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x = input('Enter any number ') | ||
sum = 0 | ||
for i in x: | ||
y = int(i) | ||
a = y**3 | ||
sum = sum+a | ||
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print(sum) |
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print("hello sandeep. Its was a nice meeting with you") |
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Rank,Name,Platform,Year,Genre,Publisher,NA_Sales,EU_Sales,JP_Sales,Other_Sales,Global_Sales | ||
1,Wii Sports,Wii,2006,Sports,Nintendo,41.49,29.02,3.77,8.46,82.74 | ||
2,Super Mario Bros.,NES,1985,Platform,Nintendo,29.08,3.58,6.81,0.77,40.24 | ||
3,Mario Kart Wii,Wii,2008,Racing,Nintendo,15.85,12.88,3.79,3.31,35.82 | ||
4,Wii Sports Resort,Wii,2009,Sports,Nintendo,15.75,11.01,3.28,2.96,33 | ||
5,Pokemon Red/Pokemon Blue,GB,1996,Role-Playing,Nintendo,11.27,8.89,10.22,1,31.37 | ||
6,Tetris,GB,1989,Puzzle,Nintendo,23.2,2.26,4.22,0.58,30.26 | ||
7,New Super Mario Bros.,DS,2006,Platform,Nintendo,11.38,9.23,6.5,2.9,30.01 | ||
8,Wii Play,Wii,2006,Misc,Nintendo,14.03,9.2,2.93,2.85,29.02 | ||
9,New Super Mario Bros. Wii,Wii,2009,Platform,Nintendo,14.59,7.06,4.7,2.26,28.62 | ||
10,Duck Hunt,NES,1984,Shooter,Nintendo,26.93,0.63,0.28,0.47,28.31 | ||
11,Nintendogs,DS,2005,Simulation,Nintendo,9.07,11,1.93,2.75,24.76 | ||
12,Mario Kart DS,DS,2005,Racing,Nintendo,9.81,7.57,4.13,1.92,23.42 | ||
13,Pokemon Gold/Pokemon Silver,GB,1999,Role-Playing,Nintendo,9,6.18,7.2,0.71,23.1 | ||
14,Wii Fit,Wii,2007,Sports,Nintendo,8.94,8.03,3.6,2.15,22.72 | ||
15,Wii Fit Plus,Wii,2009,Sports,Nintendo,9.09,8.59,2.53,1.79,22 |
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from yattag import indent | ||
with open("E:/python/Tools/style.css", "r") as file: | ||
data = file.read() | ||
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result = indent( | ||
data, | ||
indentation=' ', | ||
newline='\r\n', | ||
indent_text=True | ||
) | ||
print(result) |
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# python program to convert any csv file into html file | ||
# made by : rakesh kumar | ||
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import csv | ||
html = "<table>" | ||
with open("E:/python/Tools/SampleData.csv") as csv_file: | ||
csv_data = csv.reader(csv_file) | ||
count = 1 | ||
for row in csv_data: | ||
html += "<tr>" | ||
if count == 1: | ||
for y in row: | ||
html += "<th>"+y+"</th>" | ||
else: | ||
for y in row: | ||
html += "<td>"+y+"</td>" | ||
html += "</tr>" | ||
count += 1 | ||
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html += "</table>" | ||
print(html) |
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import csv | ||
import json | ||
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data = [] | ||
keys = [] | ||
with open("E:/python/Tools/SampleData.csv") as csv_file: | ||
csv_data = csv.reader(csv_file) | ||
count = 1 | ||
for row in csv_data: | ||
if count == 1: | ||
for y in row: | ||
keys.append(y) | ||
else: | ||
element = {} | ||
for y in range(len(row)): | ||
element[keys[y]] = row[y] | ||
data.append(element) | ||
count = count+1 | ||
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print(json.dumps(data,)) |
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# program to convert CSV file into PDF file | ||
from fpdf import FPDF | ||
import csv | ||
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with open("e:/python/tools/SampleData.csv", "r") as csv_file: | ||
data = csv.reader(csv_file) | ||
for row in data: | ||
print(row) | ||
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pdf = FPDF(orientation='P', unit='mm', format='A4') # P -potrait L-Landscape | ||
pdf.add_page() | ||
pdf.set_font("Arial", size=12) | ||
pdf.cell(200, 10, txt=str(d), ln=1, align="C") | ||
pdf.output("simple_demo.pdf") |
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# python program to convert any csv file into xml file | ||
