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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/centerpoint_02pillar_second_secfpn_nus.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:14.881974 | voxel_size = [0.2, 0.2, 8]
model = dict(
type='CenterPoint',
pts_voxel_layer=dict(
max_num_points=20, voxel_size=voxel_size, max_voxels=(30000, 40000)),
pts_voxel_encoder=dict(
type='PillarFeatureNet',
in_channels=5,
feat_channels=[64],
with_distance=False,
vo... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/centerpoint_01voxel_second_secfpn_nus.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:14.883072 | voxel_size = [0.1, 0.1, 0.2]
model = dict(
type='CenterPoint',
pts_voxel_layer=dict(
max_num_points=10, voxel_size=voxel_size, max_voxels=(90000, 120000)),
pts_voxel_encoder=dict(type='HardSimpleVFE', num_features=5),
pts_middle_encoder=dict(
type='SparseEncoder',
in_channels=5,
... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/centerpoint_dcn_nus.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:14.958820 | voxel_size = [0.1, 0.1, 0.2]
model = dict(
type='CenterPoint',
pts_bbox_head=dict(
type='CenterHead',
in_channels=sum([256, 256]),
tasks=[
dict(num_class=1, class_names=['car']),
dict(num_class=2, class_names=['truck', 'construction_vehicle']),
dict(nu... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_pointpillars_fpn_lyft.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:14.986346 | _base_ = './hv_pointpillars_fpn_nus.py'
# model settings (based on nuScenes model settings)
# Voxel size for voxel encoder
# Usually voxel size is changed consistently with the point cloud range
# If point cloud range is modified, do remember to change all related
# keys in the config.
model = dict(
pts_voxel_laye... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/h3dnet.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.050071 | primitive_z_cfg = dict(
type='PrimitiveHead',
num_dims=2,
num_classes=18,
primitive_mode='z',
upper_thresh=100.0,
surface_thresh=0.5,
vote_module_cfg=dict(
in_channels=256,
vote_per_seed=1,
gt_per_seed=1,
conv_channels=(256, 256),
conv_cfg=dict(type='C... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_pointpillars_fpn_nus.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.058613 | # model settings
# Voxel size for voxel encoder
# Usually voxel size is changed consistently with the point cloud range
# If point cloud range is modified, do remember to change all related
# keys in the config.
voxel_size = [0.25, 0.25, 8]
model = dict(
type='MVXFasterRCNN',
pts_voxel_layer=dict(
max_n... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_pointpillars_secfpn_kitti.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.082866 | voxel_size = [0.16, 0.16, 4]
model = dict(
type='VoxelNet',
voxel_layer=dict(
max_num_points=32,
point_cloud_range=[0, -39.68, -3, 69.12, 39.68, 1],
voxel_size=voxel_size,
max_voxels=(16000, 40000)),
voxel_encoder=dict(
type='PillarFeatureNet',
in_channels=4,
... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_pointpillars_fpn_range100_lyft.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.155528 | _base_ = './hv_pointpillars_fpn_nus.py'
# model settings (based on nuScenes model settings)
# Voxel size for voxel encoder
# Usually voxel size is changed consistently with the point cloud range
# If point cloud range is modified, do remember to change all related
# keys in the config.
model = dict(
pts_voxel_laye... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_pointpillars_secfpn_waymo.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.229084 | # model settings
# Voxel size for voxel encoder
# Usually voxel size is changed consistently with the point cloud range
# If point cloud range is modified, do remember to change all related
# keys in the config.
voxel_size = [0.32, 0.32, 6]
model = dict(
type='MVXFasterRCNN',
pts_voxel_layer=dict(
max_n... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_second_secfpn_kitti.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.246909 | model = dict(
type='VoxelNet',
voxel_layer=dict(
max_num_points=5,
point_cloud_range=[0, -40, -3, 70.4, 40, 1],
voxel_size=[0.05, 0.05, 0.1],
max_voxels=(16000, 40000)),
voxel_encoder=dict(type='HardSimpleVFE'),
middle_encoder=dict(
type='SparseEncoder',
i... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/hv_second_secfpn_waymo.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.449817 | # model settings
