def multiprocess_pages(query_URL, job_title, job_location, page_num):
"""Grab the URLs and other relevant info. from job postings on the page.
The ZipRecruiter URL used for job searching takes an additional parameter,
`page`, that allows you to start the job search at page 0-20 (20 is the max).
Use this to grab job results from multiple pages at once, and then pass jobs
on to threads to grab relevant info.
Args:
----
base_URL: str
job_title: str
job_location: str
page_start: int
"""
url = query_URL + '&page=' + str(page_num)
#print (url)
html = get_html(url)
rows = html.select('.job_content')
#print (rows)
threads = []
mongo_update_lst = []
for row in rows:
# print (row)
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
#store_in_mongo(mongo_update_lst, 'job_postings', 'ziprecruiter')
#print (mongo_update_lst)
store_in_mongo(mongo_update_lst, 'job_postings', 'ziprecruiter_final')
def get_critic_lst_content(critics_hrefs_values, critic_lst_idx):
"""Grab the CSS element that holds all relevant info. for a critic list.
For the critic href at the inputted idx in the critics_hrefs_values, grab
all of the items with the class '.listLargeTitle'. This will then be used
to cycle through each one of them and grab information from them.
Args:
----
critics_hrefs_values: list of strings
critic_lst_idx: int
Return:
------
critic_lst_content_vals: list
soup: bs4.BeautifulSoup object
"""
base_individual_list_url = 'http://www.albumoftheyear.org'
css_selectors = ['.listLargeTitle']
critic_url = base_individual_list_url + critics_hrefs_values[critic_lst_idx]
soup = get_html(base_individual_list_url +
critics_hrefs_values[critic_lst_idx])
critic_content_lst = list(select_soup(soup, css_selectors).values())
critic_lst_content_vals = critic_content_lst[0]
# We reverse them because they are posted from the highest ranked (worst album)
# to the lowest rank (i.e. Post-1 is the highest ranked album on the critic list).
critic_lst_content_vals.reverse()
return critic_lst_content_vals, soup
def multiprocess_pages(base_URL, job_title, job_location, page_num):
"""Grab the URLs and other relevant info. from job postings on the page.
The ZipRecruiter URL used for job searching takes an additional
parameter, `page`, that allows you to start the job search at page
0-20 (20 is the max). I can use this to grab job results from multiple
pages at once. This function here takes in the base_URL, and then
adds that page={page_num} parameter to the URL, and then queries it.
It passes the results on to a thread to grab the details from each
job posting.
Args:
base_URL: String that holds the base URL to add the page_num
parameter to.
job_title: String holding the job title used for the search
job_location: String holding the job location used for the search
page_num: Integer of what the `page` paramter in the URL should
be set to.
"""
url = query_URL + '&page=' + str(page_num)
html = get_html(url)
rows = html.select('.job_result')
threads = []
mongo_update_lst = []
for row in rows:
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'ziprecruiter')
def multiprocess_pages(base_URL, job_title, job_location, page_number):
"""Grab the URLS and other relevant info. from job postings on the page.
The Simply Hired URL used for job searching takes another parameter, `pn`, that
allows you to start the job search at jobs 11-20, 21-30, etc. Use this to grab
job results from multiple pages at once, and then feed the jobs from each page
to threads for further parsing.
Args:
----
base_URL: str
job_title: str
job_location: str
page_number: int
"""
url = base_URL + '&pn=' + str(page_number)
html = get_html(url)
# Each row corresponds to a job.
jobs = html.select('.js-job')
threads = []
mongo_update_lst = []
for job in jobs:
thread = RequestInfoThread(job, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'simplyhired')
def get_critic_lst_content(critics_hrefs_values, critic_lst_idx):
"""Grab the CSS element that holds all relevant info. for a critic list.
For the critic href at the inputted idx in the critics_hrefs_values, grab
all of the items with the class '.listLargeTitle'. This will then be used
to cycle through each one of them and grab information from them.