# made by : rakesh kumar | ||
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import csv | ||
xml = '<?xml version= "1.0" encoding="UTF-8" ?><rows>' | ||
keys = [] | ||
with open("E:/python/Tools/SampleData.csv") as csv_file: | ||
csv_data = csv.reader(csv_file) | ||
count = 1 | ||
for row in csv_data: | ||
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if count == 1: | ||
for y in row: | ||
keys.append(y) | ||
else: | ||
xml += "<row>" | ||
for y in range(len(row)): | ||
xml += "<"+keys[y]+">"+row[y]+"</"+keys[y]+">" | ||
xml += "</row>" | ||
count += 1 | ||
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xml += "</rows>" | ||
print(xml) |
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from yattag import indent | ||
with open("E:/python/Tools/index.html", "r") as file: | ||
data = file.read() | ||
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result = indent( | ||
data, | ||
indentation=' ', | ||
newline='\r\n', | ||
indent_text=True | ||
) | ||
print(result) |
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<?xml version= "1.0" encoding="UTF-8" ?><rows><row><Rank>1</Rank><Name>Wii Sports</Name><Platform>Wii</Platform><Year>2006</Year><Genre>Sports</Genre><Publisher>Nintendo</Publisher><NA_Sales>41.49</NA_Sales><EU_Sales>29.02</EU_Sales><JP_Sales>3.77</JP_Sales><Other_Sales>8.46</Other_Sales><Global_Sales>82.74</Global_Sales></row><row><Rank>2</Rank><Name>Super Mario Bros.</Name><Platform>NES</Platform><Year>1985</Year><Genre>Platform</Genre><Publisher>Nintendo</Publisher><NA_Sales>29.08</NA_Sales><EU_Sales>3.58</EU_Sales><JP_Sales>6.81</JP_Sales><Other_Sales>0.77</Other_Sales><Global_Sales>40.24</Global_Sales></row><row><Rank>3</Rank><Name>Mario Kart Wii</Name><Platform>Wii</Platform><Year>2008</Year><Genre>Racing</Genre><Publisher>Nintendo</Publisher><NA_Sales>15.85</NA_Sales><EU_Sales>12.88</EU_Sales><JP_Sales>3.79</JP_Sales><Other_Sales>3.31</Other_Sales><Global_Sales>35.82</Global_Sales></row><row><Rank>4</Rank><Name>Wii Sports Resort</Name><Platform>Wii</Platform><Year>2009</Year><Genre>Sports</Genre><Publisher>Nintendo</Publisher><NA_Sales>15.75</NA_Sales><EU_Sales>11.01</EU_Sales><JP_Sales>3.28</JP_Sales><Other_Sales>2.96</Other_Sales><Global_Sales>33</Global_Sales></row><row><Rank>5</Rank><Name>Pokemon Red/Pokemon Blue</Name><Platform>GB</Platform><Year>1996</Year><Genre>Role-Playing</Genre><Publisher>Nintendo</Publisher><NA_Sales>11.27</NA_Sales><EU_Sales>8.89</EU_Sales><JP_Sales>10.22</JP_Sales><Other_Sales>1</Other_Sales><Global_Sales>31.37</Global_Sales></row><row><Rank>6</Rank><Name>Tetris</Name><Platform>GB</Platform><Year>1989</Year><Genre>Puzzle</Genre><Publisher>Nintendo</Publisher><NA_Sales>23.2</NA_Sales><EU_Sales>2.26</EU_Sales><JP_Sales>4.22</JP_Sales><Other_Sales>0.58</Other_Sales><Global_Sales>30.26</Global_Sales></row><row><Rank>7</Rank><Name>New Super Mario Bros.</Name><Platform>DS</Platform><Year>2006</Year><Genre>Platform</Genre><Publisher>Nintendo</Publisher><NA_Sales>11.38</NA_Sales><EU_Sales>9.23</EU_Sales><JP_Sales>6.5</JP_Sales><Other_Sales>2.9</Other_Sales><Global_Sales>30.01</Global_Sales></row><row><Rank>8</Rank><Name>Wii Play</Name><Platform>Wii</Platform><Year>2006</Year><Genre>Misc</Genre><Publisher>Nintendo</Publisher><NA_Sales>14.03</NA_Sales><EU_Sales>9.2</EU_Sales><JP_Sales>2.93</JP_Sales><Other_Sales>2.85</Other_Sales><Global_Sales>29.02</Global_Sales></row><row><Rank>9</Rank><Name>New Super Mario Bros. Wii</Name><Platform>Wii</Platform><Year>2009</Year><Genre>Platform</Genre><Publisher>Nintendo</Publisher><NA_Sales>14.59</NA_Sales><EU_Sales>7.06</EU_Sales><JP_Sales>4.7</JP_Sales><Other_Sales>2.26</Other_Sales><Global_Sales>28.62</Global_Sales></row><row><Rank>10</Rank><Name>Duck