def test_company_total_employee_salary(self):
company5 = Company("Apple5")
emp13 = Employee("Michael", title = "Software Enigineer", salary = 5000, rank = 3)
emp14 = Employee("Nick", title = "Software Enigineer", salary = 7000, rank = 2)
company5.addEmployee(emp13)
company5.addEmployee(emp14)
self.assertTrue(company5.getTotalSalaryofEmployee() == 12000)
def test_company_employee_count2(self):
company2 = Company("Apple2")
emp10 = Employee("Jack", title = "Secretary", salary = 3000, rank = 3)
emp11 = Employee("Kevin", title = "CTO", salary = 53000, rank = 2)
company2.addEmployee(emp10)
company2.addEmployee(emp11)
self.assertTrue(company2.getTotalNumOfEmployee() is 2)
def generate_company_with_groups(number):
bosses = [Staff() for i in range(number)]
companies = [Company() for i in range(number)]
groups = []
# construct company
gnames = ['董事会', '总经理', '副总经理', '市场总监', '技术总监', '副总经理', '财务部', '行政人事部', '商务部', '市场发展部', '客户服务部', '外部办事部', '产品研发部', '技术服务部', '系统集成部', '副总经理', '采购部', '生产部', '质检部']
for i in companies:
temp_groups = [Group(name=j, companyId=i._id) for j in gnames]
# set relation
set_parent(temp_groups, [1], 0)
set_parent(temp_groups, [2, 3, 4, 5], 1)
set_parent(temp_groups, [6, 7, 8], 2)
set_parent(temp_groups, [9, 10, 11], 3)
set_parent(temp_groups, [12, 13, 14], 4)
set_parent(temp_groups, [15, 16, 17], 5)
groups += temp_groups
group_data = [i.get_data_for_insert() for i in groups]
print(group_data)
for i in range(number):
bosses[i].companyId = companies[i]._id # keng??
companies[i].userId = bosses[i]._id
boss_data = [i.get_data_for_insert() for i in bosses]
company_data = [i.get_data_for_insert() for i in companies]
staff_sql = Staff.get_insert_sql()
group_sql = Group.get_insert_sql()
company_sql = Company.get_insert_sql()
database.execute_change(staff_sql, tuple(boss_data))
database.execute_change(company_sql, tuple(company_data))
database.execute_change(group_sql, tuple(group_data))
return companies, groups
def test_employee_job_hopping(self):
company3 = Company("Apple3")
company4 = Company("Apple4")
emp12 = Employee("Larry", title = "Software Enigineer", salary = 4000, rank = 3)
company3.addEmployee(emp12)
company3.removeEmployee(emp12)
company4.addEmployee(emp12)
self.assertTrue(company4.getTotalNumOfEmployee() is 1 and company3.getTotalNumOfEmployee() is 0)
def populate(self, legion_type):
self.name = legion_type.name
self.enum = legion_type
lt = self.legion_type = LegionHandler.load(legion_type)
for company_type, amount in lt.companies.items():
for i in range(amount):
comp = Company(self)
comp.populate(company_type)
self.companies.append(comp)
def download_data():
# mkdir
folder = os.path.exists(r".\\data\\")
if not folder:
os.makedirs(".\\data")
company_list = Company.get_code_list()
company_list = [Company(x) for x in company_list]
[i.start() for i in company_list]
[i.join() for i in company_list]
def generate_company(number):
bosses = [Staff() for i in range(number)]
companies = [Company() for i in range(number)]
for i in range(number):
bosses[i].companyId = companies[i]._id # keng??
