def _clean(self, name):

name = name.split('(')[0]

name = name.split(',')[0]

name = name.split('\u')[0]

name = re.split('[^a-zA-Z\d\s\-]', name)[0]

return name

def _browser(self):

url = "http://www.zoominfo.com/s/#!search/company"

#browser = Browser('chrome')

browser = Browser('phantomjs')

browser.visit(url)

return browser

def _fill_variables(self, ):

''' lol - lmao'''

def __search(industry=False,locale=False,name=False,employees=False,revenue=False):

''' Search '''

browser = self._browser()

self._fill_variables()

def _fill_variables(self, name, industry=False, locale=False):

browser = self._browser()

if name: browser.find_by_name('companyName').first.fill(name)

if industry: browser.find_by_name('industryKeywords').first.fill(industry)

if locale: browser.find_by_name('address').first.fill(locale)

while not browser.find_by_css('div.big').visible:

if browser.is_text_present("No Results Found."): return "nope"

time.sleep(0.2)

return browser.html

def _zoominfo_search_html_to_df(self, html):

''' Parse Zoominfo Search Results Into DF '''

the_info = pd.DataFrame()

results = BeautifulSoup(html).find('table',{'id':'resultGroup'})

results = results.findAll('tr')

for result in results:

co = result.find('td',{'class':'name'})

if co == None: continue

name = co.find('a')

website = co.findAll('a')[-1] if len(co.findAll('a')) != 1 else ""

domain = co.findAll('a')[-1]

location = co.find('span',{'class':'companyAddress'})

revenue = co.find('span',{'class':'revenueText'})

employee_count = co.find('span',{'class':'employeeCount'})

description = result.find('td',{'class':'description'})

phone = BeautifulSoup(html).find('span',{'class':'companyContactNo'})

# change variables to parse db names

columns = ['name','website','domain','city','locale','revenue',

'headcount','description', 'phone']

values = [name, website, domain, location, location, revenue,

employee_count, description, phone]

values = [val.text if val else "" for val in values]

info = dict(zip(columns, values))

info['domain'] = "{}.{}".format(tldextract.extract(info['website']).domain, tldextract.extract(info['website']).tld)

info['source'] = "zoominfo"

the_info = the_info.append(info, ignore_index=True)

# Add Check for websiteUrl must be a proper domain

return the_info

def _get_best_match(self, company_name, df):

similar = difflib.get_close_matches(company_name,

[name for name in df.company_name])

if len(similar) and process.extract(company_name, similar)[0][1] > 80:

zoominfo_profile_name = process.extract(company_name, similar)[0][0]

for i, zoominfo_profile in df.iterrows():

if zoominfo_profile['company_name'] == zoominfo_profile_name:

return zoominfo_profile.to_dict()

return "not found"

def _company_profile(self, company_name, api_key="", domain=""):

qry = 'site:zoominfo.com/c/ {0}'.format(company_name)

google_df = Google().search(qry)

data = {'company_name':company_name, "domain":domain}

if google_df.empty:

return CompanyInfoCrawl()._persist(data,"zoominfo",api_key)

url = google_df.ix[0].link

print "ZOOMINFO URL", url

html = Google().ec2_cache(url)

html = requests.get(url).text

html = self._remove_non_ascii(html)

zoominfo = self._cache_html_to_df(html)

zoominfo['company_name'] = company_name

zoominfo['domain'] = domain

zoominfo['handle'] = url

print zoominfo

CompanyInfoCrawl()._persist(zoominfo, "zoominfo", api_key)

def _domain_search(self, domain, api_key="", name=""):

qry = 'site:zoominfo.com/c/ {0}'.format(domain)

df = Google().search(qry)

if df.empty:

data = {'company_name': name, "domain":domain}

return CompanyInfoCrawl()._persist(data,"zoominfo",api_key)

df['_name'] = [i.split("Company Profile")[0].strip()

for i in df.link_text]

df["score"] = [fuzz.ratio(b, name) for b in df._name]