Hunt</Name><Platform>NES</Platform><Year>1984</Year><Genre>Shooter</Genre><Publisher>Nintendo</Publisher><NA_Sales>26.93</NA_Sales><EU_Sales>0.63</EU_Sales><JP_Sales>0.28</JP_Sales><Other_Sales>0.47</Other_Sales><Global_Sales>28.31</Global_Sales></row><row><Rank>11</Rank><Name>Nintendogs</Name><Platform>DS</Platform><Year>2005</Year><Genre>Simulation</Genre><Publisher>Nintendo</Publisher><NA_Sales>9.07</NA_Sales><EU_Sales>11</EU_Sales><JP_Sales>1.93</JP_Sales><Other_Sales>2.75</Other_Sales><Global_Sales>24.76</Global_Sales></row><row><Rank>12</Rank><Name>Mario Kart DS</Name><Platform>DS</Platform><Year>2005</Year><Genre>Racing</Genre><Publisher>Nintendo</Publisher><NA_Sales>9.81</NA_Sales><EU_Sales>7.57</EU_Sales><JP_Sales>4.13</JP_Sales><Other_Sales>1.92</Other_Sales><Global_Sales>23.42</Global_Sales></row><row><Rank>13</Rank><Name>Pokemon Gold/Pokemon Silver</Name><Platform>GB</Platform><Year>1999</Year><Genre>Role-Playing</Genre><Publisher>Nintendo</Publisher><NA_Sales>9</NA_Sales><EU_Sales>6.18</EU_Sales><JP_Sales>7.2</JP_Sales><Other_Sales>0.71</Other_Sales><Global_Sales>23.1</Global_Sales></row><row><Rank>14</Rank><Name>Wii Fit</Name><Platform>Wii</Platform><Year>2007</Year><Genre>Sports</Genre><Publisher>Nintendo</Publisher><NA_Sales>8.94</NA_Sales><EU_Sales>8.03</EU_Sales><JP_Sales>3.6</JP_Sales><Other_Sales>2.15</Other_Sales><Global_Sales>22.72</Global_Sales></row><row><Rank>15</Rank><Name>Wii Fit Plus</Name><Platform>Wii</Platform><Year>2009</Year><Genre>Sports</Genre><Publisher>Nintendo</Publisher><NA_Sales>9.09</NA_Sales><EU_Sales>8.59</EU_Sales><JP_Sales>2.53</JP_Sales><Other_Sales>1.79</Other_Sales><Global_Sales>22</Global_Sales></row></rows> |
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.underline {position: relative; margin-bottom:30px;} | ||
.underline::after{ display: block; content: ''; width: 50px; height: 1px; background: #F27316; position: absolute;bottom: -15px;left: 0%;margin-bottom: ;} |
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# python program to convert any csv file into html file | ||
# made by : rakesh kumar | ||
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||
import csv | ||
html = "<table>" | ||
with open("E:/python/Tools/SampleData.csv") as csv_file: | ||
csv_data = csv.reader(csv_file) | ||
count = 1 | ||
for row in csv_data: | ||
html += "<tr>" | ||
if count == 1: | ||
for y in row: | ||
html += "<th>"+y+"</th>" | ||
else: | ||
for y in row: | ||
html += "<td>"+y+"</td>" | ||
html += "</tr>" | ||
count += 1 | ||
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html += "</table>" | ||
print(html) |
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from yattag import indent | ||
with open("E:/python/Tools/sample.xml", "r") as file: | ||
data = file.read() | ||
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result = indent( | ||
data, | ||
indentation=' ', | ||
newline='\r\n', | ||
indent_text=True | ||
) | ||
print(result) |
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d1 = {"name": "rakesh"} | ||
print(d1) |
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L = ['the', 'in', 'out', 'the', 'in', 'ram', 'umesh', 'the'] | ||
d = {} | ||
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""" l = len(L) | ||
for i in range(0, l): | ||
key = L.count(L[i]) | ||
if key not in d: | ||
value = [] | ||
for j in range(i, l): | ||
if(L.count(L[j]) == key and L[j] not in value): | ||
value.append(L[j]) | ||
d[key] = value | ||
""" | ||
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for i in L: | ||
c = L.count(i) | ||
if c not in d: | ||
d[c] = [i] | ||
elif i not in d[c]: | ||
d[c].append(i) | ||
print(d) |
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# program to add comment at the begining of each python file having extension .py | ||
# made by : rakesh kumar | ||
# licence : MIT | ||
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import os | ||
import sys # module for terminating | ||