companies[i].userId = bosses[i]._id
boss_data = [i.get_data_for_insert() for i in bosses]
company_data = [i.get_data_for_insert() for i in companies]
staff_sql = Staff.get_insert_sql()
company_sql = Company.get_insert_sql()
database.execute_change(staff_sql, tuple(boss_data))
database.execute_change(company_sql, tuple(company_data))
return companies
def scrapCompanies(url):
print "Scrapping contents from : "+url
links[url] = True
opener = urllib2.build_opener()
opener.addheaders = [('User-agent', 'Mozilla/5.0')]
page = opener.open(url)
soup = bs4.BeautifulSoup(page,"lxml")
trs = soup.select("#company-list table.my-table tr")
for tr in trs:
tds = tr.select("td")
if len(tds) > 4:
company = {}
company["name"] = tds[2].getText().strip()
company["symbol"] = tds[3].getText().strip()
company["sector"] = tds[4].getText().strip()
company["detaillink"] = ""
linkTD = tds[5]
companyLinks = linkTD.select("a")
if len(companyLinks) > 0:
detailLink = companyLinks[0].attrs["href"]
company["detaillink"] = detailLink
scrapCompanyDetail(company)
print company
print "********************"
company1 = Company(company["name"],company["symbol"],company["sector"],company["detaillink"])
company1.displayCompany()
companies.append(company)
##Delete this
#if company["sector"] != "Sector":
# break;
allLinks = soup.select("a")
for link in allLinks:
if 'title' in link.attrs:
title = link.attrs["title"];
if title.find("Go to Page") != -1 or title.find("Next Page") != -1 or title.find("Last Page") != -1:
url = link.attrs["href"].strip()
if url not in links:
links[url] = False
nextUrl = ''
for link in links:
if links[link] == False:
nextUrl = link
break
def deserialize_json_to_object(self):
raw_items = []
companies = []
ending_brace = False
with open(self.__file_name, "r") as file:
for line in file:
if self.LEFT_BRACE in line:
ending_brace = False
elif self.RIGHT_BRACE in line:
ending_brace = True
if not ending_brace and self.LEFT_BRACE not in line and "[" not in line:
raw_items.append((line.replace('\n', '').replace('"', '').replace(',', '').strip()).split(':'))
if len(raw_items) == self.MAX_OBJECTS:
company = Company()
for iRawItem in raw_items:
if "State" in iRawItem:
company.set_state(iRawItem[1].strip())
elif "Company" in iRawItem:
company.set_company(iRawItem[1].strip())
elif "NumOfEmployees" in iRawItem:
company.set_number_of_employees(int(iRawItem[1].strip()))
companies.append(company)
raw_items.clear()
return companies
def loadCompany(self, companyName):
newCompany = Company(companyName)
newCompany.loadTicker()
self.companies.append(newCompany)
# reset minDate
# minDate is the latest start date of all companies in portfolio
startDates = []
for company in self.companies:
startDates.append(company.loadedStartDate)
self.minDate = max(startDates)
# reset maxDate
# maxdate is the earliest end date of all companies in portfolio
endDates = []
for company in self.companies:
endDates.append(company.loadedEndDate)
self.maxDate = min(endDates)
def create_company(self, data, input_file): ticker_temp = data[0] ticker_long = ticker_temp.split() ticker = ticker_long[0] bloomberg_ticker = data[0] name = data[1] industry = data[2] earnings_per_share = data[13:28] revenue_per_share = data[28:43] operating_income = data[43:58] dividends_paid = data[58:73] # Används ej. free_cash_flow = data[73:88] roe = data[88:103] roic = data[103:118] company_value = data[118:133] market_cap = data[133:148] price = data[148:163] book_value = data[163:178] # Borde läggas till. wacc = data[178:193] eqy_shares_out = data[193:208] # Borde läggas till. dividend_forecast = data[208:223] px_volume = data[223:238] dividends = data[238:253] # company = Company(name, bloomberg_ticker, ticker_short, earnings_per_share, revenue_per_share, dividend_forecast, dividends, free_cash_flow, roe, roic, operating_income, price, wacc, company_value, px_volume) company = Company(name, bloomberg_ticker, ticker, industry, earnings_per_share, revenue_per_share, dividend_forecast, dividends, free_cash_flow, roe, roic, operating_income, price, wacc, company_value, market_cap, px_volume) return company
def __import_companies(cls):
try:
with open('../Data/CompaniesData.txt', 'r') as f:
lines_arr = []
for line in f:
line = line.strip()
lines_arr.append(line)
if line == '#':
tax_id = lines_arr[0]
founder_name = lines_arr[1]
founder_surname = lines_arr[2]
company_name = lines_arr[3]
company_address = lines_arr[4]
foundation_year = lines_arr[5]
lines_arr.clear()
company = Company(founder_name, founder_surname,
company_name, company_address,
tax_id, foundation_year)
cls.companies_list.append(company)
lines_arr.clear()
except BaseException:
pass
def scrape_companies():
companies = []
chrome_options = Options()
chrome_options.add_argument("--headless")
driver = webdriver.Chrome('./driver/chromedriver.exe',
options=chrome_options,
service_log_path='NUL')
driver.get(
'https://idx.co.id/data-pasar/laporan-statistik/ringkasan-performa-perusahaan-tercatat/'
)
entries_option = driver.find_element_by_xpath(
'/html/body/main/div/div[3]/div[1]/label/select/option[4]')
driver.execute_script("arguments[0].value = '999999';", entries_option)
entries_combobox = Select(
driver.find_element_by_name('performanceTable_length'))
sleep(3)
entries_combobox.select_by_visible_text('100')
sleep(3)
table = driver.find_elements_by_tag_name('tbody')[0]
rows = table.find_elements_by_tag_name('tr')
print("\nLoading", len(rows), "companies.")
for i in range(len(rows)):
cols = rows[i].find_elements_by_tag_name('td')
company_code = cols[1].text
company_name = cols[2].text
pdf_link = cols[3].find_elements_by_tag_name('a')[0].get_attribute(
'href')
der, pbv, roe, per = extract_data_from_pdf(pdf_link)
passed = evaluate_data(der, pbv, roe, per)
current_company = Company(i + 1, company_code, company_name, pdf_link,
passed, der, pbv, roe, per)
print(f"\n({i+1}/{len(rows)})>", current_company.to_string())
companies.append(current_company)
driver.quit()
return companies
def crawl_page(skip):
""" Get urls and return companies from the page specified skip.
