Track GitHub stars per day over a date range to measure the open-source popularity of different repositories.
PyGitHub
is required to access the GitHub REST API via Python. This library enables you to manage GitHub resources such as repositories, user profiles, and organizations in your Python applications.
pip install -r requirements.txt # install
Update TOKEN
to a valid GitHub access token in count_stars.py
L15 and then run:
python count_stars.py
When run on April 10th, 2022 result is:
Counting stars for last 30.0 days from 02 May 2022
ultralytics/yolov5 1572 stars (52.4/day) : 6%|▌ | 1572/25683 [00:16<04:15, 94.53it/s]
facebookresearch/detectron2 391 stars (13.0/day) : 2%|▏ | 391/20723 [00:04<03:56, 85.86it/s]
deepmind/deepmind-research 165 stars (5.5/day) : 2%|▏ | 165/10079 [00:01<01:50, 89.52it/s]
aws/amazon-sagemaker-examples 120 stars (4.0/day) : 2%|▏ | 120/6830 [00:02<02:16, 49.17it/s]
awslabs/autogluon 127 stars (4.2/day) : 3%|▎ | 127/4436 [00:01<01:00, 71.45it/s]
microsoft/LightGBM 122 stars (4.1/day) : 1%| | 122/13730 [00:01<03:10, 71.54it/s]
openai/gpt-3 95 stars (3.2/day) : 1%| | 95/11225 [00:01<03:34, 52.00it/s]
apple/turicreate 40 stars (1.3/day) : 0%| | 40/10676 [00:00<02:24, 73.59it/s]
apple/coremltools 41 stars (1.4/day) : 2%|▏ | 41/2641 [00:00<00:46, 56.00it/s]
google/automl 55 stars (1.8/day) : 1%| | 55/4991 [00:00<01:25, 57.53it/s]
google-research/google-research 548 stars (18.3/day) : 2%|▏ | 548/23087 [00:07<05:11, 72.37it/s]
google-research/vision_transformer 279 stars (9.3/day) : 6%|▌ | 279/5043 [00:02<00:49, 95.93it/s]
google-research/bert 283 stars (9.4/day) : 1%| | 283/31066 [00:03<07:01, 73.11it/s]
NVlabs/stylegan3 158 stars (5.3/day) : 4%|▍ | 158/4045 [00:01<00:44, 86.41it/s]
Tencent/ncnn 278 stars (9.3/day) : 2%|▏ | 278/14440 [00:03<02:41, 87.55it/s]
Megvii-BaseDetection/YOLOX 273 stars (9.1/day) : 4%|▍ | 273/6286 [00:02<01:04, 92.53it/s]
PaddlePaddle/Paddle 239 stars (8.0/day) : 1%|▏ | 239/18086 [00:02<03:33, 83.73it/s]
rwightman/pytorch-image-models 772 stars (25.7/day) : 4%|▍ | 772/18169 [00:08<03:21, 86.24it/s]
streamlit/streamlit 375 stars (12.5/day) : 2%|▏ | 375/18834 [00:03<03:07, 98.67it/s]
explosion/spaCy 234 stars (7.8/day) : 1%| | 234/23249 [00:02<03:47, 101.24it/s]
PyTorchLightning/pytorch-lightning 407 stars (13.6/day) : 2%|▏ | 407/18246 [00:04<03:02, 97.83it/s]
ray-project/ray 545 stars (18.2/day) : 3%|▎ | 545/20228 [00:05<03:03, 107.33it/s]
fastai/fastai 136 stars (4.5/day) : 1%| | 136/22202 [00:01<04:28, 82.22it/s]
AlexeyAB/darknet 248 stars (8.3/day) : 1%|▏ | 248/18993 [00:02<03:40, 84.84it/s]
pjreddie/darknet 201 stars (6.7/day) : 1%| | 201/22651 [00:02<05:13, 71.62it/s]
WongKinYiu/yolor 92 stars (3.1/day) : 6%|▌ | 92/1559 [00:01<00:16, 87.69it/s]
wandb/client 66 stars (2.2/day) : 2%|▏ | 66/3853 [00:00<00:46, 82.16it/s]
Deci-AI/super-gradients 74 stars (2.5/day) : 19%|█▉ | 74/380 [00:00<00:03, 96.71it/s]
neuralmagic/sparseml 105 stars (3.5/day) : 11%|█ | 105/947 [00:01<00:08, 101.97it/s]
mosaicml/composer 247 stars (8.2/day) : 19%|█▉ | 247/1306 [00:02<00:10, 104.76it/s]
nebuly-ai/nebullvm 205 stars (6.8/day) : 20%|█▉ | 205/1045 [00:02<00:08, 97.46it/s]
Done in 125.7s