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Count GitHub Stars per Day ⭐️

Track the daily growth of GitHub stars over a time period to gauge the open-source popularity of various repositories.

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📌 Requirements

To interface with the GitHub REST API using Python, the PyGitHub library is required. Utilize this library to interact with GitHub resources such as repositories, user profiles, and organizations within your Python applications.

Installation

Run the following command to install dependencies listed in requirements.txt:

pip install -r requirements.txt  # Install required libraries

🚀 Usage

First, update the TOKEN in count_stars.py on line 15 with your valid GitHub access token. Then execute the script:

# Before running, ensure TOKEN is set to your GitHub access token.
python count_stars.py

📈 Result

The output below shows the star count for various repositories on April 10th, 2022, over the last 30 days since May 2nd, 2022:

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

💡 Contribute

Contributions are what make the open-source community thrive. We value your ideas and input! Refer to our Contributing Guide to get started and complete our Survey to give us feedback on your experience. A big thank you 🙏 to all our contributors!

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📝 License

Ultralytics offers two types of licensing options:

  • AGPL-3.0 License: This Open Source Initiative (OSI)-approved license is fit for students, hobbyists, and enthusiasts, promoting collaborative open-source development. Consult the LICENSE file for complete details.
  • Enterprise License: Tailored for commercial uses, this licensing option allows the seamless integration of Ultralytics software and AI models into commercial products and services without the obligations typically associated with AGPL-3.0. If you are looking to incorporate our solutions into your commercial products, please reach out via Ultralytics Licensing.

📬 Contact Us

For bug reports, feature requests, and contributions, head to GitHub Issues. For questions and discussions about this project and other Ultralytics endeavors, join us on Discord!


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