"""
URL = "http://ccs.career.cornell.edu/CareerFair/CarFair_SearchCode.php?link=yes&Company_Name=*&skip=" + str(skip)
r = requests.get(URL)
html = r.text.encode('utf-8')
soup = soupparser.fromstring(html)
trs = soup.xpath("//table[@id='mytables']//table[1]/tr")[3:]
companies = []
for tr in trs:
a = tr.xpath("td/a")[0]
name, url = a.text, "http://ccs.career.cornell.edu/CareerFair/" + a.attrib['href']
id = get_id(url)
company = Company(id)
company.name = name
company.url = url
company = parse_company(company, url)
companies.append(company)
return companies
def loadCompaniesDict():
companies = json.loads(open('./Companies.json').read())
currentCompanies = {}
for company in companies:
currentCompany = Company(company['id'], \
company['company'], \
company['city'], \
company['timezone'])
currentCompanies.update({currentCompany.id: currentCompany})
return currentCompanies
def create_companies_dictionary(path_to_csv):
csv_data = read_csv(path_to_csv)
companies = dict()
for index, row in csv_data.iterrows():
vendor = row['Vendor']
if vendor not in companies.keys():
company_temp = Company(vendor)
companies[vendor] = company_temp
company = companies[vendor]
company.add_product(row['Product'], row['Amount'])
return companies
def url_load():
url = "http://top500.welt.de/list/2014/U/?i=1000&e=1000&p=1"
text = r.get(url).text
tree = fromstring(text)
#tree.make_links_absolute(url)
pos = 0
companies = []
for el in tqdm.tqdm(tree.find_class("grid_6")):
a = el.find(".//a")
if a is None:
continue
pos += 1
href = a.attrib["href"]
detail_id = [int(s) for s in href.split("/") if s.isdigit()][-1]
name = str(a.text_content())
comp = Company(name, detail_id, pos)
details = get_details(detail_id)
comp.set_details(details)
companies.append(comp)
return companies
def createCompanies(self,serviceList = ["dessert","breakfast","coffee","drinks","salad"]):
# initialize a list
companyList = []
# iterate company count times
for i in range(self.companyCount):
if i == 0:
# create a random company
currentCompany = Company("Main Company" # company name
, random.randint(10, 20) # long
, random.randint(10, 20), # lat
[serviceList[random.randint(0, len(serviceList)) - 1],
serviceList[random.randint(0, len(serviceList)) - 1]],
random.randint(20, 30), # price
random.randint(10, 20), # cost
random.randint(400, 4000), # sales Vol
random.randint(10000, 100000), # fixed cost
random.randint(5, 20) / 100) # tax rate
else:
# create a random company
currentCompany = Company("Competitor{}".format(i) # company name
,random.randint(10,20) # long
,random.randint(10,20), # lat
[serviceList[random.randint(0,len(serviceList))-1],serviceList[random.randint(0,len(serviceList))-1]],
random.randint(20,30), # price
random.randint(10,20), # cost
random.randint(400,4000), # sales Vol
random.randint(10000,100000),# fixed cost
random.randint(5,20)/100) # tax rate
# append the list
companyList.append(currentCompany)
# assign the class's list
self.companyList = companyList
def company_details(url_encoded_name, year):
if app.debug: print request.args
qry = """SELECT * FROM Film
INNER JOIN CompanyCredits ON (CompanyCredits.film_imdblink = Film.imdblink)
INNER JOIN Company ON (CompanyCredits.company_imdblink = Company.imdblink)
WHERE Film.url_encoded_name = :film AND Film.year = :y;"""
cursor = g.conn.execute(text(qry), film = url_encoded_name, y = year)
companies = []
for result in cursor: companies.append(Company(result))
cursor.close()
cache['companies'] = companies
cache['current_film'] = companies[0].film_name
cache['current_film_imdblink'] = companies[0].film_imdblink
return render_template("company-details.html", **cache)
def tasks():
d1 = JavaDeveloper("Jack", 4)
d2 = PythonDeveloper("Carl", 10)
d3 = RubyDeveloper("Nick", 1)
info_about_developer(d1)
info_about_developer(d2)
info_about_developer(d3)
print(d1)
print(d2)
print(d3)
developer = PythonDeveloper("Brad", 2)
