vishal sharma vishal2612200

## Readme.md

      
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              August 23, 2021 17:12
            
              
                GSOC 2021 WITH XFCE
              
          
    FINAL WORDS ON GSOC 2021 WITH XFCE

Student: Vishal Sharma
Organisation: XFCE
GSOC Year: 2021
Mentor: @itsmanjeet

  
## Uppercase to lowercase character
def to_lower(str):
    return str.lower()
s = "Welcome To Freshlybuilt"
fresh_list = s.split() # convert string into list
fresh_list = list(map(to_lower,fresh_list)) #convert elements into lowercase
fresh_list = ' '.join(map(str, fresh_list)) # convert list into string
print(" String in lower case: ", fresh_list)

## export_inference_graph_unfrozen.py
"""
References:
https://github.com/tensorflow/models/blob/master/object_detection/g3doc/exporting_models.md
https://github.com/tensorflow/models/issues/1988

Unfortunately, the tutorial for saving a model for inference "freezes" the
variables in place and makes them unservable by tensorflow_serving.
export_inference_graph.py exports an empty "variables" directory, which needs to
be populated.

## newton raphson method
#include<stdio.h>
#include<math.h>
float f(float x){
	return x*log10(x)-1.2;
}
float df(float x){
	return log10(x) + 0.434293;
}
int main(){
	int a,b,maxitr,itr;

## cardekho.com data
from urllib.request import urlopen
from bs4 import BeautifulSoup
import requests
page=urlopen("https://www.cardekho.com/")
soup = BeautifulSoup(page.read(),"html5lib")
new =soup.find_all("div",{"class":"price"})
len(new) #to count the number of price class element i.e testing purpose
print(new[0].text)#for testing the link
about=new[0]
for about in new:

## graphical analysis
<!DOCTYPE html>
<html>
  <head>
    <script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
    <script type="text/javascript">
      google.charts.load("current", {packages:["corechart"]});
      google.charts.setOnLoadCallback(drawChart);
      function drawChart() {


## html.htm
<!DOCTYPE html>
<html>
<head>
      <meta charset="utf-8">
  <meta name="viewport" content="width=device-width, initial-scale=1">
  <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
  <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
  <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js"></script>
	def to_lower(str):
	return str.lower()
	s = "Welcome To Freshlybuilt"
	fresh_list = s.split() # convert string into list
	fresh_list = list(map(to_lower,fresh_list)) #convert elements into lowercase
	fresh_list = ' '.join(map(str, fresh_list)) # convert list into string
	print(" String in lower case: ", fresh_list)
	"""
	References:
	https://github.com/tensorflow/models/blob/master/object_detection/g3doc/exporting_models.md
	https://github.com/tensorflow/models/issues/1988

	Unfortunately, the tutorial for saving a model for inference "freezes" the
	variables in place and makes them unservable by tensorflow_serving.
	export_inference_graph.py exports an empty "variables" directory, which needs to
	be populated.
	#include<stdio.h>
	#include<math.h>
	float f(float x){
	return x*log10(x)-1.2;
	}
	float df(float x){
	return log10(x) + 0.434293;
	}
	int main(){
	int a,b,maxitr,itr;
	from urllib.request import urlopen
	from bs4 import BeautifulSoup
	import requests
	page=urlopen("https://www.cardekho.com/")
	soup = BeautifulSoup(page.read(),"html5lib")
	new =soup.find_all("div",{"class":"price"})
	len(new) #to count the number of price class element i.e testing purpose
	print(new[0].text)#for testing the link
	about=new[0]
	for about in new:
	<!DOCTYPE html>
	<html>
	<head>
	<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
	<script type="text/javascript">
	google.charts.load("current", {packages:["corechart"]});
	google.charts.setOnLoadCallback(drawChart);
	function drawChart() {