def test_getjson(self):
gd = glassdoor.parse(glassdoor.get('dropbox'))
try:
self.assertTrue(all([k in gd.keys() for k in stdkeys]),
'Missing Keys')
except Exception as e:
raise Exception('GETjson failed: %s' % e)
def test_getjson(self):
g = glassdoor.get('dropbox')
print g
try:
self.assertTrue(all([k in g.keys() for k in stdkeys]),
'Missing Keys')
except Exception as e:
raise Exception('GETjson failed: %s' % e)
def main():
response = get('dropbox')
print response
print '-' * 100
for key, value in response.iteritems():
print "(%s: %s)" % (key, value)
print '-' * 100
(satisfaction, ceo, meta, salary) = extract_fields(response)
(numRatings, score) = extract_satisfaction(satisfaction)
(numCEOReviews, approvalRate, name, avatarLink) = extract_ceo(ceo)
print "numRatings: %d, score: %d" % (numRatings, score)
print "numCEOReviews: %d, approvalRate: %d, name: %s" % (numCEOReviews, approvalRate, name)
def main():
response = get('dropbox')
print response
print '-' * 100
for key, value in response.iteritems():
print "(%s: %s)" % (key, value)
print '-' * 100
(satisfaction, ceo, meta, salary) = extract_fields(response)
(numRatings, score) = extract_satisfaction(satisfaction)
(numCEOReviews, approvalRate, name, avatarLink) = extract_ceo(ceo)
print "numRatings: %d, score: %d" % (numRatings, score)
print "numCEOReviews: %d, approvalRate: %d, name: %s" % (
numCEOReviews, approvalRate, name)
def convert_facebook_data_to_salary_category(user_data):
employer_glassdoor_data = get(user_data['employer'])
salary = attempt_get_role_mean_salary(user_data['title'], employer_glassdoor_data)
if salary is not None:
print "mean salary of role: " + str(salary)
print "your friend is " + salary_to_category(salary)
else:
company_salary = attempt_get_company_mean_salary(employer_glassdoor_data)
if company_salary is not None:
print "mean salary of company: " + str(company_salary)
print "your friend is probably " + salary_to_category(company_salary)
else:
print "not enough data is available on your friend"
print ""
def glassdoor_get_company_details():
count = 0
fp = open('company_list.txt','r')
for line in fp:
try:
x = get(line)
x = x.json()
result = json.loads(x)
except:
continue
try:
if result.get('satisfaction',None):
count +=1
title = "company1/"+str(count)+'.json'
f = open(title,'w')
f.write(json.dumps(result))
f.close()
except:
print ':('
print traceback.format_exc()
def glassdoor_get_company_details():
count = 0
fp = open('company_list.txt', 'r')
for line in fp:
try:
x = get(line)
x = x.json()
result = json.loads(x)
except:
continue
try:
if result.get('satisfaction', None):
count += 1
title = "company1/" + str(count) + '.json'
f = open(title, 'w')
f.write(json.dumps(result))
f.close()
except:
print ':('
print traceback.format_exc()
def job_details():
user = User.query.filter_by(id=session['user_id']).first()
if request.method == 'GET':
url = request.args.get('joburl')
company = request.args.get('company')
x = get('dropbox')
print x
job_response = urllib2.urlopen(url).read()
p = LinksParser()
p.feed(job_response)
p.close()
url = 'http://access.alchemyapi.com/calls/text/TextGetRankedConcepts'
apikey = '6e2ca8f176761b589a9bee72a3ff6ed8703e0706' #your API key goes here
params = urllib.urlencode({
'apikey': apikey,
'text': p.data,
'showSourceText': '0', #shows the original text sent to the API
})
alchemyThis = urllib2.urlopen(url, params).read()
xmldoc = minidom.parseString(alchemyThis)
nodes = xmldoc.getElementsByTagName('concept')
all = list()
for node in nodes:
textVal = node.getElementsByTagName('text')[0]
rel = node.getElementsByTagName('relevance')[0]
dbpedia = node.getElementsByTagName('dbpedia')[0]
concept = (textVal.childNodes[0].data, rel.childNodes[0].data,
dbpedia.childNodes[0].data)
all.append(concept)
#print job_response
return render_template("job_details.html",
title="Job Analysis",
job_des=p.data,
concepts=all,
user=user)
def job_details():
user=User.query.filter_by(id=session['user_id']).first()
if request.method == 'GET':
url=request.args.get('joburl')
company=request.args.get('company')
x = get('dropbox')
print x
job_response = urllib2.urlopen(url).read()
p = LinksParser()
p.feed(job_response)
p.close()
url = 'http://access.alchemyapi.com/calls/text/TextGetRankedConcepts'
apikey = '6e2ca8f176761b589a9bee72a3ff6ed8703e0706' #your API key goes here
params = urllib.urlencode({
'apikey': apikey,
'text': p.data,
'showSourceText': '0', #shows the original text sent to the API
})
alchemyThis = urllib2.urlopen(url, params).read()
xmldoc = minidom.parseString(alchemyThis)
nodes = xmldoc.getElementsByTagName('concept')
print "hello ",p.data
all = list()
for node in nodes:
textVal = node.getElementsByTagName('text')[0]
rel = node.getElementsByTagName('relevance')[0]
dbpedia = node.getElementsByTagName('dbpedia')[0]
concept = (textVal.childNodes[0].data, rel.childNodes[0].data, dbpedia.childNodes[0].data)
all.append(concept)
#print job_response
return render_template("job-histogram.html", title = "Job Analysis", job_des = p.data, concepts = all, user=user)
import json
from glassdoor import get
dest_path = 'company.json'
json_data = open('companies/data.json')
data = json.load(json_data)
com_list = []
for value in data:
com_list.append(value['name'])
json_data.close()
#remove duplicates
com_list = list(set(com_list))
print 'Len: ', len(com_list)
obj = open(dest_path, 'w')
obj.write('[')
for one in com_list:
info = get(one)
obj.write('{ name:' + one + ',')
obj.write(json.dumps(info))
obj.write('},')
obj.flush()
obj.write(']')
obj.close()
#-*- coding: utf-8 -*-
import json
from glassdoor import get
dest_path = 'company90000.json'
json_data = open('companies/data.json')
data = json.load(json_data)
com_list = []
for value in data:
com_list.append(value['name'])
json_data.close()
#remove duplicates
com_list = list(set(com_list))
print 'Len: ', len(com_list)
obj = open(dest_path, 'w')
obj.write('[')
com_short = com_list[90000:]
print 'new len: ', len(com_short)
for one in com_short:
#print one
info = get(one)
obj.write('{ "name": "' + one.encode('utf-8') +'",')
obj.write(' "info": ' + json.dumps(info))
obj.write('},\n')
obj.flush()
obj.write(']')
obj.close()
def test_getjson(self):
gd = glassdoor.parse(glassdoor.get("dropbox"))
try:
self.assertTrue(all([k in gd.keys() for k in stdkeys]), "Missing Keys")
except Exception as e:
raise Exception("GETjson failed: %s" % e)
from glassdoor import get
x = get('dropbox')
x.json()
