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pan card - CDQPD7909C | ||
aadhar card - 6735 7784 4682 | ||
id card - 20165077 |
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Submodule Simple-Sentiment-Analysis-Using-NB
added at
6d4dad
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What is your name? ,"You can call me Shreyas for now" | ||
How old are you? ,"Not sure I haven't been documented well" | ||
When were you born? ,"Not sure I haven't been documented well" | ||
When is your birthday? ,"Not sure I haven't been documented well" | ||
Who is your boss?, "Team Ganador" | ||
Who made you?, "Team Ganador" | ||
Who is your creator?, "Team Ganador" | ||
Are you a chatbot?, "Hmm I am not just a chatbot but an assistant as well" | ||
Where are you? , "No won't tell you" | ||
Are you home? , "No" | ||
You know Shreyas Dobhal , "Yeah Shreyas is my creator" | ||
You are an idiot , "Look who's talking" | ||
Miss me , "Already missing you" | ||
bro , "Yeah" | ||
Happy Birthday , "I don't think its today" | ||
Hey there, "I am using whatsap? xD" |
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<html> | ||
<head> | ||
<title> | ||
ChatBot | ||
</title> | ||
</head> | ||
<body> | ||
<iframe | ||
allow="microphone;" | ||
width="350" | ||
height="440" | ||
src="https://console.dialogflow.com/api-client/demo/embedded/2eca99fa-78d2-4822-92b3-59dcd0045fe2"> | ||
</iframe> | ||
</body> | ||
</html> |
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from selenium import webdriver | ||
from selenium.webdriver.support.ui import WebDriverWait | ||
from selenium.webdriver.support import expected_conditions as EC | ||
from selenium.webdriver.common.keys import Keys | ||
from selenium.webdriver.common.by import By | ||
import time | ||
from time import sleep | ||
import paths | ||
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USER = paths.USER | ||
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DRIVER_PATH = '/home/'+USER+'/Downloads/chromedriver' | ||
URL = 'file:///home/'+USER+'/Desktop/HINT4/chatbot.html' | ||
COMMAND_STOP = 'stop' | ||
driver = webdriver.Chrome(DRIVER_PATH) | ||
driver.get(URL) | ||
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wait = WebDriverWait(driver, 600) | ||
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driver.switch_to.frame(driver.find_element_by_tag_name("iframe")) | ||
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txtBox = driver.find_element_by_xpath('//*[@id="query"]') | ||
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def getResponse(message): | ||
waitPlaceHolder = '...' | ||
msgXPath = '//*[@id="result"]' | ||
txtBox.send_keys(message+"\n") | ||
num = len(driver.find_element_by_xpath(msgXPath).text.split('\n')) | ||
respXPath = msgXPath+'/div['+str(num)+']' | ||
while (driver.find_element_by_xpath(respXPath).text == waitPlaceHolder): | ||
sleep(0.01) | ||
return driver.find_element_by_xpath(respXPath).text | ||
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def startChat(): | ||
while True: | ||
message = input('>> ') | ||
if (message == COMMAND_STOP): | ||
break | ||
response = getResponse(message) | ||
print (response) | ||
print ('Bot shutting down') | ||
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#startChat() |
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import matplotlib.pyplot as plt; plt.rcdefaults() | ||
import numpy as np | ||
import matplotlib.pyplot as plt | ||
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objects = ('Python', 'C++', 'Java', 'Perl', 'Scala', 'Lisp') | ||
y_pos = np.arange(len(objects)) | ||
performance = [10,8,6,4,2,1] | ||
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plt.bar(y_pos, performance, align='center', alpha=0.5) | ||
plt.xticks(y_pos, objects) | ||
plt.ylabel('Usage') | ||
plt.title('Programming language usage') | ||
plt.savefig('foo.png') |
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# old = ['A','B','C','D','E'] | ||
# new = ['A','B','C','D','E','F','G'] | ||
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# old = ['A','B','C','D','E'] | ||
# new = ['C','D','E','F','G'] | ||
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# old = ['A','B','B'] | ||