developer()
print("\n\n")
company = Company()
company += d1
company += d2
company += d3
print(company)
company.fire("Nick")
print(company)
def setup(self):
for i in range(self.num_agents):
a = Company(i, self, self.strat(), self.tech(), self.market_cap())
self.schedule.append(a)
initial_emissions = []
prod = []
for i in self.schedule:
initial_emissions.append(i.produce_initial())
prod.append(i.prod_t)
i.setup()
emissions = sum(initial_emissions)
print("Total Production Prior to Cap: " + str(sum(prod)))
print("Emissions Prior to Cap: " + str(emissions))
self.num_allow = int((1 - self.initial_cap) * emissions)
self.max_allow = self.num_allow
print("Number of allowances under cap: " + str(self.num_allow))
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-test', action="store_true")
parser.add_argument('-clean', action='store_true')
parser.add_argument('-n', type=str)
parser.add_argument('-s', type=str)
parser.add_argument('-m', type=str)
parser.add_argument('-co', type=str)
parser.add_argument('-ci', type=str)
parser.add_argument('-fo', type=str)
parser.add_argument('-r', type=int)
parser.add_argument('-ir', type=str)
parser.add_argument('-fi', type=str)
parser.add_argument('-li', type=str)
parser.add_argument('-fr', type=int)
parser.add_argument('-ft', type=float)
parser.add_argument('-ff', type=str)
parser.add_argument('-lf', type=str)
parser.add_argument('-k', type=int, default=9)
args = parser.parse_args()
if args.test:
test(args.k)
else:
if (not is_initialized()) or args.clean:
initialize()
date_inputs = [args.fi, args.li, args.ff, args.lf, args.fo]
i = 0
while i < len(date_inputs):
if date_inputs[i]:
date_inputs[i] = datetime.date(int(date_inputs[i][:4]),
int(date_inputs[i][5:7]),
int(date_inputs[i][8:10]))
i += 1
company = Company(args.n, args.s, args.m, args.co, args.ci,
date_inputs[4], args.r, args.ir, date_inputs[0],
date_inputs[1], args.fr, args.ft, date_inputs[2],
date_inputs[3])
print(classify(company, args.k))
def getCompanyInformation(self):
service_link = "http://tevhitkarsli.com/getCompanyInformation.php"
myRequest = requests.post(url=service_link, auth=self.my_auth)
if str(myRequest.text) == '[]':
return None
companies_text = json.loads(myRequest.text)
all_companies_list = []
for i in range(0, len(companies_text)):
company = Company(companies_text[0]['CompanyID'],
companies_text[0]['CompanyName'],
companies_text[0]['CompanyNote'])
all_companies_list.append(company)
return all_companies_list
def add_company(cls, is_complete, founder_name, founder_surname,
company_name, company_address, tax_id, foundation_year):
EMPTY = ''
company_exists, company = CompanyManagement.check_company_existence(
tax_id)
if (company_exists == False and founder_name != EMPTY
and founder_surname != EMPTY and company_name != EMPTY
and company_address != EMPTY and tax_id != EMPTY
and foundation_year != EMPTY):
with open('../Data/CompaniesData.txt', 'a') as f:
company = Company(founder_name, founder_surname, company_name,
company_address, tax_id, foundation_year)
CompanyManagement.companies_list.append(company)
f.write(company.get_tax_id() + '\n')
f.write(company.get_founder_name() + '\n')
f.write(company.get_founder_surname() + '\n')
f.write(company.get_company_name() + '\n')
f.write(company.get_company_address() + '\n')
f.write(company.get_foundation_year() + '\n')
f.write('#' + '\n')
is_complete.set("Success")
elif (company_exists and founder_name != EMPTY
and founder_surname != EMPTY and company_name != EMPTY
and company_address != EMPTY and tax_id != EMPTY
and foundation_year != EMPTY):
is_complete.set("Already Exists")
else:
is_complete.set("Failed")
def PB_C(self,):
# clear all outputs
self.clearOutputs()
#getting the inputs and exception handling
if self.input_stockticker.text() is not '':
stockticker = self.input_stockticker.text()
else:
self.output_rec.setText('Error: Please input a stockticker.')
