repo_full_name stringlengths 6 93 | repo_url stringlengths 25 112 | repo_api_url stringclasses 28
values | owner stringclasses 28
values | repo_name stringclasses 28
values | description stringclasses 28
values | stars int64 617 98.8k | forks int64 31 355 ⌀ | watchers int64 990 999 ⌀ | license stringclasses 2
values | default_branch stringclasses 2
values | repo_created_at timestamp[s]date 2012-07-24 23:12:50 2025-06-16 08:07:28 ⌀ | repo_updated_at timestamp[s]date 2026-02-23 15:23:15 2026-05-03 18:52:12 ⌀ | repo_topics listlengths 0 13 ⌀ | repo_languages unknown | is_fork bool 1
class | open_issues int64 3 104 ⌀ | file_path stringlengths 3 208 | file_name stringclasses 509
values | file_extension stringclasses 1
value | file_size_bytes int64 101 84k ⌀ | file_url stringclasses 627
values | file_raw_url stringclasses 627
values | file_sha stringclasses 624
values | language stringclasses 8
values | parsed_at stringdate 2026-05-04 01:12:36 2026-05-04 19:41:55 | text stringlengths 100 102k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | maigret/permutator.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:44.892674 | # License MIT. by balestek https://github.com/balestek
from itertools import permutations
class Permute:
def __init__(self, elements: dict):
self.separators = ["", "_", "-", "."]
self.elements = elements
def gather(self, method: str = "strict" or "all") -> dict:
permutations_dict = {}... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/conftest.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:44.983816 | import glob
import logging
import os
import pytest
from _pytest.mark import Mark
from maigret.sites import MaigretDatabase
from maigret.maigret import setup_arguments_parser
from maigret.settings import Settings
from aiohttp import web
LOCAL_SERVER_PORT = 8080
CUR_PATH = os.path.dirname(os.path.realpath(__file__))... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | maigret/result.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:44.985338 | """Maigret Result Module
This module defines various objects for recording the results of queries.
"""
from enum import Enum
class MaigretCheckStatus(Enum):
"""Query Status Enumeration.
Describes status of query about a given username.
"""
CLAIMED = "Claimed" # Username Detected
AVAILABLE = "... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_activation.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:45.051649 | """Maigret activation test functions"""
import json
import yarl
import aiohttp
import pytest
from mock import Mock
from tests.conftest import LOCAL_SERVER_PORT
from maigret.activation import ParsingActivator, import_aiohttp_cookies
COOKIES_TXT = """# HTTP Cookie File downloaded with cookies.txt by Genuinous @genuin... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | maigret/settings.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:45.060235 | import os
import os.path as path
import json
from typing import List
SETTINGS_FILES_PATHS = [
path.join(path.dirname(path.realpath(__file__)), "resources/settings.json"),
path.expanduser('~/.maigret/settings.json'),
path.join(os.getcwd(), 'settings.json'),
]
class Settings:
# main maigret setting
... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_cli.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:45.570781 | """Maigret command-line arguments parsing tests"""
from argparse import Namespace
from typing import Dict, Any
DEFAULT_ARGS: Dict[str, Any] = {
'all_sites': False,
'auto_disable': False,
'connections': 100,
'cookie_file': None,
'csv': False,
'db_file': 'resources/data.json',
'debug': False... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_checking.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:45.745925 | from argparse import ArgumentTypeError
from mock import Mock
import pytest
from maigret import search
from maigret.checking import (
detect_error_page,
extract_ids_data,
parse_usernames,
update_results_info,
get_failed_sites,
timeout_check,
debug_response_logging,
process_site_result,
... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_permutator.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.308749 | import pytest
from maigret.permutator import Permute
def test_gather_strict():
elements = {'a': 1, 'b': 2}
permute = Permute(elements)
result = permute.gather(method="strict")
expected = {
'a_b': 1,
'b_a': 2,
'a-b': 1,
'b-a': 2,
'a.b': 1,
'b.a': 2,
... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_report.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.421464 | """Maigret reports test functions"""
import copy
import json
import os
import pytest
from io import StringIO
import xmind # type: ignore[import-untyped]
from jinja2 import Template
from maigret.report import (
filter_supposed_data,
sort_report_by_data_points,
_md_format_value,
generate_csv_report,
... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_data.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.511319 | """Maigret data test functions"""
import pytest
from maigret.utils import is_country_tag
TOP_SITES_ALEXA_RANK_LIMIT = 50
KNOWN_SOCIAL_DOMAINS = [
"facebook.com",
"instagram.com",
"twitter.com",
"tiktok.com",
"vk.com",
"reddit.com",
"pinterest.com",
"snapchat.com",
"linkedin.com",... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_db_updater.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.694151 | """Tests for the database auto-update system."""
