def testResultNumberAtTwoPages(self):
googlenews = GoogleNews()
googlenews.search(keyword)
result = googlenews.page_at(2)
length = len(result)
self.assertEqual(length, 10)
print('Result length at two pages is correct')
def run_alexa():
command = take_command()
print(command)
if 'music' in command:
song = command.replace('play song', '')
talk('I am playing your favourite ' + song)
# print('playing')
print(song)
# playing the first video that appears in yt search
pywhatkit.playonyt(song)
elif 'time' in command:
now = datetime.now()
time = now.strftime("%H:%M:%S")
print("time:", time)
talk("Current time is " + time)
elif ('month' or 'year') in command:
now = datetime.now()
year = now.strftime("%Y")
print("year:", year)
talk("Current year is " + year)
month = now.strftime("%m")
print("month:", month)
talk("Current month is " + month)
elif 'date' in command:
now = datetime.now()
date_time = now.strftime("%m/%d/%Y, %H:%M:%S")
print("date and time:", date_time)
talk("Current date and time is " + date_time)
# opens web.whatsapp at specified time i.e before 10 minutes and send the msg
elif 'whatsapp' in command:
talk("To which number do you have to whatsapp")
talk("Please dont forget to enter 10 digits with country code")
num = input()
talk("Enter the message you have to send")
msg = input()
talk("Enter the time to send the message")
time = int(input())
pywhatkit.sendwhatmsg(num, msg, time, 00)
pywhatkit.showHistory()
pywhatkit.shutdown(3000000000)
# pywhatkit.sendwhatmsg("+919876543210", "This is a message", 15, 00)
# Convert text to handwritten format
elif 'convert' in command:
text = command.replace('convert', '')
pywhatkit.text_to_handwriting(text, rgb=[0, 0, 0])
# Perform google search
elif 'search' in command:
key = command.replace('search', '')
pywhatkit.search("key")
elif 'wikipedia' in command:
person = command.replace('wikipedia', '')
talk("How many pages do you want to read")
num_pages = int(input())
# talk("In which language do you want to read")
# l = input()
# wikipedia.set_lang(l)
info = wikipedia.summary(person, num_pages)
print(info)
talk(info)
elif 'can you work for me' in command:
talk("sorry, I have headache. Please do your work")
elif 'are you single' in command:
talk("I am in relationshhip with wifi")
elif 'joke' in command:
talk(pyjokes.get_joke())
talk("sorry for the lamest joke")
elif 'open google browser' in command:
try:
urL = 'https://www.google.com'
chrome_path = "C:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe"
webbrowser.register('chrome', None,
webbrowser.BackgroundBrowser(chrome_path))
webbrowser.get('chrome').open_new_tab(urL)
talk("Successfully opened chrome its upto you to search")
except:
webbrowser.Error
elif 'google search' in command:
word_to_search = command.replace('google search', '')
response = GoogleSearch().search(word_to_search)
print(response)
for result in response.results:
print("Title: " + result.title)
talk("You can look for the following titles " + result.title)
elif 'weather' in command:
# base URL
BASE_URL = "https://api.openweathermap.org/data/2.5/weather?"
talk("Which city weather are you looking for")
try:
with sr.Microphone() as source:
print('listening weather...')
city_voice = listener.listen(source)
city = listener.recognize_google(city_voice)
# city = '\"'+city.lower()+'\"'
print(city)
# city="bangalore"
# API key API_KEY = "Your API Key"
API_KEY = "b5a362ef1dc8e16c673dd5049aa98d8f"
# upadting the URL
URL = BASE_URL + "q=" + city + "&appid=" + API_KEY
# HTTP request
response = requests.get(URL)
# checking the status code of the request
if response.status_code == 200:
# getting data in the json format
data = response.json()
# getting the main dict block
main = data['main']
# getting temperature
temperature = main['temp']
# getting the humidity
humidity = main['humidity']
# getting the pressure
pressure = main['pressure']
# weather report
report = data['weather']
print(f"{CITY:-^30}")
print(f"Temperature: {temperature}")
print(f"Humidity: {humidity}")
print(f"Pressure: {pressure}")
print(f"Weather Report: {report[0]['description']}")
talk("Temperature in " + city + " is " + temperature +
" humidity is " + humidity + " pressure is " +
pressure + " and your final weather report" + report)
else:
# showing the error message
print("Error in the HTTP request")
talk("Error in the HTTP request")
except:
talk("Hmmmmm, it looks like there is something wrong")
elif 'news' in command:
try:
googlenews = GoogleNews()
googlenews.set_lang('en')
# googlenews.set_period('7d')
# googlenews.set_time_range('02/01/2020', '02/28/2020')
googlenews.set_encode('utf-8')
talk("What news are you looking for")
try:
with sr.Microphone() as source:
print('listening news ...')