raise
exit
if self.input_forecastedGrowthRate.text() is not '':
forecasted_growth_rate = float(
self.input_forecastedGrowthRate.text())
else:
forecasted_growth_rate = None
if self.input_perpetualGrowthRate.text() is not '':
perpetual_growth_rate = float(
self.input_perpetualGrowthRate.text())
else:
perpetual_growth_rate = None
if self.input_quandl_API_key.text() is not '':
quandl.ApiConfig.api_key = self.input_quandl_API_key.text()
else:
self.output_rec.setText('Error: Please input an Quandl API Key.'+
' Go to https://www.quandl.com/')
raise
exit
#test if quandl apikey is valid
count = 0
while True:
try:
quandl.Dataset('WIKI/AAPL').data()
break
except:
count += 1
if count >8:
self.output_rec.setText('Error: Invalid Quandl API key. ' +
'Please check your API key '+
'and try again')
raise
exit
#test if stockticker is valid
count = 0
while True:
try:
ignore = quandl.Dataset('WIKI/' + stockticker).data()
break
except:
count += 1
if count >8:
self.output_rec.setText('Error: Invalid stockticker.')
raise
exit
#initialise Company object and store 'data' attribute [dict]
company = Company(stockticker,quandl.ApiConfig.api_key)
data = company.data
# Calculations using Company data and dcffunctions
#tax rate
atr = d.avg_tax_rate(data['taxexp'],data['ebt'])
#change in networking capital
cwc = d.cwc(data['ybca'],data['yeca'],data['ybcl'],data['yecl'])
#fcf valuation
fcf = d.fcf(data['lastebit'],
atr,
data['dep'],
data['amor'],
cwc,
data['capex'])
#5 years free cash flow
#outputs all five years as a tuple
#(convert to list, then return individual years)
fiveyearfcf = {}
if forecasted_growth_rate is None:
fiveyearfcf = d.five_year_fcf(fcf)
else:
fiveyearfcf = d.five_year_fcf(fcf,forecasted_growth_rate)
#cost of equity
re = d.re(data['rm'],data['rf'],data['beta'])
#cost of debt
rd = d.rd(data['intexp'],data['LTD'])
#weighted average cost of capital
wacc = d.wacc(data['marketcap'],data['lastD'],atr,re,rd)
#terminal value - not part of ui, but included in calculation
tv = 0
if perpetual_growth_rate is None:
tv = d.tv(fiveyearfcf,wacc)
else:
tv = d.tv(fiveyearfcf,wacc, perpetual_growth_rate)
#discounted cash flow for the current year
dcf = d.dcf(fiveyearfcf,wacc,tv)
#target price - not part of ui, but included in calculation
target_price = d.target_price(dcf,data['lastD'],data['numshares'])
#recommendation
rec = d.recommendation(
data['current_price'],data['stdev'],target_price)
#generate the outputs
#ebit - imported as a variable
self.output_ebit.setText(d.convert(data['lastebit']))
self.output_tax_rate.setText(str(round(atr,4)))
#depreciation and amortization - imported as a variable
self.output_depr.setText(d.convert(data['dep']))
self.output_amor.setText(d.convert(data['amor']))
#capital expenditure - imported as a variable
self.output_capex.setText(d.convert(data['capex']))
self.output_cwc.setText(d.convert(cwc))
self.output_fcf.setText(d.convert(fcf))
self.output_y0.setText(d.convert(fiveyearfcf[0]))
self.output_y1.setText(d.convert(fiveyearfcf[1]))
self.output_y2.setText(d.convert(fiveyearfcf[2]))
self.output_y3.setText(d.convert(fiveyearfcf[3]))
self.output_y4.setText(d.convert(fiveyearfcf[4]))
self.output_y5.setText(d.convert(fiveyearfcf[5]))
#market capitalization - imported as a variable
self.output_marketcap.setText(d.convert(data['marketcap']))
#beta - imported as a variable
self.output_beta.setText(str(data['beta']))
#expected market returns - imported as a variable
self.output_emr.setText(str(round(data['rm'],4)))
self.output_coe.setText(str(round(re,4)))
#total long term debt - imported as a variable
self.output_ltd.setText(d.convert(data['lastD']))
self.output_cod.setText(str(round(rd,4)))
self.output_wacc.setText(str(round(wacc,4)))
self.output_dcf.setText(d.convert(dcf))
self.output_rec.setText(rec) #insertPlainText
week_salary = int(line[2])
empls_list.append(SalariedEmployee(name, int(line[1]), [], week_salary))
return empls_list
def read_hourly_employees_from_file(path):
empls_list = []
with open(path) as g:
for line in g:
line = line.strip()
line = line.split(";")
empls_list.append(HourlyEmployee(line[0], int(line[1]), [], int(line[2]), int(line[3])))
return empls_list
if __name__ == '__main__':
#print_lines_in_file("tasks.txt")
#lines_list = read_lines_in_file("tasks.txt")
#print(lines_list)
tasks = read_tasks_from_file("tasks.txt")
salaried_empls = read_salaried_employees_from_file("salariedemployees.txt")
hourly_empls = read_hourly_employees_from_file("hourlyemployees.txt")
empls = salaried_empls + hourly_empls
company = Company("QuickGeo", empls, tasks)
company.dist_task(2)
company.work_all()
company.print_emp()
print(company.monty_salary)
def __init__(self, companies_id_list):
self.companies_list = []
for id in companies_id_list:
newc = Company(id)
self.companies_list.append(newc)
upcoming_movie1 = Movie('Killers of the flower Moon','Martin Scorsese','Drama',['Robert DeNiro','Leonardo DiCaprio'])
upcoming_movie2 = Movie('Avatar 2','James Cameron','Sci-Fi',['Sam Worthington','Zoe Zaldana'])
upcoming_movie3 = Movie('Anerxomeni3','Unknown','Action',['prwtos','deuteros'])
movie1.updateEarnings(560341000.)