Args:
----
critics_hrefs_values: list of strings
critic_lst_idx: int
Return:
------
critic_lst_content_vals: list
soup: bs4.BeautifulSoup object
"""
base_individual_list_url = 'http://www.albumoftheyear.org'
css_selectors = ['.listLargeTitle']
critic_url = base_individual_list_url + critics_hrefs_values[critic_lst_idx]
soup = get_html(base_individual_list_url + critics_hrefs_values[critic_lst_idx])
critic_content_lst = list(select_soup(soup, css_selectors).values())
critic_lst_content_vals = critic_content_lst[0]
# We reverse them because they are posted from the highest ranked (worst album)
# to the lowest rank (i.e. Post-1 is the highest ranked album on the critic list).
critic_lst_content_vals.reverse()
return critic_lst_content_vals, soup
def multiprocess_pages(base_URL, job_title, job_location, page_start):
"""Grab the URLS and other relevant info. from job postings on the page.
The Indeed URL used for job searching takes another parameter,
`start`, that allows you to start the job search at jobs 10-20,
20-30, etc. I can use this to grab job results from multiple pages at
once. This function takes in the base_URL and then adds that
start={page_start} parameter to the URL, and then queries it.
It passes the results on to a thread to grab the details from each
job posting.
Args:
base_URL: String that holds the base URL to add the page_start
parameter to.
job_title: String holding the job title used for the search
job_location: String holding the job location used for the search
page_start: Integer of what the `start` parameter in the URL should
be set to.
"""
url = base_URL + '&start=' + str(page_start)
html = get_html(url)
# Each row corresponds to a job.
rows = html.select('.row')
threads = []
mongo_update_lst = []
for row in rows:
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'indeed')
def get_critic_lst_content(critics_hrefs_values, idx):
"""Grab the CSS element that holds all relevant info. for a critic list.
For the critic href at the inputted idx in the critics_hrefs_values, grab
all of the items with the class '.listLargeTitle'. This will then be used
to cycle through each one of them and grab information from them.
Args:
----
critics_hrefs_values: list of strings
Holds the href attribute for each critic list, and is
used to issue a get request against that href.
idx: int
Holds the index of the current critics list that is being
looked at.
Return: list, bs4.BeautifulSoup object
"""
base_individual_list_url = 'http://www.albumoftheyear.org'
css_selectors = ['.listLargeTitle']
critic_url = base_individual_list_url + critics_hrefs_values[idx]
soup = get_html(base_individual_list_url + critics_hrefs_values[idx])
critic_lst_content_vals = select_soup(soup, css_selectors).values()[0]
# We reverse them because they are posted from the highest ranked
# (worst album) to the lowest rank (i.e. Post-1 is the highest ranked
# album on the critic list).
critic_lst_content_vals.reverse()
return critic_lst_content_vals, soup
def multiprocess_pages(base_URL, job_title, job_location, page_number):
"""Grab the URLS and other relevant info. from job postings on the page.
The Simply Hired URL used for job searching takes another parameter, `pn`, that
allows you to start the job search at jobs 11-20, 21-30, etc. Use this to grab
job results from multiple pages at once, and then feed the jobs from each page
to threads for further parsing.
Args:
----
base_URL: str
job_title: str
job_location: str
page_number: int
"""
url = base_URL + '&pn=' + str(page_number)
html = get_html(url)
# Each row corresponds to a job.
#f = open("HTML Code 2", "w", encoding = "utf-8")
#f.write(html.prettify())
jobs = html.select('.jobs')
#print (jobs)
threads = []
mongo_update_lst = []
for job in jobs:
thread = RequestInfoThread(job, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'monster')
def multiprocess_pages(base_URL, job_title, job_location, page_start):
"""Grab the URLS and other relevant info. from job postings on the page.
The Indeed URL used for job searching takes another parameter, `start`, that
allows you to start the job search at jobs 10-20, 20-30, etc. Use this to grab
job results from multiple pages at once, passing the result from a page on to
a thread to grab the details from each job posting.
Args:
----
base_URL: str
job_title: str
job_location: str
page_start: int
"""
url = base_URL + '&start=' + str(page_start)
html = get_html(url)
# Each row corresponds to a job.
rows = html.select('.row')
threads = []
mongo_update_lst = []
for row in rows:
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append((thread.json_dct))
#r = StrictRedis(host='localhost', port=6379, db=0)
#r.lpush("JOB-"+job_title+"-"+job_location, *mongo_update_lst)
return mongo_update_lst
def multiprocess_pages(base_URL, job_title, job_location, page_num):
"""Grab the URLs and other relevant info. from job postings on the page.
