Data534_Project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "74da82a8-ddae-41ea-b07a-fb9252816b88",
   "metadata": {},
   "outputs": [],
   "source": [
    "library(httr)\n",
    "library(jsonlite)\n",
    "library(tidyverse)\n",
    "library(patchwork)\n",
    "library(anytime)\n",
    "library(testthat)\n",
    "git_stats <- function(repo_name){\n",
    "    \n",
    "    #' Description: Returns the stats of user in terms of additions, commits, deletions for the requested repository by the end user.\n",
    "    #' In addition to that it also gives the option of showing visualization/trends/time series plots of additions,commits, \n",
    "    #' deletions of the github user for the requested repository by the end user.\n",
    "    #' Parameter: repo_name -> it is the repository name for which the user wants to analyze the data. \n",
    "    \n",
    "    base_url <- \"https://github.com/gitapi/repos/\"\n",
    "    params <- gsub(\" \", \"\", paste(repo_name,\"/stats/contributors\"))\n",
    "    url <- gsub(\" \", \"\", paste(base_url,params)) \n",
    "    res = GET(url)\n",
    "    test_that(\"Input should be a valid repository name.\", {\n",
    "        expect_equal(res[['status_code']], 200)\n",
    "    })\n",
    "    if (res[['status_code']] != 200) {\n",
    "     stop()}\n",
    "    flush.console()\n",
    "    data = fromJSON(rawToChar(res$content))\n",
    "    \n",
    "    loginname <- readline(prompt=\"Enter login name: \")\n",
    "    author<-data$author\n",
    "    \n",
    "    if ((loginname %in%  author$login) != TRUE) {\n",
    "     stop(\"This user login name doesn't exist.\")}\n",
    "    \n",
    "    index_data<-which(author$login == loginname)\n",
    "    data_weeks<-data$weeks\n",
    "    current_user<-data_weeks[[index_data]]\n",
    "    current_user$w<-anydate(current_user$w)\n",
    "    \n",
    "    \n",
    "    \n",
    "    adds_per_user <- function(current_user) {\n",
    "    #' Returns the stats of user in terms of additions for the requested repository by the end user. \n",
    "    #' Parameter: current_user -> the user name for which user wants to analyze the data.     \n",
    "    df_adds<-current_user%>%group_by(w)%>%summarise(adds=sum(a))%>%arrange(desc(w))\n",
    "      \n",
    "        if (length(df_adds) == 0) {\n",
    "        stop(\"This user has no data.\")}\n",
    "        return(df_adds)\n",
    "    }\n",
    "    \n",
    "    \n",
    "    \n",
    "    deletes_per_user <- function(current_user) {\n",
    "    #' Returns the stats of user in terms of deletions for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to analyze the data. \n",
    "    df_deletes<-current_user%>%group_by(w)%>%summarise(deletes=sum(d))%>%arrange(desc(w))\n",
    "        if (length(df_deletes) == 0) {\n",
    "        stop(\"This user has no data.\")}\n",
    "        \n",
    "        return(df_deletes)\n",
    "    }\n",
    "    \n",
    "    commits_per_user <- function(current_user) {\n",
    "    #' Returns the stats of user in terms of commits for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to analyze the data. \n",
    "    df_commits<-current_user%>%group_by(w)%>%summarise(commits=sum(c))%>%arrange(desc(w))\n",
    "        if (length(df_commits) == 0) {\n",
    "        stop(\"This user has no data.\")}\n",
    "        \n",
    "        return(df_commits)\n",
    "    }\n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "    everything_per_user <- function(current_user) {\n",
    "    #' Returns the stats of user in terms of additions,deletions,commits for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to analyze the data.      \n",
    "         df_everything<-current_user%>%group_by(w)%>%summarise(commits=sum(c), additions=sum(a), deletions=sum(d))%>%arrange(desc(w))\n",
    "           if (length(df_everything) == 0) {\n",
    "          stop(\"This user has no data.\")}\n",
    "        \n",
    "           return(df_everything)\n",
    "            }\n",
    "    adds_per_user_viz<-function(current_user)\n",
    "    {\n",
    "    #' This shows visualization/trends/time series plots of additions of the github user for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to look at the visualization. \n",
    "    options(repr.plot.width=16, repr.plot.height=8)\n",
    "    p <- ggplot(adds_per_user(current_user), aes(x=w, y=adds)) +\n",
    "    geom_line(color=\"green3\", size=0.8) + \n",
    "    xlab(\"Year\")+ylab(\"Adds\") + theme_bw() + theme(axis.text=element_text(size=16, face=\"bold\"),\n",
    "                axis.title=element_text(size=19,face=\"bold\")) \n",
