Tools and data for measuring the popularity & growth of various programming languages.

Overview

growth-data

Tools and data for measuring the popularity & growth of various programming languages.

Install the dependencies

$ pip install -r requirements.txt

Example queries

Number of (non-fork) repositories

sqlite> .mode column
sqlite> SELECT
    ds,
    github_search_q AS q,
    MAX(github_search_total_count) AS num_repos
  FROM github_search
  GROUP BY 1, 2
  ORDER BY 3;
ds          q                                  num_repos
----------  ---------------------------------  ---------
2021-12-22  language:tla and fork:false        64       
2021-12-22  language:lean and fork:false       75       
2021-12-22  language:idris and fork:false      140      
2021-12-22  language:agda and fork:false       192      
2021-12-22  language:ada and fork:false        438      
2021-12-22  language:coq and fork:false        509      
2021-12-22  language:erlang and fork:false     2260     
2021-12-22  language:ocaml and fork:false      2278     
2021-12-22  language:fortran and fork:false    3196     
2021-12-22  language:verilog and fork:false    3882     
2021-12-22  language:assembly and fork:false   8654     
2021-12-22  language:haskell and fork:false    10052    
2021-12-22  language:terraform and fork:false  10254    
2021-12-22  language:rust and fork:false       21906    
2021-12-22  language:go and fork:false         67601    
2021-12-22  language:r and fork:false          114942   
2021-12-22  language:c and fork:false          174439   
2021-12-22  language:c++ and fork:false        270351   
2021-12-22  language:python and fork:false     762729   
2021-12-22  language:java and fork:false       943381   
sqlite> 

Stats about the average (non-fork) repository

sqlite> .mode column
sqlite> SELECT
    github_search.ds AS ds,
    github_search_q AS q,
    COUNT(*) AS repos,
    SUM(github_repo_has_issues) AS repos_with_issues,
    SUM(github_repo_has_wiki) AS repos_with_wiki,
    SUM(github_repo_has_pages) AS repos_with_pages,
    SUM(github_repo_license_name != '') AS repos_with_license,
    SUM(github_repo_size) AS sum_repo_size,
    SUM(github_repo_stargazers_count) AS sum_stars,
    AVG(github_repo_stargazers_count) AS avg_stars,
    AVG(github_repo_forks_count) AS avg_forks,
    AVG(github_repo_size) AS avg_size,
    AVG(github_repo_open_issues_count) AS avg_open_issues
  FROM github_search INNER JOIN github_search_repo
  ON github_search.obj_id = github_search_obj_id
  GROUP BY 1, 2
  ORDER BY 3;
ds          q                              repos  repos_with_issues  repos_with_wiki  repos_with_pages  repos_with_license  sum_repo_size  sum_stars  avg_stars         avg_forks         avg_size          avg_open_issues  
----------  -----------------------------  -----  -----------------  ---------------  ----------------  ------------------  -------------  ---------  ----------------  ----------------  ----------------  -----------------
2021-12-22  language:tla and fork:false    64     63                 61               1                 23                  1393879        1937       30.265625         2.34375           21779.359375      0.359375         
2021-12-22  language:lean and fork:false   75     73                 72               5                 22                  1119783        1475       19.6666666666667  1.85333333333333  14930.44          1.61333333333333 
2021-12-22  language:idris and fork:false  140    139                136              4                 63                  108818         1242       8.87142857142857  0.85              777.271428571429  0.728571428571429
2021-12-22  language:agda and fork:false   192    188                187              9                 51                  394233         1725       8.984375          0.90625           2053.296875       0.291666666666667
2021-12-22  language:ada and fork:false    438    421                406              12                155                 2387761        2210       5.04566210045662  1.13926940639269  5451.50913242009  1.09360730593607 
2021-12-22  language:coq and fork:false    509    502                493              42                204                 2894476        4304       8.45579567779961  1.50098231827112  5686.59332023576  0.846758349705305
sqlite>