import json
import os
import hashlib
from datetime import datetime, timezone, timedelta
from unittest.mock import patch, MagicMock
import pytest
from maigret.db_updater import (
_parse_version,
_needs_check,
_is_version_compatible,
_is_update_available... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_errors.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.712315 | import pytest
from maigret.errors import notify_about_errors, CheckError
from maigret.types import QueryResultWrapper
from maigret.result import MaigretCheckResult, MaigretCheckStatus
def test_notify_about_errors():
results = {
'site1': {
'status': MaigretCheckResult(
'', '', '... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_executors.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.752326 | """Maigret checking logic test functions"""
import pytest
import asyncio
import logging
from typing import Any, List, Tuple, Callable, Dict
from maigret.executors import (
AsyncioSimpleExecutor,
AsyncioProgressbarExecutor,
AsyncioProgressbarSemaphoreExecutor,
AsyncioProgressbarQueueExecutor,
Asynci... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_settings.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:46.904022 | import unittest
from unittest.mock import patch, mock_open
from maigret.settings import Settings
class TestSettings(unittest.TestCase):
@patch('json.load')
@patch('builtins.open', new_callable=mock_open)
def test_settings_cascade_and_override(self, mock_file, mock_json_load):
file1_data = {"timeo... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_sites.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.043217 | """Maigret Database test functions"""
import re
from typing import Any, Dict
from maigret.sites import MaigretDatabase, MaigretSite
EXAMPLE_DB: Dict[str, Any] = {
'engines': {
"XenForo": {
"presenseStrs": ["XenForo"],
"site": {
"absenceStrs": [
... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_submit.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.146508 | import re
import pytest
from unittest.mock import MagicMock, patch
from maigret.submit import Submitter
from aiohttp import ClientSession
from maigret.sites import MaigretDatabase, MaigretSite
import logging
@pytest.mark.slow
@pytest.mark.asyncio
async def test_detect_known_engine(test_db, local_test_db):
# Use ... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_twitter.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.261278 | """Tests for the Twitter / X site entry and GraphQL probe."""
import re
import pytest
import requests
from maigret.sites import MaigretSite
def _twitter_site(site: MaigretSite) -> None:
assert site.name == "Twitter"
assert site.disabled is False
assert site.check_type == "message"
assert site.url_p... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.294104 | """Maigret utils test functions"""
import itertools
import re
from maigret.utils import (
CaseConverter,
is_country_tag,
enrich_link_str,
URLMatcher,
get_dict_ascii_tree,
get_match_ratio,
)
def test_case_convert_camel_to_snake():
a = 'SnakeCasedString'
b = CaseConverter.camel_to_snak... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/add_tags.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.485099 | #!/usr/bin/env python3
import random
from argparse import ArgumentParser, RawDescriptionHelpFormatter
from maigret.maigret import MaigretDatabase
from maigret.submit import Submitter
def update_tags(site):
tags = []
if not site.tags:
print(f'Site {site.name} doesn\'t have tags')
else:
tag... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/check_engines.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.594467 | #!/usr/bin/env python3
"""Maigret: Supported Site Listing with Alexa ranking and country tags
This module generates the listing of supported sites in file `SITES.md`
and pretty prints file with sites data.
"""
import asyncio
import json
import logging
from argparse import ArgumentParser, RawDescriptionHelpFormatter
fr... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/check_top_n.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.724346 | #!/usr/bin/env python3
"""
Mass site checking utility for Maigret development.
Check top-N sites from data.json and generate a report.
