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Version: 2.10.1

Mock Python query module API

The mock Python query module API enables you to develop and test query modules for Memgraph without having to run a Memgraph instance by simulating its behavior. As the mock API is compatible with the Python API, you can add modules developed with it to Memgraph as-is, without modifying the code.

It is implemented in mgp_mock.py, which contains definitions of all classes and functions provided for developing query module procedures and functions. The source file is located in the Memgraph installation directory, inside /usr/include/memgraph.

API reference​

Because the mock API’s classes and functions are compatible with the corresponding Python API classes and functions, the Python API reference applies, with the following exceptions:

  • Query procedure returns (Record class) are printable.
  • The mock API doesn’t throw errors having to do with Memgraph-internal behavior (UnableToAllocateError, InsufficientBufferError, OutOfRangeError, KeyAlreadyExistsError, SerializationError and AuthorizationError).
  • The mock API doesn’t contain two Python API methods dealing with Memgraph-internal behavior (must_abort and check_must_abort). These methods are used to check whether Memgraph has notified the query module to abort its execution.
  • The constructors of the ProcCtx and FuncCtx classes take a NetworkX MultiDiGraph because that’s the data structure the mock API uses for internal graph representations.
  • Transformation modules are currently not implemented.

Graph representation​

The mock Python API uses a graph representation based on the NetworkX MultiDiGraph, which is a directed graph that supports parallel edges (relationships) and custom node/relationship attributes.

All elements of a Memgraph graph are supported by the mock API, with the following rules about representing node labels and relationship types:

  • Node labels are stored in the node attribute named "labels" as a ":"-separated string, e.g. the node (n:Actor:Director) has {"labels": "Actor:Director"}.
  • Edge types are strings stored in "type".

Using the mock API​

Importing​

Before importing the mock API, you need to make it visible to the query module, e.g. by adding the path of mgp_mock.py to PYTHONPATH or copying mgp_mock.py to the directory containing the module.

Running​

The following code block contains an example query procedure and a runner for query procedures:

import mgp_mock as mgp
import networkx as nx

@mgp.read_proc
def example_procedure(context: mgp.ProcCtx) -> mgp.Record(status=str):
    return mgp.Record(status="Hello, world!")

graph = nx.MultiDiGraph() # Empty graph
context = mgp.ProcCtx(graph) # Create a context instance

result = example_procedure(context) # Run the procedure
print(result) # Hello, world!

Running the module with Memgraph​

As the mock Python API is compatible with the Python query module API, adding a module developed with the mock API to Memgraph is a simple task.

  1. Replace the mgp_mock import with import mgp
    • This includes refactoring the usages of mgp_mock (or alias) to mgp.
  2. Load the query module.