The ZipRecruiter URL used for job searching takes an additional parameter,
`page`, that allows you to start the job search at page 0-20 (20 is the max).
Use this to grab job results from multiple pages at once, and then pass jobs
on to threads to grab relevant info.
Args:
----
base_URL: str
job_title: str
job_location: str
page_start: int
"""
url = query_URL + "&page=" + str(page_num)
html = get_html(url)
rows = html.select(".job_result")
threads = []
mongo_update_lst = []
for row in rows:
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, "job_postings", "ziprecruiter")
def multiprocess_pages(base_URL, job_title, job_location, page_start):
"""Grab the URLS and other relevant info. from job postings on the page.
The Indeed URL used for job searching takes another parameter,
`start`, that allows you to start the job search at jobs 10-20,
20-30, etc. I can use this to grab job results from multiple pages at
once. This function takes in the base_URL and then adds that
start={page_start} parameter to the URL, and then queries it.
It passes the results on to a thread to grab the details from each
job posting.
Args:
base_URL: String that holds the base URL to add the page_start
parameter to.
job_title: String holding the job title used for the search
job_location: String holding the job location used for the search
page_start: Integer of what the `start` parameter in the URL should
be set to.
"""
url = base_URL + '&start=' + str(page_start)
html = get_html(url)
# Each row corresponds to a job.
rows = html.select('.row')
threads = []
mongo_update_lst = []
for row in rows:
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'indeed')
def process_album_title_hrefs(album_title_hrefs, album_titles):
"""Grab the critic and user scores for each inputted href.
Loop over the hrefs in `album_title_hrefs`, issue a get request on the URL
associated with that href, and then parse the content to grab the User and
Critic scores for that album. Store the User and Critic scores in a dictionary
along with the Album title. Output it all in a list, with one entry per href.
Args:
----
album_title_hrefs: list of strings
album_titles: list of strings
Return:
------
final_json_lst: list
"""
base_url = 'http://www.albumoftheyear.org'
final_json_lst = []
album_title_hrefs_lst = list(album_title_hrefs.values())
for idx, href in enumerate(album_title_hrefs_lst[0]):
soup = get_html(base_url + href)
center_content_lst = list(select_soup(soup, '#centerContent').values())
center_content = center_content_lst[0][0]
user_score = int(find_score(center_content, 'USER SCORE'))
critic_score = int(find_score(center_content, 'CRITIC SCORE'))
json_dct = {'Album Title': album_titles[idx], "User Score": user_score,
"Critic Score": critic_score}
final_json_lst.append(json_dct)
return final_json_lst
def multiprocess_pages(base_URL, job_title, job_location, page_start):
"""Grab the URLS and other relevant info. from job postings on the page.
The Indeed URL used for job searching takes another parameter, `start`, that
allows you to start the job search at jobs 10-20, 20-30, etc. Use this to grab
job results from multiple pages at once, passing the result from a page on to
a thread to grab the details from each job posting.
Args:
----
base_URL: str
job_title: str
job_location: str
page_start: int
"""
url = base_URL + '&start=' + str(page_start)
html = get_html(url)
# Each row corresponds to a job.
rows = html.select('.row')
threads = []
mongo_update_lst = []
for row in rows:
thread = RequestInfoThread(row, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'indeed')
def scrap(job_title, job_location, radius, result_nb):
base_URL = 'http://www.indeed.fr/emplois?'
query_parameters = [
'q={}'.format('+'.join(job_title.split())),
'&l={}'.format('+'.join(job_location.split())),
'&rq={}'.format(radius), '&sort=date', '&fromage=last'
]
query_URL = format_query(base_URL, query_parameters)
print(query_URL)
html = get_html(query_URL)
try:
num_jobs_txt = str(html.select('#searchCount'))
num_jobs = int(parse_num(num_jobs_txt, 2))
except:
print('No jobs for search {} in {}'.format(job_title, job_location))
sys.exit(0)
current_date = str(datetime.datetime.now(pytz.timezone('US/Mountain')))
storage_dct = {
'job_site': 'indeed',
'num_jobs': num_jobs,
'date': current_date,
'title': job_title,
'location': job_location
}
# Cycle through all of the job postings that we can and grab the url pointing to
# it, to then query it. All of the jobs should be available via the
# .turnstileLink class, and then the href attribute will point to the URL.
max_start_position = 1000 if num_jobs >= 1000 else num_jobs
start_positions = range(0, max_start_position, 10)
db_path = "".join([
"db_", job_title, "_", job_location, "_",
str(radius), "_",
str(result_nb)
])
jobs = []
for i in range(0, result_nb, 10):
try:
jobs.extend(
multiprocess_pages(query_URL, job_title, job_location, i))
except RuntimeError:
pass
#retry ?
