gourab5139014

import pandas as pd
import json
import time
from duckduckgo_search import DDGS

def enrich_profiles(csv_input, json_output):
    """
    Reads a CSV of LinkedIn URLs and enriches them with professional metadata
    found via search snippets, saving the result to a structured JSON.
    """

gourab5139014

vim.cmd("set expandtab")
vim.cmd("set tabstop=4")
vim.cmd("set softtabstop=4")
vim.cmd("set shiftwidth=4")
vim.g.mapleader=" "
vim.cmd("set number")

local lazypath = vim.fn.stdpath("data") .. "/lazy/lazy.nvim"
if not (vim.uv or vim.loop).fs_stat(lazypath) then
  local lazyrepo = "https://github.com/folke/lazy.nvim.git"

gourab5139014

# coding: utf-8

# In[118]:


import gzip, io, os.path, json


# In[119]:

gourab5139014

-- Best used for learning purposes. Original developer also has an ER diagram available at https://tinyurl.com/oracle-hr-schema-postgres
--create tables
BEGIN; 

CREATE TABLE regions
    ( region_id      SERIAL primary key,       
      region_name    VARCHAR(25) 
    );

CREATE TABLE countries 

gourab5139014

doInstall <- TRUE
toInstall <- c("twitteR", "dismo", "maps", "ggplot2")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

searchTerm <- "#rstats"
searchResults <- searchTwitter(searchTerm, n = 1000)  # Gather Tweets 
tweetFrame <- twListToDF(searchResults)  # Convert to a nice dF

userInfo <- lookupUsers(tweetFrame$screenName)  # Batch lookup of user info

gourab5139014

extractLongLatData <- function(file)
{
  	library(ggmaps) #In case you dont have the package, use this command - install.packages(ggmaps, dependencies = TRUE)
	data <- read.csv(file)	
	v <- as.list(data["pincode"]) #assuming the attribute containing the pincodes in the supplied CSV file is named "pincode"
	pc <- sapply(v,as.character)
	pc <- sapply(pc,function(x) { paste(x,"India", sep = " ")}) #change the argument in paste() from "India" to whichever country the pincodes belong to
	longlatpc <- geocode(pc, source = "google")
	library(xlsx) #In case you dont have the package, use this command - install.packages(xlsx, dependencies = TRUE)
	write.xlsx2(longlatpc,'longlatpincode.xlsx')

gourab5139014

tweets <- searchTwitter("hardik patel", n = 1000)
text <- sapply(tweets, function(x) x$getText())
dat3 <- grep("text",iconv(text,"latin1","ASCII",sub = "text"))
dat4 <- text[-dat3]
dat5 <- paste(dat4, collapse = ", ")
corpus <- Corpus(VectorSource(dat5))

tdm = TermDocumentMatrix(
  corpus,
  control = list(

gourab5139014

import java.util.concurrent.BlockingQueue;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.logging.Level;
import java.util.logging.Logger;

public class ProducerConsumerPattern
{
    public static void main(String args[])
    {
        BlockingQueue sharedQueue = new LinkedBlockingQueue<>();

gourab5139014

import java.util.logging.Level;
import java.util.logging.Logger;

//Producer Consumer using Threads

public class ProducerConsumerTest
{
    public static void main(String args[])
    {

gourab5139014

javascript: (function() {
    a = document.location.href;
    a = a.replace(/.*?:\/\//g, "");
    b = "http://bcdboot.appspot.com/";
    c = b.concat(a);
    this.document.location.href = c;
})();