Usage:
python utils/check_top_n.py --top 100 # Check top 100 sites
python utils/check_top_n.py --top 50 --parallel 10 # Check with 10 parallel requests... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/fp_probe_top_sites.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.816499 | #!/usr/bin/env python3
"""
Probe likely false-positive sites among the top-N Alexa-ranked entries.
For each of K random *distinct* usernames taken from ``usernameClaimed`` fields in
the Maigret database, runs a clean ``maigret`` scan (``--top-sites N --json simple|ndjson``).
Sites that return CLAIMED in *every* run ar... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/generate_db_meta.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.882839 | """Generate db_meta.json from data.json for the auto-update system."""
import argparse
import hashlib
import json
import os.path as path
import sys
from datetime import datetime, timezone
RESOURCES_DIR = path.join(path.dirname(path.dirname(path.abspath(__file__))), "maigret", "resources")
DATA_JSON_PATH = path.join(R... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/import_sites.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:47.953212 | #!/usr/bin/env python3
import json
import random
import re
import alive_progress
from mock import Mock
import requests
from maigret.maigret import *
from maigret.result import MaigretCheckStatus
from maigret.sites import MaigretSite
URL_RE = re.compile(r"https?://(www\.)?")
TIMEOUT = 200
async def maigret_check(si... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/site_check.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:48.125258 | #!/usr/bin/env python3
"""
Site check utility for Maigret development.
Quickly test site availability, find valid usernames, and diagnose check issues.
Usage:
python utils/site_check.py --site "SiteName" --check-claimed
python utils/site_check.py --site "SiteName" --maigret # Test via Maigret
pyt... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/sites_diff.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:48.172492 | import sys
import difflib
import requests
a = requests.get(sys.argv[1]).text
b = requests.get(sys.argv[2]).text
tokens_a = set(a.split('"'))
tokens_b = set(b.split('"'))
a_minus_b = tokens_a.difference(tokens_b)
b_minus_a = tokens_b.difference(tokens_a)
print(a_minus_b)
print(b_minus_a)
print(len(a_minus_b))
pri... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | utils/update_site_data.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:48.315519 | #!/usr/bin/env python3
"""Maigret: Supported Site Listing with Alexa ranking and country tags
This module generates the listing of supported sites in file `SITES.md`
and pretty prints file with sites data.
"""
import sys
import socket
import requests
import logging
import threading
import xml.etree.ElementTree as ET
fr... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | maigret/sites.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:49.494490 | # ****************************** -*-
"""Maigret Sites Information"""
import copy
import json
import sys
from typing import Optional, List, Dict, Any, Tuple
from .utils import CaseConverter, URLMatcher, is_country_tag
class MaigretEngine:
site: Dict[str, Any] = {}
def __init__(self, name, data):
self... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | maigret/submit.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:49.638780 | import asyncio
import json
import re
import os
import logging
from typing import Any, Dict, List, Optional, Tuple
from aiohttp import ClientSession, TCPConnector
import cloudscraper # type: ignore[import-untyped]
from colorama import Fore, Style
from .activation import import_aiohttp_cookies
from .result import Maig... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_notify.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:50.867733 | from maigret.errors import CheckError
from maigret.notify import QueryNotifyPrint
from maigret.result import MaigretCheckStatus, MaigretCheckResult
def test_notify_illegal():
n = QueryNotifyPrint(color=False)
assert (
n.update(
MaigretCheckResult(
username="test",
... |
soxoj/maigret | https://github.com/soxoj/maigret | null | null | null | null | 23,748 | null | null | mit | null | null | null | null | null | null | null | tests/test_maigret.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:51.277547 | """Maigret main module test functions"""
import asyncio
import copy
from unittest.mock import patch
import pytest
from mock import Mock
from maigret.maigret import self_check, maigret
from maigret.maigret import (
extract_ids_from_page,
extract_ids_from_results,
)
from maigret.checking import site_self_check... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/gat.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.560499 | import argparse
import torch
import torch.nn.functional as F
from citation import get_planetoid_dataset, random_planetoid_splits, run
from torch_geometric.nn import GATConv
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str, required=T... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/datasets.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.562121 | import os.path as osp
import torch_geometric.transforms as T
from torch_geometric.datasets import Planetoid
def get_planetoid_dataset(name, normalize_features=False, transform=None):
path = osp.join(osp.dirname(osp.realpath(__file__)), '..', 'data', name)
dataset = Planetoid(path, name)
