86_64, aarch64), macOS (x86_64, arm64), and Windows (x86_64).
Quick start
import frogql
# Open or create a .gdb database
conn = frogql.open("movies.gdb")
# Run a query — returns a list of {alias: value} dicts.
# Use `AS name` in RETURN to pick the dict key; otherwise the
# projection falls back to col0, col1, ...
rows = conn.execute(
"MATCH (p:Person)-[:ACTED_IN]->(m:Movie) "
"WHERE m.released = 1999 "
"RETURN p.name AS actor, m.title AS title",
limit=10,
)
for row in rows:
print(row["actor"], "->", row["title"])
# Inspect the graph
print(conn.node_count, conn.edge_count)
print(conn.schema())
Bare patterns (no RETURN)
A query without RETURN projects each row as a dict of the matched
variables plus a special _paths key holding the full match:
rows = conn.execute("(p:Person)-[:ACTED_IN]->(m:Movie)", limit=1)
row = rows[0]
row["p"] # {"kind": "node", "id": ..., "labels": [...], "props": {...}}
row["m"] # the movie node
row["_paths"] # [[node_p, edge, node_m]] — list of paths, each a
# list of node/edge dicts in match order
_paths is a list because comma-joined patterns produce one path per
joined sub-pattern. For a single pattern, _paths[0] is the full path.
Data import
# From JSON
frogql.import_json("graph.gdb", "graph.json")
# From a CSV directory with spanner_import_config.json
frogql.import_csv("graph.gdb", "path/to/csv_dir/")
Graph types and indexes
The catalog persists inside the .gdb file. DDL is plain GQL:
conn.execute("CREATE GRAPH TYPE movies { (:Movie {title STRING, released INT}) }")
conn.execute("USE GRAPH TYPE movies")
conn.execute("VALIDATE GRAPH TYPE movies")
conn.execute("CREATE BTREE INDEX ON :Movie(released)")
A DEFAULT graph type is auto-inferred at import time. Auto-built secondary indexes (hash + btree) cover unique (label, prop) pairs and are picked up by the optimizer for constant-folding and range filters.
API surface
| Call | Returns |
|---|---|
frogql.open(path) |
Connection |
frogql.import_json(db_path, json_path) |
None |
frogql.import_csv(db_path, csv_dir) |
None |
Connection.execute(query, limit=0) |
list[dict] (with RETURN: keys = aliases or colN; without RETURN: keys = pattern variables plus _paths) |
Connection.schema() |
dict |
Connection.graph_types() |
list[dict] |
Connection.node_count / Connection.edge_count |
int |
Connection is not thread-safe across Python threads (PyO3 unsendable).
License
MIT. See LICENSE in the source repository.
Links
Release files for frogql 0.5.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| frogql-0.5.9.tar.gz | 1.2 MB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| frogql-0.5.9-cp38-abi3-win_amd64.whl | CPython 3.8 | abi3 | Windows x86-64 | Details |
| frogql-0.5.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.8 | abi3 | Linux glibc 2.17+ x86-64 | Details |
| frogql-0.5.9-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl | CPython 3.8 | abi3 | Linux glibc 2.17+ ARM64 | Details |
| frogql-0.5.9-cp38-abi3-macosx_11_0_arm64.whl | CPython 3.8 | abi3 | macOS 11.0+ ARM64 | Details |
| frogql-0.5.9-cp38-abi3-macosx_10_12_x86_64.whl | CPython 3.8 | abi3 | macOS 10.12+ x86-64 | Details |
Total release size: 8.4 MB
Release files / frogql-0.5.9.tar.gz
| Download URL | frogql-0.5.9.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4390552587739d3a539079784889a12442b6bab1ff177cabe094db6801e9e4a2
|
|
BLAKE2b-256 checksum How to use checksums |
ca554c32bfebd513240ffc55dca53837024de20ba8d6ddbd9d8ce58e302dee48
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
maturin/1.15.0
|
Release files / frogql-0.5.9-cp38-abi3-win_amd64.whl
| Download URL | frogql-0.5.9-cp38-abi3-win_amd64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | CPython 3.8 Windows x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
ce02f97d93a2b0e6867972a09b50cb0e6e47ac17e039277f9e02d551d649bc47
|
|
BLAKE2b-256 checksum How to use checksums |
57b2fb23a89567532b63ed745468ef62fae29d7b059438d3f76f6a355de69978
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
maturin/1.15.0
|
Release files / frogql-0.5.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | frogql-0.5.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
|---|---|
| Size | 1.5 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
1f9a125fb36eb139ecf057dc2b46b0f5774d86126325f2d61a7e303702993235
|
|
BLAKE2b-256 checksum How to use checksums |
7e12632bef697b277ccef89bd1decd0e212194777d97db8358022715d85e1725
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
maturin/1.15.0
|
Release files / frogql-0.5.9-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
| Download URL | frogql-0.5.9-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl |
|---|---|
| Size | 1.5 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ ARM64 abi3 |
|
SHA-256 checksum How to use checksums |
9993bdc48502c78d836037ad65c3507e3b5f2ea8e9b658097c129ab15ed0bb6f
|
|
BLAKE2b-256 checksum How to use checksums |
21a927fb18e00c587c3e2dbbf70b19e8e9b4fd7f6f74efdcdfee4e44d7892b9c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
maturin/1.15.0
|
Release files / frogql-0.5.9-cp38-abi3-macosx_11_0_arm64.whl
| Download URL | frogql-0.5.9-cp38-abi3-macosx_11_0_arm64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | CPython 3.8 abi3 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
ea7d298dd4ff087b2c80e7fc37d94bed60b3dfa3f42336e999f2abcd29abcaf4
|
|
BLAKE2b-256 checksum How to use checksums |
fb3201965ead5a9cc94476f7e0632302244a09948a5a64419192a941ebd1efca
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
maturin/1.15.0
|
Release files / frogql-0.5.9-cp38-abi3-macosx_10_12_x86_64.whl
| Download URL | frogql-0.5.9-cp38-abi3-macosx_10_12_x86_64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | CPython 3.8 abi3 macOS 10.12+ x86-64 |
|
SHA-256 checksum How to use checksums |
73502cf9c1093fe7d417fcab55ac6cde80fa96b7ba033d6af471602d9758c32e
|
|
BLAKE2b-256 checksum How to use checksums |
036b3bce034f79822b475fb29608f48e782d608870673daa35881cd79abaf39b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
maturin/1.15.0
|