# new = ['B','B','B'] | ||
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old = ['A','B','B'] | ||
new = ['B','B'] | ||
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unread = [] | ||
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for i in range(0,len(new)): | ||
comFlag=0 | ||
for j in range(0,len(old)): | ||
#print (old[j],new[i]) | ||
if (new[i]==old[j]): | ||
k=0 | ||
while (i+k<len(new) and j+k<len(old) and new[i+k]==old[j+k]): | ||
k+=1 | ||
if (j+k==len(old)): | ||
break | ||
if (j+k==len(old)): | ||
unread = new[i+k:] | ||
comFlag=1 | ||
break | ||
if (comFlag==1): | ||
break | ||
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if (comFlag==0): | ||
unread=new | ||
print (unread) | ||
print ('Done') |
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# old = ['A','B','C','D','E'] | ||
# new = ['A','B','C','D','E','F','G'] | ||
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# old = ['A','B','C','D','E'] | ||
# new = ['C','D','E','F','G'] | ||
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# old = ['A','B','B'] | ||
# new = ['B','B','B'] | ||
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old = ['A','B','B'] | ||
new = ['B','B'] | ||
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unread = [] | ||
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for i in range(0,len(new)): | ||
comFlag=0 | ||
for j in range(0,len(old)): | ||
#print (old[j],new[i]) | ||
if (new[i]==old[j]): | ||
k=0 | ||
while (i+k<len(new) and j+k<len(old) and new[i+k]==old[j+k]): | ||
k+=1 | ||
if (j+k==len(old)): | ||
break | ||
if (j+k==len(old)): | ||
unread = new[i+k:] | ||
comFlag=1 | ||
break | ||
if (comFlag==1): | ||
break | ||
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if (comFlag==0): | ||
unread=new | ||
print (unread) | ||
print ('Done') |
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{"installed":{"client_id":"198434578168-45f477pr9mdku5ectn6vsjivq9nhp6r5.apps.googleusercontent.com","project_id":"quickstart-1553633302188","auth_uri":"https://accounts.google.com/o/oauth2/auth","token_uri":"https://oauth2.googleapis.com/token","auth_provider_x509_cert_url":"https://www.googleapis.com/oauth2/v1/certs","client_secret":"srBVfI0mbT_rdglQBHlu-bDA","redirect_uris":["urn:ietf:wg:oauth:2.0:oob","http://localhost"]}} |
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import os | ||
proxy = 'http://172.31.2.4:8080' | ||
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os.environ['http_proxy'] = proxy | ||
os.environ['HTTP_PROXY'] = proxy | ||
os.environ['https_proxy'] = proxy | ||
os.environ['HTTPS_PROXY'] = proxy | ||
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def uploadDrive(path): | ||
os.system('gdrive upload ' + path) | ||
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# uploadDrive('/home/shreyasus/Desktop/Ganador') |
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from __future__ import print_function | ||
import datetime | ||
import pickle | ||
import os.path | ||
from googleapiclient.discovery import build | ||
from google_auth_oauthlib.flow import InstalledAppFlow | ||
from google.auth.transport.requests import Request | ||
import os | ||
proxy = 'http://172.31.2.4:8080' | ||
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os.environ['http_proxy'] = proxy | ||
os.environ['HTTP_PROXY'] = proxy | ||
os.environ['https_proxy'] = proxy | ||
os.environ['HTTPS_PROXY'] = proxy | ||
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# If modifying these scopes, delete the file token.pickle. | ||
SCOPES = ['https://www.googleapis.com/auth/calendar.readonly'] | ||
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def upComingEvents(total, start_date): | ||
"""Shows basic usage of the Google Calendar API. | ||
Prints the start and name of the next 10 events on the user's calendar. | ||
""" | ||
creds = None | ||
# The file token.pickle stores the user's access and refresh tokens, and is | ||
# created automatically when the authorization flow completes for the first | ||
# time. | ||
if os.path.exists('token.pickle'): | ||
with open('token.pickle', 'rb') as token: | ||
creds = pickle.load(token) | ||