if transform is ... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/sgc.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.563006 | import argparse
import torch
import torch.nn.functional as F
from citation import get_planetoid_dataset, random_planetoid_splits, run
from torch_geometric.nn import SGConv
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str, required=Tr... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/cheb.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.586409 | import argparse
import torch
import torch.nn.functional as F
from citation import get_planetoid_dataset, random_planetoid_splits, run
from torch_geometric.nn import ChebConv
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str, required=... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/appnp.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.587940 | import argparse
import torch
import torch.nn.functional as F
from citation import get_planetoid_dataset, random_planetoid_splits, run
from torch.nn import Linear
from torch_geometric.nn import APPNP
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParser()
parser.add_argument('--data... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/arma.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.588962 | import argparse
import torch
import torch.nn.functional as F
from citation import get_planetoid_dataset, random_planetoid_splits, run
from torch_geometric.nn import ARMAConv
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str, required=... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/train_eval.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.590165 | import time
import torch
import torch.nn.functional as F
from torch import tensor
from torch.optim import Adam
from torch_geometric.profile import timeit, torch_profile
from torch_geometric.utils import index_to_mask
if torch.cuda.is_available():
device = torch.device('cuda')
elif hasattr(torch.backends, 'mps') ... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.635035 | from .datasets import get_planetoid_dataset
from .train_eval import random_planetoid_splits, run
__all__ = [
'get_planetoid_dataset',
'random_planetoid_splits',
'run',
]
|
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/gcn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.673832 | import argparse
import torch
import torch.nn.functional as F
from citation import get_planetoid_dataset, random_planetoid_splits, run
from torch_geometric.nn import GCNConv
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str, required=T... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/citation/statistics.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:54.675398 | from citation import get_planetoid_dataset
def print_dataset(dataset):
data = dataset[0]
print('Name', dataset)
print('Nodes', data.num_nodes)
print('Edges', data.num_edges // 2)
print('Features', dataset.num_features)
print('Classes', dataset.num_classes)
print('Label rate', data.train_ma... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/inference/inference_benchmark.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.187128 | import argparse
import warnings
from collections import defaultdict
from contextlib import nullcontext
import torch
from benchmark.utils import (
emit_itt,
get_dataset_with_transformation,
get_model,
get_split_masks,
save_benchmark_data,
test,
write_to_csv,
)
from torch_geometric.io import... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/asap.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.188180 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import (
ASAPooling,
GraphConv,
JumpingKnowledge,
global_mean_pool,
)
class ASAP(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden, ratio=0.8, dropout=0):
super().__init__()
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.232021 | from .datasets import get_dataset
from .train_eval import cross_validation_with_val_set
__all__ = [
'get_dataset',
'cross_validation_with_val_set',
]
|
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/edge_pool.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.261394 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import (
EdgePooling,
GraphConv,
JumpingKnowledge,
global_mean_pool,
)
class EdgePool(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
self.conv1 =... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/diff_pool.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.262425 | from math import ceil
import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import DenseSAGEConv, JumpingKnowledge, dense_diff_pool
class Block(torch.nn.Module):
def __init__(self, in_channels, hidden_channels, out_channels, mode='cat'):
super().__init__()
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/gin.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.263770 | import torch
import torch.nn.functional as F
from torch.nn import BatchNorm1d as BN
from torch.nn import Linear, ReLU, Sequential
from torch_geometric.nn import GINConv, JumpingKnowledge, global_mean_pool
class GIN0(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/datasets.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.299661 | import os.path as osp
import torch
import torch_geometric.transforms as T
from torch_geometric.datasets import TUDataset
from torch_geometric.utils import degree
class NormalizedDegree:
def __init__(self, mean, std):
self.mean = mean
self.std = std
def __call__(self, data):
deg = de... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/global_attention.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.301025 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import AttentionalAggregation, SAGEConv