# Voxel size for voxel encoder
# Usually voxel size is changed consistently with the point cloud range
# If point cloud range is modified, do remember to change all related
# keys in the config.
voxel_size = [0.08, 0.08, 0.1]
model = dict(
type='VoxelNet',
voxel_layer=dict(
max_num_poin... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/imvotenet_image.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.467318 | model = dict(
type='ImVoteNet',
img_backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
style='caffe'),
img_neck=dict(
type='FPN... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/mask_rcnn_r50_fpn.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.493767 | # model settings
model = dict(
type='MaskRCNN',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/sst_base.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.552466 | # Configurations of neck, head and assigner, same as PointPillar
model = dict(
type='DynamicVoxelNet',
neck=dict(
type='SECONDFPN',
norm_cfg=dict(type='naiveSyncBN2d', eps=1e-3, momentum=0.01),
in_channels=[128,],
upsample_strides=[1,],
out_channels=[384, ]
),
b... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/cosine.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.612943 | # This schedule is mainly used by models with dynamic voxelization
# optimizer
lr = 0.003 # max learning rate
optimizer = dict(
type='AdamW',
lr=lr,
betas=(0.95, 0.99), # the momentum is change during training
weight_decay=0.001)
optimizer_config = dict(grad_clip=dict(max_norm=10, norm_type=2))
lr_co... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/models/votenet.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.617641 | model = dict(
type='VoteNet',
backbone=dict(
type='PointNet2SASSG',
in_channels=4,
num_points=(2048, 1024, 512, 256),
radius=(0.2, 0.4, 0.8, 1.2),
num_samples=(64, 32, 16, 16),
sa_channels=((64, 64, 128), (128, 128, 256), (128, 128, 256),
(128... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/cosine_2x.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.650330 | lr=1e-5
optimizer = dict(
type='AdamW',
lr=lr,
betas=(0.9, 0.999), # the momentum is change during training
weight_decay=0.05,
paramwise_cfg=dict(custom_keys={'norm': dict(decay_mult=0.)}),
)
optimizer_config = dict(grad_clip=dict(max_norm=10, norm_type=2))
lr_config = dict(
policy='cyclic'... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/cosine_iter.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.718720 | # For nuScenes dataset, we usually evaluate the model at the end of training.
# Since the models are trained by 24 epochs by default, we set evaluation
# interval to be 20. Please change the interval accordingly if you do not
# use a default schedule.
# optimizer
# This schedule is mainly used by models on nuScenes dat... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/cyclic_40e.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.792309 | # The schedule is usually used by models trained on KITTI dataset
# The learning rate set in the cyclic schedule is the initial learning rate
# rather than the max learning rate. Since the target_ratio is (10, 1e-4),
# the learning rate will change from 0.0018 to 0.018, than go to 0.0018*1e-4
lr = 0.0018
# The optimiz... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/cyclic_20e.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:15.792820 | # For nuScenes dataset, we usually evaluate the model at the end of training.
# Since the models are trained by 24 epochs by default, we set evaluation
# interval to be 20. Please change the interval accordingly if you do not
# use a default schedule.
# optimizer
# This schedule is mainly used by models on nuScenes dat... |
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/mmdet_schedule_1x.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:16.044568 | # optimizer
optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=[8, 11])
total_epochs = 12
|
ADLab-AutoDrive/BEVFusion | https://github.com/ADLab-AutoDrive/BEVFusion | null | null | null | null | 963 | null | null | apache-2.0 | null | null | null | null | null | null | null | configs/_base_/schedules/schedule_1x.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:16.045048 | # optimizer
# This schedule is mainly used by models on nuScenes dataset
optimizer = dict(type='AdamW', lr=0.001, weight_decay=0.01)
# max_norm=10 is better for SECOND
optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=1000,
w... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | evaluation/evaluation.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.569516 | # pylint: skip-file
# flake8: noqa
import os
import json
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
import pickle
import numba
from run_script import data_prep
from sklearn.svm import SVC, LinearSVC
from sklearn.model_selection import StratifiedKFold, LeaveOneOut
from sklearn.neighbo... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | demo/demo_utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.695410 | import matplotlib.pyplot as plt
def generate_figure(embedding, labels, title):
fig, ax = plt.subplots(1, 1, figsize=(6, 6))
ax.scatter(embedding[:, 0], embedding[:, 1], s=0.5, c=labels, cmap='Spectral')
ax.axis('off')
ax.set_title(title)
plt.savefig(f"./{title}.png")
def generate_combined_figure... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | demo/transform_demo.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.695947 | '''
A script that demonstrates the transform feature of pacmap.
The MNIST dataset will be separated into n-folds, where (n-1) folds will be used
to fit a PaCMAP instance, and the last fold will be used as a test set.
