Lakshmi-1212

# 5 Years Data
DATA_RANGE_DAYS = 365*5
END_DATE = date.today() 
START_DATE = END_DATE - timedelta(DATA_RANGE_DAYS)

def get_stock_data(scrip, start_date=START_DATE, end_date=END_DATE, is_index=False):
    return get_history(symbol=scrip, start=start_date, end=end_date,index = is_index)

Lakshmi-1212

intents:
- goodbye
- greet
- recent_matches
- upcoming_matches
entities:
- team
slots:
  team:
    type: text

Lakshmi-1212

class ActionGetUpcomingMatches(Action):
	def name(self):
		return 'action_get_upcoming_matches'

	def run(self, dispatcher, tracker, domain):
		res = requests.get(CRIC_API_URL + "matches" + "?apikey=" + CRIC_API_KEY + "&offset=0")
		if res.status_code == 200:

			matches_data = res.json()["data"]

Lakshmi-1212

class ActionGetRecentMatches(Action):
	def name(self):
		return 'action_get_recent_matches'

	def run(self, dispatcher, tracker, domain):
		res = requests.get(CRIC_API_URL + "currentMatches" + "?apikey=" + CRIC_API_KEY + "&offset=0")
		if res.status_code == 200:
			matches_data = res.json()["data"]
			matches_data.sort(key=lambda x: x["date"], reverse=True)
			matches_data = [x for x in matches_data if "matchType" in x]

Lakshmi-1212

docs_path = 'sample_files'
ignore_words = ['Fig','like','e.g.','i.e.','one']
all_keywords = []

for filename in os.listdir(docs_path):
    filepath = os.path.join(docs_path, filename)
    if os.path.isfile(filepath) and filename.endswith('.pdf'):
        print(f'Parsing file: {filename}')
        try:
            file_text = read_file(filepath)

Lakshmi-1212

filepath = 'sample_files/AI_Blockchain_Survey_2022.pdf'
file_text = read_file(filepath)
keywords = extract_keywords(file_text, min_word_length = 3)
create_word_cloud(keywords,maximum_words=200)

Lakshmi-1212

def create_word_cloud(keywords, maximum_words = 100, bg = 'white', cmap='Dark2',
                     maximum_font_size = 256, width = 3000, height = 2000,
                     random_state = 42, fig_w = 15, fig_h = 10, output_filepath = None):
    
    # Convert keywords to dictionary with values and its occurences
    word_could_dict=Counter(keywords)

    wordcloud = WordCloud(background_color=bg, max_words=maximum_words, colormap=cmap, 
                          stopwords=STOPWORDS, max_font_size=maximum_font_size,
                          random_state=random_state, 

Lakshmi-1212

def extract_keywords(text, ignore_words = [],
                     min_word_length = 0,
                     ignore_numbers = True,
                     ignore_case = True):
    # Remove words with special characters
    filtered_text = ''.join(filter(lambda x:x in string.printable, text))
    
    # Create word tokens from the text string
    tokens = word_tokenize(filtered_text)
    

Lakshmi-1212

def read_file(filepath, use_method = 'textract'):
    
    text = ""
    if not os.path.isfile(filepath):
        print(f'Invalid file:{filepath}')
    else:
        if use_method == 'textract':
            return read_file_textract(filepath)
        elif use_method == 'pypdf':
            return read_file_pypdf(filepath)

Lakshmi-1212

def read_file_pypdf(filepath):
    pdfFileObj = open(filepath,'rb')
    pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
    num_pages = pdfReader.numPages
    text = ""
    # Read all the pages
    for pg in range(num_pages):
        page = pdfReader.getPage(pg)
        text += page.extractText()
    return text