import glob | ||
import tkinter as tk | ||
from tkinter import filedialog | ||
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str = "# program to comment on every file \n" | ||
str = str + "# made by : rakesh kumar \n" | ||
str = str+" # class - : xi A \n" | ||
str = str+" # session :2019-20 \n\n" | ||
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def add_comment(filename): | ||
with open(filename, "r") as f: | ||
data = f.read() | ||
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with open("abc.txt", "w") as f: | ||
f.write(str) | ||
f.write(data) | ||
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os.unlink(filename) | ||
os.rename("abc.txt", filename) | ||
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if __name__ == "__main__": | ||
root = tk.Tk() | ||
root.withdraw() | ||
directory = filedialog.askdirectory() # source folder | ||
count = 0 | ||
for root, SubFolders, files in os.walk(directory): | ||
os.chdir(root) | ||
files = glob.glob('*.py') | ||
# print(files) | ||
for filename in files: | ||
print(filename, 'Comment Added') | ||
add_comment(filename) | ||
count += 1 |
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import csv | ||
import json | ||
with open(r'C:/Users/rakesh\Desktop/python/fileHandling/convert.csv') as csf_file: | ||
with open('e:/python/tools/SampleData.csv') as csf_file: | ||
csv_reader = csv.reader(csf_file) | ||
line=0 | ||
keys=[] | ||
jon=[] | ||
line = 0 | ||
keys = [] | ||
jon = [] | ||
for row in csv_reader: | ||
d = {} | ||
if line==0: | ||
if line == 0: | ||
for col in row: | ||
keys.append(col) | ||
else: | ||
for i in range(len(row)): | ||
d[keys[i]]=row[i] | ||
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if(line>=1): | ||
jon.append(d) | ||
line+=1 | ||
#print(jon) | ||
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with open("jsonFile.json","w") as json_file: | ||
json_file.write( json.dumps(jon,)) | ||
d[keys[i]] = row[i] | ||
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if(line >= 1): | ||
jon.append(d) | ||
line += 1 | ||
# print(jon) | ||
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with open("jsonFile.json", "w") as json_file: | ||
json_file.write(json.dumps(jon,)) |
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import json | ||
import requests | ||
source = requests.get('https://jsonplaceholder.typicode.com/todos/1') | ||
print(source.read()) | ||
url = ('https://newsapi.org/v2/top-headlines?' | ||
'country=in&' | ||
'apiKey=2121032f088e4370affe13ca317f8d1a') | ||
response = requests.get(url) | ||
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#source = requests.get('https://jsonplaceholder.typicode.com/todos/1') | ||
data = json.loads(response.text) | ||
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for article in data['articles']: | ||
print(article['author'], end="-") | ||
print(article['title']) |
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@@ -1 +1 @@ | ||
[{"album": "The White Stripes", " year": "1999", " US_peak_chart_post": " -"}, {"album": "De Stijl", " year": "2000", " US_peak_chart_post": " -"}, {"album": "White Blood Cells", " year": "20.01", " US_peak_chart_post": "61"}, {"album": "Elephant", " year": "2003", " US_peak_chart_post": "6"}, {"album": "Get Behind Me Satan", " year": "2005", " US_peak_chart_post": "3"}, {"album": "Icky Thump", " year": "2007", " US_peak_chart_post": "2"}, {"album": "Under Great White Northern Lights", " year": "2010", " US_peak_chart_post": "11"}, {"album": "Live in Mississippi", " year": "2011", " US_peak_chart_post": " -"}, {"album": "Live at the Gold Dollar", " year": "2012", " US_peak_chart_post": " -"}, {"album": "Nine Miles from the White City", " year": "2013", " US_peak_chart_post": " -"}] | ||