movie1.updateTickets(70042625)
movie2.updateEarnings(150000000.)
movie2.updateTickets(18750000)
movie3.updateEarnings(2790439000.)
movie3.updateTickets(348804875)
movie4.updateEarnings(345800450.)
movie4.updateTickets(43225056)
movie5.updateEarnings(230170000.)
movie5.updateTickets(28771250)
company = Company(1)
cinema1 = Cinema('Athina',20)
cinema2 = Cinema('Thesaloniki',15)
cinema3 = Cinema('Volos',10)
cinema4 = Cinema('Xalkida',2)
cinema5 = Cinema('Larisa',10)
cinema6 = Cinema('Kifisia',15)
cinema7 = Cinema('Pireas',10)
cinema8 = Cinema('Xania',5)
cinema9 = Cinema('Ioannina',8)
cinema10 = Cinema('Alexandroupoli',3)
cinema1.setPeakHours(0,34) # 0 ennow stis5
cinema1.setPeakHours(1,70)
cinema1.setPeakHours(2,70)
if __name__ == "__main__":
url = 'https://www.trustpilot.com/review/www.dropbox.com'
page = requests.get(url).text
soap = BeautifulSoup(page, 'html.parser')
name = soap.find('span', {'class': 'multi-size-header__big'}).text.strip()
average_rating = soap.find('p', {
'class': 'header_trustscore'
}).text.strip()
review_count = int(
soap.find('h2', {
'class': 'header--inline'
}).text.strip().split('•')[0].replace(',', ''))
review_per_page = 20
pages = review_count // review_per_page
if review_count % review_per_page != 0:
pages = review_count // review_per_page + 1
company = Company(name, average_rating)
review_scrapper = ReviewScrape()
for page in range(1, pages + 1):
page_url = f'{url}?languages=all&page={page}'
company.add_reviews(review_scrapper.scrape(page_url))
time.sleep(10)
print(f"page {page}")
ReviewUtil.save(f'{company.company_name}.csv', company.reviews)
def company(self):
if self._company is None:
self._company = Company.get_by_id(self.company_key.id())
return self._company
print("\t1 - Crear Compañia")
print("\t2 - Crear Cliente")
print("\t3 - Crear Producto")
print("\t4 - Realizar Compra")
print("\t9 - salir")
while True:
menu()
opcionMenu = input("Elije una opcion : ")
if opcionMenu == "1":
company = Company()
nombreCompany = input('Ingrese nombre de la compañia ').upper()
precioCompany = input('Ingrese rfc de la compañia ')
direccionCompany = input('Ingrese dirección de la compañia ')
company.insertarCompany(nombreCompany, precioCompany, direccionCompany)
input("Presione enter para continuar")
elif opcionMenu == "2":
cliente = Cliente()
company2 = Company()
company2.fetchCompany()
if len(company2.companyList) == 0:
print("No puedes crear cliente sin compañias existentes")
def test_company_employee_count(self):
company1 = Company("Apple")
emp9 = Employee("Ian", title = "Program Manager", salary = 7000, rank = 4)
company1.addEmployee(emp9)
self.assertTrue(company1.getTotalNumOfEmployee() is 1)
def grab_position(keyword, gj='', xl='', yx='', gx='', st='', lc='', workAddress='', city='全国'):
reload(sys)
sys.setdefaultencoding('utf-8')
url = "http://www.lagou.com/jobs/list_" + keyword
params = {'spc': 1, 'pl': "", 'xl': xl, 'yx': yx, 'gx': gx, 'st': st, 'labelWords': '', 'city': city,
'requestId': ""}
list = requests.get(url, params=params)
parser = BeautifulSoup(list.content)
# print list.content
posistions = []
companys = []
pos_html = parser.find_all("div", class_="hot_pos_l")
cmp_html = parser.find_all("div", class_="hot_pos_r")
for i in range(len(pos_html)):
p2 = BeautifulSoup(repr(pos_html[i]))
cmp_parser = BeautifulSoup(repr(cmp_html[i]))
p = Position()
c = Company()
# 抓取职位信息
spans = p2.find_all('span')
p.salary = spans[1].text
p.experience = spans[2].text
p.edu = spans[3].text
p.candy = spans[4].text
p.name = pos_html[i].div.a.text
p.place = pos_html[i].div.span.text
p_url = pos_html[i].div.a['href']
p_detail = requests.get(p_url)
detail_parser = BeautifulSoup(p_detail.content)
