Count GitHub Stars ⭐

Overview

Count GitHub Stars per Day

Track GitHub stars per day over a date range to measure the open-source popularity of different repositories.

Requirements

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 PyGithub

Usage

Update TOKEN to a valid GitHub access token in count_stars.py L15 and then run:

python count_stars.py

Result

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
Owner
Ultralytics
YOLOv5 🚀 and Vision AI ⭐
Ultralytics
Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)

ImageProcessingTransformer Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)

61 Jan 01, 2023
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.

ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in

Gabriel Nützi 390 Dec 31, 2022
My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

Marko Njegomir 7 Dec 14, 2022
Open-sourcing the Slates Dataset for recommender systems research

FINN.no Recommender Systems Slate Dataset This repository accompany the paper "Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sa

FINN.no 48 Nov 28, 2022
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

93 Nov 06, 2022
State-of-the-art language models can match human performance on many tasks

Status: Archive (code is provided as-is, no updates expected) Grade School Math [Blog Post] [Paper] State-of-the-art language models can match human p

OpenAI 259 Jan 08, 2023
KE-Dialogue: Injecting knowledge graph into a fully end-to-end dialogue system.

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

CAiRE 42 Nov 10, 2022
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification

Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification (ACDNE) This is a pytorch implementation of the Adv

陈志豪 8 Oct 13, 2022
Pytorch implementation of the paper: "SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Image Deraining"

SAPNet This repository contains the official Pytorch implementation of the paper: "SAPNet: Segmentation-Aware Progressive Network for Perceptual Contr

11 Oct 17, 2022
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.

Documentation: https://mmgeneration.readthedocs.io/ Introduction English | 简体中文 MMGeneration is a powerful toolkit for generative models, especially f

OpenMMLab 1.3k Dec 29, 2022
Data-depth-inference - Data depth inference with python

Welcome! This readme will guide you through the use of the code in this reposito

Marco 3 Feb 08, 2022
Semi-supervised semantic segmentation needs strong, varied perturbations

Semi-supervised semantic segmentation using CutMix and Colour Augmentation Implementations of our papers: Semi-supervised semantic segmentation needs

146 Dec 20, 2022
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios

Cooperative Driving Dataset (CODD) The Cooperative Driving dataset is a synthetic dataset generated using CARLA that contains lidar data from multiple

Eduardo Henrique Arnold 124 Dec 28, 2022
Metrics to evaluate quality and efficacy of synthetic datasets.

An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://

The Synthetic Data Vault Project 129 Jan 03, 2023
This code is a near-infrared spectrum modeling method based on PCA and pls

Nirs-Pls-Corn This code is a near-infrared spectrum modeling method based on PCA and pls 近红外光谱分析技术属于交叉领域,需要化学、计算机科学、生物科学等多领域的合作。为此,在(北邮邮电大学杨辉华老师团队)指导下

Fu Pengyou 6 Dec 17, 2022
PyTorch code for training MM-DistillNet for multimodal knowledge distillation

There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge MM-DistillNet is a

51 Dec 20, 2022
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow

Phil Wang 235 Dec 27, 2022
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble

datasketch: Big Data Looks Small datasketch gives you probabilistic data structures that can process and search very large amount of data super fast,

Eric Zhu 1.9k Jan 07, 2023
DCSL - Generalizable Crowd Counting via Diverse Context Style Learning

DCSL Generalizable Crowd Counting via Diverse Context Style Learning Requirement

3 Jun 13, 2022
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst

HPC-AI Tech 7.9k Jan 08, 2023