diff --git a/.gitignore b/.gitignore index ceef717..29b309e 100644 --- a/.gitignore +++ b/.gitignore @@ -151,3 +151,5 @@ download run *.gz *.whl + +.python_history diff --git a/ng_ai/engines.py b/ng_ai/engines.py index 67d8c6e..983c756 100644 --- a/ng_ai/engines.py +++ b/ng_ai/engines.py @@ -116,15 +116,35 @@ class NebulaEngine(BaseEngine): def __init__(self, config=None): self.type = "nebula" self.config = config + + # let's make all nx related import here + import networkx as nx + import ng_nx + from ng_nx import NebulaReader as NxReader + from ng_nx import NxScanReader, NxWriter + from ng_nx.utils import NxConfig, result_to_df + + self.nx = nx + self.ng_nx = ng_nx + self.nx_reader = NxReader + self.nx_writer = NxWriter + self.nx_scan_reader = NxScanReader + self._nx_config = NxConfig + + self.result_to_df = result_to_df + + self.nx_config = None self.parse_config() def __str__(self): - return f"NebulaEngine: {self.config}" + return ( + f"NebulaEngine(NetworkX): {self.config}, " + f"nx version: {self.nx.__version__}, " + f"ng_nx version: {self.ng_nx.__version__}" + ) def parse_config(self): """parse and validate config""" if self.config is None: return - - def prepare(self): - pass + self.nx_config = self._nx_config(**self.config.__dict__) diff --git a/ng_ai/nebula_algo.py b/ng_ai/nebula_algo.py index 6369cef..d577a5b 100644 --- a/ng_ai/nebula_algo.py +++ b/ng_ai/nebula_algo.py @@ -366,6 +366,7 @@ class NebulaGraphAlgorithm: def __init__(self, graph): self.graph = graph self.algorithms = [] + self.engine = graph.engine def register_algo(self, func): self.algorithms.append(func.__name__) @@ -384,14 +385,28 @@ def check_engine(self): For spark, we need to convert the NebulaGraphObject to NebulaDataFrameObject """ - if self.graph.engine.type == "spark": + if self.engine.type == "spark": raise Exception( "For NebulaGraphObject in spark engine," "Plz transform it to NebulaDataFrameObject to run algorithm", "For example: df = nebula_graph.to_df; df.algo.pagerank()", ) + if self.engine.type == "networkx": + return True + else: + raise Exception("Unsupported engine type") @algo - def pagerank(self, reset_prob=0.15, max_iter=10): + def pagerank(self, reset_prob=0.15, max_iter=10, **kwargs): self.check_engine() - pass + g = self.graph._graph + weight = kwargs.get("weight", None) + assert type(weight) in [str, type(None)], "weight must be str or None" + assert type(reset_prob) == float, "reset_prob must be float" + assert type(max_iter) == int, "max_iter must be int" + tol = kwargs.get("tol", 1e-06) + assert type(tol) == float, "tol must be float" + + return self.engine.nx.pagerank( + g, alpha=1 - reset_prob, max_iter=max_iter, tol=tol, weight=weight + ) diff --git a/ng_ai/nebula_data.py b/ng_ai/nebula_data.py index 1706878..86d9818 100644 --- a/ng_ai/nebula_data.py +++ b/ng_ai/nebula_data.py @@ -3,8 +3,6 @@ from __future__ import annotations -import networkx as nx - class NebulaGraphObject: def __init__(self, df: NebulaDataFrameObject): @@ -19,9 +17,16 @@ def get_engine(self): @property def algo(self): - from ng_ai.nebula_algo import NebulaAlgorithm as NebulaAlgorithmImpl + if self.engine.type == "spark": + print( + "NebulaGraphObject.algo is not supported in spark engine, " + "please use NebulaDataFrameObject.algo instead" + ) + raise NotImplementedError + if self.engine.type == "nebula": + from ng_ai.nebula_algo import NebulaAlgorithm as NebulaAlgorithmImpl - return NebulaAlgorithmImpl(self) + return NebulaAlgorithmImpl(self) def get_nx_graph(self): if self.engine.type == "nebula": @@ -81,9 +86,16 @@ def get_engine(self): @property def algo(self): - from ng_ai.nebula_algo import NebulaAlgorithm as NebulaAlgorithmImpl + if self.engine.type == "spark": + from ng_ai.nebula_algo import NebulaAlgorithm as NebulaAlgorithmImpl - return NebulaAlgorithmImpl(self) + return NebulaAlgorithmImpl(self) + else: + print( + "NebulaDataFrameObject.algo is not supported in nebula engine, " + "please use NebulaGraphObject.algo instead" + ) + raise NotImplementedError def to_spark_df(self): if self.engine.type == "spark": @@ -103,14 +115,11 @@ def to_pandas_df(self): raise NotImplementedError def to_networkx(self): - if self.engine.type == "nebula": - return nx.from_pandas_edgelist(self.data, "src", "dst") - else: - # for now the else case will be spark, to networkx is not supported - raise Exception( - "For NebulaDataFrameObject in spark engine," - "convert to networkx graph is not supported", - ) + # for now the else case will be spark, to networkx is not supported + raise Exception( + "For NebulaDataFrameObject in spark engine," + "convert to networkx graph is not supported", + ) def to_graphx(self): if self.engine.type == "spark": @@ -128,4 +137,9 @@ def to_graph(self): return NebulaGraphObject(self) def show(self, *keywords, **kwargs): - return self.data.show(*keywords, **kwargs) + if self.engine.type == "spark": + self.data.show(*keywords, **kwargs) + elif self.engine.type == "nebula": + print(self.data) + else: + raise NotImplementedError diff --git a/ng_ai/nebula_reader.py b/ng_ai/nebula_reader.py index c3ec862..9c2ef30 100644 --- a/ng_ai/nebula_reader.py +++ b/ng_ai/nebula_reader.py @@ -5,6 +5,8 @@ from ng_ai.config import NebulaGraphConfig from ng_ai.nebula_data import NebulaDataFrameObject +DEFAULT_NEBULA_QUERY_LIMIT = 1000 + class NebulaReaderBase(object): def __init__(self, engine=None, config=None, **kwargs): @@ -54,22 +56,52 @@ def __init__(self, config: NebulaGraphConfig, **kwargs): self.engine = NebulaEngine(config) self.raw_df = None self.df = None + self.reader = None def scan(self, **kwargs): # Implement the scan method specific to Nebula engine raise NotImplementedError def query(self, **kwargs): - # Implement the query method specific to Nebula engine - raise NotImplementedError + limit = kwargs.get("limit", DEFAULT_NEBULA_QUERY_LIMIT) + assert type(limit) == int, "limit should be an integer" + assert "space" in kwargs, "space is required" + space = kwargs["space"] + assert "edges" in kwargs, "edges is required" + edges = kwargs["edges"] + assert type(edges) == list, "edges should be a list" + length_of_edges = len(edges) + props = kwargs.get("props", [[]] * length_of_edges) + assert type(props) == list, "props should be a list" + assert ( + len(props) == length_of_edges + ), "length of props should be equal to length of edges" + for prop in props: + assert type(prop) == list, "props should be a list of list" + for item in prop: + assert type(item) == str, "props should be a list of list of string" + + self.reader = NebulaReader( + space=space, + edges=edges, + properties=props, + nebula_config=self.engine._nx_config, + limit=limit, + ) + + return self.reader def load(self, **kwargs): # Implement the load method specific to Nebula engine raise NotImplementedError def read(self, **kwargs): - # Implement the read method specific to Nebula engine - raise NotImplementedError + if self.reader is None: + raise Exception( + "reader is not initialized, please call query or scan first" + ) + self._graph = self.reader.read() + return self._graph def show(self, **kwargs): # Implement the show method specific to Nebula engine diff --git a/pdm.lock b/pdm.lock index 7f996e0..485841b 100644 --- a/pdm.lock +++ b/pdm.lock @@ -45,18 +45,6 @@ dependencies = [ "tokenize-rt>=3.2.0", ] -[[package]] -name = "certifi" -version = "2022.12.7" -requires_python = ">=3.6" -summary = "Python package for providing Mozilla's CA Bundle." - -[[package]] -name = "charset-normalizer" -version = "3.1.0" -requires_python = ">=3.7.0" -summary = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." - [[package]] name = "chispa" version = "0.9.2" @@ -131,12 +119,6 @@ dependencies = [ "pyparsing!