grm-rs 0.1.0a8

Pre-release Python bindings for grm-rs runtime graph sessions.

grm-rs Python bindings

This crate packages a first-pass Python API for the grm-rs runtime session surface. It includes embedded Session, service-backed ServiceSession, and direct Neo4jSession implementations of a portable synchronous GraphSession core.

The Python package is an alpha pre-release. Its API and supported backend capabilities may change between alpha versions, but it is published for public evaluation, tutorials, and early application development.

Install the latest published alpha from PyPI:

python -m pip install --pre grm-rs

Pin a specific release when reproducibility matters:

python -m pip install grm-rs==0.1.0a8

The distribution package is named grm-rs; the import package is grm_rs.

Build

cd grm-python
maturin develop

Build a shareable wheel from the repository root:

python -m pip install maturin
maturin build --manifest-path grm-python/Cargo.toml --release --out dist

See ../docs/python-package-distribution.md for local builds and release details.

Example

from grm_rs import GraphId, GraphSession, Session


def add_user(session: GraphSession, name: str) -> GraphId:
    return session.node_create("User", {"name": name})["id"]

session = Session()
session.model_create(
    "User",
    "userId",
    [
        {"name": "name", "type": "string", "required": True},
        {"name": "age", "type": "int", "required": False},
    ],
)
session.model_create(
    "Post",
    "postId",
    [
        {"name": "title", "type": "string", "required": True},
    ],
)
session.link_create(
    "AUTHORED",
    "User",
    "Post",
    "authoredId",
    [
        {"name": "year", "type": "int", "required": True},
    ],
)

alice = session.node_create("User", {"name": "Alice", "age": 42})
post = session.node_create("Post", {"title": "Hello"})
edge = session.edge_create("AUTHORED", alice["id"], post["id"], {"year": 2024})
users = session.node_find("User", {"name": "Alice"})

The same add_user function accepts Session, ServiceSession, or Neo4jSession; applications do not need to redeclare the session API.

Portable Store Injection

Application stores can depend on GraphSession and receive either backend:

from grm_rs import GraphSession, Neo4jSession, ServiceSession


class UserStore:
    def __init__(self, graph: GraphSession) -> None:
        self.graph = graph

    def find_named(self, name: str):
        return self.graph.node_find("User", {"name": name})


graph: GraphSession
if use_neo4j:
    graph = Neo4jSession(uri=uri, user=user, password=password)
else:
    graph = ServiceSession(endpoint=endpoint, workspace_ref="demo", mode="open")

users = UserStore(graph).find_named("Ada")

The portable core has compatible schema inspection, CRUD/find, and atomic batch semantics. GraphId is opaque application-facing identity: code may pass returned IDs back to the same graph session, but must not assume physical ID preservation when moving data between backends.

Capability	Portable GraphSession	Workspace only	Neo4j native
Schema define/list	yes	yes	yes, GRM-owned session metadata
Node/edge CRUD and simple find	yes	yes	yes
Atomic batch writes	yes	yes	yes, one Neo4j transaction
Non-atomic batch writes	no	yes	no
Traversal-shaped node_find	no	yes	no
Explain/profile, indexes, import/export	no	yes	no
Native Cypher via execute_query	no	no	yes

Use session.capabilities() for lightweight discovery. The stable capability names currently include graph, atomic_batch, non_atomic_batch, workspace, traversal, explain_profile, persistence, and neo4j_native_query; applications should test membership rather than assume every session has optional methods.

