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> 
Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers

beyond masking Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers The code is coming Figure 1: Pipeline of token-based pre-

Yunjie Tian 23 Sep 27, 2022
Minimal GUI for accessing the Watson Text to Speech service.

Description Minimal graphical application for accessing the Watson Text to Speech service. Requirements Python 3 plus all dependencies listed in requi

Moritz Maxeiner 1 Oct 22, 2021
PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.09

Keon Lee 142 Jan 06, 2023
Nested Named Entity Recognition for Chinese Biomedical Text

CBio-NAMER CBioNAMER (Nested nAMed Entity Recognition for Chinese Biomedical Text) is our method used in CBLUE (Chinese Biomedical Language Understand

8 Dec 25, 2022
State of the Art Natural Language Processing

Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide

John Snow Labs 3k Jan 05, 2023
This project deals with a simplified version of a more general problem of Aspect Based Sentiment Analysis.

Aspect_Based_Sentiment_Extraction Created on: 5th Jan, 2022. This project deals with an important field of Natural Lnaguage Processing - Aspect Based

Naman Rastogi 4 Jan 01, 2023
👄 The most accurate natural language detection library for Python, suitable for long and short text alike

1. What does this library do? Its task is simple: It tells you which language some provided textual data is written in. This is very useful as a prepr

Peter M. Stahl 334 Dec 30, 2022
BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

OpenBMB 377 Jan 02, 2023
A curated list of FOSS tools to improve the Hacker News experience

Awesome-Hackernews Hacker News is a social news website focusing on computer technologies, hacking and startups. It promotes any content likely to "gr

Bryton Lacquement 141 Dec 27, 2022
Tools, wrappers, etc... for data science with a concentration on text processing

Rosetta Tools for data science with a focus on text processing. Focuses on "medium data", i.e. data too big to fit into memory but too small to necess

207 Nov 22, 2022
Transformation spoken text to written text

Transformation spoken text to written text This model is used for formatting raw asr text output from spoken text to written text (Eg. date, number, i

Nguyen Binh 16 Dec 28, 2022
运小筹公众号是致力于分享运筹优化(LP、MIP、NLP、随机规划、鲁棒优化)、凸优化、强化学习等研究领域的内容以及涉及到的算法的代码实现。

OlittleRer 运小筹公众号是致力于分享运筹优化(LP、MIP、NLP、随机规划、鲁棒优化)、凸优化、强化学习等研究领域的内容以及涉及到的算法的代码实现。编程语言和工具包括Java、Python、Matlab、CPLEX、Gurobi、SCIP 等。 关注我们: 运筹小公众号 有问题可以直接在

运小筹 151 Dec 30, 2022
Beyond the Imitation Game collaborative benchmark for enormous language models

BIG-bench 🪑 The Beyond the Imitation Game Benchmark (BIG-bench) will be a collaborative benchmark intended to probe large language models, and extrap

Google 1.3k Jan 01, 2023
硕士期间自学的NLP子任务,供学习参考

NLP_Chinese_down_stream_task 自学的NLP子任务,供学习参考 任务1 :短文本分类 (1).数据集:THUCNews中文文本数据集(10分类) (2).模型:BERT+FC/LSTM,Pytorch实现 (3).使用方法: 预训练模型使用的是中文BERT-WWM, 下载地

12 May 31, 2022
Translate - a PyTorch Language Library

NOTE PyTorch Translate is now deprecated, please use fairseq instead. Translate - a PyTorch Language Library Translate is a library for machine transl

775 Dec 24, 2022
Model parallel transformers in JAX and Haiku

Table of contents Mesh Transformer JAX Updates Pretrained Models GPT-J-6B Links Acknowledgments License Model Details Zero-Shot Evaluations Architectu

Ben Wang 4.9k Jan 04, 2023
DomainWordsDict, Chinese words dict that contains more than 68 domains, which can be used as text classification、knowledge enhance task

DomainWordsDict, Chinese words dict that contains more than 68 domains, which can be used as text classification、knowledge enhance task。涵盖68个领域、共计916万词的专业词典知识库,可用于文本分类、知识增强、领域词汇库扩充等自然语言处理应用。

liuhuanyong 357 Dec 24, 2022
☀️ Measuring the accuracy of BBC weather forecasts in Honolulu, USA

Accuracy of BBC Weather forecasts for Honolulu This repository records the forecasts made by BBC Weather for the city of Honolulu, USA. Essentially, t

Max Halford 12 Oct 15, 2022
Kurumi ChatBot

KurumiChatBot Just another Telegram AI chat bot written in Python using Pyrogram. A public running instance can be found on telegram as @TokisakiChatB

Yoga Pranata 3 Jun 28, 2022
It analyze the sentiment of the user, whether it is postive or negative.

Sentiment-Analyzer-Tool It analyze the sentiment of the user, whether it is postive or negative. It uses streamlit library for creating this sentiment

Paras Patidar 18 Dec 17, 2022