We use the transform feature to map the test set into the already constructed
embedding space.
'''
imp... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | experiments/FA2.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.699570 | # pylint: skip-file
# flake8: noqa
import os
import json
import numpy as np
import matplotlib.pyplot as plt
from run_script import data_prep
from fa2 import ForceAtlas2 as FA2
from sklearn.preprocessing import scale
from sklearn.decomposition import PCA
from sklearn.neighbors import NearestNeighbors
def transform_by_... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | experiments/run_experiments_LargeVis.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.700511 | # pylint: skip-file
# flake8: noqa
import FlowCal
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import LargeVis
from sklearn import manifold, datasets
from time import time
from sklearn.decomposition import PCA
from sklearn.datasets import make_swiss_roll, make_s_curve
def data_path_finder(... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | demo/specify_nn_demo.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.701584 | import pacmap
import numpy as np
import matplotlib.pyplot as plt
from annoy import AnnoyIndex
# loading preprocessed coil_20 dataset
X = np.load("../data/coil_20.npy", allow_pickle=True)
X = X.reshape(X.shape[0], -1)
y = np.load("../data/coil_20_labels.npy", allow_pickle=True)
# create nearest neighbor pairs
# here w... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | experiments/run_experiments_tSNE.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.702893 | # pylint: skip-file
# flake8: noqa
import FlowCal
import json
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import manifold, datasets
from time import time
from MulticoreTSNE import MulticoreTSNE as TSNE
from sklearn.decomposition import PCA
from sklearn.datasets import make_swis... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | rainbow_plot/rainbow_plots_for_good_loss.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.704410 | # pylint: skip-file
# flake8: noqa
import matplotlib.pyplot as plt
import numpy as np
from scipy import integrate
cmap_fig = plt.cm.get_cmap("Spectral")
cmap = plt.cm.get_cmap("RdYlGn_r")
cmap_ = plt.cm.get_cmap("gist_yarg")
# If you would like discrete ladders, use ladder_map
# Otherwise, just leave it, see exampl... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | demo/basic_demo.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.705736 | import pacmap
import numpy as np
import matplotlib.pyplot as plt
# loading preprocessed coil_20 dataset
# you can change it with any dataset that is in the ndarray format, with the shape (N, D)
# where N is the number of samples and D is the dimension of each sample
X = np.load("../data/coil_20.npy", allow_pickle=True... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | experiments/run_experiments.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:18.707208 | # pylint: skip-file
# flake8: noqa
import umap
import trimap
import FlowCal
import json
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn import manifold, datasets
from time import time
from tqdm import tqdm
from sklearn.decomposition import PCA
from PaCMAP import PaCMAP
from sklearn.... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | source/pacmap/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.310796 | from .pacmap import PaCMAP, sample_neighbors_pair, LocalMAP
from importlib.metadata import version, PackageNotFoundError
try:
__version__ = version('pacmap')
except PackageNotFoundError:
__version__ = "unknown"
__all__ = ["PaCMAP", "sample_neighbors_pair", "LocalMAP"]
|
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_transform.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.543867 | '''A script that tests the transform feature of pacmap
'''
import pacmap
import numpy as np
import pytest
from sklearn.model_selection import StratifiedKFold
from test_utils import generate_combined_figure, mnist_data
def setup_transform_test(mnist_data, n_splits, save_tree=False):
"""Setup test data and run PaCM... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_transform_iris.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.718579 | '''
A script that tests the transform feature of pacmap
'''
import pacmap
import numpy as np
import pytest
from test_utils import generate_combined_figure, iris_data
def test_iris_transform_with_tree(iris_data):
"""Test PaCMAP transform functionality with save_tree=True."""
iris, label = iris_data
reduce... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_localmap.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.722105 | '''
A general test script that ensures LocalMAP can be successfully loaded and run with different backends.
Refactored to use pytest parametrization for better test isolation and reporting.
'''
import pytest
from pacmap import pacmap
import numpy as np
import os
from test_utils import get_available_backends, sample_dat... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/conftest.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.722612 | """
Pytest configuration file to set up the test environment.
"""
import sys
from pathlib import Path
import pytest
# Add the source directory to Python path so we can import pacmap
source_dir = Path(__file__).parent.parent / "source"
sys.path.insert(0, str(source_dir))
# Ensure test output directory exists
test_out... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_general.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.723924 | '''
A general test script that ensures PaCMAP can be successfully loaded and run with different backends.
Refactored to use pytest parametrization for better test isolation and reporting.