#cPickle.dump(jobs, "jobs")
with open("".join([db_path, ".pkl"]), 'w') as f:
cPickle.dump(jobs, f)
f.close()
return jobs
def scrape_pages(self):
"""Scrape all pages stored in `self.web_urls`."""
for article in self.articles_to_scrape:
url = article['web_url']
if url.startswith('/'):
url = 'http://www.nytimes.com' + url
sleep(1 / 20)
soup = get_html(url)
article_txt = self._parse_soup(soup)
if article_txt:
article['text'] = article_txt
def scrape_pages(self):
"""Scrape all pages stored in `self.web_urls`."""
for article in self.articles_to_scrape:
url = article['web_url']
if url.startswith('/'):
url = 'http://www.nytimes.com' + url
sleep(1/20)
soup = get_html(url)
article_txt = self._parse_soup(soup)
if article_txt:
article['text'] = article_txt
def _query_href(self):
"""Grab the text from the href.
Returns: str of visible text from the href.
"""
try:
soup = get_html(self.href)
texts = soup.findAll(text=True)
visible_texts = filter(find_visible_texts, texts)
except Exception as e:
print(e)
visible_texts = ['SSLError', 'happened']
return ' '.join(visible_texts)
def _query_href(self):
"""Grab the text from the href.
Now we want to actually follow the href that is given in the
job posting, and grab the posting text from there.
Args:
href: String of the href to the job posting.
"""
try:
soup = get_html(self.href)
texts = soup.findAll(text=True)
visible_texts = filter(find_visible_texts, texts)
except Exception as e:
print e
visible_texts = ['SSLError', 'happened']
return ' '.join(visible_texts)
def _query_href(self):
"""Grab the text from the href.
Now we want to actually follow the href that is given in the
job posting, and grab the posting text from there.
Args:
href: String of the href to the job posting.
"""
try:
soup = get_html(self.href)
texts = soup.findAll(text=True)
visible_texts = filter(find_visible_texts, texts)
except Exception as e:
print e
visible_texts = ['SSLError', 'happened']
return ' '.join(visible_texts)
def multiprocess_pages(base_URL, job_title, job_location, page_number):
"""Grab the URLS and other relevant info. from job postings on the page.
The Simply Hired URL used for job searching takes another parameter,
`pn`, that allows you to start the job search at jobs 11-20,
21-30, etc. Use this to grab job results from multiple pages at
once.
This function takes in the base_URL, then adds that
pn={page_number} parameter to the URL, and then queries it.
It passes the results on to a thread to grab the details from each
job posting.
Args:
----
base_URL: str
Holds the base URL to add the page_start parameter to.
job_title: str
Holds the job title used for the search.
job_location: str
Holds the job location used for the search.
page_number: int
Holds what the `start` parameter in the URL should be set to.
"""
url = base_URL + '&pn=' + str(page_number)
html = get_html(url)
# Each row corresponds to a job.
jobs = html.select('.js-job')
threads = []
mongo_update_lst = []
for job in jobs:
thread = RequestInfoThread(job, job_title, job_location)
thread.start()
threads.append(thread)
for thread in threads:
thread.join()
mongo_update_lst.append(thread.json_dct)
store_in_mongo(mongo_update_lst, 'job_postings', 'simplyhired')
def process_album_title_hrefs(album_title_hrefs, album_titles):
'''
Input: List
Output: Dictionary
For each of the inputted hrefs, go to the href and grab the overall
critic and user scores.