class GlobalAttentionNet(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
self.conv1 = SAGEConv(dataset.num_features, hidde... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/gcn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.373353 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import GCNConv, JumpingKnowledge, global_mean_pool
class GCN(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
self.conv1 = GCNConv(dataset.num_features, hidden)
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/graclus.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.411957 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.data import Batch
from torch_geometric.nn import (
GraphConv,
JumpingKnowledge,
global_mean_pool,
graclus,
max_pool,
)
class Graclus(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/graph_sage.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.824794 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import JumpingKnowledge, SAGEConv, global_add_pool
class GraphSAGE(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
self.conv1 = SAGEConv(dataset.num_features, hid... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/main.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.825355 | import argparse
from itertools import product
from asap import ASAP
from datasets import get_dataset
from diff_pool import DiffPool
from edge_pool import EdgePool
from gcn import GCN, GCNWithJK
from gin import GIN, GIN0, GIN0WithJK, GINWithJK
from global_attention import GlobalAttentionNet
from graclus import Graclus
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/main_performance.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.845868 | import argparse
from itertools import product
import torch
from datasets import get_dataset
from gcn import GCN
from gin import GIN
from graph_sage import GraphSAGE
from train_eval import eval_acc, inference_run, train
from torch_geometric import seed_everything
from torch_geometric.loader import DataLoader
from torc... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/set2set.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.863222 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import SAGEConv, Set2Set
class Set2SetNet(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
self.conv1 = SAGEConv(dataset.num_features, hidden)
self.convs =... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/sag_pool.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.887841 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import (
GraphConv,
JumpingKnowledge,
SAGPooling,
global_mean_pool,
)
class SAGPool(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden, ratio=0.8):
super().__init__()
sel... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/sort_pool.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.888438 | import torch
import torch.nn.functional as F
from torch.nn import Conv1d, Linear
from torch_geometric.nn import SAGEConv, SortAggregation
class SortPool(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden):
super().__init__()
self.conv1 = SAGEConv(dataset.num_features, hidden)
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/top_k.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.918051 | import torch
import torch.nn.functional as F
from torch.nn import Linear
from torch_geometric.nn import (
GraphConv,
JumpingKnowledge,
TopKPooling,
global_mean_pool,
)
class TopK(torch.nn.Module):
def __init__(self, dataset, num_layers, hidden, ratio=0.8):
super().__init__()
self.... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/statistics.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:55.956689 | from kernel.datasets import get_dataset
def print_dataset(dataset):
num_nodes = num_edges = 0
for data in dataset:
num_nodes += data.num_nodes
num_edges += data.num_edges
print('Name', dataset)
print('Graphs', len(dataset))
print('Nodes', num_nodes / len(dataset))
print('Edges... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/loader/neighbor_loader.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.049028 | import argparse
import ast
import os.path as osp
from contextlib import nullcontext
from timeit import default_timer
import tqdm
from ogb.nodeproppred import PygNodePropPredDataset
import torch_geometric.transforms as T
from torch_geometric.datasets import OGB_MAG
from torch_geometric.loader import NeighborLoader
fro... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/kernel/train_eval.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.070141 | import time
import torch
import torch.nn.functional as F
from sklearn.model_selection import StratifiedKFold
from torch import tensor
from torch.optim import Adam
from torch_geometric.loader import DataLoader
from torch_geometric.loader import DenseDataLoader as DenseLoader
if torch.cuda.is_available():
device =... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/multi_gpu/training/training_benchmark_cuda.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.416844 | import argparse
import os
from typing import Union
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from benchmark.multi_gpu.training.common import (
get_predefined_args,
run,
supported_sets,
)
from benchmark.utils import get_dataset
from torch_geometric.data import Data, H... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/multi_gpu/training/training_benchmark_xpu.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.460408 | import os