    "    return(p)\n",
    "    }\n",
    "        \n",
    "    deletes_per_user_viz<-function(current_user)\n",
    "    {\n",
    "    #' This shows visualization/trends/time series plots of deletions of the github user for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to look at the visualization. \n",
    "    options(repr.plot.width=16, repr.plot.height=8)\n",
    "    p <- ggplot(deletes_per_user(current_user), aes(x=w, y=deletes)) +\n",
    "    geom_line(color=\"green3\", size=0.8) + \n",
    "    xlab(\"Year\")+ylab(\"Deletes\") + theme_bw() + theme(axis.text=element_text(size=16, face=\"bold\"),\n",
    "                axis.title=element_text(size=19,face=\"bold\")) \n",
    "    return(p)\n",
    "    }\n",
    "        \n",
    "    commits_per_user_viz<-function(current_user)\n",
    "    {\n",
    "    #' This shows visualization/trends/time series plots of commits of the github user for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to look at the visualization. \n",
    "    options(repr.plot.width=16, repr.plot.height=8)\n",
    "    p <- ggplot(commits_per_user(current_user), aes(x=w, y=commits)) +\n",
    "    geom_line(color=\"green3\", size=0.8) + \n",
    "    xlab(\"Year\")+ylab(\"Commits\") + theme_bw() + theme(axis.text=element_text(size=16, face=\"bold\"),\n",
    "                axis.title=element_text(size=19,face=\"bold\")) \n",
    "    return(p)\n",
    "    }\n",
    "    everything_per_user_viz<-function(current_user)\n",
    "    {\n",
    "    #' This shows visualization/trends/time series plots of additions,commits, deletions of the github user for the requested repository by the end user\n",
    "    #' Parameter: current_user -> the user name for which user wants to look at the visualization. \n",
    "    options(repr.plot.width=16, repr.plot.height=8)\n",
    "    pc <- ggplot(everything_per_user(current_user), aes(x=w, y=commits)) +\n",
    "      geom_line(color=\"magenta3\", size=0.8) + \n",
    "      xlab(\"Year\")+ylab(\"Commits\") + theme_bw() + theme(axis.text=element_text(size=16, face=\"bold\"),\n",
    "                axis.title=element_text(size=19,face=\"bold\"))\n",
    "    \n",
    "    pd <- ggplot(deletes_per_user(current_user), aes(x=w, y=deletes)) +\n",
    "      geom_line(color=\"royalblue3\", size=0.8) + \n",
    "      xlab(\"Year\")+ylab(\"Deletes\") + theme_bw() + theme(axis.text=element_text(size=16, face=\"bold\"),\n",
    "                axis.title=element_text(size=19,face=\"bold\"))    \n",
    "    \n",
    "    pa <- ggplot(adds_per_user(current_user), aes(x=w, y=adds)) +\n",
    "      geom_line(color=\"green3\", size=0.8) + \n",
    "      xlab(\"Year\")+ylab(\"Adds\") + theme_bw() + theme(axis.text=element_text(size=16, face=\"bold\"),\n",
    "                axis.title=element_text(size=19,face=\"bold\"))     \n",
    "\n",
    "    options(repr.plot.width=13, repr.plot.height=15)    \n",
    "    pe <- (pa / pd / pc)\n",
    "\n",
    "    return(pe)    \n",
    "    }\n",
    "\n",
    "    while(1){\n",
    "    user_stats_choice <- readline(prompt=\"Enter which stats you are looking for the user(type from the following options - \\n 1. Additions \\n 2. Deletions \\n 3. Commits \\n 4.All \\n 5. None): \\n \")\n",
    "    \n",
    "    if(user_stats_choice  == \"1\"){\n",
    "        df<-adds_per_user(current_user)\n",
    "        df<-df%>%arrange(desc(adds))\n",
    "        print(\"/n Here are the top dates with respect to adds\")\n",
    "        print(head(df))\n",
    "        flush.console()\n",
    "        \n",
    "        user_viz_choice <- readline(prompt=\"\\n Do you want to look at the timeseries visualization for this user? \\n yes \\n no: \")\n",
    "        if(user_viz_choice  == \"yes\"){\n",
    "            print(adds_per_user_viz(current_user))\n",
    "        flush.console()\n",
    "    }\n",
    "    break;    \n",
    "    }\n",
    "    \n",
    "    else if(user_stats_choice == \"2\"){\n",
    "        df<-deletes_per_user(current_user)\n",
    "        df<-df%>%arrange(desc(deletes))\n",
    "        print(\"/n Here are the top dates with respect to deletes\")\n",
    "        print(head(df))\n",
    "        flush.console()\n",
    "        user_viz_choice <- readline(prompt=\"\\n Do you want to look at the timeseries visualization for this user? \\n yes \\n no: \\n\")\n",
    "        if(user_viz_choice  == \"yes\"){\n",
    "            print(deletes_per_user_viz(current_user))\n",
    "        flush.console()\n",
    "    }\n",
    "    break; \n",
    "    }\n",
    "        \n",
    "    else if(user_stats_choice == \"3\"){\n",
