mushroomdb (Python)

Python bindings for mushroomdb — the embedded graph database where edges are declared, not inserted.

import mushroomdb

db = mushroomdb.GraphDb.open("./db")
db.insert_node("Org", "org-01", {"founded_year": 2010})

GraphDb.open creates the directory if it does not exist. The handle is also a context manager, so with mushroomdb.GraphDb.open("./db") as db: closes on exit.

Writing nodes

db.insert_node("Person", "alice", {"team": "red"})   # raises if 'alice' exists
db.upsert_node("Person", "alice", {"team": "blue"})  # "inserted" or "updated"
db.set_prop("alice", "team", "green")
db.set_prop("alice", "team", None)                   # same as remove_prop
db.remove_prop("alice", "team")                      # False if already absent
report = db.delete_node("alice")                     # {"manual_edges", "derived_edges"}

upsert_node writes only the fields you pass whose value differs from the stored one. Fields you omit are left alone, and unchanged fields produce no WAL record, so rules do not re-fire needlessly. An existing key under a different label raises ValueError — relabelling is not an upsert.

Querying

query and query_write both accept parameters as a dict, as a list of (name, value) tuples, or not at all. Parameters are bound, never interpolated into the Cypher string.

rows = db.query(
    "MATCH (n:Person) WHERE n.age > $min RETURN key(n) AS id",
    {"min": 18},
)
db.query_write(
    "MATCH (n:Person) WHERE key(n) = $k SET n.age = 31 RETURN key(n)",
    {"k": "alice"},
)

A node's key is not a property, so n.key does not resolve. Use the key(n) scalar function to project or filter on it. node_info returns the key too.

Rules

db.create_rule({
    "name": "same_team",
    "src_label": "Person",
    "dst_label": "Person",
    "predicate": {"kind": "field_equal", "fields": ["team"]},
    "edge_type": "SAME_TEAM",
    "weight_prop": None,
})

The canonical predicate shape is snake_case — {"kind": ..., "fields": [...]} plus whatever numeric knob the kind takes (min, tolerance, km, or parts for all/any). This is exactly the shape explain emits, so an explanation round-trips straight back into a new rule:

why = db.explain("alice", "bob")
clone = {**base, "name": "same_team_clone", "predicate": why[0]["predicate"]}
db.create_rule(clone)

The Rust-native externally-tagged form is still accepted: {"FieldEqual": {"field": "team"}}, {"Overlap": {"field": "skills", "min": 0.5}}.

create_rule returns True when it created the rule. Pass if_not_exists=True to get False instead of an exception when a rule of that name is already registered.

Concurrency

One writer at a time across processes; readers see commits after refresh(). The store carries an advisory write lock. A read-write handle holds it for as long as it is open, so opening a second one anywhere on the machine raises MushroomBusy rather than letting two writers corrupt the store:

from mushroomdb import GraphDb, MushroomBusy

try:
    db = GraphDb.open("./db")
except MushroomBusy:
    ...  # another process is writing; nothing was changed, retry later

A handle does not poll the store, so another process's commits stay invisible until you ask for them. refresh() applies them in place and returns how many arrived — no close() and reopen:

n = db.refresh()   # rules fire and derived edges appear, as on a fresh open

Readers never take the lock. read_only=True opens immediately even while a writer holds it, writes nothing to disk, raises RuntimeError on any mutation, and can still refresh() to follow the writer:

reader = GraphDb.open("./db", read_only=True)
reader.refresh()

A commit another process is midway through writing is left alone and picked up by the next refresh(); a partial write is never an error.

Within one process the handle is guarded by a mutex, so calls from multiple threads are serialized and safe. They are not isolated transactions: readers can observe intermediate states while a batch is being applied.

Type stubs

The wheel ships __init__.pyi and a py.typed marker, so mypy and Pyright pick up signatures without extra configuration.

Full documentation, the rules tour, and benchmarks live in the main repository.