from typing import Any, Tuple
import intel_extension_for_pytorch as ipex
import oneccl_bindings_for_pytorch # noqa
import torch.distributed as dist
from benchmark.multi_gpu.training.common import (
get_predefined_args,
run,
supported_sets,
)
from benchmark.utils import get_dataset
def get_dis... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/datasets.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.494325 | import os.path as osp
import torch_geometric.transforms as T
from torch_geometric.datasets import ModelNet
def get_dataset(num_points):
name = 'ModelNet10'
path = osp.join(osp.dirname(osp.realpath(__file__)), '..', 'data', name)
pre_transform = T.NormalizeScale()
transform = T.SamplePoints(num_points... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/edge_cnn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.495272 | import argparse
import torch
import torch.nn.functional as F
from points.datasets import get_dataset
from points.train_eval import run
from torch.nn import Linear as Lin
from torch.nn import ReLU
from torch.nn import Sequential as Seq
from torch_geometric.nn import DynamicEdgeConv, global_max_pool
from torch_geometri... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/mpnn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.523987 | import argparse
import torch
import torch.nn.functional as F
from points.datasets import get_dataset
from points.train_eval import run
from torch.nn import Linear as Lin
from torch.nn import ReLU
from torch.nn import Sequential as Seq
from torch_geometric.nn import NNConv, fps, global_mean_pool, radius_graph
from tor... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.525017 | from .datasets import get_dataset
from .train_eval import run
__all__ = [
'get_dataset',
'run',
]
|
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/multi_gpu/training/common.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.561387 | import argparse
import ast
from time import perf_counter
from typing import Any, Callable, Tuple, Union
import torch
import torch.distributed as dist
import torch.nn.functional as F
from torch.nn.parallel import DistributedDataParallel as DDP
from benchmark.utils import get_model, get_split_masks, test
from torch_geo... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/point_cnn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.562655 | import argparse
import torch
import torch.nn.functional as F
from points.datasets import get_dataset
from points.train_eval import run
from torch.nn import Linear as Lin
from torch_geometric.nn import XConv, fps, global_mean_pool
from torch_geometric.profile import rename_profile_file
parser = argparse.ArgumentParse... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/point_net.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.625766 | import argparse
import torch
import torch.nn.functional as F
from points.datasets import get_dataset
from points.train_eval import run
from torch.nn import Linear as Lin
from torch.nn import ReLU
from torch.nn import Sequential as Seq
from torch_geometric.nn import PointNetConv, fps, global_max_pool, radius_graph
fro... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/spline_cnn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:56.669593 | import argparse
import torch
import torch.nn.functional as F
from points.datasets import get_dataset
from points.train_eval import run
from torch.nn import Linear as Lin
from torch_geometric.nn import SplineConv, fps, global_mean_pool, radius_graph
from torch_geometric.profile import rename_profile_file
parser = arg... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/train_eval.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.099562 | import time
import torch
import torch.nn.functional as F
from torch.optim import Adam
from torch_geometric.loader import DataLoader
from torch_geometric.profile import timeit, torch_profile
if torch.cuda.is_available():
device = torch.device('cuda')
elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_a... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/dgl/gcn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.142774 | import dgl.function as fn
import torch
import torch.nn.functional as F
from torch.nn import Parameter
from torch_geometric.nn.inits import glorot, zeros
class GCNConv(torch.nn.Module):
def __init__(self, g, in_channels, out_channels):
super().__init__()
self.g = g
self.weight = Parameter(... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/dgl/hidden.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.143420 | import os
import sys
import warnings
warnings.filterwarnings('ignore')
class HiddenPrint:
def __enter__(self):
self._original_stdout = sys.stdout
sys.stdout = open(os.devnull, 'w')
def __exit__(self, exc_type, exc_val, exc_tb):
sys.stdout.close()
sys.stdout = self._original_s... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/dgl/rgcn.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.156078 | import dgl.function as fn
import torch
import torch.nn.functional as F
from torch.nn import Parameter as Param
from torch_geometric.nn.inits import uniform
class RGCNConv(torch.nn.Module):
def __init__(self, g, in_channels, out_channels, num_relations, num_bases):
super().__init__()
self.g = g
... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/points/statistics.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.156636 | from points.datasets import get_dataset
from torch_geometric.transforms import RadiusGraph
def print_dataset(train_dataset, test_dataset):