    "        df<-commits_per_user(current_user)\n",
    "        df<-df%>%arrange(desc(commits))\n",
    "        print(\"/n Here are the top dates with respect to commits\")\n",
    "        print(head(df))\n",
    "        flush.console()\n",
    "        user_viz_choice <- readline(prompt=\"\\n Do you want to look at the timeseries visualization for this user? \\n yes \\n no: \\n\")\n",
    "        if(user_viz_choice  == \"yes\"){\n",
    "            print(commits_per_user_viz(current_user))\n",
    "        flush.console()\n",
    "    }\n",
    "    break; \n",
    "    }\n",
    "    else if(user_stats_choice == \"4\"){\n",
    "        df<-everything_per_user(current_user)\n",
    "        df<-df%>%arrange(desc(commits))\n",
    "        print(\"/n Here are the top dates with respect to commits\")\n",
    "        print(head(df))\n",
    "        flush.console()\n",
    "        user_viz_choice <- readline(prompt=\"\\n Do you want to look at the timeseries visualization for this user? \\n yes \\n no: \\n\")\n",
    "        if(user_viz_choice  == \"yes\"){\n",
    "            print(everything_per_user_viz(current_user))\n",
    "        flush.console()\n",
    "    }\n",
    "    break; \n",
    "    }\n",
    "    else if(user_stats_choice == \"5\") {\n",
    "        break; }\n",
    "    else {\n",
    "        print(\"\\n Invalid Input \\n\")\n",
    "        }\n",
    "        }}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5feb41a6-f400-489e-a4d1-48409d35e0b9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mTest passed\u001b[39m \n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter login name:  87\n",
      "Enter which stats you are looking for the user(type from the following options - \n",
      " 1. Additions \n",
      " 2. Deletions \n",
      " 3. Commits \n",
      " 4.All \n",
      " 5. None): \n",
      "  4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"/n Here are the top dates with respect to commits\"\n",
      "\u001b[90m# A tibble: 6 x 4\u001b[39m\n",
      "  w          commits additions deletions\n",
      "  \u001b[3m\u001b[90m<date>\u001b[39m\u001b[23m       \u001b[3m\u001b[90m<int>\u001b[39m\u001b[23m     \u001b[3m\u001b[90m<int>\u001b[39m\u001b[23m     \u001b[3m\u001b[90m<int>\u001b[39m\u001b[23m\n",
      "\u001b[90m1\u001b[39m 2011-09-10      10       139        61\n",
      "\u001b[90m2\u001b[39m 2011-10-15       8       389       347\n",
      "\u001b[90m3\u001b[39m 2012-09-08       6       103        52\n",
      "\u001b[90m4\u001b[39m 2012-09-01       6        29        25\n",
      "\u001b[90m5\u001b[39m 2011-10-22       6        96        26\n",
      "\u001b[90m6\u001b[39m 2012-09-15       5       168       110\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "\n",
      " Do you want to look at the timeseries visualization for this user? \n",
      " yes \n",
      " no: \n",
      " yes\n"
     ]
    },
    {
     "data": {
      "image/png": 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mlOZkNgj2GwIFC1nGH4dPg+218GHo5WTC7NyWwI7DEMFgSqljMM3XuNVvv3IJUP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\n/wF8cZWuOzt1awAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 900,
       "width": 780
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "git_stats('numpy/numpy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fce43f90-cece-4c1a-8fbe-c50bdd287148",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Installing package into 'C:/Users/Navdeep Singh Saini/R/win-library/4.1'\n",
      "(as 'lib' is unspecified)\n",
      "\n",
      "Warning message:\n",
      "\"package 'githubapistats' is not available for this version of R\n",
      "\n",
      "A version of this package for your version of R might be available elsewhere,\n",
      "see the ideas at\n",
      "https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages\"\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"githubapistats\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "67833864-d9f9-4a3f-868d-1e755dd3cff7",
   "metadata": {},
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in library(githubapistats): there is no package called 'githubapistats'\n",
     "output_type": "error",
     "traceback": [
      "Error in library(githubapistats): there is no package called 'githubapistats'\nTraceback:\n",
      "1. library(githubapistats)"
     ]
    }
   ],
   "source": [
    "library(githubapistats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54f426bc-1164-4ee1-991e-7533063d52e1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.1.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}