'''
base_url = 'http://www.albumoftheyear.org'
final_json_lst = []
for idx, href in enumerate(album_title_hrefs.values()[0]):
soup = get_html(base_url + href)
center_content = select_soup(soup, '#centerContent').values()[0][0]
user_score = int(find_score(center_content, 'USER SCORE'))
critic_score = int(find_score(center_content, 'CRITIC SCORE'))
json_dct = {'Album Title': album_titles[idx], "User Score": user_score,
"Critic Score": critic_score}
final_json_lst.append(json_dct)
return final_json_lst
def get_critic_lst_content(critics_hrefs_values, idx):
'''
Input: List, Integer
Output: List, BeautifulSoup object
For the critic href at the inputted idx in the critics_hrefs_values, grab
all of the items with the class '.listLargeTitle'. This will then be used
to cycle through each one of them and grab information from them.
'''
base_individual_list_url = 'http://www.albumoftheyear.org'
css_selectors = ['.listLargeTitle']
critic_url = base_individual_list_url + critics_hrefs_values[idx]
soup = get_html(base_individual_list_url + critics_hrefs_values[idx])
critic_lst_content_vals = select_soup(soup, css_selectors).values()[0]
# We reverse them because they are posted from the highest ranked
# (worst album) to the lowest rank (i.e. Post-1 is the highest ranked
# album on the critic list).
critic_lst_content_vals.reverse()
return critic_lst_content_vals, soup
def get_critic_lst_content(critics_hrefs_values, idx):
'''
Input: List, Integer
Output: List, BeautifulSoup object
For the critic href at the inputted idx in the critics_hrefs_values, grab
all of the items with the class '.listLargeTitle'. This will then be used
to cycle through each one of them and grab information from them.
'''
base_individual_list_url = 'http://www.albumoftheyear.org'
css_selectors = ['.listLargeTitle']
critic_url = base_individual_list_url + critics_hrefs_values[idx]
soup = get_html(base_individual_list_url + critics_hrefs_values[idx])
critic_lst_content_vals = select_soup(soup, css_selectors).values()[0]
# We reverse them because they are posted from the highest ranked
# (worst album) to the lowest rank (i.e. Post-1 is the highest ranked
# album on the critic list).
critic_lst_content_vals.reverse()
return critic_lst_content_vals, soup
def process_album_title_hrefs(album_title_hrefs, album_titles):
"""Grab the critic and user scores for each inputted href.
Loop over the hrefs in `album_title_hrefs`, issue a get request
on the URL associated with that href, and then parse the content
to grab the User and Critic scores for that album. Store the
User and Critic scores in a dictionary along with the Album title,
and then append that to a list to output for easy storage.
Args:
----
album_title_hrefs: list of strings
Holds the hrefs of each album title to issue a get
request on.
album_titles: list of strings
Holds the album titles to store with the User and
Critic scores that we're grabbing. This will allow
identification of a User/Critic score with a particular
album.
Return: list of dictionaries
"""
base_url = 'http://www.albumoftheyear.org'
final_json_lst = []
for idx, href in enumerate(album_title_hrefs.values()[0]):
soup = get_html(base_url + href)
center_content = select_soup(soup, '#centerContent').values()[0][0]
user_score = int(find_score(center_content, 'USER SCORE'))
critic_score = int(find_score(center_content, 'CRITIC SCORE'))
json_dct = {'Album Title': album_titles[idx], "User Score": user_score,
"Critic Score": critic_score}
final_json_lst.append(json_dct)
return final_json_lst
rating_txt: str
Text that potentially holds the rating.
idx: int
Holds the rating if the text does not.
Return: int
"""
if len(rating_txt) >= 1:
rating = int(rating_txt[0].replace('.', ''))
else:
rating = idx
return rating
if __name__ == '__main__':
lists_url = 'http://www.albumoftheyear.org/lists.php'
soup = get_html(lists_url)
critics_content = select_soup(soup, '.criticListBlockTitle')
critics_names = grab_contents_key(critics_content, "text")
critics_links = grab_contents_key(critics_content, 'a')
critics_hrefs = grab_contents_key(critics_links, 'href')
raw_output = grab_critics_info(critics_names, critics_hrefs)
formatted_output = [{"Album Title": k, "Critics Scores": v} for \
k, v in raw_output.items()]
store_in_mongo(formatted_output, 'music', 'music_lists',
key="Album Title")
job_location = sys.argv[2]
radius = sys.argv[3]
except IndexError:
raise Exception(
'Program needs a job title, job location, and radius inputted!')