'''
import pytest
from pacmap import pacmap
import numpy as np
import matplotlib.pyplot as plt
from test_utils import get_available_... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_randomness.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.724497 | '''
A test script ensuring PaCMAP produces deterministic results across backends.
'''
import pytest
from pacmap import pacmap
import numpy as np
from test_utils import get_available_backends, sample_data
@pytest.mark.parametrize("backend", get_available_backends())
def test_pacmap_randomness_deterministic(backend, sam... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_metric.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.725000 | '''
A test script that ensures PaCMAP can be successfully used with other metrics across different backends.
Refactored for pytest with optimized metric-backend mapping.
'''
import pytest
from pacmap import pacmap
import numpy as np
from test_utils import get_available_backends, get_backend_metric_pairs, sample_data, o... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/data_loader.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.749902 | """
Data loader utilities for loading datasets from fixtures.
"""
import json
from sklearn.datasets import fetch_openml
def load_datasets_from_fixture(path=None):
"""
Load datasets from a JSON fixture file.
Args:
path (str): Path to the JSON fixture file containing dataset specifications.
... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | source/pacmap/pacmap.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:19.750790 | import datetime
import logging
import math
import os
import time
import pickle as pkl
from typing import Optional
import numba
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.decomposition import TruncatedSVD, PCA
from sklearn.utils.validation import check_is_fitted
from sklearn import preproces... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_transform_tree.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:20.128364 | '''A script that tests the transform feature of pacmap, with the trees
'''
import numpy as np
from test_transform import mnist_data, setup_transform_test
def test_transform_tree_2_splits(mnist_data):
"""Test transform feature with trees and 2 splits"""
X_train, X_test, embeddings = setup_transform_test(mnist... |
YingfanWang/PaCMAP | https://github.com/YingfanWang/PaCMAP | null | null | null | null | 962 | null | null | apache-2.0 | null | null | null | null | null | null | null | test/test_utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:20.751161 | import os
import pytest
import numpy as np
import matplotlib.pyplot as plt
import tempfile
from pathlib import Path
def get_available_backends():
backends = ['annoy']
try: import faiss; backends.append('faiss')
except ImportError: pass
try: import voyager; backends.append('voyager')
except Impor... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/autogen/agentchat/mcp.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.293953 | import ast
import json
from agentic_radar.analysis.ast_utils import (
kwargize_params,
parse_simple_function_call_assignment,
)
from .models import MCPServer
MCP_SERVER_TYPES = [
"StdioServerParams",
"SseServerParams",
"StreamableHttpServerParams",
]
STDIO_SERVER_PARAM_NAMES = [
"command",
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/autogen/agentchat/graph.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.294581 | import re
from agentic_radar.graph import (
Agent,
EdgeDefinition,
GraphDefinition,
NodeDefinition,
NodeType,
ToolType,
)
from .models import Agent as AutogenAgent
from .models import Team, TeamType
def get_swarm_team_edges(team: Team) -> list[EdgeDefinition]:
assert len(team.members) > ... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/analyze.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.305868 | import abc
from ..graph import GraphDefinition
class Analyzer(abc.ABC):
def analyze(self, root_directory: str) -> GraphDefinition:
raise NotImplementedError()
|
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/ast_utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.312484 | import ast
from typing import Generator, Optional, Union
from pydantic import BaseModel
from agentic_radar.analysis.utils import walk_python_files
def get_nth_arg_value(call_node: ast.Call, n: int) -> ast.AST:
"""
Retrieves the value of a specific positional argument from an ast.Call node.