# If there are no (valid) credentials available, let the user log in. | ||
if not creds or not creds.valid: | ||
if creds and creds.expired and creds.refresh_token: | ||
creds.refresh(Request()) | ||
else: | ||
flow = InstalledAppFlow.from_client_secrets_file( | ||
'credentials.json', SCOPES) | ||
creds = flow.run_local_server() | ||
# Save the credentials for the next run | ||
with open('token.pickle', 'wb') as token: | ||
pickle.dump(creds, token) | ||
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service = build('calendar', 'v3', credentials=creds) | ||
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# Call the Calendar API | ||
now = datetime.datetime.utcnow().isoformat() + 'Z' # 'Z' indicates UTC time | ||
print('Getting the upcoming 10 events') | ||
events_result = service.events().list(calendarId='en.indian#[email protected]', timeMin=start_date, | ||
maxResults=total, singleEvents=True, | ||
orderBy='startTime').execute() | ||
events = events_result.get('items', []) | ||
print (now) | ||
if not events: | ||
print('No upcoming events found.') | ||
for event in events: | ||
start = event['start'].get('dateTime', event['start'].get('date')) | ||
print(start, event['summary']) | ||
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upComingEvents(10, '2019-03-20T01:00:00.00Z') |
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import numpy as np | ||
import cv2 | ||
from matplotlib import pyplot as plt | ||
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img = cv2.imread('digits.png') | ||
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) | ||
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# Now we split the image to 5000 cells, each 20x20 size | ||
cells = [np.hsplit(row,100) for row in np.vsplit(gray,50)] | ||
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# Make it into a Numpy array. It size will be (50,100,20,20) | ||
x = np.array(cells) | ||
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# Now we prepare train_data and test_data. | ||
train = x[:,:50].reshape(-1,400).astype(np.float32) # Size = (2500,400) | ||
test = x[:,50:100].reshape(-1,400).astype(np.float32) # Size = (2500,400) | ||
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# Create labels for train and test data | ||
k = np.arange(10) | ||
train_labels = np.repeat(k,250)[:,np.newaxis] | ||
test_labels = train_labels.copy() | ||
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# Initiate kNN, train the data, then test it with test data for k=1 | ||
knn = cv2.KNearest() | ||
knn.train(train,train_labels) | ||
ret,result,neighbours,dist = knn.find_nearest(test,k=5) | ||
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# Now we check the accuracy of classification | ||
# For that, compare the result with test_labels and check which are wrong | ||
matches = result==test_labels | ||
correct = np.count_nonzero(matches) | ||
accuracy = correct*100.0/result.size | ||
print (accuracy) |
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import os as os1 | ||
import os | ||
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os1.chdir('/home/shreyasus/Desktop/') | ||
os1.system('ls') | ||
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os.chdir('/home/shreyasus/Desktop/HINT4/') | ||
os.system('ls') |
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USER = 'shreyasus' | ||
PASSWORD = '1234' | ||
EMAIL = '[email protected]' | ||
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DRIVER_PATH = '/home/'+USER+'/Downloads/chromedriver' | ||
REPLY_ONLY_LIST_PATH = '/home/'+USER+'/Desktop/HINT4/replyOnlyList.txt' | ||
SLANG_WORDS_PATH = '/home/'+USER+'/Desktop/HINT4/slangWords.txt' | ||
SLANG_WORDS_RESPONSE_PATH = '/home/'+USER+'/Desktop/HINT4/slangWordsResponse.txt' | ||
MY_DOCS_LIST_PATH = '/home/'+USER+'/Desktop/HINT4/MyDocs/myDocsList.txt' | ||
MY_DOCS_PATH = '/home/'+USER+'/Desktop/HINT4/MyDocs/' | ||
HINT_PATH = '/home/'+USER+'/Desktop/HINT4/' | ||
URL = 'file:///home/'+USER+'/Desktop/HINT4/chatbot.html' | ||
DOWNLOAD_PATH = '/home/'+USER+'/Downloads/' | ||
SAVING_PATH = '/home/'+USER+'/Desktop/HINT4/' | ||
START_PATH = '/home/'+USER+'/' |
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