p.detail = detail_parser.find_all("dd", class_="job_bt")[0].text
# 抓取公司信息
hot_pos_r = cmp_parser.find_all("span")
if len(hot_pos_r) == 4:
c.field = hot_pos_r[0].text
c.founder = hot_pos_r[1].text
c.funding = hot_pos_r[2].text
c.extent = hot_pos_r[3].text
elif len(hot_pos_r) == 3:
c.field = hot_pos_r[0].text
c.funding = hot_pos_r[1].text
c.extent = hot_pos_r[2].text
# 关联
tmp = cmp_parser.find_all("a")
c_id_a = tmp[1]
c.name = c_id_a.text
c_id = c_id_a['href']
c_id = re.findall('\d+', c_id)
cmp_page = requests.get(c_id_a['href'])
page_parser = BeautifulSoup(cmp_page.content)
intro = page_parser.find_all("div", class_="c_intro")
if len(intro) > 0:
c.mainPage = intro[0].text
else:
c.mainPage = '暂无简介'
p.cmp_id = c_id
c.id = c_id
write_to_db.add_pos(p, 'position')
write_to_db.add_pos(c, 'company')
print len(posistions)
company_dict = {
"goog": pagedata.alphabet,
"aapl": pagedata.apple,
"brk": pagedata.berkshire_hathaway,
"fb": pagedata.facebook,
"ilmn": pagedata.illumina,
"jnj": pagedata.johnson_and_johnson,
"lin": pagedata.linde,
"msft": pagedata.microsoft,
"nflx": pagedata.netflix,
"nvda": pagedata.nvidia,
"tsla": pagedata.tesla,
"txn": pagedata.texas_instruments,
"ul": pagedata.unilever,
}
all_structured_press_releases = []
for arg in vars(args):
if arg in company_dict.keys() and (getattr(args, arg) or args.all):
company = Company(arg, company_dict[arg])
company_struct = company.get_structured_press_releases()
all_structured_press_releases = [
*all_structured_press_releases,
*company_struct,
]
all_structured_press_releases.sort(key=lambda x: x[1])
display_structured_press_releases(all_structured_press_releases, args.weeks)
# May want to use adjusted close price instead of regular close price
df_goog = pd.read_excel(
"C:\Justin\PYTHON\Stock Project\Historical Data Excel\GOOG_Data.xlsx"
)
df_amzn = pd.read_excel(
"C:\Justin\PYTHON\Stock Project\Historical Data Excel\AMZN_Data.xlsx"
)
df_ford = pd.read_excel(
"C:\Justin\PYTHON\Stock Project\Historical Data Excel\FORD_Data.xlsx"
)
goog_company = Company(
"GOOG",
pd.to_datetime(df_goog["Date"]).dt.date.tolist(),
df_goog["Adj Close"].tolist(),
df_goog["Volume"].tolist(),
)
amzn_company = Company(
"AMZN",
pd.to_datetime(df_amzn["Date"]).dt.date.tolist(),
df_amzn["Adj Close"].tolist(),
df_amzn["Volume"].tolist(),
)
ford_company = Company(
"FORD",
pd.to_datetime(df_ford["Date"]).dt.date.tolist(),
df_ford["Adj Close"].tolist(),
df_ford["Volume"].tolist(),
def PB_C(self, ):
#getting the inputs
stockticker = self.input_stockticker.text()
if self.input_forecastedGrowthRate.text() is not '':
forecasted_growth_rate = float(
self.input_forecastedGrowthRate.text())
else:
forecasted_growth_rate = None
if self.input_perpetualGrowthRate.text() is not '':
perpetual_growth_rate = float(
self.input_perpetualGrowthRate.text())
else:
perpetual_growth_rate = None
company = Company(stockticker)
data = company.data
#generate the outputs
#ebit - imported as a variable
self.output_ebit.setText(d.convert(data['lastebit']))
#tax rate
atr = d.avg_tax_rate(data['taxexp'], data['ebt'])
self.output_tax_rate.setText(str(round(atr, 4)))
#depreciation and amortization - imported as a variable
self.output_depr.setText(d.convert(data['dep']))
self.output_amor.setText(d.convert(data['amor']))
#capital expenditure - imported as a variable
self.output_capex.setText(d.convert(data['capex']))
#change in networking capital
cwc = d.cwc(data['ybca'], data['yeca'], data['ybcl'], data['yecl'])
self.output_cwc.setText(d.convert(cwc))
#fcf valuation
fcf = d.fcf(data['lastebit'], atr, data['dep'], data['amor'], cwc,
data['capex'])
self.output_fcf.setText(d.convert(fcf))
#5 years free cash flow
#outputs all five years as a tuple
#(convert to list, then return individual years)