Args:
ca... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/autogen/agentchat/analyze.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.395765 | from pathlib import Path
from agentic_radar.analysis.analyze import Analyzer
from agentic_radar.analysis.ast_utils import walk_and_parse_python_files
from agentic_radar.graph import GraphDefinition
from .graph import create_graph_definition
from .mcp import (
find_listed_mcp_tool_adapters,
find_server_params,... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.399272 | from .analyze import Analyzer
from .autogen import AutogenAgentChatAnalyzer
from .crewai import CrewAIAnalyzer
from .langgraph import LangGraphAnalyzer
from .n8n import N8nAnalyzer
from .openai_agents import OpenAIAgentsAnalyzer
__all__ = [
"Analyzer",
"LangGraphAnalyzer",
"CrewAIAnalyzer",
"N8nAnalyze... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/autogen/agentchat/models.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.874129 | from enum import Enum
from pydantic import BaseModel
class FunctionDefinition(BaseModel):
name: str
description: str
class ModelClient(BaseModel):
name: str
model: str
class FunctionTool(BaseModel):
name: str
description: str
class MCPServer(BaseModel):
name: str
description: st... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/autogen/agentchat/parse.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.892596 | import ast
from agentic_radar.analysis.ast_utils import parse_simple_function_call_assignment
from .models import (
Agent,
FunctionDefinition,
FunctionTool,
MCPServer,
ModelClient,
Team,
TeamType,
)
AUTOGEN_MODELS_IMPORT_PREFIX = "autogen_ext.models"
def find_model_client_imports(trees:... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/models/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.935388 | from .agent import CrewAIAgent, PartialCrewAIAgent
from .graph import CrewAIGraph, CrewAINodeType
from .mcp import CrewAIMCPServer
from .tool import CrewAITool
__all__ = [
"CrewAIGraph",
"CrewAITool",
"CrewAINodeType",
"CrewAIAgent",
"PartialCrewAIAgent",
"CrewAIMCPServer",
]
|
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/graph_converter.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.935907 | from agentic_radar.analysis.crewai.models import (
CrewAIAgent,
CrewAIGraph,
CrewAINodeType,
)
from agentic_radar.analysis.crewai.prompt import build_system_prompt
from agentic_radar.analysis.crewai.tool_categorizer import categorize_tool
from agentic_radar.graph import (
Agent as ReportAgent,
)
from ag... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/crew_process.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.937509 | from collections import defaultdict
from enum import Enum
class CrewProcessType(str, Enum):
SEQUENTIAL = "sequential"
HIERARCHICAL = "hierarchical"
def infer_agent_connections(
task_agent_mapping: dict[str, str],
crew_task_mapping: dict[str, list[str]],
crew_process_mapping: dict[str, CrewProces... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/analyze.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.956565 | from pathlib import Path
from agentic_radar.analysis.analyze import Analyzer
from agentic_radar.analysis.crewai.crew_process import infer_agent_connections
from agentic_radar.analysis.crewai.graph_converter import convert_graph
from agentic_radar.analysis.crewai.models import CrewAIAgent, CrewAIGraph
from agentic_rada... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/models/agent.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.957630 | from typing import Optional
from pydantic import BaseModel
from .mcp import CrewAIMCPServer
from .tool import CrewAITool
class PartialCrewAIAgent(BaseModel):
role: Optional[str] = None
goal: Optional[str] = None
backstory: Optional[str] = None
tools: Optional[list[CrewAITool]] = None
mcp_servers... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/models/graph.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:24.997949 | import json
from enum import Enum
from typing import Optional
from pydantic import BaseModel, Field
from agentic_radar.analysis.crewai.models.mcp import CrewAIMCPServer
from .tool import CrewAITool
class CrewAINodeType(str, Enum):
AGENT = "Agent"
TOOL = "Tool"
CUSTOM_TOOL = "CustomTool"
BASIC = "Ba... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/models/mcp.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:25.029283 | from pydantic import BaseModel
class CrewAIMCPServer(BaseModel):
name: str
params: dict[str, str] = {}
|
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/models/tool.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:25.725634 | from pydantic import BaseModel, Field
class CrewAITool(BaseModel):
name: str = Field(..., description="Name of the tool")
custom: bool = Field(
False, description="Indicator of whether it is a custom or predefined tool"
)
description: str = Field("", description="Short description of what the ... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/__init__.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:25.757300 | from .agents import collect_agents
from .crews import CrewProcessType, collect_crews
from .custom_tools import collect_custom_tools
from .mcp import collect_dicts_and_mcp_params
from .predefined_tools import collect_predefined_tools
from .tasks import collect_tasks
__all__ = [
"collect_agents",
"collect_tasks"... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/custom_tools.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:25.758584 | import ast
from agentic_radar.analysis.crewai.models.tool import CrewAITool
from agentic_radar.analysis.utils import walk_python_files
class CustomToolsVisitor(ast.NodeVisitor):
CREWAI_CUSTOM_TOOL_DECORATOR = "tool"
CREWAI_CUSTOM_TOOL_BASE_CLASS = "BaseTool"
def __init__(self) -> None:
self.cust... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:25.823589 | import ast