num_nodes = num_edges = 0
for data in train_dataset:
data = RadiusGraph(0.2)(data)
num_nodes += data.num_nodes
num_edges += data.num_edges
for... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/dgl/main.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.185370 | from itertools import product
import dgl
import torch
from dgl import DGLGraph
from dgl.contrib.data import load_data
from dgl.data import citation_graph
from runtime.dgl.gat import GAT, GATSPMV
from runtime.dgl.gcn import GCN, GCNSPMV
from runtime.dgl.hidden import HiddenPrint
from runtime.dgl.rgcn import RGCN, RGCNS... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/dgl/gat.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.225291 | import dgl.function as fn
import torch
import torch.nn.functional as F
from dgl.nn.pytorch import EdgeSoftmax
from torch.nn import Parameter
from torch_geometric.nn.inits import glorot, zeros
class GATConv(torch.nn.Module):
def __init__(self, g, in_channels, out_channels, heads=1,
negative_slope... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/dgl/train.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.254919 | import time
import torch
import torch.nn.functional as F
def train_runtime(model, data, epochs, device):
if hasattr(data, 'features'):
x = torch.tensor(data.features, dtype=torch.float, device=device)
else:
x = None
mask = data.train_mask if hasattr(data, 'train_mask') else data.train_idx... |
pyg-team/pytorch_geometric | https://github.com/pyg-team/pytorch_geometric | null | null | null | null | 23,718 | null | null | mit | null | null | null | null | null | null | null | benchmark/runtime/gat.py | null | null | null | null | null | null | Python | 2026-05-04T02:28:57.323483 | import torch
import torch.nn.functional as F
from torch_geometric.nn import GATConv
class GAT(torch.nn.Module):
def __init__(self, in_channels, out_channels):
super().__init__()
self.conv1 = GATConv(in_channels, 8, heads=8, dropout=0.6)
self.conv2 = GATConv(8 * 8, out_channels, dropout=0.... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/csv_scraper_graph/ollama/csv_scraper_graph_multi_ollama.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.390699 | """
Basic example of scraping pipeline using CSVScraperMultiGraph from CSV documents
"""
import os
from scrapegraphai.graphs import CSVScraperMultiGraph
from scrapegraphai.utils import prettify_exec_info
# ************************************************
# Read the CSV file
# ****************************************... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/csv_scraper_graph/openai/csv_scraper_graph_multi_openai.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.391244 | """
Basic example of scraping pipeline using CSVScraperMultiGraph from CSV documents
"""
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import CSVScraperMultiGraph
from scrapegraphai.utils import prettify_exec_info
load_dotenv()
# ************************************************
# Read the CSV f... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/custom_graph/openai/custom_graph_openai.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.401493 | """
Example of custom graph using existing nodes
"""
import os
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from scrapegraphai.graphs import BaseGraph
from scrapegraphai.nodes import (
FetchNode,
GenerateAnswerNode,
ParseNode,
RAGNode,
RobotsNode,
)
lo... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | docs/source/conf.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.402825 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/csv_scraper_graph/openai/csv_scraper_openai.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.405132 | """
Basic example of scraping pipeline using CSVScraperGraph from CSV documents
"""
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import CSVScraperGraph
from scrapegraphai.utils import prettify_exec_info
load_dotenv()
# ************************************************
# Read the CSV file
# ***... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/code_generator_graph/ollama/code_generator_graph_ollama.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.406170 | """
Basic example of scraping pipeline using Code Generator with schema
"""
from typing import List
from dotenv import load_dotenv
from pydantic import BaseModel, Field
from scrapegraphai.graphs import CodeGeneratorGraph
load_dotenv()
# ************************************************
# Define the output schema fo... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/custom_graph/ollama/custom_graph_ollama.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.409765 | """
Example of custom graph using existing nodes
"""
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from scrapegraphai.graphs import BaseGraph
from scrapegraphai.nodes import (
FetchNode,
GenerateAnswerNode,
ParseNode,
RobotsNode,
)
# ************************************************
# Defi... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/csv_scraper_graph/ollama/csv_scraper_ollama.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.411029 | """
Basic example of scraping pipeline using CSVScraperGraph from CSV documents
"""
import os
from scrapegraphai.graphs import CSVScraperGraph
from scrapegraphai.utils import prettify_exec_info
# ************************************************
# Read the CSV file
# ************************************************
... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/code_generator_graph/openai/code_generator_graph_openai.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.421112 | """
