chore: import upstream snapshot with attribution

easygraph/datasets/web_google.py

@@ -0,0 +1,118 @@
+"""Web-Google Dataset
+
+This dataset is a web graph based on Google's web pages and their hyperlink
+structure, as crawled by the Stanford WebBase project in 2002.
+
+Each node represents a web page, and a directed edge from u to v indicates
+a hyperlink from page u to page v.
+
+Statistics:
+- Nodes: 875713
+- Edges: 5105039
+- Features: None
+- Labels: None
+
+Reference:
+J. Leskovec, A. Rajaraman, J. Ullman, “Mining of Massive Datasets.”
+Dataset from SNAP: https://snap.stanford.edu/data/web-Google.html
+"""
+
+import gzip
+import os
+import shutil
+
+import easygraph as eg
+
+from easygraph.classes.graph import Graph
+
+from .graph_dataset_base import EasyGraphBuiltinDataset
+from .utils import download
+from .utils import extract_archive
+
+
+class WebGoogleDataset(EasyGraphBuiltinDataset):
+    r"""Web-Google hyperlink network dataset.
+
+    Parameters
+    ----------
+    raw_dir : str, optional
+        Directory to store the raw downloaded files. Default: None
+    force_reload : bool, optional
+        Whether to re-download and process the dataset. Default: False
+    verbose : bool, optional
+        Whether to print detailed processing logs. Default: True
+    transform : callable, optional
+        Optional transform to apply on the graph.
+
+    Examples
+    --------
+    >>> from easygraph.datasets import WebGoogleDataset
+    >>> dataset = WebGoogleDataset()
+    >>> g = dataset[0]
+    >>> print("Nodes:", g.number_of_nodes())
+    >>> print("Edges:", g.number_of_edges())
+    """
+
+    def __init__(self, raw_dir=None, force_reload=False, verbose=True, transform=None):
+        name = "web-Google"
+        url = "https://snap.stanford.edu/data/web-Google.txt.gz"
+        super(WebGoogleDataset, self).__init__(
+            name=name,
+            url=url,
+            raw_dir=raw_dir,
+            force_reload=force_reload,
+            verbose=verbose,
+            transform=transform,
+        )
+
+    def download(self):
+        r"""Download and extract .gz edge list."""
+        if self.url is not None:
+            file_path = os.path.join(self.raw_dir, self.name + ".txt.gz")
+            download(self.url, path=file_path)
+            extract_archive(file_path, self.raw_path)
+
+    def process(self):
+        graph = eg.DiGraph()  # Web-Google is directed
+        edge_list_path = os.path.join(self.raw_path, self.name + ".txt")
+
+        with open(edge_list_path, "r") as f:
+            for line in f:
+                if line.startswith("#") or line.strip() == "":
+                    continue
+                u, v = map(int, line.strip().split())
+                graph.add_edge(u, v)
+
+        self._g = graph
+        self._num_nodes = graph.number_of_nodes()
+        self._num_edges = graph.number_of_edges()
+
+        if self.verbose:
+            print("Finished loading Web-Google dataset.")
+            print(f"  NumNodes: {self._num_nodes}")
+            print(f"  NumEdges: {self._num_edges}")
+
+    def __getitem__(self, idx):
+        assert idx == 0, "WebGoogleDataset only contains one graph"
+        return self._g if self._transform is None else self._transform(self._g)
+
+    def __len__(self):
+        return 1
+
+    def download(self):
+        r"""Download and decompress the .txt.gz file."""
+        if self.url is not None:
+            compressed_path = os.path.join(self.raw_dir, self.name + ".txt.gz")
+            extracted_path = os.path.join(self.raw_path, self.name + ".txt")
+
+            # Download .gz file
+            download(self.url, path=compressed_path)
+
+            # Ensure output directory exists
+            if not os.path.exists(self.raw_path):
+                os.makedirs(self.raw_path)
+
+            # Decompress manually
+            with gzip.open(compressed_path, "rb") as f_in:
+                with open(extracted_path, "wb") as f_out:
+                    shutil.copyfileobj(f_in, f_out)