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from apiclient.discovery import build
service = build('translate', 'v2', developerKey='')

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def save_author_names():
    authors = [cmnt.author.name for cmnt in reddit.subreddit(sub).comments(limit=None)]
    with open('authors'+'_mexico_'+str(time.time())+'.txt', 'w', encoding='utf8') as f:
        for a in authors:
            f.write(a+'\n')

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import youtube_dl

def download_vtt(url,lang):  
    ydl_opts = {
            'quiet': True,
            'subtitleslangs': [lang],
            'writeautomaticsub': 'yes',
            'skip_download': 'yes'            
            }
    with youtube_dl.YoutubeDL(ydl_opts) as ydl:

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from faker import Faker
fake = Faker('es_MX')

for n in range(10):
    print(fake.name())
    
'''
Humberto Menchaca Berríos
Lic. Irma Menchaca
Elisa Barrera

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from faker import Faker
fake = Faker('es_MX')

for n in range(10):
    print(fake.job())
    
'''
Geologist, wellsite
Sports development officer
Telecommunications researcher

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from faker import Faker
from translate import Translator

fake = Faker('es_MX')
translator= Translator(to_lang="es")

for n in range(10):
    print(translator.translate(fake.job()))
    
'''

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def strip_punct(line):
    line = str(line)
    charset = set()
    for ch in line:
        charset.update(ch)
    punct = [ch for ch in charset if not ch.isalpha()]
    if ' ' in punct:
        punct.remove(' ')
    for ch in punct:
        line = line.replace(ch, ' ').lower()

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import stanfordnlp
MODELS_DIR = 'C:\\Users\\user\\stanfordnlp_resources\\'
nlp = stanfordnlp.Pipeline(processors='tokenize,pos,lemma', models_dir=MODELS_DIR, lang='es')

def get_lemmas(line):
    line = nlp(line)
    tagged = [[w.lemma for w in sent.words if w.pos == 'ADV' or w.pos == 'ADJ' or w.pos == 'VERB'] 
            for sent in line.sentences]
    return ' '.join([w for sent in tagged for w in sent])

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#Get bilingual data from the European Comission translation memories
#https://ec.europa.eu/jrc/en/language-technologies/dgt-translation-memory#More%20details%20/%20Reference%20publication

#I needed to extract just EN-ES bilingual data from the tmx files for my machine translation experiment.
#Their Java TM exporter was not working on my side. 
#I wrote this script to get the data 

import xmltodict
import pandas as pd
import os

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