base_URL = 'https://www.ziprecruiter.com/candidate/search?'
query_parameters = [
'search={}'.format('+'.join(job_title.split())),
'&location={}'.format('+'.join(job_location.split())),
'&radius={}'.format(radius), '&days=5', '&include_near_duplicates=1'
]
query_URL = format_query(base_URL, query_parameters)
#print (query_URL)
html = get_html(query_URL)
try:
num_jobs_txt = str(html.select('#job_results_headline')[0].text)
num_jobs = int(parse_num(num_jobs_txt, 0))
print(num_jobs)
except:
print('No jobs for search {} in {}'.format(job_title, job_location))
sys.exit(0)
current_date = str(datetime.datetime.now(pytz.timezone('US/Mountain')))
storage_dct = {
'job_site': 'ziprecruiter',
'num_jobs': num_jobs,
'date': current_date,
'title': job_title,
job_location = sys.argv[2]
radius = sys.argv[3]
except IndexError:
raise Exception("Program needs a job title, job location, and radius inputted!")
base_URL = "https://www.ziprecruiter.com/candidate/search?"
query_parameters = [
"search={}".format("+".join(job_title.split())),
"&location={}".format("+".join(job_location.split())),
"&radius={}".format(radius),
"&days=5",
"&include_near_duplicates=1",
]
query_URL = format_query(base_URL, query_parameters)
html = get_html(query_URL)
try:
num_jobs_txt = str(html.select("#job_results_headline")[0].text)
num_jobs = int(parse_num(num_jobs_txt, 0))
except:
print("No jobs for search {} in {}".format(job_title, job_location))
sys.exit(0)
current_date = str(datetime.datetime.now(pytz.timezone("US/Mountain")))
storage_dct = {
"job_site": "ziprecruiter",
"num_jobs": num_jobs,
"date": current_date,
"title": job_title,
"location": job_location,
def format_output(raw_output):
'''
Input: Dictionary
Output: List
Reformat the dictionary so that we can easily insert it into our Mongo
database. Basically, right now the dictionary consists of album titles
as the keys, and lists of their ratings on critics lists as the values.
We need it to be a list of dictionaries in the format:
{'Album Title': album_title, 'Critics Scores' : critics_scores_lst}
'''
output_lst = [{"Album Title": k, "Critics Scores": v} for \
k, v in raw_output.iteritems()]
return output_lst
if __name__ == '__main__':
lists_url = 'http://www.albumoftheyear.org/lists.php'
soup = get_html(lists_url)
critics_content = select_soup(soup, '.criticListBlockTitle')
critics_names = grab_contents_key(critics_content, "text")
critics_links = grab_contents_key(critics_content, 'a')
critics_hrefs = grab_contents_key(critics_links, 'href')
raw_output = grab_critics_info(critics_names, critics_hrefs)
formatted_output = format_output(raw_output)
store_in_mongo(formatted_output, 'music', 'music_lists', key="Album Title")
while attribute.find('Other') == -1:
values[attribute] = value
points_misc_idx += 1
# The value is always the last item present, surrounded by (), and the
# 1+ items before that are the attributes to which those points belong.
split_text = sum_points_misc_lst[points_misc_idx].split()
attribute = ' '.join(split_text[:-1])
value = split_text[-1].replace('(', '').replace(')', '')
values[attribute] = value
points_misc_idx += 1
return values, points_misc_idx
if __name__ == '__main__':
try:
year = sys.argv[1]
except Exception as e:
print(e)
raise Exception('<Usage> Input a year to grab music data for.')
URL = 'http://www.albumoftheyear.org/list/summary/' + year + '/'
soup = get_html(URL)
css_selectors = ['.artistTitle', '.albumTitle', '.summaryPoints',
'.summaryPointsMisc']
desired_contents = select_soup(soup, css_selectors)
desired_contents_text = grab_contents_key(desired_contents, "text")
desired_contents_renamed = rename_keys(desired_contents_text)
final_lst = parse_contents(desired_contents_renamed)
store_in_mongo(final_lst, 'music', 'music_lists')