[{"Rank": "1", "Name": "Wii Sports", "Platform": "Wii", "Year": "2006", "Genre": "Sports", "Publisher": "Nintendo", "NA_Sales": "41.49", "EU_Sales": "29.02", "JP_Sales": "3.77", "Other_Sales": "8.46", "Global_Sales": "82.74"}, {"Rank": "2", "Name": "Super Mario Bros.", "Platform": "NES", "Year": "1985", "Genre": "Platform", "Publisher": "Nintendo", "NA_Sales": "29.08", "EU_Sales": "3.58", "JP_Sales": "6.81", "Other_Sales": "0.77", "Global_Sales": "40.24"}, {"Rank": "3", "Name": "Mario Kart Wii", "Platform": "Wii", "Year": "2008", "Genre": "Racing", "Publisher": "Nintendo", "NA_Sales": "15.85", "EU_Sales": "12.88", "JP_Sales": "3.79", "Other_Sales": "3.31", "Global_Sales": "35.82"}, {"Rank": "4", "Name": "Wii Sports Resort", "Platform": "Wii", "Year": "2009", "Genre": "Sports", "Publisher": "Nintendo", "NA_Sales": "15.75", "EU_Sales": "11.01", "JP_Sales": "3.28", "Other_Sales": "2.96", "Global_Sales": "33"}, {"Rank": "5", "Name": "Pokemon Red/Pokemon Blue", "Platform": "GB", "Year": "1996", "Genre": "Role-Playing", "Publisher": "Nintendo", "NA_Sales": "11.27", "EU_Sales": "8.89", "JP_Sales": "10.22", "Other_Sales": "1", "Global_Sales": "31.37"}, {"Rank": "6", "Name": "Tetris", "Platform": "GB", "Year": "1989", "Genre": "Puzzle", "Publisher": "Nintendo", "NA_Sales": "23.2", "EU_Sales": "2.26", "JP_Sales": "4.22", "Other_Sales": "0.58", "Global_Sales": "30.26"}, {"Rank": "7", "Name": "New Super Mario Bros.", "Platform": "DS", "Year": "2006", "Genre": "Platform", "Publisher": "Nintendo", "NA_Sales": "11.38", "EU_Sales": "9.23", "JP_Sales": "6.5", "Other_Sales": "2.9", "Global_Sales": "30.01"}, {"Rank": "8", "Name": "Wii Play", "Platform": "Wii", "Year": "2006", "Genre": "Misc", "Publisher": "Nintendo", "NA_Sales": "14.03", "EU_Sales": "9.2", "JP_Sales": "2.93", "Other_Sales": "2.85", "Global_Sales": "29.02"}, {"Rank": "9", "Name": "New Super Mario Bros. Wii", "Platform": "Wii", "Year": "2009", "Genre": "Platform", "Publisher": "Nintendo", "NA_Sales": "14.59", "EU_Sales": "7.06", "JP_Sales": "4.7", "Other_Sales": "2.26", "Global_Sales": "28.62"}, {"Rank": "10", "Name": "Duck Hunt", "Platform": "NES", "Year": "1984", "Genre": "Shooter", "Publisher": "Nintendo", "NA_Sales": "26.93", "EU_Sales": "0.63", "JP_Sales": "0.28", "Other_Sales": "0.47", "Global_Sales": "28.31"}, {"Rank": "11", "Name": "Nintendogs", "Platform": "DS", "Year": "2005", "Genre": "Simulation", "Publisher": "Nintendo", "NA_Sales": "9.07", "EU_Sales": "11", "JP_Sales": "1.93", "Other_Sales": "2.75", "Global_Sales": "24.76"}, {"Rank": "12", "Name": "Mario Kart DS", "Platform": "DS", "Year": "2005", "Genre": "Racing", "Publisher": "Nintendo", "NA_Sales": "9.81", "EU_Sales": "7.57", "JP_Sales": "4.13", "Other_Sales": "1.92", "Global_Sales": "23.42"}, {"Rank": "13", "Name": "Pokemon Gold/Pokemon Silver", "Platform": "GB", "Year": "1999", "Genre": "Role-Playing", "Publisher": "Nintendo", "NA_Sales": "9", "EU_Sales": "6.18", "JP_Sales": "7.2", "Other_Sales": "0.71", "Global_Sales": "23.1"}, {"Rank": "14", "Name": "Wii Fit", "Platform": "Wii", "Year": "2007", "Genre": "Sports", "Publisher": "Nintendo", "NA_Sales": "8.94", "EU_Sales": "8.03", "JP_Sales": "3.6", "Other_Sales": "2.15", "Global_Sales": "22.72"}, {"Rank": "15", "Name": "Wii Fit Plus", "Platform": "Wii", "Year": "2009", "Genre": "Sports", "Publisher": "Nintendo", "NA_Sales": "9.09", "EU_Sales": "8.59", "JP_Sales": "2.53", "Other_Sales": "1.79", "Global_Sales": "22"}] |
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@@ -1,8 +1,12 @@ | ||
from __future__ import unicode_literals | ||
import youtube_dl | ||
# import urllib | ||
# import shutil | ||
# import shutil | ||
ydl_opts = {} | ||
with youtube_dl.YoutubeDL(ydl_opts) as ydl: | ||
<<<<<<< HEAD | ||
ydl.download(['https://www.youtube.com/watch?v=wF_B_aagLfI']) | ||
======= | ||
ydl.download( | ||
['https://www.youtube.com/watch?v=SCoGwHCNXVw']) | ||
>>>>>>> 4862d6baee53c91054712373dd7190e101b83a22 |