=3.0.0,!=3.0.1,!=3.0.2,!=3.0.3,<4,>=2.4.2; python_version > \"3.0\"", ] -[[package]] -name = "idna" -version = "3.4" -requires_python = ">=3.5" -summary = "Internationalized Domain Names in Applications (IDNA)" - [[package]] name = "importlib-metadata" version = "4.2.0" @@ -247,12 +229,44 @@ version = "2.6.3" requires_python = ">=3.7" summary = "Python package for creating and manipulating graphs and networks" +[[package]] +name = "ng-nx" +version = "0.1.6" +requires_python = ">=3.7,<3.11" +summary = "NebulaGraph NetowrkX adaptor" +dependencies = [ + "nebula3-python", + "networkx>=2.5.1", + "numpy>=1.21.6", + "pandas>=1.3.5", + "scipy>=1.7.3", +] + +[[package]] +name = "numpy" +version = "1.21.6" +requires_python = ">=3.7,<3.11" +summary = "NumPy is the fundamental package for array computing with Python." + [[package]] name = "packaging" version = "23.0" requires_python = ">=3.7" summary = "Core utilities for Python packages" +[[package]] +name = "pandas" +version = "1.3.5" +requires_python = ">=3.7.1" +summary = "Powerful data structures for data analysis, time series, and statistics" +dependencies = [ + "numpy>=1.17.3; platform_machine != \"aarch64\" and platform_machine != \"arm64\" and python_version < \"3.10\"", + "numpy>=1.19.2; platform_machine == \"aarch64\" and python_version < \"3.10\"", + "numpy>=1.20.0; platform_machine == \"arm64\" and python_version < \"3.10\"", + "python-dateutil>=2.7.3", + "pytz>=2017.3", +] + [[package]] name = "parso" version = "0.8.3" @@ -364,21 +378,27 @@ dependencies = [ "tomli>=1.0.0; python_version < \"3.11\"", ] +[[package]] +name = "python-dateutil" +version = "2.8.2" +requires_python = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +summary = "Extensions to the standard Python datetime module" +dependencies = [ + "six>=1.5", +] + [[package]] name = "pytz" version = "2022.7.1" summary = "World timezone definitions, modern and historical" [[package]] -name = "requests" -version = "2.28.2" -requires_python = ">=3.7, <4" -summary = "Python HTTP for Humans." +name = "scipy" +version = "1.7.3" +requires_python = ">=3.7,<3.11" +summary = "SciPy: Scientific Library for Python" dependencies = [ - "certifi>=2017.4.17", - "charset-normalizer<4,>=2", - "idna<4,>=2.5", - "urllib3<1.27,>=1.21.1", + "numpy<1.23.0,>=1.16.5", ] [[package]] @@ -423,12 +443,6 @@ version = "4.5.0" requires_python = ">=3.7" summary = "Backported and Experimental Type Hints for Python 3.7+" -[[package]] -name = "urllib3" -version = "1.26.15" -requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" -summary = "HTTP library with thread-safe connection pooling, file post, and more." - [[package]] name = "wcwidth" version = "0.2.6" @@ -451,7 +465,7 @@ summary = "Backport of pathlib-compatible object wrapper for zip files" [metadata] lock_version = "4.1" -content_hash = 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"Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", ] [project.urls] Homepage = "https://github.com/wey-gu/nebulagraph-ai" @@ -143,7 +144,12 @@ build-backend = "pdm.pep517.api" [project.optional-dependencies] # pyspark 2.4.8 doesn't work with python 3.8+, so we use 3.2.3 spark = ["pyspark>=3.2.3"] -networkx = ["networkx>=2.5.1"] +networkx = [ + "ng_nx>=0.1.6", + "pandas>=1.3.5", + "numpy>=1.21.6", + "scipy>=1.7.3", +] all = ["ng_ai[spark,networkx]"] lint = [ "flake8>=4.0.1", @@ -152,7 +158,7 @@ lint = [ ] test = [ "pytest>=7.2.2", - "chispa", - "requests", + "chispa>=0.9.2", + "nebula3-python", ] dev = ["ng_ai[all,lint,test]"] diff --git a/tests/integration/setup/docker-compose.yaml b/tests/integration/setup/docker-compose.yaml index 32f77ab..4aca738 100644 --- a/tests/integration/setup/docker-compose.yaml +++ b/tests/integration/setup/docker-compose.yaml @@ -3,7 +3,7 @@ services: labels: - 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