Custom query modules
Python
Mock Python API

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 (opens in a new tab) 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 (opens in a new tab), 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.