from typing import Optional, Sequence, Union, cast
def find_return_of_function_call(
node: Union[ast.AST, Sequence[ast.AST]], function_name: str
) -> Optional[ast.Call]:
"""
Recursively search for and return the function call node contained in an expression of the form 'return {function_name}()... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/mcp.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:25.849247 | import ast
from typing import Union
from agentic_radar.analysis.ast_utils import parse_call
from agentic_radar.analysis.utils import walk_python_files
CREWAI_MCP_STDIO_SERVER_PARAMS_CTOR = "StdioServerParameters"
def collect_dicts_and_mcp_params(root_dir: str) -> dict[str, dict[str, str]]:
"""Parses all Python ... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/predefined_tools.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.028842 | import ast
from agentic_radar.analysis.crewai.models.tool import CrewAITool
from agentic_radar.analysis.crewai.tool_descriptions import (
get_crewai_tools_descriptions,
)
from agentic_radar.analysis.utils import walk_python_files
class PredefinedToolsVisitor(ast.NodeVisitor):
CREWAI_TOOLS_MODULE = "crewai_to... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/crews.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.293768 | import ast
from typing import Optional
from agentic_radar.analysis.crewai.crew_process import CrewProcessType
from agentic_radar.analysis.crewai.parsing.utils import (
find_return_of_function_call,
is_function_call,
)
from agentic_radar.analysis.utils import walk_python_files
class CrewsVisitor(ast.NodeVisit... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/prompt.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.323685 | from typing import cast
from agentic_radar.analysis.crewai.models import CrewAIAgent
def build_system_prompt(agent: CrewAIAgent) -> str:
try:
from crewai.utilities.prompts import I18N, Prompts # type: ignore
except ImportError:
raise ImportError("Please install the crewai package to use this... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/tool_descriptions.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.334465 | import ast
import importlib.util
import os
import re
from typing import Optional
def is_package_installed(package_name: str) -> bool:
"""
Check if a package is installed in the current environment.
Args:
package_name: Name of the package to check
Returns:
True if the package is insta... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/tool_categorizer.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.348092 | import json
import importlib_resources as resources
from agentic_radar.graph import ToolType
def categorize_tool(tool_name: str) -> ToolType:
"""
Load the tool type from the JSON file and return a ToolType.
"""
try:
# Use resources.files().joinpath() to get the path, then use .read_text() to... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/agents.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.381099 | import ast
from typing import Optional
from pydantic import ValidationError
from agentic_radar.analysis.ast_utils import (
get_keyword_arg_value,
get_nth_arg_value,
)
from agentic_radar.analysis.crewai.models import (
CrewAIAgent,
CrewAIMCPServer,
CrewAITool,
PartialCrewAIAgent,
)
from agentic... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/agent_tracking.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.415911 | import ast
from agentic_radar.analysis.langgraph.utils import get_source_from_file
from agentic_radar.analysis.utils import walk_python_files_and_notebooks
def find_agent_llm_variables(root_dir: str) -> set[str]:
"""
Scan all .py files in root_dir for assignments like `llm_var = llm_var.bind_tools(...)`.
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/tasks.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.471064 | import ast
from typing import Optional
from agentic_radar.analysis.crewai.parsing.utils import (
find_return_of_function_call,
is_function_call,
)
from agentic_radar.analysis.crewai.parsing.yaml_config import (
collect_task_agents_from_config,
)
from agentic_radar.analysis.utils import walk_python_files
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/analyze.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.593396 | from pathlib import Path
from ...analysis.analyze import Analyzer
from ...graph import Agent, GraphDefinition, NodeType, ToolType
from ...graph import EdgeDefinition as Edge
from ...graph import NodeDefinition as Node
from .agent_tracking import (
find_agent_llm_variables,
find_functions_calling_agent_invoke,
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/crewai/parsing/yaml_config.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.651333 | from typing import Any, Optional
import yaml
from agentic_radar.analysis.crewai.models import CrewAITool, PartialCrewAIAgent
from agentic_radar.analysis.crewai.tool_descriptions import (
get_crewai_tools_descriptions,
)
from agentic_radar.analysis.utils import walk_yaml_files
def read_yaml_config_file(file_path... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/custom_tools.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.853107 | import ast
import json
from typing import Dict, List
from agentic_radar.analysis.utils import walk_python_files_and_notebooks
def extract_custom_tools_with_ast(
file_content: str, file_path: str
) -> List[Dict[str, str]]:
custom_tools = []
try:
tree = ast.parse(file_content)
except Exception... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/graph.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.864919 | import ast
import json
from typing import Any, Dict, List, Optional, Set, Tuple, Union
from agentic_radar.analysis.utils import walk_python_files_and_notebooks
class GraphInstanceTracker(ast.NodeVisitor):
"""
A node visitor that:
