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setup.py
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setup.py
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#### Before Running This Read STEPS Below!:
import os
#import processing.app_processing.py
"""
os.system('scrapy runspider functionality/glassdoor/glassdoor_reviews.py')
os.system('scrapy runspider functionality/glassdoor/glassdoor_interviews.py')
os.system('scrapy runspider yelp_scrapy.py')
os.system('scrapy runspider functionality/glassdoor/glassdoor_jobs.py')
import functionality.glassdoor.glassdoor_ratings
os.system('scrapy runspider functionality/yelp/yelp_reviews.py')
import processing.processing_best_worse.py
import processing.processing_df_stock_old.py
import processing.interview_processing.py
import processing.glassdoor_processing.py
import processing.ratings_processing.py
import processing.stock_df_dict.py
import processing.stock_processing.py
os.system('scrapy runspider functionality/glassdoor/glassdoor_benefits.py')
python fb_page_scrap.py nike scraped_file.csv
os.system("python upwork_linkedin_scrap_final_jobs.py youremailaddresshere yourpasswrdhere 'bjs restaurant'")
os.system("fb_page_scrap.py 'BJs Restaurant and Brewhouse' scraped_file.csv")
os.system("python functionality/linkedin/linkedin_observations.py youremailaddresshere yourpasswordhere 'bjs restaurant'")
os.system("python functionality/linkedin/upwork_linkedin_scrap_final_jobs.py youremailaddresshere yourpasswordhere'bjs restaurant'")
#os.system("python new_fb_try.py CocaCola feed.json feed.csv likes.csv comments.csv 2016-10-31")
"""
#os.system('scrapy runspider functionality/yelp/yelp_scrapy_nearest.py')
""""
STEPS
1. Open input_fields.csv and add all the firms you want to benchmark/analyse
2. Go get correlations from google, get weekly info from yahoo.
os.makedirs(os.path.dirname("files_chart/"), exist_ok=True)
#os.system("python upwork_linkedin_scrap_final.py youremailaddresshere yourpasswordhere 'BJs Restaurant'")
import processing.interview_descriptions.py # still have to find the right thing.
import processing.input.py - > Something
BJRI
DIN
CAKE
EAT
BJRI
RRGB
BJRI
MOrningstarscrapare one for one in python 2
"""