Basic example of scraping pipeline using Code Generator with schema
"""
import os
from typing import List
from dotenv import load_dotenv
from pydantic import BaseModel, Field
from scrapegraphai.graphs import CodeGeneratorGraph
load_dotenv()
# ************************************************
# Define the output... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/depth_search_graph/ollama/depth_search_graph_ollama.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:00.421616 | """
depth_search_graph_opeani example
"""
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import DepthSearchGraph
load_dotenv()
openai_key = os.getenv("OPENAI_APIKEY")
graph_config = {
"llm": {
"model": "ollama/llama3.1",
"temperature": 0,
"format": "json", # Ollama... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/document_scraper_graph/openai/document_scraper_openai.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.220006 | """
document_scraper example
"""
import json
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import DocumentScraperGraph
load_dotenv()
openai_key = os.getenv("OPENAI_APIKEY")
graph_config = {
"llm": {
"api_key": openai_key,
"model": "openai/gpt-4o",
}
}
source = """
... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/authenticated_playwright.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.220984 | """
Example leveraging a state file containing session cookies which
might be leveraged to authenticate to a website and scrape protected
content.
"""
import os
import random
from dotenv import load_dotenv
# import playwright so we can use it to create the state file
from playwright.async_api import async_playwright... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/document_scraper_graph/ollama/document_scraper_ollama.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.391342 | """
document_scraper example
"""
import json
from dotenv import load_dotenv
from scrapegraphai.graphs import DocumentScraperGraph
load_dotenv()
# ************************************************
# Define the configuration for the graph
# ************************************************
graph_config = {
"llm": ... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/custom_prompt.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.391854 | """
Basic example of scraping pipeline using SmartScraper
"""
import json
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import SmartScraperGraph
from scrapegraphai.utils import prettify_exec_info
load_dotenv()
# ************************************************
# Define the configuration for t... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/cond_smartscraper_usage.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.400584 | """
Basic example of scraping pipeline using SmartScraperMultiConcatGraph with Groq
"""
import json
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import SmartScraperGraph
load_dotenv()
# ************************************************
# Define the configuration for the graph
# ***************... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/chromium_selenium.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.408427 | import asyncio
import json
import os
from aiohttp import ClientError
from dotenv import load_dotenv
from scrapegraphai.docloaders.chromium import ( # Import your ChromiumLoader class
ChromiumLoader,
)
from scrapegraphai.graphs import SmartScraperGraph
# Load environment variables for API keys
load_dotenv()
# ... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/force_mode.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.409666 | """
Basic example of scraping pipeline using SmartScraper
"""
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import SmartScraperGraph
from scrapegraphai.utils import prettify_exec_info
load_dotenv()
# ************************************************
# Define the configuration for the graph
# *... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/browser_base_integration.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:01.438186 | """
Basic example of scraping pipeline using SmartScraper
"""
import json
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import SmartScraperGraph
from scrapegraphai.utils import prettify_exec_info
load_dotenv()
# ************************************************
# Define the configuration for th... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/html_mode.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:02.118463 | """
Basic example of scraping pipeline using SmartScraper
By default smart scraper converts in md format the
code. If you want to just use the original code, you have
to specify in the confi
"""
import json
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import SmartScraperGraph
from scrapegraphai... |
ScrapeGraphAI/Scrapegraph-ai | https://github.com/ScrapeGraphAI/Scrapegraph-ai | null | null | null | null | 23,444 | null | null | mit | null | null | null | null | null | null | null | examples/extras/conditional_usage.py | null | null | null | null | null | null | Python | 2026-05-04T02:29:02.127457 | """
Basic example of scraping pipeline using SmartScraperMultiConcatGraph with Groq
"""
import json
import os
from dotenv import load_dotenv
from scrapegraphai.graphs import SmartScraperMultiGraph
load_dotenv()
# ************************************************
# Define the configuration for the graph
# **********... |
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