news_voice = listener.listen(source)
news_input = listener.recognize_google(news_voice)
news_input = news_input.lower()
print(news_input)
googlenews.get_news(news_input)
googlenews.search(news_input)
googlenews.get_page(2)
result = googlenews.page_at(2)
news = googlenews.get_texts()
print(news)
talk(news)
except:
print("Error")
talk("Error in reading input")
except:
print("No news")
talk(" I couldn't find any news on this day")
elif 'play book' or 'read pdf' in command:
talk("Which pdf do you want me to read")
book_input = input()
print(book_input)
book = open(book_input, 'rb')
# create pdfReader object
pdfReader = PyPDF2.PdfFileReader(book)
# count the total pages
total_pages = pdfReader.numPages
total_pages = str(total_pages)
print("Total number of pages " + total_pages)
talk("Total number of pages " + total_pages)
# initialise speaker object
# speaker = pyttsx3.init()
# talk("Enter your starting page")
# start_page = int(input())
talk(
" here are the options for you, you can press 1 to Play a single page 2 to Play between start and end points and 3 to Play the entire book "
)
talk("Enter your choice")
choice = int(input())
if (choice == 1):
talk("Enter index number")
page = int(input())
page = pdfReader.getPage(page)
text = page.extractText()
talk(text)
# speaker.say(text)
# speaker.runAndWait()
elif (choice == 2):
talk("Enter starting page number")
start_page = int(input())
talk("Enter ending page number")
end_page = int(input())
for page in range(start_page + 1, end_page):
page = pdfReader.getPage(start_page + 1)
text = page.extractText()
talk(text)
# speaker.say(text)
# speaker.runAndWait()
elif (choice == 3):
for page in range(total_pages + 1):
page = pdfReader.getPage(page)
text = page.extractText()
talk(text)
# speaker.say(text)
# speaker.runAndWait()
else:
talk("Haha!! Please enter valid choice")
else:
talk(
"Hiii Rashika, I am so bored can you please give me some proper commands"
)
def main() -> None:
# Load in scraped stories
with open('../stories.pickle', 'rb') as infile:
stories = pickle.load(infile)
# Compute keyword frequency where each story contributes once to count
keyword_freq = defaultdict(int)
for story in stories:
keywords = story.keywords
for keyword in keywords:
keyword_freq[keyword] += 1
# Select top NUM_QUERIES keywords by frequency as queries for evaluation
queries2count = sorted(keyword_freq.items(),
key=lambda item: item[1],
reverse=True)[:NUM_QUERIES]
# Set up Google News fetcher for plausible date range of start of 2020 to date after we scraped
# (to avoid potential boundary condition)
gn = GoogleNews(lang='en', start='01/01/2020', end='05/07/2021')
# Poll Google News for evaluation queries and save results
query2urls_relevant = {}
for query, _ in tqdm(queries2count,
total=NUM_QUERIES,
desc='Polling GoogleNews Step'):
gn.search(query)
time.sleep(1) # Avoid HTTP Error 429: Too Many Requests
urls = []
for i in range(1, NUM_PAGES + 1): # Make sue NUM_PAGES is included
articles = gn.page_at(i) # GoogleNews is one-based
urls.extend([article['link'] for article in articles])
time.sleep(1) # Avoid HTTP Error 429: Too Many Requests
query2urls_relevant[query] = urls
# Save relevant queries as Pickle file just in case
with open('relevant_queries.pickle', 'wb') as outfile:
pickle.dump(query2urls_relevant,
outfile,
protocol=pickle.HIGHEST_PROTOCOL)
# Obtain ordering of documents from our system for the same evaluation queries
query2urls_results = {}
doc_vecs_db = SqliteDict(doc_vecs_db_path)
for query, _ in tqdm(queries2count,
total=NUM_QUERIES,
desc='Our System Step'):
doc_ids: list[str] = get_nearest(string2vec(query), return_all=True)
query2urls_results[query] = [
doc_vecs_db[doc_id].link for doc_id in doc_ids
]
# Compute precision at
median_ranks = []
intersection_sizes = []
for query, _ in queries2count:
intersection = set(query2urls_results[query]) & set(
query2urls_relevant[query])
ranks = [
query2urls_results[query].index(url) + 1 for url in intersection
]
median_ranks.append(np.median(ranks))
intersection_sizes.append(len(intersection))
# recalls = np.linspace(0.0, 1.0)
# precisions = []
# for recall in recalls:
# precisions.append(precision_at(recall, query2urls_results[query], query2urls_relevant[query]))
# plt.plot(recalls, precisions)
# plt.show()
queries = list(range(1, NUM_QUERIES + 1)) # Make x-axis 1-based
plt.plot(queries, median_ranks)
plt.title("Median Rank over Our Ordering w.r.t. Google News")
plt.xlabel('Query Index')
plt.ylabel('Median Rank')
plt.plot(queries, intersection_sizes)
plt.title(
"Number of Common Articles between All Relevant and Returned Articles")
plt.xlabel('Query Index')
plt.ylabel('Size of Overlap')