fiveyearfcf = {}
if forecasted_growth_rate is None:
fiveyearfcf = d.five_year_fcf(fcf)
else:
fiveyearfcf = d.five_year_fcf(fcf, forecasted_growth_rate)
self.output_y0.setText(d.convert(fiveyearfcf[0]))
self.output_y1.setText(d.convert(fiveyearfcf[1]))
self.output_y2.setText(d.convert(fiveyearfcf[2]))
self.output_y3.setText(d.convert(fiveyearfcf[3]))
self.output_y4.setText(d.convert(fiveyearfcf[4]))
self.output_y5.setText(d.convert(fiveyearfcf[5]))
#market capitalization - imported as a variable
self.output_marketcap.setText(d.convert(data['marketcap']))
#beta - imported as a variable
self.output_beta.setText(str(data['beta']))
#expected market returns - imported as a variable
self.output_emr.setText(str(round(data['rm'], 4)))
#cost of equity
re = d.re(data['rm'], data['rf'], data['beta'])
self.output_coe.setText(str(round(re, 4)))
#total long term debt - imported as a variable
self.output_ltd.setText(d.convert(data['lastD']))
#cost of debt
rd = d.rd(data['intexp'], data['LTD'])
self.output_cod.setText(str(round(rd, 4)))
#weighted average cost of capital
wacc = d.wacc(data['marketcap'], data['lastD'], atr, re, rd)
self.output_wacc.setText(str(round(wacc, 4)))
#terminal value - not part of ui, but included in calculation
tv = 0
if perpetual_growth_rate is None:
tv = d.tv(fiveyearfcf, wacc)
else:
tv = d.tv(fiveyearfcf, wacc, perpetual_growth_rate)
#discounted cash flow for the current year
dcf = d.dcf(fiveyearfcf, wacc, tv)
self.output_dcf.setText(d.convert(dcf))
#target price - not part of ui, but included in calculation
target_price = d.target_price(dcf, data['lastD'], data['numshares'])
#recommendation
rec = d.recommendation(data['current_price'], data['stdev'],
target_price)
self.output_rec.setText(rec) #insertPlainText
import sys
sys.path.append('/app/address_book/backend/module')
sys.path.append('/zyt/python/work/work/address_book/backend/module')
from Company import Company
from Attendance import Attendance
from datetime import datetime, timedelta
from DB import DB
from db import config
from Logger import Logger
logger = Logger(handler='file', handler_file_dir='/app/log')
# logger = Logger()
c = Company()
dbase = config.DATABASE
# These cities have no employees yet
skip_cities = []
gender_color = {'M': 'blue', 'F': 'red', 'U': 'white'}
db_con, db_cur = DB().connect()
test_con, test_cur = DB().connect(host=config.HOST,
user=config.USERNAME,
passwd=config.PASSWORD)
def is_connected_contact():
global test_con, test_cur
try:
test_con.ping()
except:
test_con, test_cur = DB().connect(host=config.HOST,
def mapCompany(self, object):
json = object
return Company(id=json['id'], name=json['name'], address=json['address'], city=json['city'], country=json['country'], mail=json['mail'], phone=json['phone'])
from Person import Person
from Order import Order
from Product import Product
from Company import Company
from Client import Client
from Employee import Employee
from datetime import datetime
company = Company()
person1 = Client("ahmad", "0993893", "male", "*****@*****.**")
person2 = Employee("majed", "46565", "male", 5000, "12 hours")
# person3 = Person("sara", "546852", "female")
# client1 = Client("ahmad", "0993893", "male", "*****@*****.**")
# client2 = Client("majed", "5645655", "male", "*****@*****.**")
# client3 = Client("sara", "546852", "female", "*****@*****.**")
# employee1 = Employee("majed", "46565", "male", 5000, "12 hours")
# employee2 = Employee("abody", "78465", "male", 4000, "8 hours")
# employee3 = Employee("amira", "44465", "female", 3000, "4 hours")
product1 = Product("tide", 100)
product2 = Product("fire", 50)
product3 = Product("shambow", 30)
product4 = Product("ditol", 40)
product5 = Product("dak", 21.6)