df = df[df.score > 70]

df = df.sort('score',ascending=False)

if df.empty:

data = {'company_name': name, "domain":domain}

return CompanyInfoCrawl()._persist(data,"zoominfo",api_key)

df = df.reset_index().drop('index',1)

url = df.ix[0].link

print "ZOOMINFO URL", url

html = Google().cache(url)

html = requests.get(url).text

html = self._remove_non_ascii(html)

zoominfo = self._cache_html_to_df(html)

zoominfo['company_name'] = name

zoominfo['handle'] = url

zoominfo["domain_search"] = True

zoominfo["domain"] = domain

print zoominfo

CompanyInfoCrawl()._persist(zoominfo, "zoominfo", api_key)

def _remove_non_ascii(self, text):

return ''.join(i for i in text if ord(i)<128)

def _cache_html_to_df(self, html):

company = BeautifulSoup(html)

title = company.find('div',{'class':'companyTitle'})

description = company.find('div',{'class':'companyDescription'})

revenue = company.find('div',{'class':'companyRevenue'})

address = company.find('div',{'class':'companyAddress'})

employee_count = company.find('p',{'class':'companyEmployeeCountText'})

website = company.find('div',{'class':'website'})

phone = company.find('span',{'class':'hq'})

industries = company.find('p', {'class':'industry'})

industries = industries.find_all('span') if industries else []

industries = [industry.text for industry in industries]

data = [title, description, revenue, address, employee_count,

website, phone]

columns = ["name", "description", "revenue", "address",

"headcount","website","phone"]

# add industries

data = [val.text.strip() if val else "" for val in data]

data = dict(zip(columns, data))

data["industry"] = industries

print data

data["domain"] = "{}.{}".format(tldextract.extract(data["website"]).domain,

tldextract.extract(data["website"]).tld)

try:

data['logo'] = company.find('img',{'class':'companyLogo'})['src']

except:

data['logo'] = ""

data["source"] = "zoominfo"

data['headcount'] = data['headcount'].split('Employees')[0]

data['description'] = data['description'].split('Company Description')[-1]

data['revenue'] = data['revenue'].split('in Revenue')[0]

# add fullcontact address support

print data

return data

def _profile_to_df(self, html):

''' lol '''

title = company.find('h1',{'class':'companyName'})

description = company.find('span',{'class':'companyDesc'})

revenue = company.find('span',{'class':'revenueText'})

address = company.find('span',{'class':'companyAddress'})

employee_count = company.find('span',{'class':'employeeCount'})

website = company.find('div',{'class':'website'})

phone = company.find('span',{'class':'companyContactNo'})

data = [title, description, revenue, address, employee_count,

website, phone, url, logo]

columns = ["name", "description", "revenue", "address",

"address","employee_count","website","phone", "url", "logo"]

data = [val.text if val else "" for val in data]

data = dict(zip(columns, data))

data["domain"] = "{}.{}".format(tldextract.extract(data["website"]).domain,

tldextract.extract(data["website"]).tld)

data["source"] = "zoominfo"

try:

data['logo'] = company.find('img',{'class':'companyImgLogo'})['src']

except:

data['logo'] = ""

print data

return data

def _search(self, company_name):

name = self._clean(company_name)

zoominfo_html = self._fill_variables(company_name)

# click first

# companyResultsName

# scrape

def search(self, company_name):

'''

Input: Name and Possibly Location, Parse Object ObjectId

Output: Update Parse Object

'''

name = self._clean(company_name)

zoominfo_html = self._fill_variables(company_name)

#zoominfo_html = get_html_results_from_zoominfo(name)

if zoominfo_html == "nope": return "not found"

zoominfo_df = self._zoominfo_search_html_to_df(zoominfo_html)

best_match = self._get_best_match(name, zoominfo_df)

return best_match

# Get Email

# Update Parse With New Website and Phone Number

# r = requests.put('https://api.parse.com/1/classes/Prospects/'+objectId,