Traversal queries mirror CLI node.find ... via=... semantics with structured Python inputs:

posts = session.node_find(
    "User",
    {"name": "Alice"},
    via=[
        {"dir": "out", "link": "AUTHORED", "model": "Post"},
    ],
)

authored_edges = session.node_find(
    "User",
    {"name": "Alice"},
    via=[
        {"dir": "out", "link": "AUTHORED", "model": "Post"},
    ],
    end_filters={"title": "Hello"},
    edge_filters={"year": 2024},
    return_="edge",
)

Explain and profile use the same query arguments and return structured plan data:

plan = session.explain_node_find(
    "User",
    {"name": "Alice"},
    via=[{"dir": "out", "link": "AUTHORED", "model": "Post"}],
)

profile = session.profile_edge_find("AUTHORED", {"from": alice["id"]})
assert profile["result_rows"] >= 0

indexes = session.indexes()
assert indexes["indexes"][0]["kind"] == "system"

Index catalog entries describe GRM-maintained derived acceleration structures such as node-label, exact node-property, relationship-type, and adjacency indexes. They are not user-defined indexes, and their contents are not durable source-of-truth data.

Batch operations share the same runtime semantics as MCP grm_batch, including atomic rollback, indexed errors, batch-local refs, and one autocommit snapshot after successful applied operations:

result = session.batch(
    [
        {"op": "node_create", "args": {"model": "User", "props": {"name": "Bob"}, "ref": "bob"}},
        {"op": "node_create", "args": {"model": "Post", "props": {"title": "Hello"}, "ref": "post"}},
        {
            "op": "edge_create",
            "args": {"model": "AUTHORED", "from": "bob", "to": "post", "props": {"year": 2026}},
        },
    ],
    response="detailed",
)

The portable GraphSession.batch() contract is atomic-only and therefore has no atomic argument. For Neo4j it stages GRM schema changes, executes all graph writes in one backend transaction, and installs staged schema only after commit. A failed operation rolls back graph writes and discards staged schema. Workspace sessions additionally implement WorkspaceBatchCapability, whose atomic=False mode is intentionally outside the portable contract.

Use save_json / load_json or save_binary / load_binary for local workspace snapshots. Use export_json, export_dict, and import_json for portable grm.interchange graph files; import_json currently imports into an empty session only.

Service-Backed Session

ServiceSession routes supported operations through the gRPC workspace service using workspace-scoped ExecuteWorkspace. The supported subset is schema define/list, node and edge create/update/delete/find, traversal-capable node_find for node/root/end/edge results, batch, and reopen by constructing another ServiceSession with mode="open" and the same workspace_ref.

from grm_rs import ServiceSession

session = ServiceSession(
    endpoint="http://127.0.0.1:50051",
    workspace_ref="python-demo",
    mode="create",
)
session.model_create("User", "userId", [{"name": "name", "type": "string", "required": True}])
ada = session.node_create("User", {"name": "Ada"})
assert session.node_find("User", {"id": ada["id"]})[0]["props"]["name"] == "Ada"

reopened = ServiceSession(
    endpoint="http://127.0.0.1:50051",
    workspace_ref="python-demo",
    mode="open",
)
assert len(reopened.node_find("User", {"name": "Ada"})) == 1

For a local TLS service, use an https:// endpoint and either pass trust material explicitly:

session = ServiceSession(
    endpoint="https://127.0.0.1:50051",
    workspace_ref="python-demo",
    mode="create",
    tls_ca_cert="/tmp/grm-tls/ca.crt",
    tls_domain_name="localhost",
    tls_client_cert="/tmp/grm-tls/client.crt",
    tls_client_key="/tmp/grm-tls/client.key",
)

or set GRM_SERVICE_TLS_CA_CERT, GRM_SERVICE_TLS_DOMAIN_NAME, GRM_SERVICE_TLS_CLIENT_CERT, and GRM_SERVICE_TLS_CLIENT_KEY in the environment before constructing ServiceSession. Client certificate/key parameters are paired and are required when the server enforces mutual TLS.

Service workspaces use binary persistence by default. Pass workspace_format="json" explicitly when you need JSON workspace files. The Python service path supports typed traversal-capable node_find, explain_node_find, and profile_node_find through workspace-scoped service requests. Direct unscoped service RPCs, free-form query parity, import/export, hosted durability, RBAC, production certificate lifecycle, and multi-writer coordination are not provided by this Python service path.