def run():
if (len(sys.argv) != 3):
print("Too few/not enough arguments.")
return
json = sys.argv[1]
lever_list = sys.argv[2]
applicant = Applicant()
applicant.read_from_json(json)
auto_lever = Auto_Lever()
lever_urls = open(lever_list, 'r').readlines()
lever_failed = open('failed' + os.sep + 'lever_failed.txt', 'w')
for url in lever_urls:
auto_lever.load_url(url)
auto_lever.load_applicant(applicant)
try:
response = auto_lever.run()
if (response != 'success'):
print(response, file=lever_failed)
print()
except:
print("Oops! Something went wrong. Skipping URL...")
print(url.strip(), file=lever_failed)
lever_failed.close()
def get_applicant(self, applicantID):
r = self.session.get("%sapi/Applicant/%s" % (self.url, applicantID),
headers=self.headers)
if r.status_code != 200:
raise JSONError("Status code %s returned. Json returned: \n\n%s" %
(r.status_code, r.text))
applicant_json = json.loads(json.dumps(r.text))
return Applicant(json_data=applicant_json)
def __init__(self, email: str) -> None:
self.failed_email_user_id = 0
self.bot_email = email
self.queue_from_bot = email
self.applicant = Applicant()
self.loop = asyncio.get_event_loop()
self.current_appeal: Optional[dict] = None
self.stop_timer = Timer(self.stop_appeal_sending, self.loop)
self.captcha_solver = CaptchaSolver()
self.user_captcha_text: Optional[str] = None
def create_applicants(self, scores, real_scores, ir_limit):
applicants = []
for i in range(0, self.size):
applicants.append(
Applicant(self, scores[i], real_scores[i], ir_limit))
return applicants
self.quality = max(min(r.gauss(50, 30), 100), 1) # on a scale 0-100
self.number_to_interview = 10 * tname.openings
self.observe_1 = r.gauss(1, .2)
self.observe_2 = tname.observe_2 = (r.gauss(1, .1)- tname.observe_1)
self.observed_1 = r.gauss(1, .2)
self.observed_2 = (r.gauss(1, .1)- tname.observed_1) # based on applicant interviewed, percentage
self.num_to_rank = 7 * tname.openings
self.accept_range = [.7, None] # as a % [.5, 1.5] if [.7, None] then there is no upper limit
#Make the list of Applicants
print('Make a list of Applicants')
all_applicants = []
for x in range(1, 5000):
tname = 'app'+str(x)
tname = Applicant()
tname.name = x
# Comment out the Following to use defualt
tname.quality = max(min(r.gauss(50, 20), 100), 1) # on a scale 0-100
tname.observe_1 = r.gauss(1, .2) # as a percentage, Applicant error in observing the institutions quality
tname.observe_2 = (r.gauss(1, .1)- tname.observe_1)
tname.observed_1 = r.gauss(1, .2) # as a percentage, Institutions error (as seen) in observing the applicants quality
tname.observed_2 = (r.gauss(1, .1)- tname.observed_1) # CORRECT change to observed_1 after interview default = 1
tname.applied_to_range = [.8, 1.2] # as a percentage, for example [0.8, 1.2]
tname.num_applied_to = 12 # the maximum number that the applicant applies to
all_applicants.append(tname) #Add Applicant to the list of Applicants
# Import institution mAtch data
# Make the list of Institutions
print('importing institution data')
def get_applicants(cls):
from applicant import Applicant
return [
Applicant(raw_applicant) for raw_applicant in cls.applicants_data
]
