fix: optimize import modules #170
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Summary of ChangesHello @ChenZiHong-Gavin, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request introduces comprehensive optimizations to the module import strategy across the Highlights
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Code Review
This pull request introduces a comprehensive optimization of module imports across the codebase to improve startup time and reduce memory usage. The changes primarily involve lazy-loading dependencies by moving imports into functions/methods where they are used, leveraging typing.TYPE_CHECKING for type-only imports, and using PEP 562 for lazy-loading submodules in packages.
Overall, the changes are well-executed and follow best practices for import optimization. My review includes a couple of suggestions for improving maintainability in cases where a core dependency is repeatedly imported within multiple methods of the same class. Consolidating these imports would reduce code duplication while still respecting the goal of lazy loading.
graphgen/common/init_storage.py
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| self.actor = actor_handle | ||
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| def data(self) -> Dict[str, Any]: | ||
| import ray |
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Importing ray in every method of RemoteKVStorageProxy and RemoteGraphStorageProxy introduces significant code duplication. Since these classes are tightly coupled with Ray, consider importing ray once at the top of the file. This would simplify the code and improve maintainability. Python's import caching mechanism ensures that subsequent imports are very fast, so there's minimal performance overhead.
| return self._graph.number_of_edges() | ||
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| def get_connected_components(self, undirected: bool = True) -> List[Set[str]]: | ||
| import networkx as nx |
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Importing networkx in multiple methods within the NetworkXStorage class leads to code duplication. Since this class is a wrapper around a NetworkX graph, networkx is a core dependency. Consider importing it once at the top of the file. This will make the code cleaner and more maintainable without a significant performance penalty, thanks to Python's module caching.
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| import pandas as pd | ||
| import ray | ||
| if TYPE_CHECKING: | ||
| import numpy as np |
| from graphgen.models import ( | ||
| ChineseRecursiveTextSplitter, | ||
| RecursiveCharacterSplitter, | ||
| Tokenizer, | ||
| ) |
| from graphgen.bases.base_reader import BaseReader | ||
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| if TYPE_CHECKING: | ||
| import ray |
| from graphgen.bases.datatypes import Community | ||
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| if TYPE_CHECKING: | ||
| import igraph as ig |
| from graphgen.bases.base_reader import BaseReader | ||
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| if TYPE_CHECKING: | ||
| import ray |
| from graphgen.utils import logger, pick_device | ||
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| if TYPE_CHECKING: | ||
| import ray |
| from graphgen.utils import logger | ||
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| if TYPE_CHECKING: | ||
| import ray |
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| if TYPE_CHECKING: | ||
| import ray | ||
| import rdflib |
| import ray | ||
| import rdflib | ||
| from ray.data import Dataset | ||
| from rdflib import Literal |
| from graphgen.bases.base_reader import BaseReader | ||
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| if TYPE_CHECKING: | ||
| import ray |
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/gemini review |
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Code Review
This pull request does an excellent job of optimizing module imports throughout the codebase. The use of TYPE_CHECKING blocks, lazy imports within functions, and the PEP 562 __getattr__ pattern are all effective strategies for improving startup performance and managing dependencies. The changes are applied consistently and correctly. My review includes a couple of minor suggestions to address some stylistic formatting issues related to excessive blank lines, which would improve code readability.
| return ray.get(self.actor.get_all_node_degrees.remote()) | ||
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| def get_node_count(self) -> int: | ||
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This blank line is unnecessary and harms readability by making the method less compact. This applies to many other simple proxy methods in this class as well (e.g., get_edge_count, has_node). For simple one-line proxy methods, it's best to keep them compact.
| return self._graph.number_of_edges() | ||
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| def get_connected_components(self, undirected: bool = True) -> List[Set[str]]: | ||
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This added blank line is unnecessary. Please consider removing it to keep the code compact. This comment also applies to other places in this file where extra blank lines have been added within method bodies (e.g., in load_nx_graph, _stabilize_graph).
This pull request introduces optimizations to the module import strategy across the
graphgenlibrary. The primary goal is to enhance application performance by minimizing startup time and reducing memory consumption.