1. Finds instantiations of the Graph class (by fully-qualified name).
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/mcp.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.874629 | import ast
import json
from typing import Dict, List
from agentic_radar.analysis.utils import walk_python_files_and_notebooks
STDIO_SERVER_PARAMS_CLASS = "mcp.StdioServerParameters"
MULTISERVER_MCP_CLIENT_CLASS = "langchain_mcp_adapters.client.MultiServerMCPClient"
class MCPServerInstanceTracker(ast.NodeVisitor):
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/models.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.929402 | from enum import Enum
from typing import Optional
from pydantic import BaseModel, Field
class NodeType(str, Enum):
AGENT = "Agent"
BASIC = "Basic"
TOOL = "Tool"
CUSTOM_TOOL = "CustomTool"
class NodeCategory(str, Enum):
LLM = "LLM"
CODE_INTERPRETER = "Code Interpreter"
WEB_SEARCH = "Web ... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/utils.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.958780 | import ast
import json
import os
from typing import Dict, Tuple, Union
def get_source_from_file(filepath: str) -> str:
"""
Return the source code from a .py or .ipynb file as a single string.
"""
if filepath.endswith(".py"):
with open(filepath, "r", encoding="utf-8") as f:
return f... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/langgraph/predefined_tools.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:26.970197 | import ast
import json
from typing import Dict, List, Set
import importlib_resources as resources
from agentic_radar.analysis.utils import walk_python_files_and_notebooks
def extract_imports_with_ast(file_content: str, file_path: str) -> List[str]:
imports = []
try:
tree = ast.parse(file_content)
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/n8n/analyze.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:27.045584 | import json
import os
from typing import List, Tuple
from ...analysis.analyze import Analyzer
from ...graph import GraphDefinition
from .converter import convert_connections, convert_nodes
from .models import N8nConnection, N8nNode
from .parsing import parse_n8n_connections, parse_n8n_nodes
class N8nAnalyzer(Analyze... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/n8n/converter.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:27.180435 | import json
from typing import Any, List, Optional, Tuple
import importlib_resources as resources
from ...graph import EdgeDefinition, NodeDefinition, NodeType, ToolType
from .models import N8nConnection, N8nNode
def convert_nodes(
n8n_nodes: List[N8nNode],
) -> Tuple[List[NodeDefinition], List[NodeDefinition]]... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/n8n/models.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:27.227683 | from typing import Any, Optional
from pydantic import BaseModel, Field
class N8nNode(BaseModel):
type: str = Field(..., description="Type of the node")
name: str = Field(..., description="Name of the node")
id: str = Field(..., description="Id of the node")
parameters: dict[str, Any] = Field(
... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/n8n/parsing.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:27.596694 | from typing import Dict, List
from .models import N8nConnection, N8nNode
def parse_n8n_nodes(nodes_list: List[Dict]) -> List[N8nNode]:
n8n_nodes = []
for node in nodes_list:
n8n_nodes.append(
N8nNode(
id=node["id"],
name=node["name"],
type=n... |
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/openai_agents/exceptions.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:27.776766 | class InvalidAgentConstructorError(Exception):
def __init__(self, *args):
super().__init__(*args)
class InvalidHandoffDefinitionError(Exception):
def __init__(self, *args):
super().__init__(*args)
|
splx-ai/agentic-radar | https://github.com/splx-ai/agentic-radar | null | null | null | null | 961 | null | null | apache-2.0 | null | null | null | null | null | null | null | agentic_radar/analysis/openai_agents/analyze.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:27.832365 | from pathlib import Path
from agentic_radar.analysis.analyze import Analyzer
from agentic_radar.analysis.openai_agents.graph import create_graph_definition
from agentic_radar.analysis.openai_agents.parsing import (
collect_agent_assignments,
collect_guardrails,
collect_mcp_servers,
collect_tool_assignm... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/examples/real_app.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.420730 | """Small real-app proof.
One process is a web request. A second process is already waiting like
a worker:
* insert an order
* enqueue an email
* publish a durable stream event
* notify a live listener
All four writes commit together. The worker process must wake, claim the
email, observe the notification, and read t... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | bench/ext_bench.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.424735 | """Bench the loadable extension from raw Python sqlite3.