Stats about the average recently-updated (non-fork) repository

sqlite> .mode column
sqlite> SELECT
    github_search.ds AS ds,
    github_search_q AS q,
    COUNT(*) AS repos,
    SUM(github_repo_has_issues) AS repos_with_issues,
    SUM(github_repo_has_wiki) AS repos_with_wiki,
    SUM(github_repo_has_pages) AS repos_with_pages,
    SUM(github_repo_license_name != '') AS repos_with_license,
    SUM(github_repo_size) AS sum_repo_size,
    SUM(github_repo_stargazers_count) AS sum_stars,
    AVG(github_repo_stargazers_count) AS avg_stars,
    AVG(github_repo_forks_count) AS avg_forks,
    AVG(github_repo_size) AS avg_size,
    AVG(github_repo_open_issues_count) AS avg_open_issues
  FROM github_search INNER JOIN github_search_repo
  ON github_search.obj_id = github_search_obj_id
  WHERE github_repo_updated_at >= '2021-01-01T00:00:00Z'
  GROUP BY 1, 2
  ORDER BY 3;
ds          q                              repos  repos_with_issues  repos_with_wiki  repos_with_pages  repos_with_license  sum_repo_size  sum_stars  avg_stars         avg_forks         avg_size          avg_open_issues  
----------  -----------------------------  -----  -----------------  ---------------  ----------------  ------------------  -------------  ---------  ----------------  ----------------  ----------------  -----------------
2021-12-22  language:tla and fork:false    33     32                 30               1                 18                  1322462        1921       58.2121212121212  4.39393939393939  40074.6060606061  0.636363636363636
2021-12-22  language:idris and fork:false  44     44                 43               3                 23                  33576          1052       23.9090909090909  2.22727272727273  763.090909090909  1.61363636363636 
2021-12-22  language:lean and fork:false   46     44                 43               3                 14                  1116533        1442       31.3478260869565  2.93478260869565  24272.4565217391  2.58695652173913 
2021-12-22  language:agda and fork:false   77     74                 75               8                 24                  310115         1520       19.7402597402597  1.93506493506494  4027.46753246753  0.376623376623377
2021-12-22  language:ada and fork:false    168    165                148              10                82                  1615474        2065       12.2916666666667  2.67261904761905  9615.91666666667  2.80357142857143 
2021-12-22  language:coq and fork:false    211    206                201              32                113                 1962100        4018       19.042654028436   3.22748815165877  9299.05213270142  1.89099526066351 
sqlite> 
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.

Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic

Shivanand Roy 220 Dec 30, 2022
Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields

Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields [project page][paper][cite] Geometry-Consistent Neural Shape Represe

Yifan Wang 100 Dec 19, 2022
GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form

GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.

GNES.ai 1.2k Jan 06, 2023
This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP

This repo is to provide a list of literature regarding Deep Learning on Graphs for NLP

Graph4AI 230 Nov 22, 2022
Graph Coloring - Weighted Vertex Coloring Problem

Graph Coloring - Weighted Vertex Coloring Problem This project proposes several local searches and an MCTS algorithm for the weighted vertex coloring

Cyril 1 Jul 08, 2022
This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini!

About CappuccinoJs This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini! Este conversor criar

Arthur Ottoni Ribeiro 48 Nov 15, 2022
A collection of Classical Chinese natural language processing models, including Classical Chinese related models and resources on the Internet.

GuwenModels: 古文自然语言处理模型合集, 收录互联网上的古文相关模型及资源. A collection of Classical Chinese natural language processing models, including Classical Chinese related models and resources on the Internet.

Ethan 66 Dec 26, 2022
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

TOPSIS implementation in Python Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) CHING-LAI Hwang and Yoon introduced TOPSIS

Hamed Baziyad 8 Dec 10, 2022
Ceaser-Cipher - The Caesar Cipher technique is one of the earliest and simplest method of encryption technique

Ceaser-Cipher The Caesar Cipher technique is one of the earliest and simplest me

Lateefah Ajadi 2 May 12, 2022
customer care chatbot made with Rasa Open Source.

Customer Care Bot Customer care bot for ecomm company which can solve faq and chitchat with users, can contact directly to team. 🛠 Features Basic E-c

Dishant Gandhi 23 Oct 27, 2022
A Chinese to English Neural Model Translation Project

ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C

Zhenbang Feng 29 Nov 26, 2022
PortaSpeech - PyTorch Implementation

PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor

Keon Lee 276 Dec 26, 2022
Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks

Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks. It takes raw videos/images + text as inputs, and outputs task predictions. ClipB

Jie Lei 雷杰 612 Jan 04, 2023
Input english text, then translate it between languages n times using the Deep Translator Python Library.

mass-translator About Input english text, then translate it between languages n times using the Deep Translator Python Library. How to Use Install dep

2 Mar 04, 2022
KoBART model on huggingface transformers

KoBART-Transformers SKT에서 공개한 KoBART를 편리하게 사용할 수 있게 transformers로 포팅하였습니다. Install (Optional) BartModel과 PreTrainedTokenizerFast를 이용하면 설치하실 필요 없습니다. p

Hyunwoong Ko 58 Dec 07, 2022
Py65 65816 - Add support for the 65C816 to py65

Add support for the 65C816 to py65 Py65 (https://github.com/mnaberez/py65) is a

4 Jan 04, 2023
KoBERT - Korean BERT pre-trained cased (KoBERT)

KoBERT KoBERT Korean BERT pre-trained cased (KoBERT) Why'?' Training Environment Requirements How to install How to use Using with PyTorch Using with

SK T-Brain 1k Jan 02, 2023
Pre-Training with Whole Word Masking for Chinese BERT

Pre-Training with Whole Word Masking for Chinese BERT

Yiming Cui 7.7k Dec 31, 2022
Honor's thesis project analyzing whether the GPT-2 model can more effectively generate free-verse or structured poetry.

gpt2-poetry The following code is for my senior honor's thesis project, under the guidance of Dr. Keith Holyoak at the University of California, Los A

Ashley Kim 2 Jan 09, 2022
Visual Automata is a Python 3 library built as a wrapper for Caleb Evans' Automata library to add more visualization features.

Visual Automata Copyright 2021 Lewi Lie Uberg Released under the MIT license Visual Automata is a Python 3 library built as a wrapper for Caleb Evans'

Lewi Uberg 55 Nov 17, 2022