Compares:
1. Raw sqlite3 + extension (single pattern per iteration):
SELECT honker_claim_batch(...); SELECT honker_ack_batch(...);
2. Same pattern but with a batched claim+ack per tx cycle.
3. Same but using batch=128.
Reference: how much of our P... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | bench/wake_latency_bench.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.426028 | """Cross-process wake-latency microbench.
Measures what the README headline actually claims: the time from a
`tx.notify()` commit in one process to the corresponding wake in an
idle listener in another process. NOT throughput under saturation —
`real_bench.py` covers that.
Design: parent opens a DB, pre-seeds by comm... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | examples/demo.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.433757 | """Minimal honker demo: enqueue a job, claim it, ack it."""
import asyncio
import os
import honker
async def main():
if os.path.exists("app.db"):
os.remove("app.db")
db = honker.open("app.db")
emails = db.queue("emails")
with db.transaction() as tx:
tx.execute(
"CREATE T... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | bench/honker_bench.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.439046 | """Throughput + latency benchmark for honker.
Measures:
- enqueue ops/s (producer side)
- claim+ack ops/s (single consumer)
- end-to-end enqueue -> handler p50/p99 latency (async worker)
Usage:
uv run python bench/honker_bench.py [--n 10000] [--workers 1]
"""
import argparse
import asyncio
import os
import stati... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/examples/notify_listen.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.452869 | """Ephemeral pub/sub — pg_notify semantics on SQLite.
Starts a listener on the 'orders' channel in one asyncio task, fires
three notifications from another, and prints each received payload.
Wake latency is ~1 ms cross-process; same-process (this example) is
faster.
python examples/notify_listen.py
"""
import as... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | bench/real_bench.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.454194 | """Realistic concurrent bench: N workers + M enqueuers, sustained load.
The fresh-DB single-threaded benchmarks don't catch what actually matters
in production:
- multiple workers contending for the write lock (WAL serializes)
- enqueue hitting the DB while workers are draining
- the DB file larger than the pag... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | bench/stream_bench.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.459331 | """Stream publish + subscribe throughput + latency."""
import argparse
import asyncio
import os
import statistics
import sys
import tempfile
import time
sys.path.insert(0, os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "packages"))
import honker # noqa: E402
async def main():
ap = ar... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/examples/atomic.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.459851 | """Atomic business-write + enqueue in one transaction.
This is honker's killer feature vs Redis/Celery: the job enqueue
commits in the same SQLite transaction as your business INSERT.
Rollback drops both. No dual-write window, no outbox pattern needed.
python examples/atomic.py
"""
import os
import tempfile
imp... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/examples/scheduler.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:30.488872 | """Crontab-style periodic tasks with leader election.
Scheduler enqueues into a named queue on every cron boundary. Workers
consume those jobs like any other. Multiple scheduler processes can
run — only one holds the leader lock at a time, so nothing fires
twice.
This example uses the every-minute schedule (`* * * * ... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/examples/stream.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:31.007512 | """Durable pub/sub with per-consumer offsets.
`db.stream(name)` gives you an append-only event log with per-consumer
offset tracking. Reconnect, resume. Publish atomically with a business
write (rollback drops both, just like queue.enqueue).
This example publishes 5 events, subscribes, processes 3, then
simulates a r... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/examples/tasks.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:31.060362 | """Huey-style task decorators.
`@queue.task()` wraps a function so calling it enqueues a job instead
of running it in-process. A separate worker (or the same process via
`db.run_workers()`) picks it up, runs it, stores the return value.
python -m honker worker packages/honker/examples/tasks:db
Or inline, all-in-... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/python/honker/__main__.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:31.061660 | """`python -m honker` CLI.
Usage:
python -m honker worker <module:db_var> [options]
Example:
python -m honker worker myapp.tasks:db --queue=emails --concurrency=4
This is a thin front for `honker.run_workers(...)`. See the Python
quickstart for details.
"""
from __future__ import annotations
import argpa... |
russellromney/honker | https://github.com/russellromney/honker | null | null | null | null | 960 | null | null | apache-2.0 | null | null | null | null | null | null | null | packages/honker/python/honker/_scheduler.py | null | null | null | null | null | null | Python | 2026-05-04T02:38:31.070089 | """Time-trigger scheduler for honker.
A scheduler process holds a set of named schedules (cron expressions
→ queue + payload). On each cron boundary, it enqueues the payload
into the named queue. Regular workers claim and execute it. The
scheduler itself doesn't run handlers — it just dispatches.
Registration + fire-... |
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